6,062 Matching Annotations
  1. May 2026
    1. On 2020-04-14 11:02:19, user Philip Davies wrote:

      This is a very interesting pre-print. BUT, I think the data in table 3 has been mixed up (deaths for low v high dose are incorrect). The authors need to correct this and then ensure the tables are correct everywhere else. I have asked the authors to look at this and re-issue a corrected version (I also question whether the qSOFA results (table 1) were meant to be for values >2 rather than <2.

      This is important. It could mean that lower dose chloroquine is not only safe but could prove to be statistically better than placebo (will need the full 28 days analysis to know that).

      Dr Phil Davies

      http://thevirus.uk

    2. On 2020-04-15 11:35:12, user GP MD wrote:

      Ceftriaxone and azithromycin have their own toxicities....including mitochondrial dysfunction and ROS over-production in mammalian cells. The dosing of all three agents means a much higher risk of oxidative damage to mammalian DNA, proteins and membrane lipids. This would be worsened in those with impaired production of glutathione or reduced glutathione levels due to acetaminophen dosing.

    3. On 2020-04-15 18:47:50, user Y H wrote:

      Over thirty years ago, we found that chloroquine and related chemicals block muscarinic agonist binding. Similar findings were reported afterwards. This effect may link to a cause for cardiac arrhythmia induced by chloroquine. YH

      Antimuscarinic effects of chloroquine in rat pancreatic acini<br /> Yoshiaki Habara, John A Williams, Seth R Hootman<br /> Biochemical and biophysical research communications 137 (2), 664-669, 1986

    1. On 2020-04-14 17:58:53, user Badly Shaved Monkey wrote:

      From a U.K. perspective:

      My common sense reservation is that if Coronavirus was going to hit, say 60% of the U.K. population and 0.1% of those would die as suggested by Silverman and Washburne, that’d be about 40,000 deaths in total in the U.K. We’ve already hit 12,000 under the influence of a significant degree of social restriction over several weeks. While it is hard to predict the logistic asymptote from the exponential-like phase, it stretches credulity to suggest that the unmoderated U.K. epidemic would have burnt itself out with 40,000 deaths.

    1. On 2020-04-14 19:47:35, user Sinai Immunol Review Project wrote:

      Main findings:

      The aim of this study was to assess an association between reduced blood lymphocyte counts at hospital admission and prognosis of COVID-19 patients (n=192). The authors found:<br /> - Patients with lymphopenia are more likely to progress to severe disease or succumb to COVID-19 (32.1% of COVID-19 patients with lymphocyte reduction died). <br /> - Reduction of lymphocytes mainly affects the elderly (> 70 years old). <br /> - Lymphocyte reduction is more prevalent in COVID-19 patients with cardiac disease and pulmonary disease, patients with increase in the chest CT score (key marker of lung injury) and a decrease in several respiratory function markers (PaCO2, SpO2, oxygenation index).

      Limitations of the study:

      Reduced blood lymphocyte counts with aging have been known (https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.03.08.20031229v2)") https://onlinelibrary.wiley... "https://onlinelibrary.wiley.com/doi/epdf/10.1111/sji.12413)"). Therefore, it is not unexpected that a larger fraction of COV ID-19 patients above 70 years old have lower lymphocytes counts. Since age has been reported to be a major factor that determines outcome for COVID-19, lymphocyte counts and prognosis should have been adjusted by age. Multivariate analysis to identify independent risk factors is lacking.

      Relevance:

      Previous studies demonstrated that SARS-CoV-2 infection leads to a decrease of the T cell count. This study confirms these results and shows that lymphocyte reduction mainly affects the elderly. Lymphopenia was associated with disease severity as well as worse prognosis. Future studies need to address if lymphopenia is a negative predictive factor independent from age.

      Review by Meriem Belabed as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn school of medicine, Mount Sinai

    1. On 2020-04-15 11:04:57, user Dr Eric Grossi Neurocirurgia wrote:

      I would like to highlight a serious methodological error in this study. What we want for a drug treatment of COVID-19, only two objectives, to avoid and / or treat SARS and reduce contagion, therefore pragmatism in the selection of patients must be as close as possible to the clinical reality, which did NOT occur, since only patients between the ages of 29.4 to 60 years were analyzed. This alone invalidates any useful result, since the vast majority of human losses are over the age of 64.

    1. On 2020-04-15 15:04:27, user Mehee f wrote:

      this is completely unscientific the US has a population of 335M on this basis it will have 4M cases and 100,000 fatalities by now. Also you did not compare figures with other countries there is a big variation of mortality rates between 0.5% in South Korea to 12% in Italy. It is very biased report based on all estimates and no data pure speculation.

    1. On 2020-04-15 19:07:06, user Gregory Armstong wrote:

      Thanks for contributing this. It's a very important topic. There are few well controlled studies of risk factors for COVID-19.

      My one comment--and I didn't read the entire manuscript: I'd strongly recommend removing vital signs and laboratory findings from the regression. Those are manifestations of severe disease, not risk factors for it. They're some of the main considerations in deciding whether to hospitalize and whether to admit to the ICU. They should correlate strongly with both, and including them in the model will severely dilute the impact of true risk factors and could completely hide them. They shouldn't be considered independent variables.

    1. On 2020-04-15 20:48:45, user empiricist2 wrote:

      According to the French study, the addition of Azithromycin cleared out the virus in 4 days, versus at least twice that without it. And others use zinc, considered a very important factor. So why just test HCQ alone? And what were the antivirals that hampered results? Certainly there are other studies to report on that include zinc etc. Even in China they had reported that IV Vit C helped significantly. One doctor takes 10g daily as preventative. Vit C has a long history of antiviral benefits in large doses.

    2. On 2020-04-18 21:54:04, user Jim Trader wrote:

      Kind of a useless study. With an average delay of 16 days from symptom onset to enrollment and treatment in this trial, those patients are pretty much past the viral phase of the disease, where an antiviral treatment would have the most value, and are well on their way to pneumonia and a cytokine storm problem, which is ultimately what kills. Even the subset analysis of patients with a 7 day delay from symptoms to enrollment is still too long. As the authors state, it is very difficult to do these kinds of trials when patients average 12 days from symptoms before they come into the hospital, and can be explored as trial participants. So unfortunately there is no signal here, and from a molecular biology viewpoint, that is exactly what I would expect with this trial design. HCQ therapy needs to start within 48 hrs of symptom onset, ideally 24.

    1. On 2020-04-16 14:51:37, user agoraks wrote:

      Quote: "The assays are sensitive and specific, allowing for screening and identification of COVID19 "

      Question: what is the actual sensitivity and specificity of the assay for detecting active disease by IgM or convalescence IgG in Sars-CoV-2 infected patients ?

    1. On 2020-04-16 19:48:56, user Stef Verlinden wrote:

      It is troublesome that the article does not give the materials and the method used to derive/calculate the QTc. Formally a QTc can only be calculated from a signal derived from Lead II of V5 registered with a 12 lead ECG machine. QTc's calculated by a computer algorithm (unless it is specifically validated to do that job) are not to be trusted. This needs to be done by hand by a well-trained person.

      Most importantly, the QTc calculation is not linear. A heart rate of 90 gives an overestimation of the QTc of 50 ms (when using the Bazett method). Did the authors correct for this? Based on this paper, it is not possible to establish whether the QTc's are truly prolonged or that these are false positive outcomes.

      For reference check; QTc: how long is too long? https://www.ncbi.nlm.nih.go...

    1. On 2020-04-17 20:43:16, user Drew Middlesworth wrote:

      I was estimating the true infected numbers were 10-20x higher than the reported numbers based off the hospitalization rates, I wasn't expecting it to be this high. Although folding these numbers into NY infected counts would mean that over 100% were infected which can't be right. My estimate would show about 25-50% infected currently.

      Although the other thing that would skew this, by using Facebook ads and not doing a random population pick, you would skew the results higher as people who were sick in Jan-Feb would be more likely to respond to the ad to get tested. They could easly be 2-3x too high which would be more inline with the numbers I was estimating based off hospitalization rates.

    2. On 2020-04-18 00:16:22, user Rob Kuchta wrote:

      I am very suspicious of the 50- to 85-fold difference in confirmed cases based on the NY (and NYC) infection rates. NY has a 1.2% infection rate as a whole, and for NYC it is 1,5%. Using these values, that would indicate that from 60-100% of the population have been infected in NY state, and infections should be dropping rapidly (also, I have never heard of a virus having this sort of infectivity). In NYC, the infection rate would be 75-100%. This suggests that either there is an unknown issue with the test or that the Ab generated by being infected by this virus do not prevent subsequent infection. This latter situation would be rather worrisome in terms of a vaccination strategy to prevent infection.

    3. On 2020-04-18 16:15:43, user spacecat56 wrote:

      In reading the draft report of the study (pre-print, dated April 11, 2020) my predominant thought was, in choosing to respond to the invitation to the study participants are overwhelmingly likely to have self-selected based on their recent prior experience of symptoms that they suspect may have been due to COVID-19 infection.

      The draft acknowledges the possibility of this bias but tosses it off as "hard to ascertain". But the draft also says that data on prior symptoms were collected; data which are entirely omitted both from the published analysis and from the published tables.

      Because the analysis ignores this factor and because of the potential for this bias to totally dominate the analysis, in my opinion after reading the study draft, we still know effectively nothing at all about the prevalence of infection in the studied population. Accordingly I would expect to vigorously object to any attempt to incorporate the reported results into public policy and planning.

      I would urge the study team to bend their efforts to addressing this deficiency. At a minimum, I suggest, the report should include the withheld prior-symptoms data. Preferably, some efforts should be made to deal with the difficulty of estimating the bias. Perhaps it would be helpful to subdivide the sample data based on yes/no prior symptoms and analyze each subset?

    4. On 2020-04-18 16:27:11, user Zev Waldman MD wrote:

      I agree with other commenters that people who suspected prior Covid infection (or exposure) are more likely to seek antibody testing than those who did not. While participants were asked about prior symptoms, it is not clear what was done with this information. The rate of symptoms/exposure could be reported, compared to the community rates, used as a risk factor for positive antibody testing, etc.

      My other concern that has gone less discussed is their calculation of the case fatality rate. While they recognize that reported case numbers as of April 1 are an underestimate, it seems that they forget this skepticism when looking at reported deaths. They seem to take it as a given that 50 people died of Covid in the county as of April 10 as reported, and used this to project to deaths by April 22; however, like case counts, there are multiple reasons to suspect this number of deaths might be higher:

      1. Reporting of deaths is well-known to be delayed - i.e., date of reporting does not equal date of death

      2. People who actually died of Covid may never have been tested, and thus may not be included as cases or deaths

      3. The doubling time of deaths used to project to April 22 is also based on reported deaths; if reporting of deaths is delayed, the doubling time may appear slower than it actually was.

      If the death estimate due to illness before April 1 is too low, their corresponding CFR would be an underestimate as well. (This would be exacerbated if their case estimate is too high due to self-selection into the study, as seems possible.) At the very least, some sort of uncertainty around the death estimate should be provider, which in turn would increase the uncertainty around the final CFR.

      I know CFR wasn't the main focus on the article, but worry that, because these results support their prior beliefs, some readers may take the results at face value and push them to policymakers before they have been more widely vetted by the scientific community.

    5. On 2021-12-12 01:32:39, user Wild Bill, Jr. ????:????:?? wrote:

      When I first read this paper, a year ago, I was skeptical about it. The alarmists presented what seemed to be some strong arguments against it

      However, with the passing of time, infection-fatality rate statistics and deaths from all causes statistics support the Stanford team's hypothesis: The dreaded virus has turned out to be a lot less lethal than the alarmists claimed it was.

    6. On 2020-04-23 15:59:44, user gmshedd wrote:

      If we take the observed fatalities (by residence) in the Bronx (2258 as of 4-22) and Queens (3432), and apply the suggested infection fatality rates of 0.12% to 0.20%, we can infer that between 80% and 133% of Bronx residents have already been infected, and that between 76% and 127% of Queens residents have also been infected. Therefore, Bronx and Queens residents have achieved herd immunity, so they can re-open everything immediately. This is such great news! Oh, but you say, these populations aren't similar. OK, so I'll use Nassau County (Long Island)--median income $111k vs $116k in Santa Clara County. 1431 Nassau County residents have died, from which we would infer that between 53% and 88% of the 1,356,924 county residents have been infected. My point is that the suggested infection fatality rates don't pass the eye test, and, since they are derived from the infection rates that are at the center of the controversy, it would seem that the publication's Santa Clara County infection rates are higher than seems reasonable for the NYC area--unless California COVID-19 has a significantly lower infection fatality rate than New York COVID-19.

    7. On 2020-04-24 05:58:27, user JM V wrote:

      With 80 (1.7%) people dead in Castiglione d'Adda (Caveats: Old/Smoking/Unlucky/Collapse of Health care system/Some would have died anyway) this was already extremely unlikely. Now, with NYC 0.22% excess deaths and 21.2% of shoppers having antibodies, an IFR of 0.8% - 1.2% appears plausible.

    8. On 2020-04-25 07:19:42, user John Smith wrote:

      1. A local website (SFGate, I think) mentioned a person who emailed many friends about the free test and this selected wealthier people who might have more exposure to international travel. This would boost the percentage with antibodies above a population sample that had more poor people in the sample. It did mention the team tried to correct for this email by recruiting from other areas of the county. 2. Santa Clara county has more international travel than most other areas of the USA that have fewer immigrants, so people who are saying other areas of the USA might have the same higher level of recovered patients would be wrong.
    1. On 2020-11-19 18:22:04, user Ivan Ivanov wrote:

      Impressive work. It is probably misunderstanding but the authors use 10mM KCl/10mM NH4SO4 in the buffer for Bst 2.0 and they call it 1x Isothermal Buffer which infact is the commonly known ThermoPol buffer (optimal for Bst LF, not for Bst 2.0). NEB sells Bst 2.0 with Isothermal buffer containng 50mM KCl/10mM NH4SO4.

    1. On 2020-11-20 02:26:46, user Prasad Kasibhatla wrote:

      Interesting.. scaling reported median risk (2e-6) for individual touches by average touches per day (336), gives a transmission risk by fomites of 10-12% over a 6 month period (roughly length of pandemic ). Seems high .. so my scaling must not be appropriate. Any thoughts?

    1. On 2020-11-23 23:12:54, user Louis Rossouw wrote:

      Why does this paper compare mortality July 2019 to June 2020 to try and determine the impact "after" COVID-19 when the pandemic started in Feb-March 2020? So the "after COVID-19" of the title of the paper includes more time before COVID-19 than after the epidemic started?

      The authors also do not allow for any changes in age distribution / popualtion mix that may be affecting observed mortality trends.

    1. On 2020-11-25 07:42:20, user Carol Shadford wrote:

      When you say 'continual sensation of having had a “nasal douche”' are you referring to a feeling that the sinuses have been cleared out and are now empty or is that referring to the rushing feeling you get when chlorinated water accidentally goes up your nose -- a wasabi-like feeling?

    1. On 2020-11-26 05:48:46, user Community Medicine with velz wrote:

      Re-infection can be defined only by viral genome sequencing. The implication of these results can be mis-leading as re-infection has been defined by RT-PCR in this study.

    1. On 2020-11-27 19:21:54, user Jackie A wrote:

      This work is useful because it is the first modeling paper reckoning IFN role in the disease - and an early administration of it could be beneficial, which is consistent with recent RTC for IFN-beta. However, it is built on rodents and the extrapolation to humans is not clear and not validated by tissue data extracted from humans. The authors assume that tissue viral loads correlate with organ failure which has not been demonstrated.

    1. On 2020-11-27 21:02:26, user Robert Brown wrote:

      Vitamin D, Magnesium, Steroids, PPI and COVID-19; Interactions and Outcomes - Response to ‘Effect of Vitamin D3 Supplementation vs Placebo on Hospital Length of Stay in Patients with Severe COVID-19: A Multicenter, Double-blind, Randomized Controlled Trial’ [Preprint] [1]

      Thank you and congratulations on your important and significant paper. This is only the fourth[2] [3] [4] reported RCT examining vitamin D supplementation as a therapeutic intervention for COVID-19. Biology provides multiple pathways by which vitamin D hydroxylated-derivatives[5] may impact Covid-19 risks [including via; ACE2 receptors; airway-epithelial-cell tight-junction-function, immune responses [affecting lymphocytes, macrophages T cells, T helper cells, Th1, -17; Tregs; cytokine secretion IL-1, -2, -4, -5, -6 -10,-12; IFN-beta, TNF-alpha; defensins and cathelicidin, and receptors HLA-DR, CD4, CD8, CD14, CD38. Vitamin D also regulates; mitochondrial respiratory, inflammatory, oxidative and other functions; RXR and other receptor links between steroids, retinoids, hormonal vitamin D, thyroid hormone, oxidised lipids and peroxisomal pathway immune responses.][6]

      Significant evidence [40+ patient-papers[7]] suggests higher Vitamin D status [serum/plasma 25(OH)D concentration] is associated with diminished COVID-19 infection rates,and reduced severity [including ICU admission and mortality].[2 3 4]

      Thus, it is crucial, to consider if the preprint’s broad-based conclusion “Vitamin D3 supplementation does not confer therapeutic benefits among hospitalized patients with severe COVID-19”, [time to discharge as well as lack of observed ICU and mortality rate benefits], stands scrutiny when any one, or combination of, the following factors are considered: -

      Delay in vitamin D administration after severe symptoms onset

      Patients presented “10.2 days after symptoms”, thus were already verging on serious outcomes at admission; “89.6% required supplemental oxygen at baseline [183 oxygen therapy; 32 non-invasive ventilation] and 59.6% had computed tomography<br /> scan findings suggestive of COVID-19.” [Days to dyspnoea from overt infection average 7-8, and acute-respiratory-distress-syndrome [ARDS] develops after median 2.5 days.[8]]

      Further, the timing of vitamin D supplementation, at or after <br /> hospitalisation, was not specified, despite timing clearly being an important factor, given the advanced stage of illness at admission.

      Baseline vitamin D status [serum 25(OH)D concentrations] were relatively ‘good’

      Baseline 25(OH)D values averaged 21.0ng/ml and 20.6ng/ml in the treatment and control groups respectively, i.e. they were relatively ‘good’, and above levels reported as being associated with the greatest COVID-19 risks.[9] [10]Sub-analysis of patients < 10ngml +/-Dexamethasone would be instructive. Further, deficiencies such as magnesium (an essential ‘D’ enzyme co-factor) might factor more in the lack of observed benefits for Covid-19 severity, than vitamin D status itself.

      Corticosteroids

      COVID-19 related corticosteroid vitamin ‘D’ interactions require<br /> investigation. 64.2%(Treatment) and 60.8%(Control) group patients respectively, were treated with Corticosteroids (Dexamethasone?), and mortality was somewhat higher in the Treatment than Control arm. Interactions between vitamin D and steroids including dexamethasone are observed[11], including “decreased synthesis of active vitamin D, and impairment of biological action at tissue level.”[12] However these potential effects have not been investigated in COVID-19 patients treated with both vitamin D and dexamethasone.

      It would be most useful to know therefore, at what stage corticosteroid treatment began, and at what dosages, what other treatments were given [and at what dosage], and when such treatments were stopped, so that potential interactions between vitamin D, corticosteroids and other treatments for COVID-19<br /> patients could be elucidated.

      In particular, any negative or neutralising effect of corticosteroids on<br /> ‘D’-derivatives and pathways, could account for the lack of reduction in risks of ICU and mortality outcomes, including slightly higher mortality, in those given vitamin D, a matter of importance, since dexamethasone, given before onset of serious ARDS, was reported in Oxford[13] to increase, not reduce, mortality.

      Proton pump inhibitors.

      PPI are known to lower serum magnesium,[14] an essential ‘D’ hydroxylase-enzyme co-factor. 47/120-(39%)[Treatment] and 49/120-40%[Control] used PPI, compared to 9.2% population usage in USA.[15] PPI-induced related serum magnesium reduction, +/- dietary insufficiency, is a reported COVID-19 risk factor,[16] thus possibly helping account, for D3 treatment, failing to reduce Brazilian Covid-19 mortality. Thought-provokingly a Brazilian paper reported “There is chronic latent magnesium deficiency in apparently healthy university students”, which deficiency is potentially more widespread.[17]

      Conversely, RCT administration of magnesium with vitamin D reduced COVID-19 in-patient mortality.2

      Rate of increase of Serum 25(OH)D

      It is unclear when blood was sampled for determination of serum 25(OH)D concentrations, or if this was standardised for all patients.

      A large bolus will increase 25(OH)D values in the healthy, “Oral D2 and D3 (100,000 to 600,000 IU) significantly increased serum 25(OH)D from baseline in all reviewed studies” . . . “peak levels were measured at 3 days (34) and 7 days following dosing,”[18]

      However, timing matters, because hepatic hydroxylation5 to form 25(OH)D (Calcifediol) is likely reduced by; severe illness, as well as by obesity diabetes, and possibly hypertension,[19] conditions already recognised as risk factors for covid-19 severity.[20]

      The Cordoba study[3] suggests that 25(OH)D [Calcifediol, that could be given together with vitamin D3, cholecalciferol], may be key to effective treatment of severe COVID-19 illness. There is no suggestion Cordoba patients were treated with corticosteroids. Cordoba patients were administered calcifediol on admission-day, but the period between overt infection and hospital admission <br /> was not reported.

      Risk-factor Differentials in Patient Groups

      A skew in risk factors favouring the control?

      Control-Placebo to Treatment-D3:

      Increased risk factors - Overweight (31/37, 0,84); Obesity (58/63, 0,92); Hypertension (58/68, 0,74); Diabetes II 35/49, 0,71); COPD (5/7,0,71); Asthma (7/8, 0,88); Chronic Kidney Disease (0/2, 0,0); Rheumatic Disease (10/13, 0,77)[21]; Black (14/20) Male 965/70).

      Decreased factors - White (79/62) Female (55-50)

      Improved oxygen parameters are not reflected in conclusion

      Despite the D3 group being at a greater risk, including due to hypertension, COPD and diabetes, known risk factors, significant differences in oxygen supplementation favour the D3 treatment group“.21

      Oxygen supplementation (%) Placebo No. (%) D3 <br /> No oxygen therapy 9 (7.5) 16 (13.3)<br /> Oxygen therapy 97 (80.8) 86 (71.7)<br /> Non-invasive ventilation 14 (11.7) 18 (15.0)

      Conclusion requires Caveats?

      Thus, the un-caveated conclusion “Vitamin D3 supplementation does not confer therapeutic benefits among hospitalized patients with severe COVID-19”, likely requires caveats about possible effects of the several factors discussed above.

      Further, the reported finding cannot be extrapolated to care of all Covid-19 patients, since the above- mentioned-potential interactions require further investigation, including; as to effects of; magnesium

      status; treatment with PPI inhibitors, impact of corticosteroids in severe Covid-19 illness on vitamin D biology and outcomes, and consideration of pre-existing vitamin D status.

      Further public health policy directed at reducing vitamin D, and other nutrient deficiencies for mitigation of COVID-19 risks at population levels, should not be conflated with clinical optimisation of vitamin D and metabolites for treatment of severe COVID-19 illness.

      [1] Murai,I., Fernandes, A., Sales, L., Pinto, A., Goessler, K., et. al. 17th November 2020). Effect of Vitamin D3 Supplementation vs placebo on Hospital Length of Stay in Patients with Severe COVID-19 A Multicenter, Double-blind, Randomized Controlled Trial. medRxiv 2020.11.16.20232397; doi: https://doi.org/10.1101 /2020.11.16.20232397 Available at: https://www.medrxiv.org/content/10.1101/2020.11.16.20232397v1<br /> [2] Tan, C., Ho, L., Kalimuddin, S., Cherng, B., Teh, Y., et.al. (10th June 2020). A cohort study to evaluate the effect of combination Vitamin D, Magnesium and Vitamin B12 (DMB) on progression to severe outcome in older COVID-19 patients. doi: https://doi.org/10.1101/202... Available at: https://www.medrxiv.org/content/10.1101/2020.06.01.20112334v2<br /> Now published in Nutrition doi:10.1016/j.nut.2020.111017 <br /> [3] Entrenas Castillo, M., Entrenas Costa, L., Vaquero Barrios, J., Alcalá Díaz, J., López Miranda, J., Bouillon, R., & Quesada Gomez, J. (29th August 2020). Effect of calcifediol treatment and best available therapy versus best available therapy on intensive care unit admission and mortality among patients hospitalized for COVID-19: A pilot randomized clinical study. The Journal of steroid biochemistry and molecular biology, 203, 105751. https://doi.org/10.1016/j.j... Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456194/<br /> [4] Rastogi, A., Bhansali, A., Khare, N., et. Al. (12th November 2020).<br /> Short term, high-dose vitamin D supplementation for COVID-19 disease: a randomised, placebo-controlled, study (SHADE study). Postgraduate Medical Journal Published Online First:. doi: 10.1136/postgradmedj-2020-139065 Available at: https://pmj.bmj.com/content/early/2020/11/12/postgradmedj-2020-139065<br /> [5] Bouillon, R., & Bikle, D. (2019). Vitamin D Metabolism Revised: Fall of Dogmas. J Bone Miner Res. 2019 Nov;34(11):1985-1992. doi:<br /> 10.1002/jbmr.3884. Epub 2019 Oct 29. PMID: 31589774. Available at: https://asbmr.onlinelibrary.wiley.com/doi/full/10.1002/jbmr.3884<br /> [6] Brown, R., Rhein, H., Alipio, M., Annweiler, C., Gnaiger, E., Holick M., Boucher, B., Duque, G., Feron, F., Kenny, R., Montero-Odasso, M., Minisola, M., Rhodes, J.,Haq., A, Bejerot, S., Reiss, L., Zgaga, L., Crawford, M., Fricker, R., Cobbold, P., Lahore, H., Humble, M., Sarkar, A., Karras, S., Iglesias-Gonzalez, J.,Gezen-Ak, D., Dursun E., Cooper, I., Grimes, D. & de Voil C. (April 20, 2020). COVID-19 ’ICU’ risk – 20-fold greater in the Vitamin D Deficient. BAME, African Americans, the Older, Institutionalised and Obese, are at greatest<br /> risk. Sun and ‘D’-supplementation – Game-changers? Research urgently required’: ‘Rapid response re: Is ethnicity linked to incidence or outcomes of COVID-19?’: BMJ, 369(m1548). DOI: 10.1136/bmj.m1548. Available at: https://www.bmj.com/content... (Accessed: 24 November2020. - Alipio study<br /> now in question – rest stands)<br /> [7] Brown R. (15 Oct 2020). Vitamin D Mitigates COVID-19, Say 40+ Patient Studies (listed below) – Yet BAME, Elderly, Care-homers, and Obese are still ‘D’ deficient, thus at greater COVID-19 risk - WHY? BMJ 2020;371:m3872 Available at https://www.bmj.com/content/371/bmj.m3872/rr-5 (Retrieved 24 Nov 2020) <br /> [8] Cohen, P., Blau, J., Eds: Elmore, J., Kunins, L., & Bloom, A. (2020). MD disease 2019 (COVID-19): Outpatient evaluation and management in adults. Literature review. Wolters Kluwner. Available at: https://www.uptodate.com/contents/coronavirus-disease-2019-covid-19-outpatient-evaluation-and-management-in-adults/print<br /> (retrieved 25th November 2020)<br /> [9] Jain, A., Chaurasia, R., Sengar, N., Singh, M., Mahor, S., & Narain, S. (19th Nov 2020). Analysis of vitamin D level among asymptomatic and critically ill COVID-19 patients and its correlation with inflammatory markers. Sci Rep. 2020 Nov 19;10(1):20191. doi: 10.1038/s41598-020-77093-z. PMID: 33214648; PMCID: PMC7677378. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677378/<br /> [10] Radujkovic, A., Hippchen, T., Tiwari-Heckler, S., Dreher, S., Boxberger, M., & Merle, U. Vitamin D Deficiency and Outcome of COVID-19 Patients. Nutrients 2020, 12, 2757. Available at https://www.mdpi.com/2072-6643/12/9/2757 <br /> [11] Hidalgo, A. A., Trump, D. L., & Johnson, C. S. (2010). Glucocorticoid regulation of the vitamin D receptor. The Journal of steroid biochemistry and molecular biology, 121(1-2), 372–375. https://doi.org/10.1016/j.j... Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907065/<br /> [12] Giustina, A., Bilezikian, J. (eds) (2018). Vitamin D and Glucocorticoid-Induced Osteoporosis. Vitamin D in Clinical Medicine. Front Horm Res. Basel, Karger, 2018, vol 50, pp 149-160 (DOI:10.1159/000486078) Available at https://www.karger.com/Article/Pdf/486078<br /> [13] The RECOVERY Collaborative Group. (17th July 2020). Dexamethasone in Hospitalized Patients with Covid-19 — Preliminary Report. J New England Journal of Medicine R10.1056/NEJMoa2021436 https://www.nejm.org/doi/fu... Available at https://www.nejm.org/doi/full/10.1056/NEJMoa2021436<br /> [13] FDA. (8th Apr 2017). FDA Drug Safety Communication: Low magnesium levels can be associated with long-term use of Proton Pump Inhibitor drugs (PPIs) https://www.fda.gov/drugs/drug-safety-and-availability/fda-drug-safety-communication-low-magnesium-levels-can-be-associated-long-term-use-proton-pump (Accessed 25th November 2020)<br /> [14] Hughes, J., Chiu, D., Kalra, P., & Green, D. (2018). Prevalence and outcomes of proton pump inhibitor associated hypomagnesemia in chronic kidney disease. PLoS ONE 13(5): e0197400. https://doi.org/10.1371/jou... Available at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0197400<br /> [15] Lee, S., Ha, E., Yeniova, A., et. al. (30th July 2020). Severe clinical outcomes of COVID-19 associated with proton pump inhibitors: a nationwide cohort study with propensity score matching. Gut Published Online First: 30 July 2020. doi: <br /> 10.1136/gutjnl-2020-322248 Available at: <br /> https://gut.bmj.com/content/early/2020/07/30/gutjnl-2020-322248<br /> [17] Hermes Sales, C., Azevedo Nascimento, D., Queiroz Medeiros, A., Costa Lima, K., Campos Pedrosa, L., & Colli, C. (2014). There is chronic latent magnesium deficiency in apparently healthy university students. Nutr Hosp. 2014 Jul 1;30(1):200-4. doi: 10.3305/nh.2014.30.1.7510. PMID: 25137281. Available at: http://www.aulamedica.es/nh/pdf/7510.pdf<br /> [18] Kearns, M., Alvarez, J., & Tangpricha, V. (2014). Large, single-dose, oral vitamin D supplementation in adult populations: a systematic review. Endocrine practice: official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists, 20(4), 341–351. https://doi.org/10.4158/EP1... Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4128480/<br /> [19] Kheiri,B., Abdalla, A., Osman, M. et al. (2018) Vitamin D deficiency and risk of cardiovascular diseases: a narrative review. Clin Hypertens 24, 9 (2018). https://doi.org/10.1186 /s40885-018-0094-4 Available at https://clinicalhypertension.biomedcentral.com/articles/10.1186/s40885-018-0094-4 <br /> [20] Kruglikov, L,. Shah, M., Scherer, E. (Sept 2020). Obesity and diabetes as comorbidities for COVID-19: Underlying mechanisms and the role of viral-bacterial interactions. Elife. 2020 Sep 5;9:e61330. doi: 10.7554/eLife.61330. PMID: 32930095; PMCID: PMC7492082.<br /> [21] Borsche L. Private email 19.11.20

    2. On 2020-12-01 21:23:17, user NubOfTheMatter wrote:

      This trial appears to have been a wasted opportunity.

      It is unclear why Vitamin D3 was orally administered to severely ill C-19 patients. It can take a fortnight to be metabolised into Calcifediol, the active, metabolised form required to trigger an immune response. A most unhelpful delay to the effective treatment of severely ill COVID-19 patients.

      The RCT conducted at the teaching hospital in Cordoba used Calcifediol, with dramatic results. Compared to the untreated ‘control group’ there was a 96% reduction in the need for Intensive Care Unit admission, and a commensurate reduction in deaths.

      One has to ask, therefore, why, in Sao Paulo, it was decided to administer un-metabolised Vitamin D3 rather than Calcifediol to severely ill C-19 patients for whom every day of non-treatment reduces the chance of a good outcome if not survival? Indeed, an experienced physician could have forecast the results obtained without the need for a trial.

    3. On 2020-12-07 13:02:33, user Fernando wrote:

      Good morning, I have some comments: I couldn’t find the final D level at 7 and 10 days (hospital discharge), this information is crucial to establish the effectiveness of the ministered dose. <br /> At a first glance, considering the patients were mostly deficient in vitamin D and obese (slow D absorption) the dose provided seamed too low to produce results in such a short time (7-10 days), specially as it was vitamin D in its over the counter form (not calcifediol).<br /> Also not clear how many days after testing positive did the patients take vitamin D. It seems that in Brazil people are only hospitalized after aggravation.<br /> Thank You!

    1. On 2020-12-01 14:30:16, user Peter Griffiths wrote:

      Published as: Griffiths, P., Saville, C., Ball, J., Culliford, D., Pattison, N., Monks, T., 2020. Performance of the Safer Nursing Care Tool to measure nurse staffing requirements in acute hospitals: a multicentre observational study. BMJ Open 10 (5), e035828.10.1136/bmjopen-2019-035828

    1. On 2020-12-01 17:48:06, user Pandora wrote:

      Interesting. Did you take into account regular medication taken for each group. Studies have been done on Ace2 inhibitors and blockers. There's also studies on proton-pump inhibitors and Sarscov2. They seem inconclusive too, but it may skew your results. Interestingly, a lot of these drugs and a diabetes drug are under recall for NDMA contamination at present.

    2. On 2020-10-30 18:25:19, user gatwood wrote:

      I suspect there could be a strong corellation between vaccination status<br /> and following a strict adherence to all COVID anti-infection <br /> guidelines, PPE etc... Experienced and medically trained Drs and nurses<br /> more likely have been vaccinated and also are more likely to follow PPE<br /> wearing and careful anti-infection routines. Support staff (food <br /> service, assistants and claening staff) with less formal medical <br /> training and understanding of infection are probably less likely to be <br /> vacinnated and also may be less likely to carefully employ all technical<br /> anti-infection measures. Would this account for the vaccinated folks <br /> having less COVID infection?

    1. On 2020-12-03 15:34:00, user joetanic wrote:

      Quite interesting data. I'm wondering whether anyone knows why France does not perform these tests?

      Or the US? It seems a broad study, especially in France which seems to be bucking the trend, so to speak, would make clear what the future holds in many places.

    1. On 2020-12-11 16:21:41, user Fred wrote:

      Disappointing study. I would not expect that antivirals are of any use if started when patients are already hospitalized. I would recommend to start with antivirals as soon as possible regardless wheter the patient has symptoms or not. But in this case we need studies comprising many more patients than in this small study

    1. On 2020-12-12 17:48:59, user Patrick Karas wrote:

      Congratulations on this excellent work. Molecular subtyping for meningioma is much needed to help develop future therapies, and your work pushes this forward. How do you think your subtypes A, B and C compare to the meningioma molecular types similarly labeled type A, B, and C published last year in PNAS by Patel et al (doi: 10.1073/pnas.1912858116)? It seems like there is a lot of overlap (group A with intact NF2; group B and C with NF2 loss; group C with increased FOXM1 expression and high copy number variation). This is a great step forward validating these subtypes through a different approach.

    1. On 2020-12-16 20:05:03, user Wolfgang Lins wrote:

      the authors discuss "anterior nasal (AN)" swabs, and on page 4 refer to this as:

      Participants first underwent collection of the AN-sample, using the specific nasal swab provided in the test kit of the manufacturer, according to the instructions for use, which also correspond to the U.S. CDC instructions [4]. Briefly, while tilting the patient’s head back 70 degrees, the swab was inserted about 2cm into each nostril, parallel to the palate until resistance was met at turbinates, then rotated 3-4 times against the nasal walls on each side

      First, the collection procedure described here in act matches to one in that CDC manual [4], however not to the AN collection but to the collection of Nasal mid-turbinate (NMT) specimen. That is a floppy usage of the terms AN versus NMT, and should at least been detailled when defining AN in this paper.

      Second, the paper refers to a "specific nasal swab provided in the test kit of the manufacturer" for AN collection. Three lines later they write "a separate NP-swab (provided in the manufacturer test kit) for the Ag-RDT". <br /> As of my knowledge, the "STANDARD Q COVID-19 Ag Test" of SD Biosensor/Roche comes with a single kit - a NFS-1 from Noble Biosciences Inc., which is a swab for NP.

      I think it would help this paper to identify the particular "specific nasal swab" used here to obtain the AN/NMT swab - since the conclusions of this paper make a claim that "using a professional AN-sampling kit is at least equal to....". Reference 5 with a link to a sdbiosensor IFU that refers to NP swab only does not put any more light into this.

      Such a finding without properly identifying the particular kit unnecessarily reduces the value of this work.

    1. On 2020-12-25 14:25:32, user muthu venkat wrote:

      The Systematic Review and Meta-Analysis is interesting to read and need of the time to compile such an evidence particularly for middle and low income country. The authors have made sure that there is no bias in selection and reporting the evidences through use of appropriate software and methods.

    2. On 2020-12-26 19:56:50, user Dr S K Maheshwari wrote:

      This systematic review is focusing on measuring effectiveness of mHealth interventions on antenatal and postnatal care utilization in low and middle-income countries. A strong methodology was used along with wide inclusion of relevant studies from low and middle-income countries. The search strategy criteria were used very specific. I appreciate this work and recommend.

    1. On 2020-12-26 04:49:01, user Peter Tomasi wrote:

      Correction: If we assume a latency of 28 days, a substantial amount of samples REPRESENTING A POINT IN TIME WHEN THE level of the exposure in the environment was not yet as high as the one the authors draw their conclusions for, could have been collected.

    1. On 2021-01-05 07:56:40, user Rita Pizzi wrote:

      previous researches

      Ghate VS, Ng KS, Zhou W, Yang H, Khoo GH, Yoon WB, Yuk HG.

      “Antibacterial effect of light emitting diodes of visible wavelengths on

      selected foodborne pathogens at different illumination temperatures.”

      International Journal of Food Microbiology. 166 (2013) 399.

      Ghate VS, Leong AL, Kumar A, Bang WS, Zhou W, Yuk HG. “Enhancing the

      antibacterial effect of 461 and 521 nm light emitting diodes on selected

      foodborne pathogens in trypticase soy broth by acidic and alkaline pH

      conditions” Food Microbiology. 48 (2015) 49.

      Ghate, V, A Kumar, W Zhou and HG Yuk. 2015. Effect of organic acids

      on the photodynamic inactivation of selected foodborne pathogens using

      461 nm LEDs. Food Control 57:333–340.

      Vaitonis and Ž. Lukšiene – Institute of Applied Research, Vilnius

      University, Saul?etekio 10, LT-10223 Vilnius, Lithuania “Led-based light

      sources for decontamination of food: modelling photosensitization-based

      inactivation of pathogenic bacteria” Lithuanian Journal of Physics,

      Vol. 50, No. 1, pp. 141–145 (2010)

      http://www.lmaleidykla.lt/p...

      Nicolai Ondrusch, Jürgen Kreft “Blue and Red Light Modulates

      SigB-Dependent Gene Transcription, Swimming Motility and Invasiveness in

      Listeria monocytogenes” Published: January 11, 2011DOI:

      10.1371/journal.pone.0016151

      http://journals.plos.org/pl...

    1. On 2021-01-07 08:06:09, user Giuseppe novelli wrote:

      Congratulations, the work confirms and extends the considerations reported by us in two published papers, which happy if the authors could quote in an updated version of the manuscript Thanks

      Giuseppe Novelli

      1. Novelli A, et al., Analysis of ACE2 genetic variants in 131 Italian SARS-CoV-2-positive patients. Hum Genomics. 2020 Sep 11; 14 (1): 29. doi: 10.1186 / s40246-020-00279-z. PMID: 32917283

      2. Latini A, et al., COVID-19 and Genetic Variants of Protein Involved in the SARS-CoV-2 Entry into the Host Cells. Genes (Basel). 2020 Aug 27; 11 (9): E1010. doi: 10.3390 / genes11091010. PMID: 32867305

    1. On 2021-01-07 14:34:51, user Meerwind7 wrote:

      Households with single parents are also considered as socially deprived in other contexts. For infection rates, it might be of benefit if there is no second adult that could bring infections to the family. It was a pity if the effect was not taken into account. I also do not know if the social deprivation was evaluated for each individual child and its infection risks, or just for the schools and the aggregat of their pupils overall.

    1. On 2021-01-08 21:53:07, user Marek J wrote:

      Your study says that methylglyoxal contained in honey cause immunostimulatory or pro-inflammatory action via stimulating the production of immunological mediators, also IL-1?. This study https://www.nature.com/arti...<br /> Shows that low levels of IL-1 are linked to lower mortality.<br /> Is it then safe to recommend using honey rich for MGO, e.g. Manuka honey?

    1. On 2021-01-10 19:47:40, user Wayne Griff wrote:

      21 days after the 1st dose of the Pfizer Vaccine, patients have 1/5th the viral neutralizing power of Convalescent Plasma. In contrast, 7 days after the 2nd dose, patients have 2-4 times the neutralizing power of Convalescent Plasma. NEJM Also, the 47% effectiveness rate is only up to 3 weeks. It's definitely going to be less at 6, 9, or 12 weeks.<br /> Giving only 1 vaccination is a waste of a vaccination. It provides little, if any immunity.

    1. On 2021-01-12 20:36:18, user Michael Meyer wrote:

      Can someone tell me if this study has completed the peer-review process prior to publication in the Journal of Infectious Diseases? If not, is it currently in that process?

    1. On 2021-01-14 00:01:25, user Emmanuel Aluko wrote:

      Will such a study be done on older cohorts to show the age-dependent efficacy of Ivermectin on reducing mortality, for mortality is seen mainly in older patients with associated co-morbidities? Days to negative tests on such cohorts would also provide a better basis for accepting Ivermectin as a worthy COVID-19 therapeutic.

    1. On 2021-01-15 12:19:29, user Kit Byatt wrote:

      Given that:<br /> 1. Excess mortality for a year can't be known for several weeks into the following year <br /> 2. Especially in a year with Christmas & New Year's Day on Fridays, and a pandemic impeding the bureaucracy of collecting & collating mortality data - particularly in cases where the Coroner [or equivalent] is involved)<br /> 3. Different countries have exhibited different patterns (or none) of winter excess mortality peaks (as shown in Figure 1c)

      a) Is it not premature to undertake a comparison before all the data are in (or alternatively, at least title as 'Preliminary observations on...'?

      b) Might not the association end up significantly higher, the same, or lower, then?

    2. On 2021-01-27 10:12:04, user Elias Hasle wrote:

      some countries being hardly hit while others to date are almost unaffected

      Readers will tend to read this as "barely hit", the opposite of the intended meaning. "hit hardly" would be less ambiguous.

    1. On 2021-01-18 11:40:13, user Kit Byatt wrote:

      Re Length of stay [LOS]

      1. Was there a sex difference in LOS?

      2. We know there are age differences in LOS (median & variance increasing with age). What were the LOSs for age brackets (e.g. each decade)?

      3. Given the very skew LOS distributions in hospital in-patients usually, and especially here, mightn't it be helpful to put the inter-quartile range for the median LOS in 'Outcomes' para 2?

      4. Could you calculate the 'decay' in in-patient numbers (i.e. the equation for the 'current number of inpatients' curve from time zero, for 1000 pts with the LOS distribution you know)? This could be invaluable for modelling bed occupancy.

      Minor presentational points:

      1. Figure 15 Middle (symptoms combination in ICU patients matrix) p 23

      It is difficult to know the percentage figure for each bar in the symptom combinations and ICU admission matrix. Either putting the number over/in each column (as in Figure 15 Top), or at least showing minor tick marks at 0.01 intervals would greatly improve the clarity of this chart.

      1. Is there a reason for presenting LOS data as a density plot and time from symptoms to admission as a Gamma distribution curve? They are essentially the same phenomena: time to an occurrence; why the different graphical representation?
    1. On 2021-01-21 13:24:54, user Miroslava Stancíková wrote:

      Testing was not voluntary, it was in conflict with the Constitution of the Slovak Republic and the Charter of Fundamental Human Rights

    1. On 2021-01-25 15:10:24, user Chip Hughes wrote:

      Thank you all for this great research. It will really help OSHA target enforcement to the highest risk sectors and job classifications so that we can hope to reduce deaths among frontline workers with the highest level of COVID19 exposures on the job. Chip Hughes, USDOL-OSHA DAS

    2. On 2021-02-02 18:17:42, user Robert Enger wrote:

      The #1 candidate is "cook". Frequently that person stands in proximity to the grill, which is a high air flow location, due to the high power exhaust fan system in the range-hood over the grill. This acts as a funnel, sucking air from the kitchen (and surrounding areas back to the various points of makeup-air ingress). The cook is thus "downstream" from numerous co-workers in the kitchen, and from persons in other locations between the makeup-air ingress points and the range hood (potentially all the restaurant patrons, if interior dining resumes).

      This should sound familiar. Recall the studies of remote distance Covid transmission studied in Korea and China. In those studies, high air flow from air conditioner output ports carried virus from infected individuals to victims many feet removed from the infected party. In this case, the cook near the range-hood is "downstream" from potentially significant numbers of individuals (depending on the location of makeup-air ingress points, etc).

      If this line of reasoning is found to be sound, then providing a direct ingress path for outside fresh air to enter into the kitchen "may" reduce the exposure of the cook (and nearby kitchen staff).

    1. On 2021-01-26 01:57:03, user Steven David Stoffers wrote:

      what about a model run where there wasn't any air travel at all, including private air travel, that needed to still be made let alone any actual air travel at all, as of January 30, 2020 thru to today? what does that model show?

    1. On 2021-01-30 20:33:49, user Michael Höhle wrote:

      Dear authors,

      thanks for posting this very relevant manuscript! Please consider having a look at the statistical methodology of the two following papers, which are very closely related to your work, as they also use an imputation + nowcast + backprojection approach:

      Best regards,<br /> Michael Höhle

    1. On 2021-02-22 19:53:12, user Alexander Porter wrote:

      What does: '8,041 individuals received two doses of a COVID-19 vaccine and were at risk for infection at least 36 days after their first dose.' mean? Were these individuals exposed to SARS-CoV-2 directly every day?

      Were all PCR methods run with the same cycle threshold before and after administration?

    1. On 2020-11-06 05:07:01, user Schneide Fu wrote:

      Not sure they got the dosage correctly, as Nitazoxanide has a half life of 2.9 hrs. Should have been on divided doses, several times a day.

    1. On 2020-11-06 14:33:43, user Dr. Thiagarajan wrote:

      Timely need article and very interesting. We need to understand the challenges faced by dialysis professionals during this COVID 19. I congratulate Dr. Ravi Kumar for this timely article. Looking for this complete manuscript.

    1. On 2021-08-10 22:41:16, user Ashley Derrick wrote:

      I had covid in May of 2020. I had many long covid issues for months after - but the biggest issue was chest (heart and lung) pain. The symptoms included shortness of breath, burning sensation in the chest, difficulty getting a deep breath and feeling as if I was having a heart attack when more active (exercising). I went to both a heart specialist and a pulmonary specialist and nothing ever was found to be "wrong". The heart doctor was convinced it was inflammation in and around my lungs and heart that caused this. After 9 months, it went away (shortly before my first vaccine). I felt "normal" for about 4.5 months, but two weeks ago, the chest and heart issues came back. Same feelings. I am a fit 49 year old woman. Wondering if there are any studies that see symptoms going away and then months later coming back. Thanks -

    1. On 2021-08-12 06:11:36, user Gabriele Pizzino wrote:

      The study brings up relevant insights.<br /> I agree with Richard, uniformity of testing frequency is a potential confounding factor that should be taken into account.

      Also, you may have a selection bias generated by vaccination policies, and timeline.<br /> I’m gonna use Italy to give you the idea: Pfizer was rolled out earlier, and in a much more massive way, than Moderna. The same was true for the AstraZeneca one.<br /> The Italian government gave priority to high-risk workers (especially health workers, and whoever was working into medical facilities or nursing homes), and to high-risk individuals (so elderly people, and/or people with severe underlying conditions).<br /> At the time, the choice was between Pfizer and AstraZeneca; considering Pfizer showed a better efficacy, and it was better perceived in terms of safety profile by the public, the very very large majority of those high-risk categories received the Pfizer shots.

      That is a textbook-level selection bias, which could potentially affect the results in a significant way.<br /> I live in Italy, so I followed the vaccination process here much more closely; I don’t know if the same dynamics I described stand true also for the US, but I think it is worth to take a look and check it.

    2. On 2021-08-12 19:49:26, user Steven Ramirez wrote:

      From the preprint:

      "Date of vaccination (bucketed). For a given individual in the mRNA-1273 cohort who<br /> received their first vaccine dose on a given date, only individuals in the BNT162b2<br /> cohort who were vaccinated on the same date or within two weeks after that date were<br /> considered for matching. This match helps to ensure that matched individuals reach their<br /> date of full vaccination (14 days after the second dose) on approximately the same date."

      This seemingly addresses my point and effectively controls for diminution over time.

      Perhaps an explicit sentence in the preprint would help clarify this point.

    1. On 2021-08-12 17:18:46, user Iñigo Ximeno wrote:

      Although the observation is very interesting, it does not lead to the conclusion that it is the most prudent thing to continue with indiscriminate vaccination in the middle of a pandemic when the vaccine does not prevent the transmission of the pathogen.

      It is not relevant how many mutations are detected but the importance of them. It is obvious that among people with some immunity the mutations for which the antibodies can neutralize the virus will not be spreaded and therefore those will not be detected. However the mutations that can evade the immunity, even if they are few, will be more virulent and letal.

    1. On 2021-08-14 05:50:28, user Brad Mellen wrote:

      I assume the 167 infected people tracked in the study were previously vaccinated. Is it possible that antibody mitigated viral enhancement played a role in the increased viral loads? A study done by Wen Shi Lee et al in the Nature Microbiology volume 5, pages 1185–1191 (2020) noted the potential dangers of Covid 19 vaccinations could increase viral loads and ultimately increase the spread of Covid 19.

    1. On 2021-08-15 14:53:19, user Johannes Hambura wrote:

      The study authors found that the prevalence of mutations is higher in B cell epitopes than in T cell epitopes. They infer that vaccines that rely primarily on T cell immunity should confer protection more durable against the worrisome variants of SARS-CoV-2.<br /> It would be logical and consistent to assess this T cell immunity in unvaccinated and recovered Covid-19 patients, in order to better coordinate the strategy towards collective immunity.

      The authors report, based only on 47 cases studied, that unvaccinated patients share significantly more genomic mutational similarities with the variants of concern than patients with a breakthrough infection.<br /> This finding is interesting, but it requires statistically significant evaluation and verification.<br /> Especially since<br /> - in vitro, the selection pressure imposed by the antibodies, induced by the vaccines, has led to the emergence of new variants of SARS-CovV-2 (1);<br /> - in vivo, the case of a severe and prolonged form of infection by SARS-CoV-2, treated with antibodies taken from convalescents, favored the appearance of a variant. The variants decreased when the treatment with the injected antibodies was stopped and reappeared with new doses of the injected antibodies. In the absence of the antibodies, the wild strains again became the majority (2).

      In addition, the following findings by the authors tend to favor selective pressure exerted by vaccinations:<br /> - the diversity of SARS-CoV-2 lines decreases at country level with an increased rate of mass vaccination (negatively correlated with the increase in the rate of mass vaccination in the countries analyzed);<br /> - The decline in lineage diversity is coupled with the increased dominance of variants of concern;<br /> - vaccine breakthrough patients harbor viruses with significantly lower diversity compared to unvaccinated COVID-19 patients.

      The question still remains open, whether vaccination should not be limited to only vulnerable people in the world population, in analogy with a risk calculator for the population proposed by American scientists (3).

      1. Wang, Z., Schmidt, F., Weisblum, Y. et al. mRNA vaccine-elicited antibodies to SARS-CoV-2 and circulating variants. Nature 592, 616–622 (2021). https://doi.org/10.1038/s41...
      2. Kemp, S.A., Collier, D.A., Datir, R.P. et al. SARS-CoV-2 evolution during treatment of chronic infection. Nature 592, 277–282 (2021). https://doi.org/10.1038/s41...<br /> (3) Jin, J., Agarwala, N., Kundu, P. et al. Individual and community-level risk for COVID-19 mortality in the United States. Nat Med 27, 264–269 (2021). https://doi.org/10.1038/s41...
    1. On 2021-08-18 16:51:05, user Diane Krall wrote:

      We need data for severe COVID patients and reactogenicity. These patients had high dose steroids during their illness, which may be a confounding factor.

    1. On 2021-08-18 17:39:03, user John Baron wrote:

      The first sentence states that this is a study of individuals who underwent SARS-CoV-2 testing, presumably (though not stated) during the study period. Unless there was population testing surveillance in place, there must have been selection factors (e.g. COVID exposure or symptoms) prompting testing. This would bias estimates of infection rates upward, though the bias is unlikely to differ between vaccine groups and may not differ much between vaccinated and unvaccinated groups. Tthe relative infection measures might be OK.

      In the "final" paper, it would be important to account for the usual cohort issues: censoring, movement out of the health care system, etc. Also, the first paragraph of the Methods section should include unvaccinated individuals.

    1. On 2021-08-21 17:14:03, user Alan wrote:

      How will increased vaccination make a difference if the efficacy is as is being reported less than 50%? Once one is infected it does not appear to reduce one's odds of being hospitalized. So if the efficacy approaches zero, there would be zero benefit to being vaccinated, with the currently available vaccines.

    1. On 2021-08-23 13:04:39, user Eyal Oren wrote:

      I don't see any mention of vaccination status. Were these patients vaccinated or unvaccinated? Also the study would be stronger if comparison done to other patients in your catchment area vs CDC data (I believe that dataset is across US and not limited to Georgia?).

    1. On 2021-08-24 09:17:07, user Martin Steppan wrote:

      A fundamental methodological caveat of this article is the date / season of sample collection. Breakthrough infection samples were collected in the sprjng-summer period of 2021 only (apr-jul), whereas unvaccinated samples seem to be predominantly from fall / winter 2020 (apr-dec). It has been shown in many studies that sars-cov-2 virions are temperature-sensitive and less active / infectious in warm environments. Hence, the results of this manuscript may reflect a seasonal pattern in infectivity. The authors may want to control for this statistically by either (1) using a matched design of samples from similar dates; (2) include historical temperature data for the Netherlands as a covariate / proxy for this likely bias. Due to this reason, the analyses in their current form do not rule out this bias, which casts doubt on the authors' implicit hypothesis that vaccination status moderates the link between viral load and infectiousness.

    1. On 2021-08-26 11:54:58, user Gubbedefekt wrote:

      Can someone confirm: what difference did it make if the natural immunity was acquired from a delta variant infection compared with one from another variant? Did the study look at this?

      In any case the comparison looks devastating for Pfizer and other vaccine producers.

    2. On 2021-08-26 18:20:25, user thestreetlawyer1 wrote:

      Love to see this peer reviewed. Been really trying to determine what is the best move for me. Hard to put all the dogma and peer pressure aside (from both sides). I'm curious how this data reckons with u.s data on hospitalizations, seems most of our hosp cases are unvaccinated.

    3. On 2021-08-28 19:52:31, user Catriona wrote:

      “ individuals who were previously infected with SARS-CoV-2 and given a single dose of the BNT162b2 vaccine gained additional protection against the Delta variant.”

      I’m confused. Didn’t your study show no significant difference for symptomatic infections in previously infected individuals with or without a single vaccination dose? Or did I get that wrong? The table says the previously infected and vaccinated odds ratio for symptomatic infection is 0.65 but confidence intervals were 0.34-1.25 and P value was 0.194.

      In which case, exactly what were they protected against? Is there some sort of clinical significance regarding a positive PCR in the absence of any symptoms? Or are you implying that individuals can have atypical symptoms that can cause them health problems but aren’t recorded as symptoms? The study didn’t look at infectivity.

      Are you claiming the vaccinated individuals were healthier in some way because they had fewer positive PCRs? Or are you claiming they did not pass on the Delta variant as often? Or was there something else that you meant by “additional protection against the Delta variant?”

      Would love some clarification on these issues.

    4. On 2021-12-24 18:05:32, user Michael Ruimerman wrote:

      Natural Immunity > Vaccinated Immunity!!! Governments should be considering EVERY unvaccinated person that has survived a COVID infection as "immunized", since they have a stronger, more robust resistance to another COVID infection.

    1. On 2021-08-27 11:08:39, user Lakesha Scout wrote:

      Most people do not understand how their immune system works, and fall back upon the inept press as their inept narratives. Antibodies do not continue long term, as such a condition would in fact prove disastrous.

      Long term immunity relies upon the creation of memory .. specifically memory B and T cells. These are the cells which identify later reemergence of a pathogen (such as SARS-CoV-2) in the body and mount a successful and rapid response to its demise.

      There are two pathways to "Active" immunity (infection, and inoculation) <br /> Also there is "Passive" immunity which occurs through such things as a blood plasma infusion from a prior infected person who has existing antibodies. <br /> Any of these three paths, can provide immunity to a pathogen.

      The false narrative being pumped by the media is that the only way to overcome a pathogen is through inoculation (vaccination).... that quite simply is not true, neither in medical sense nor in scientific sense. As a mater of medical fact, some inoculations (specifically mRNA) have been proven to enhance a pathogens capability to infect. This condition is known as Antibody Dependent Enhancement or (ADE).

    1. On 2021-08-03 22:35:32, user Gemma Hollie wrote:

      Can you advise how many pregnant women / live births / still births there was during this period. Also, for moderate to severe disease, you report 45% for the delta variant. Can you advise, is this of the total 3371 women or the 1137 admitted due to symptoms of covid? <br /> Vaccine safety for pregnant women has not been well filtered down to health care professionals, therefore the uptake of women getting the vaccine has not high. Now more women are having the vaccine, i wonder if future results of women getting moderate to severe disease will continue to support recommending the vaccine. Will you be doing another study in the near futute to update the findings? Thank you

    1. On 2021-08-04 16:08:46, user Sam Chico wrote:

      They compare raw Ct values which are meaningless in qPCR testing and must be correlated with something, e.g. a dilutions series of positive control COVID RNA at the very least. Should really be related back to viral counts using plates and plaques.

      This is very lazy research that only shows that vaccinated people can harbor detectable amounts of viral RNA, its quite a reach to say that implications of this data is to say that vaccinated people are infectious. The only way to do that without clearly and reproducibly demonstrating it is looking at the population level data.

      Its irresponsible and borderline unethical to publish data like this, the MIQE guidelines made clear what publishable qPCR data should look like. These sorts of publications undermine the impact of properly performed studies with truly actionable data. The authors should know better.

    2. On 2021-08-05 17:53:16, user Ultrafiltered wrote:

      Not even peered reviewed and yet the authors and local news stations in Dane County are promoting and reporting on this paper. That sends a dangerous message to the public that anyone can write anything and its believable/credible. Seeing the other comments here on the fallibility of the PCR test, as CDC has called out and published authoritatively along with other FDA withdrawals of rapid assay test procedures, indicates mine and their comments are just as good as this paper. The authors should remember that information is like a match, it can burn a whole lot of people if left unchecked/ unqualified / uncontrolled.

    1. On 2021-08-05 16:37:19, user circleofmamas wrote:

      So by not being vaccinated, I am reducing my relative risk of a 'severe adverse event' by 74%. And my absolute risk to become a "case" is less than 4%, and severe COVID is 0.1%.

    2. On 2022-03-09 21:24:14, user Les Funk wrote:

      Figure 1 caption contains the false statement, "Disposition is presented for all enrolled participants..." There are 1841 participants not included in the figure after dose 2: 1258 from the BNT162b2 group and 583 from the placebo group. What happened to them?

    1. On 2021-08-09 18:06:43, user MJ wrote:

      ".....assuming that baseline mitigation measures of simple ventilation and handwashing reduce the second+ary attack rate by 40%".

      Congress gave billions of dollars to upgrade schools, to properly fit them with the necessary equipment for proper ventilation/air purification. Schools have had a year to do it, yet it hasn't been done. Schools are going to be reopened in the next few weeks without proper mitigation strategies for airflow.. Schools will be a breeding ground for this virus, even scarier now that the transmission rate is triple what it was a year ago. Speaking as someone who was infected via classroom exposure, and still suffering effects from the virus, more needs to be done to protect and reduce the risk to the children and staff

    1. On 2021-12-08 00:42:55, user Sam Smith wrote:

      Summary:<br /> These data demonstrate that both heterologous Ad26.COV2.S and homologous BNT162b2 increased antibody responses in individuals who were vaccinated at least 6 months previously with BNT162b2. <br /> Ad26.COV2.S and BNT162b2 led to Similar antibody titers by week 4 following the boost immunization but exhibited different immune kinetics5. <br /> Ad26.COV2.S led to greater increases in CD8+ T cell responses than BNT162b2!!<br /> However, the durability of these immune responses remain to be determined.<br /> These data suggest different immune phenotypes following heterologous (“mix-and-match”) compared with homologous boost strategies for COVID-19.

    1. On 2021-12-08 18:41:55, user Brian Mowrey wrote:

      ~18k rapid antigen tests from before Nov 8 were added to the NICD data on November 23, and are included in the results in this update per the text.

      How many positives in the Nov 23 dump were missing sample dates? Sample dates are implied not to be "complete within the data set" per the text. Hence why receipt dates were used - but "problems have been identified with accuracy of specimen receipt dates for tests associated with substantially delayed reporting from some laboratories," again per the text.

      How many with missing sample dates were scored as "reinfections" in November? 1? 100? 1000? Delayed, non-sample-dated rapid antigen tests for summer Delta infections dumped on Nov 23 could account for the entirety of the "Omicron reinfections" presented in the update, or certainly a significant portion of them.

    1. On 2021-12-13 18:57:26, user joetanic wrote:

      breakthrough infections in previously infected

      Is this some assumption of the equality of natural immunity to vaccinations? It seems there are more antibodies generated in natural immunity, some that are external to the spike, and furthermore natural immunity seems far longer lasting than does vaccination.

      So from whence does this belief come?

    1. On 2021-12-17 16:06:10, user PasserBy wrote:

      This article makes several claims of significant differences, yet does not report the statistical tests used. Given the very small sample size, it would be beneficial to know the tests used, the actual data, and the probability levels associated with the statistical test values.

    1. On 2021-12-21 11:23:13, user Shallee Page wrote:

      These descriptive data provide really useful data for thinking about LC and the visualizations are good.

      It seems like there is a lot of room for more caveats for this self-selected groups.

      The speculation about why so many tested negative for COVid seems shoddy. Primer sets are not the main problem here. There is a subset of respondents where there is little evidence that their symptoms are caused by SARS-CoV2. The number of negatives is higher than the false negative rates reported by the molecular biologists. Consulting some would be wise because I think timing of virus load is much more likely to be the problem than some primer pair problems that tests suffered from in early 2020.

    1. On 2021-12-22 18:19:23, user Kurt the Turk wrote:

      I hope the post boost samples can be made available to the Emory lab to show neutralization of live viruses. That would really complete the picture.

    1. On 2021-12-23 08:00:42, user Patrick Bowen wrote:

      This study did not control for vaccination status or prior infection. Their findings could be entirely due to these factors.

      “Some of this reducton is likely a result of high population immunity.”

    1. On 2021-12-23 12:09:50, user Matthew Nelson wrote:

      This is a superb paper, especially the careful approach to CNV calling and the Bayesian methods used throughout. Searching through the supplementary material, there is one important piece of the story that appears to be missing. Where are the counts of de novo missense, PTV, and CNV mutations per gene? These were nicely captured in the Satterstrom and Kaplanis NDD publications. These are really important for understanding potential population sizes for prioritizing therapeutic discovery and development. Have I missed them?

    1. On 2021-12-30 16:39:32, user Igor Chudov wrote:

      Very interesting article!

      Could you please clarify something for me.

      You say "Moreover, the magnitude of Omicron cross-reactive T cells was similar to that of the Beta and Delta variants, despite Omicron harbouring considerably more mutations. Additionally, in Omicron-infected hospitalized patients (n = 19), there were comparable T cell responses to ancestral spike, nucleocapsid and membrane proteins to those found in patients hospitalized in previous waves dominated by the ancestral, Beta or Delta variants (n = 49).".

      This is great, but no Covid vaccine generates or in any way is related to "nucleocapsids" or "membrane proteins". If so, is the mentioned T-Cell reaction to nucleocapsids somehow related to vaccination? Covid-naive vaccinees never come in contact with "nucleocapsids".

      Were the nucleocapsid T cell reactions only in the covid-recovered?

      A clarification would be greatly appreciated. Thank you very much.

    1. On 2021-12-31 07:47:11, user eriugena wrote:

      The current stats in countries like Ireland show 1/3 to 1/2 people testing positive every day. Ok, the PCR test - putting it mildly - is imperfect. However, we can take it using very simple math that 100% of the population is infected within a week. End of "pandemic".

    2. On 2022-01-10 20:48:26, user Siguna Mueller, PhD, PhD wrote:

      Dear authors,

      Thank you for providing these important data. I am afraid I cannot see how you actually arrive at your conclusion. Can you please help me understand:

      1. How did you actually know people got infected - with the respective variant? You state that cases were identified by “by whole-genome sequencing or a novel variant specific PCR test targeting the 452L mutation.” How many were verified by the former? As for the PCR test, can you please comment how your modifications overcome the limitations as recently announced by the CDC when withdrawing its EUA (https://www.cdc.gov/csels/d...? "https://www.cdc.gov/csels/dls/locs/2021/07-21-2021-lab-alert-Changes_CDC_RT-PCR_SARS-CoV-2_Testing_1.html)?")

      2. Can you say more how VE relates to individual people rather than the numbers that your results and conclusions are based on? You seem to draw your conclusion on statistical means alone. Yet, the average person just does not exist. Moreover, your analysis involves huge standard deviation values.

      3. You say that in the first month already, for some, VE is only 23.5% or even -69%, for vaccination with the Moderna or Pfizer vaccine respectively. How is this supporting your conclusion, please? Are you suggesting more repeated boosters than every month? What would that do to the already minimal or even negative protection? How could a repeated and ongoing “negative protection” – meaning that the vaccine causes an increased risk of infection - as experienced by some (Moderna), suddenly become positive and even truly protective?

      4. You also say that VE is re-established upon revaccination. I am afraid I do not see the results. All I see is numbers – which are less than encouraging: the for the BNT162b2 vaccine: 54.6%, 95% CI: 30.4 to 70.4%. Even if for many the VE may be 54%, this does not mean that VE is re-established. But perhaps the data supporting the VE are still missing? I cannot find details supporting your assertion. The legend to the Table states that there was “[i]insufficient data to estimate mRNA-1273 booster VE against Omicron.” Yet, I am having difficulty finding the data that would support your conclusion that VE is reestablished for revaccination with the Pfizer vaccine. Actually, both the Figure and the Table show the same details for both vaccines under consideration. I am afraid I don’t see anything in your manuscript as to why there are more data for Pfizer, and why these would support your assertion.

      5. Your methods section describes that unvaccinated individuals were followed up from November 20th. Unfortunately I do not see any specific outcomes for the unvaccinated. Your data in the Table and Figure list vaccinated persons only.

      6. Can you please further explain how VE is calculated? Is zero efficacy relative to those who were unvaccinated? Yet, in the Results section you say that, relative to the booster you used “those with only primary vaccination as comparison.”

      7. Further, when assessing the effect of boosters, you state that your “analysis [is] restricted to 60+ year-olds.” Yet, as stated in the beginning of the Results section, the median age of those infected with Omicron by December was 28 years. Why are you suddenly shifting to a different population group when analyzing boosters?

      8. You suggest that the “negative estimates in the final period arguably suggest different behaviour and/or exposure patterns in the vaccinated and unvaccinated cohorts causing underestimation of the VE.” While behavioral issues may indeed impact the outcome of your analysis, your data are not merely negative in the final period. Moreover, for Moderna, there were obviously always some individuals for whom the VE was indeed negative. By contrast, for Pfizer, during the first month at least, VE was in the non-negative range (larger than 23.5, that is). So, it cannot be behavior alone. Else, how could there be such a drastic difference between Pfizer and Moderna (23.5 versus -69.9)?

      9. Cases of reinfections are exploding for both vaccines, for Omicron but also Delta, in an exponential way (as seen in the Table). Moreover, the negative entries in most of your points of analysis, makes me wonder how VE relates to individual patients? Other than in the 1-30 day group for Pfizer and Omicron, each of the other points contain individuals that obviously are more susceptible to infection once they have been vaccinated. Can you say more about those, please? You say that “VE was calculated as 1-HR with HR (hazard ratio) estimated in a Cox regression model adjusted for age, sex and geographical region.” From your data it is apparent that there are many in your study population who experienced negative VE. They are obviously a large proportion, and according to your VE calculation, apparently not isolated cases only. It instead seems as if those with negative VE comprise entire groups of individuals, stratified according to your analysis. Who are they? Are these the elderly, the immune-compromised, or who else?

    1. On 2022-01-03 14:25:00, user sad wrote:

      The disrespect of these French researchers for international efforts of genomic surveillance is astounding. GISAID explicitly requests that all providers of sequences analyzed be credited, and a collaboration is encouraged. None of this happened here. <br /> And they dare name a variant based on a hospital acronym despite the Pango designation. Just mediocre and sad… Luckily other countries are more respectful.<br /> A proper analysis would have also estimated the emergence date with confidence intervals (not as done here) and the growth dynamics of the lineage.

    1. On 2022-01-04 18:02:40, user Barbara A. Zambrano wrote:

      What do the 21 “uncomplicated pregnancies” mean with respect to the babies, and how does this differ from the 29 who delivered healthy babies? Were the 21 babies born from uncomplicated pregnancies also healthy???

    1. On 2022-01-05 17:26:08, user Terry Baines wrote:

      I greatly appreciate this effort of trying to analyze the unique challenges which Tribes and Tribal members in managing COVID-19 when confounding social, medical, and community issues are involved. With the complex challenges Tribes face, unique and robust solutions need to be devised. Thank you for those efforts; I would love to see more like it.

    1. On 2022-01-06 12:47:12, user Anonymous wrote:

      As far as I know that delta variant doesnt have the Deletion at 69 and 70. Yet the Taqpath kit gave sgtf s gene target failure for 8 delta variant samples. This shows that the kit is not a foolproof kit and rather has many issues which is why it was taken out from the market when it started giving false negative results during the alpha variant breakout. Also the authors have conveniently kept mum and skipped over the fact of these questionable 8 delta variant positive cases.

    1. On 2022-01-07 19:58:49, user Clive wrote:

      Hi, please correct me if I'm wrong, but reading this study I'm not seeing any comparison to the baseline population that has not contracted COVID. If, as I'm sure you're aware of, a broader worsening of health conditions has increased across the population during the time frame of this study, could the data be misrepresenting a change to the mean in both the vaccinated and unvaccinated groups. For a specific example, I've heard anxiety rates have tripled since the start of the pandemic across the population, and if that pattern was ongoing at the time of this study could the study be overestimating the increase in anxiety among both vaccinated and unvaccinated groups, as everyone, not just those who contracted COVID, experienced an increase in anxiety?

    1. On 2022-01-08 19:16:50, user madza wrote:

      Excuse my ignorance but when SAR % is lower in unvaxxed than in vaxxed, how come the Conclusion is that vax reduces the transmissibility?

    1. On 2022-01-09 17:21:03, user Kevin McKernan wrote:

      You should test if the primers light up on SARs-CoV-2.<br /> With the high break through rate, People want to differentiate vax from C19. Would also be interested to know if SARs-CoV-2 also ends up in the lipid fraction. I suspect not. The heavy methylation of these RNAs changes their lipophilicity.

      Longer testing window would help answer some questions.

      Thank you for putting the primers public.

    1. On 2022-01-11 20:23:50, user Sam Smith wrote:

      What is the optimal RH = relative humidity for health? Too dry air increases covid risk because it is not healthy for your airways.

    1. On 2022-01-12 17:54:37, user Martha Metevelis wrote:

      I am blown away with the similarity to PCS and toxic B6 symptoms I have endured for over three years. I and many others are often dismissed as just suffering anxiety and told thatour symptoms are not real. Many of us rely on a face book site called exploring b6 toxicity for support and share our experiences and what helps. Being ignored and unfairly labeled is the norm. Suicide has occurred with those unable to cope with what becomes a debilitating issue. We experience insomnia, intense pain, sensory and mobility issues, tinnitus that is unbearable, facial pain, anxiety off the chart,vision changes,peripheral neuropathy,swallowing issues, palpitations, internal and extremity tremors, brain fog, memory loss, hair loss to name a few. <br /> I am anxious to know if the subjects involved in your research have vitamin n6 levels checked and if they are taking more than rda of b6 in any form.<br /> I pray that we all get answers soon. The vitamin I took contained 75 mg of b6! And was suggested by my physician. I had been 100% healthy! This upended my life. <br /> I know exactly how long haul suffers feel and hope my input leads to a solution. Thanks for listening.

    1. On 2022-01-13 15:00:50, user Wendi wrote:

      This is fascinating because early on a common theme of discussion in some only support groups was that of how covid seemed to have altered one's body odor.

    1. On 2022-01-17 11:18:12, user Free Man in London wrote:

      This is another Coke vs. Pepsi paper. There are only 2 conditions in this paper: vaccinated vs. unvaccinated. There are multiple conditions: vaccinated with supplements, unvaccinated with supplements Vitamin D, Quercetin, Melatonin, unvaccinated with supplements quercetin and zinc, etc. The paper prima facie is interesting but devoid of an answer to the real underlying question: are supplements more effective than the vaccines? Moderna and pfizer are more interested in keeping the question framed around simply 2 conditions. Until we force a re-framing to the way this effectiveness question is answered, we are not really solving the problem of stopping the virus. That said, omicron seems to be doing that quite well on its own.

    1. On 2022-01-18 16:19:10, user NoSafeSpaces wrote:

      Perfect information on who received a vaccine versus imperfect information on who got COVID. Add in a side of everyone gets the vaccine and not everyone gets COVID with a dash of some of the people getting the vaccine have natural immunity from COVID, and you get a weak justification for putting your children at risk because you don't understand bad assumptions.

    1. On 2022-01-31 18:32:19, user Jared Roach wrote:

      These are very minor comments about the wording of the Abstract that I would make if I was reviewing the paper:

      "strikingly different"<br /> I would delete the vague adjective "strikingly" as it could be interpreted many different ways. Rather insert the exact number of mutations or some similar quantitative metric.

      "rapidly replaced"<br /> maybe OK to leave "rapidly", but also add in a sense of how long (e.g., over a period of 3.5 weeks) - or whatever the number of weeks was.<br /> "rapidly" makes sense only in context of other strain replacements such as Alpha-> Delta or Delta-> Omicron. If it isn't much faster than these, I would use an exact time rather than the comparative and vague adjective "rapidly"

    1. On 2022-02-04 18:46:24, user asciguy wrote:

      Thank you for the new vocabulary word. I should have noticed ‘inflammasome’ by now in “Laboratory Medicine” but must have missed it somehow.

    1. On 2022-03-22 03:17:02, user ST wrote:

      The scientific article was very intriguing, and the abstract sparked my interest when the link between detecting changes in the gut microbiome and concussion diagnosis was made. The introduction was informative and included different helpful statistics on football players and the number of concussions they may receive in a singular football season. <br /> The PCR target region was the full 16S gene (V1-V9). The reason why the authors sequenced the full gene rather than the more common use of one region (i.e. V3-V4) should be included. A strength of the paper is that the scientists included the number of PCR cycles, however, 35 cycles is quite high. The higher the cycle number, the more errors that can be produced (Sze & Schloss, The impact of DNA polymerase and number of rounds of amplification in PCR on 16S rRNA gene sequence data 2019). This should be listed as a potential study limitation. PCR primers were not specifically listed and should be included in the methods section to ensure replicability. IF part of the Barcoding Kit, that should be stated as well. The scientists did state that there were problems with the ONT primer but there should be follow-up discussion of Bifidobacteriaceae taxa found in this study, if any. No quality controls/filtering steps for the sequences (such as removing low quality sequences and chimeras) were included. The scientists do not analyze specifically dominant and rare taxa. Given that microbial communities are highly dominated and uneven, analysis of the dominant taxa alone can be revealing, since metrics using all taxa can be strongly affected by the very numerous but low abundant rare taxa. The rare and dominant taxa of environmental pathogens are mentioned but what does this mean for the microbes found in the oral cavity and the gut? I suggest that bioinformatics should be performed on dominant as well as all taxa. The scientists do include rare taxa abundance in three of their figures to show the abundance of the different microbes found in fecal samples and salivary samples. I thought that the description of the sampling was good but there could be more of a description of what was in the tubes for collection? Were buffers used? What specific tubes were used? Were the samples taken straight to the lab? It would also be helpful to say what kit the tubes were from before stating that a collection tube and funnel were used. The fecal sample and saliva sample collection were described well but I think that scientists should make saliva sample collection have its own paragraph. One flaw of the article is that the scientists never discussed variance in 16S copy number and genome size in bacteria, which affects abundance data of 16S profiles. Were sequences binned or clustered before identification with Kraken? A rarefaction curve would be beneficial to include, and also sequencing coverage measures, such as Good’s coverage and Chao1 compared to observed OTUs. The article should include internal standards for PCR, DNA extraction, and sequencing. These internal standards may include utilizing a negative control, a strain grown in the lab, running a gel, and utilizing a known DNA sequence. I would like to comment that DNA extraction and amplification should be in the same section as I was a tiny bit confused when I read amplification in the sequencing section. The best option for readers would be to list the methods performed in chronological order. The sampling strategy is very well described and figure 1 demonstrates the samples collected as well as a visual representation of the collection strategy. The scientists discuss the number of classified reads for the samples but the number of reads per sample is not stated. Additionally, the study does not include any methods that quantify total bacterial numbers (16S community sequencing is normalized and only contains relative abundance data, not absolute abundance). <br /> Authors should include the specific parameters that were utilized when the samples were vortexed for replicability. Additionally, the stool and the saliva samples were stored at room temperature, and this needs clarification as storing the samples at room temperature for a long period of time may invalidate the experiment. The amount of time that the samples were stored at room temperature needs to be added for clarification. The specific statistical test that is done in figure 2e should be clearly stated. Data that was collected in this experiment could be compared to The Human Microbiome Project.<br /> The optic nerve sheath should be better explained, and it would be beneficial to know what is normal without a concussion and with a concussion. The relationship between the optic nerve and concussions should be better explained so the reader understands its significance.

      Overall an interesting study! Thank you!

      -Sydney T.<br /> #SHSU5394

    1. On 2023-01-13 11:35:49, user SB wrote:

      Hi, thanks for the preprint.<br /> I do not understand the last sentence of the conclusion "Individuals with hybrid immunity had the highest magnitude and durability of protection against all outcomes". That's because the results section pointed out: "Against reinfection at 6 months, there was similar protection from HE with first booster vaccination (effectiveness 46·5% [36·0-57·3%]), HE with primary series (60·4% [49·6-70·3%]), and prior infection alone (51·2% [38·6-63·7%]), with all three types of immunity conferring significantly greater protection than primary series vaccination alone (15·1% [11·3-19·8%]) or first booster vaccination alone (24·8% [18·5-32·5%])"<br /> So the protection against reinfections seems to be for hybrid immunity NOT OVER then for other types of immunity.

    1. On 2024-02-26 17:17:59, user Ciarán McInerney wrote:

      The sensitivity analysis is<br /> commendable. If I understand your logic correctly, the 20% inaccuracy in<br /> clinical coding informs a random 20% reclassification of cases and controls. To<br /> commit to this logic, all +19-thousand clinical codes also need to be randomly<br /> reclassified because there is no reason to assume that only the clinical coding<br /> for cancer is inaccurate in 20% of your sample.

    1. On 2020-07-04 07:47:05, user Martijn Hoogeveen wrote:

      The updated re-submitted pre-print clarifies the methods more in detail, the definitions used, provides a somewhat more expanded review of COVID-19 & meteorological variables, and log10 transforms seemingly logarithmic datasets. Conclusions are the same, though here and there more cautiously formulated.

    1. On 2022-02-03 21:28:46, user Bruce Futcher wrote:

      Here, as with other vaccines, titres against omicron are only about one-tenth as high as against the vaccine strain. There is no indication of this central fact in the title or the abstract. There is no indication here that this vaccine is relatively better against omicron than is any other vaccine.

    1. On 2022-02-05 13:34:23, user GregoryGG wrote:

      Hello,<br /> I saw an error after posting my comment, so I post it again because I do not see it, my apologies in advance if it was ok.

      Unless I misunderstood :

      1)<br /> How can you guarantee that the people's behaviour (over-confidence of vaccinated people) , the transmission prevention mesures and the testing entry rules were the same between <br /> A) delta and omicron<br /> B) vaccinated and unvaccinated people. <br /> => this could impact ratios like the positive rate of a group.

      2)<br /> Assuming that immunity against a specific variant diminishes over time, can we still considered single- double -dosed people as still immunised. <br /> Could they be considered as non-vaccinated after a given time?

      Thank you

    1. On 2022-02-09 21:44:37, user Xin Wu wrote:

      Since this preprint published in 2020, (1) the CDC changed its mask guidance from wearing face coverings to protect others to wearing proper masks to protect you and others on Nov, 2020, and suggested wearing N95 and KN95 in later 2021 and 2022; (2) the White House Coronavirus Task Force reported some covid-19 strategies were compromised in many places on Dec. 2020; (3) More articles were published regarding patient isolation and contact tracing problems; (4) More covid-19 dashboards monitoring health care capacity were created; (5) free N95 masks to public from government in 2022; (6) COVID lockdowns had ‘little to no effect’ on mortality rate, study says (https://sites.krieger.jhu.e... "https://sites.krieger.jhu.edu/iae/files/2022/01/A-Literature-Review-and-Meta-Analysis-of-the-Effects-of-Lockdowns-on-COVID-19-Mortality.pdf)"). This paper discussed all of these issues with Table and figures.

    1. On 2025-10-18 15:00:12, user Evolutionary Health Group wrote:

      We at the Evolutionary Health Group ( https://evoheal.github.io/) "https://evoheal.github.io/)") really enjoyed this paper.

      Here are our highlights:

      The combined biotic/abiotic approach can guide resource allocation, outbreak management, or pollution mitigation efforts specific to each region's exposure landscape.

      Abiotic signatures help to identify the cause of biotic signals which could be driven by infectious disease outbreaks or changes in human hygiene, diet, or mobility.

      This study supports a much larger-scale spatiotemporal range than most wastewater epidemiology efforts enabling the evaluation of seasonal shifts, regional differences, and post-pandemic changes in microbial and chemical profiles.

      Wastewater surveillance has typically been a reactive infection-tracking tool. Continuously mapping exposures, as performed here, can identify risks before they manifest clinically, supporting not only intervention but prevention.

    1. On 2022-02-15 21:25:00, user Cabeça Livre wrote:

      Introduction

      The spread of a novel infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the first epidemic wave. The point of transition between phases I and II is known as the herd immunity threshold (HIT) [...]

      Did you mean "between phases II and III"?

    1. On 2022-02-17 20:37:35, user RT1C wrote:

      Please consider correcting the following: "To adjust for this, we defined the proximate overt immunologic challenge (POIC) as the most recent exposure to SARS-CoV-2 by infection or vaccination." The vaccine does not give SARS-CoV-2 exposure. Thus, as written this is confusing and incorrect.

    1. On 2020-03-22 16:58:48, user Peterson Biodiversity Lab wrote:

      Unsolicited peer review …

      Comments on “Spread of SARS-CoV-2 Coronavirus likely to be constrained by climate”<br /> Comments offered by A. Townsend Peterson, University of Kansas

      I read the above-referenced manuscript preprint with interest. Araújo and Naimi are leaders in the field of distributional ecology, so I was (and am) interested in their perspective on the distributional ecology of SARS-CoV-2, and the COVID-19 disease that it causes. Obviously, the question is quite current, such that I’m interested in the topic and the ideas, but also in getting answers that will prove robust and predictive. For this reason, I take the rather odd step of offering a peer review, even though no one has asked for it…

      My interest in this manuscript was piqued most of all by the statement in the Abstract that “the disease will likely marginally affect the tropics.” If true, this would be an interesting, and quite promising and optimistic result, as many are concerned about what will happen when SARS-CoV-2 begins to spread in Southeast Asia, Oceania, sub-Saharan Africa, Latin America, etc. So I will focus my comments on this result and the assumptions that revolve around it.

      PRESENCE DATA<br /> The occurrence data in the analysis were derived from available COVID-19 case occurrence data. “Coronavirus cases by the 10/03/2020 with data compiled and made available to the John Hopkins University Mapping 2019-nCoV portal... Regions with fewer than 5 positive cases were not included in the models. Exclusion of such sites was based on the working assumption that sites with small numbers of positive cases are likely imported from infected regions, thus failing to provide evidence that the SARS-CoV-2 Coronavirus is being transmitted locally within its ecological niche.” And also, in the Discussion of the manuscript… “Firstly, there is little reason to suspect that out-of-China contaminations would have occurred only, or mainly, with trade partners in the northern hemisphere... China is a big world player, having key commercial partnerships with Africa and Latin America. Yet there is not indication that meaningful local infections have taken place in these areas despite the global reporting of Coronavirus cases generally attributed to travelers coming from infected regions.”

      This seemingly logical methodological step has rather important implications. It is true that many of the “singleton” occurrences will represent imported cases that were the result of infection taking place in early foci of infections (e.g., central China, Italy) and being taken to those places by travelers. In that sense, this methodological step is reasonable and logical. However, one should consider some important sources of bias that are likely associated with elimination of regions with few records…

      1. Connectivity is nonrandom. That is, consider Wuhan, in central China. Check out the airline network connectivity visualizations shown in http://rocs.hu-berlin.de/co.... Its primary connections are all to northern, mesic, and temperate regions, and not at all directly to tropical and arid regions. Indeed, even given that major desert regions lie not too far to the west of Wuhan, they are not densely populated, such that land-based connections are also mostly to the east, and not to desert or tropical regions.

      2. Testing bias. The relative unavailability of testing for COVID-19 cases has been commented extensively, even in the United States. The lack of testing clearly has resulted in broad (but silent) spread of COVID-19 prior to recognition of the broader extent of case distributions, as has been documented in Washington State, a COVID-19 focus in the western United States. With developing-world public health infrastructures being challenged with other, perhaps more pressing and immediate questions (e.g., dengue, malaria), COVID-19-caused respiratory problems and a few deaths from some pneumonia syndrome of unknown cause can easily go unrecognized. As COVID-19 testing becomes easier and faster, and the possibility for point-of-contact testing becomes a reality, I strongly suspect that many more tropical/humid cities will emerge as additional sites of viral transfer and COVID-19 infection.

      ABSENCE OR BACKGROUND DATA<br /> The authors appear not to have provided any information about the region over which they calibrated and evaluated their models (I will not go into problems with ROC AUC that are well-known, and do not need restating). This choice is well-known to make important differences in modeling outcomes [see Anderson, R. P., and A. Raza. 2010. The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela. Journal of Biogeography 37:1378-1393.]. Indeed, the calibration region should be a combination of the area that has been accessible to the species over relevant time periods, and the area over which sampling was conducted (Barve, N., V. Barve, A. Jimenez-Valverde, A. Lira-Noriega, S. P. Maher, A. T. Peterson, J. Soberón, and F. Villalobos. 2011. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecological Modelling 222:1810-1819.).

      Not only should the calibration area and the assumptions that led to that set of choices be made explicit, but they should be made in consideration of real-world features of the system at hand. That is, if the authors indeed calibrated their models at global extents, then that is a tacit assumption that the virus had had access to the entire Earth’s surface, but only “liked” (in a niche sense) the places where >5 cases have been manifested. At least in the early stages of this epidemic, this assumption clearly is not robust, and will bias the model results against the suitability of humid tropical areas. A better approach might be to take primary and perhaps secondary linkages of air and land transportation, and to use them to create an accessible area hypothesis that responds better to the actual phenomenon at hand. Such a more conservative estimate of an accessible area might well reveal that hot and humid sites were not available to SARS-CoV-2 given realistic hypotheses of the dispersal potential of the virus, and the resulting conclusions about the distributional potential of the virus would likely be quite different.

      CONCLUSIONS<br /> The authors interpreted the importance and significance of their results thus: “… it appears the virus favors cool and dry conditions being largely absent under extremely cold and very hot and wet conditions.” And… “Much of the tropics have low levels of climate suitability for spread of SARS-CoV-2 Coronavirus owing to their high temperatures and precipitation (used here as a surrogate for humidity), followed by polar climates, where conditions of extreme cold temperatures seem to be beyond the virus critical minimum tolerance values. In most of such low climate suitability areas, human populations will likely be spared from outbreaks arising from local transmissions...”

      Very simply, methodological decisions were made in this analysis that will lead to different conclusions. Decisions such as eliminating sites with few records, or using a global calibration area, as well as the testing bias discussed above, all align in leading to overfit models that will snug overmuch to the areas and environmental regimes where cases have already occurred. I do not think that the conclusions about low tropical/humid suitability are likely to prove robust, and I do not know enough about the conclusions of seasonality (which I have not discussed or assessed above).

      Town Peterson

    1. On 2022-02-19 00:11:02, user Sam Smith wrote:

      Breakthrough cases were defined only from day 8 (in each arm as well as in the control group), to exclude early infections due to exposure before vaccine is effective.

      Was 8 days too early?

      Was control group a good idea, instead randomly been given a vaccine or not be given a vaccine?

    2. On 2022-02-19 17:39:42, user Zywicki wrote:

      Are the Supplementary Tables available? Particularly Table S4 with the breakdown of AE's. There is a Figure that summarizes it but not the raw data. I didn't see it linked here--forgive me if I overlooked it. Thanks.

    1. On 2022-02-21 00:22:33, user consalg wrote:

      Log0=1, not zero. That distribution is discontinuous. Shouldn’t you recalculate means without counting in the samples that produce no foci?

    1. On 2025-11-30 16:56:07, user Cyril Burke wrote:

      RESPONSE TO REVIEWER #1

      June 27, 2022<br /> Re: Longitudinal changes in creatinine signal early decline in glomerular filtration rate without consideration of age, sex, ‘race’, and nationality

      We greatly appreciate that the reviewers were thorough, fair, and helpful in their comments.

      Comments to the Author

      Reviewer #1: Burke et al submit a somewhat unusual paper, devoted to a topic of potential major clinical relevance, and as yet understudied.

      General comments

      1. The thesis of the authors, that using the baseline serum creatinine of a given patient would potentially improve the earlier diagnosis of kidney disease, even in the normal range, is in line with the experience of this reviewer, who always retrieves, whatever the difficulty of reaching that goal, past results of blood tests, and uses them as a way to date the onset of kidney disease, sometimes with important prognostic implications.

      Your experience adds support to the literature suggesting that historical sCr levels provide a context for sCr changes. These benefits might encourage investments in digital data exchanges so that electronic health records (EHRs) can ease collection and presentation of sCr results from multiple commercial and hospital laboratories.

      2. Yet, the authors do not provide data strongly supporting their thesis. For instance, when looking at case 2 [now Patient 3], should the last point (the most recent one) be omitted, there would be very little evidence supporting progressive early kidney disease.

      We advocate prospective monitoring of longitudinal sCr as a proxy for glomerular filtration rate (GFR). The Cases were meant to show that charting the data and simple follow-up over several visits and months can allow general clinicians to differentiate CKD from other explanations for increased sCr. The four case histories represent patients in a non-nephrology medical practice with borderline eGFR that raised the possibility of CKD. In each of these cases, retrospective collection of sCr values suggested varied explanations for the elevated sCr, and we expect many cases will represent sCr influences other than CKD, not necessarily warranting nephrology referral. Armed with this tool, and used prospectively, Physicians, nurse practitioner, and physician assistants (PCPs) might identify and manage the 90% of patients with currently unrecognized CKD.

      3. The claim that the statistics fit the data better when all points are used (page 9,11) should not come as a surprise. Using thresholds instead of the full range of values has long been known to be more powerful for statistical analysis. But fitting the data does not equal to a high positive predictive value!

      We agree that this is counterintuitive, so we thought this was an important point to discuss. Research methods that get translated into clinical settings rely on assumptions that are not always familiar to healthcare workers. Whatever the merits of thresholding conventions, understanding their mathematical underpinnings can inform a more nuanced interpretation of lab results. The revision includes our initial, intuitive assessment of the data and the interpretation of the residuals – from a mathematics perspective. Lack of awareness about residuals can easily lead to improper interpretation of thresholded lab data. The use of statistics is not intended to document superiority of fit but rather to demonstrate how simplifications with practical clinical value may gloss over clinically relevant information in some cases. The inclusion of additional charts seeks to take it away from abstracted statistics and toward more intuitive clinical concerns. We favor early diagnosis of kidney injury through investigation of nonspecific changes in longitudinal sCr. This method seems usable and may be manageable by PCPs using a time frame of several visits over several months to separate false positives, which may be influenced by chance attributable to the mathematical properties of lab data.

      4. A key question is whether in a real-world context, the earlier diagnosis of kidney disease would be possible, without too much background noise from intercurrent illness (functional), drugs (NSAIDS, etc.). In other words, would the specificity (or PPV) of the suspicion of early kidney disease be reasonable enough to catch the attention of clinicians

      We think so. We believe longitudinal serum creatinine (sCr) will encourage dialogue between patients and clinicians, raising awareness of the importance of avoiding kidney injuries that often happen out of sight and out of mind until, for far too many, culminating in urgent dialysis. In the same way that patients now ask for their blood pressure, we anticipate patients tracking their own sCr and kidney risks. Decades after introduction of the mercury sphygmomanometer, PCPs learned how to manage blood pressure to improve health. We believe longitudinal sCr can soon be a widely used tool because the concepts are old, there is a broad literature supporting this approach, and the value can be enhanced by more frequent testing of sCr. This is what PCPs do – sort the random cough, costochondritis, or stress response from nascent pneumonia, angina, and hypertension. PCPs already worry about the kidneys. They may welcome a tool to accompany the chest radiograph, electrocardiogram, and sphygmomanometer.

      Of interest, the decision analysis by den Hartog et al found markedly more false-positive diagnoses of CKD with eGFR than with serum creatinine alone.

      5. Even though there has been improvement in the standardization of measurement of serum creatinine (IDMS), the comparability of results measured by different labs remains suboptimal, at least in the experience of this reviewer, and medical shopping is not uncommon, making the availability of all previous results in the same graph a logistical challenge.

      We share this concern, which laboratorians have wrestled with for many years and will not be solved soon. However, we propose utilizing the maximum serum creatinine (sCr-max) to smooth the variability of these inputs (as well as the variability from patient diet and hydration). One laboratory will be the highest, and when patients use multiple laboratories, one laboratory may more often define the sCr-max. As patients learn the rationale for using the same lab, we believe most (not all) will voluntarily use one or perhaps two labs (as they mostly do when we repeating longitudinal MRI imaging studies, for example). The sCr-max reduces the effect of variability between laboratories, allowing clinical insights even without future improvements in sCr assays.

      Australia, Canada, and the United Kingdom have stricter sCr analytical performance goals than the United States, which could improve its sCr comparability by matching their standards.

      Specific comments

      1. The authors should mention that the USPTFS decided a month ago to revisit the question of screening for kidney disease in high-risk groups (page …)

      One reference stated that this initiative has not been announced publicly but is “under active consideration” by USPTFS because “…for a screening to help people live longer, healthier lives, clinicians must be able to treat the condition once it is found. The existence of effective treatments is one of many important factors that the Task Force considers.” This perspective is surprising because it ignores the potential of effective prevention by avoiding NSAIDs, hypotension, dehydration, and nephrotoxic medical treatments (e.g., aminoglycosides). We, too, look forward to updated findings from USPTFS.

      2. Even though ESRD has a legal meaning in the USA, not very relevant to the topic of this paper about early kidney disease, the authors should stick to the nomenclature proposed by a recent KDIGO consensus conference (see Levey et al. Nature Reviews in Nephrology). In particular, use kidney failure instead of ESRD/ESKD. When the topic is glomerular filtration, use that wording instead of kidney function (page…)

      We have adopted this terminology and would welcome any further recommendations.

      3. The authors allude to the concepts of prediabetes and prehypertension. But this reviewer points to the fact that the levels used to define those entities are currently “generic”, rather than based on previous values in an individual subject. Please discuss.

      We understand that the normal population ranges for serum glucose and blood pressure are narrower, with less interindividual variation, so population reference ranges work well for monitoring diabetes mellitus and hypertension. Unfortunately, this is not true for serum creatinine, though within-individual reference of longitudinal sCr appears to facilitate diagnosis of pre-CKD.

      4. The authors repeatedly mention in the discussion section evidence that even small increases in serum creatinine have prognostic significance. This has indeed been known for decades but is a different topic: AKI. Admittedly, there is growing evidence that AKI and CKD are linked. But that the stability of a biological parameter is prognostically best is all except surprising: the same is true for body weight, mood, blood pressure etc.

      We agree that AKI and CKD appear to be merging and this may become clearer from more frequent sampling and charting of longitudinal sCr. What has been missing is graphical representation of the data to allow quick assessment for CKD in long-term trends, and this may soon be obtainable from EHRs and IT departments, which should end the practice of deleting historical data of value to longitudinal analysis.

      [See next comment for Response to Reviewer #2.]

    2. On 2025-12-01 00:10:43, user Cyril Burke wrote:

      [Note: This is the third of several rounds of review of an earlier version of our combined manuscript, aiming to reduce ‘racial’ disparity in kidney disease. The comments were kindly offered by nephrologists, through a medical journal, and we remain grateful to them for the time and care they gave to improve our manuscript.

      We removed identifying features and included our response, at the end. The changing title and line numbers refer to earlier versions.]

      October 10, 2022

      Dear Dr. Burke III,

      REDACTED.

      Editor: The re-revised manuscript is further improved. However, it remains the main issue of the extremely length of the manuscript, as highlighted by both Reviewers, that precludes me to accept this paper in the present format. I could offer you the possibility to shorten the manuscript just focusing on what you define “Part One” plus “section A of Part Two”. You can briefly address the “race” issue in the discussion. The full content of “Part Two, section B”, “Part Three” and “Part Four” could be for another manuscript.

      REDACTED.

      Reviewer #1: The authors have improved the readability of their paper, which remains however very lengthy! As part one is important and should trigger further studies, after reading the comments of reviewer 2 , I am ready to recommend acceptance, leaving of course the final decision to the Editor in charge of the paper

      Reviewer #2: Thank-you for the opportunity to review this manuscript- which raises some important issues.

      As in round 1 of reviews it is still this reviewer’s opinion that the manuscript is too lengthy and covers such a large range of topics that the scientifically meaningful points are lost in the commentary/ perspective style of the manuscript and lack of robust evidence. This concern was shared with the editor in round 2. To quote the editor in round 2:

      “… the authors need to drastically shorten the manuscript focusing on the main key message. Please consider that the race part is irrelevant for the key point (race does not change over time, and thus is not relevant when looking at longitudinal serum creatinine or eGFR) and should be deleted.”

      Instead of drastically shortening the manuscript the authors have added to the length thereof. The manuscript (without figures) is now at 77 pages! In round 1 and 2 the manuscript was 27 and 67 pages respectively. This reviewer has chosen not to provide further comment on the new additions to the manuscript.

      524 – 527. Once again, this reviewer in no way questions the often-overlooked inaccuracies in mGFR methods. However, the authors cannot quote a well conducted review which shed light on the methodological bias and imprecision which exists between mGFR methods and claim that this methodological bias is “physiologic variability”. The authors should review: Rowe, Ceri, et al. "Biological variation of measured and estimated glomerular filtration rate in patients with chronic kidney disease." Kidney international 96.2 (2019): 429-435. Intra-individual variation (CVI) for serum creatinine ranges from around 2.8 – 8.5% while cystatin C ranges from around 3.9 – 8.6%, inter-individual variation (CVG) of serum creatinine: 7.0 – 17.4% and cystatin C: 12 – 15.1%. Biological variation (CVI and CV¬G) are not the same as analytical variation, which also exists for serum creatinine and cystatin C. The author’s statement is not backed up by scientific evidence.

      It is this reviewer’s opinion that this manuscript is unpublishable as a research article, due to the authors unwillingness to shorten and focus their work. This is a shame as the main point of the article, although difficult to decipher, is highly relevant.

      RESPONSE TO EDITOR AND REVIEWERS

      December 1, 2022

      Early detection of kidney injury by longitudinal creatinine to end racial disparity in chronic kidney disease: The impact of race corrections for individuals, clinical care, medical research, and social justice

      Editor: The re-revised manuscript is further improved. However, it remains the main issue of the extremely length of the manuscript, as highlighted by both Reviewers, that precludes me to accept this paper in the present format. I could offer you the possibility to shorten the manuscript just focusing on what you define “Part One” plus “section A of Part Two”. You can briefly address the “race” issue in the discussion. The full content of “Part Two, section B”, “Part Three” and “Part Four” could be for another manuscript.<br /> Comments to the Author

      Reviewer #1: The authors have improved the readability of their paper, which remains however very lengthy! As part one is important and should trigger further studies, after reading the comments of reviewer 2 , I am ready to recommend acceptance, leaving of course the final decision to the Editor in charge of the paper

      Reviewer #2: Thank-you for the opportunity to review this manuscript- which raises some important issues.

      As in round 1 of reviews it is still this reviewer’s opinion that the manuscript is too lengthy and covers such a large range of topics that the scientifically meaningful points are lost in the commentary/ perspective style of the manuscript and lack of robust evidence. This concern was shared with the editor in round 2. To quote the editor in round 2:

      “… the authors need to drastically shorten the manuscript focusing on the main key message. Please consider that the race part is irrelevant for the key point (race does not change over time, and thus is not relevant when looking at longitudinal serum creatinine or eGFR) and should be deleted.”

      Instead of drastically shortening the manuscript the authors have added to the length thereof. The manuscript (without figures) is now at 77 pages! In round 1 and 2 the manuscript was 27 and 67 pages respectively. This reviewer has chosen not to provide further comment on the new additions to the manuscript.

      524 – 527. Once again, this reviewer in no way questions the often-overlooked inaccuracies in mGFR methods. However, the authors cannot quote a well conducted review which shed light on the methodological bias and imprecision which exists between mGFR methods and claim that this methodological bias is “physiologic variability”. The authors should review: Rowe, Ceri, et al. "Biological variation of measured and estimated glomerular filtration rate in patients with chronic kidney disease." Kidney international 96.2 (2019): 429-435. Intra-individual variation (CVI) for serum creatinine ranges from around 2.8 – 8.5% while cystatin C ranges from around 3.9 – 8.6%, inter-individual variation (CVG) of serum creatinine: 7.0 – 17.4% and cystatin C: 12 – 15.1%. Biological variation (CVI and CV¬G) are not the same as analytical variation, which also exists for serum creatinine and cystatin C. The author’s statement is not backed up by scientific evidence.

      It is this reviewer’s opinion that this manuscript is unpublishable as a research article, due to the authors unwillingness to shorten and focus their work. This is a shame as the main point of the article, although difficult to decipher, is highly relevant.

      We totally understand that our manuscript may no longer be a good fit for [the journal].

      Although we feel the Parts work best together, in a single manuscript, we tried to make it more readable even though we could not significantly shorten it. All the suggested methods for trimming length put more work on the reader (e.g., to search original sources for the quotations we found illuminating) than simply inviting the reader to skip over paragraphs, sections, or Parts of less interest, as readers often do.

      We cut a fair amount, but then added (e.g., to the creatinine Part 2, an important section on “gold standard” references prompted by the excellent reference kindly offered by Reviewer #2). In the second and third rounds, major then less-than-major revisions lengthened the manuscript. We have now reorganized in hope of improving readability; updated the title and abstract, hoping to convey that ‘race’ is a main topic; and again, tried to respond to your kind criticisms, which we believe greatly strengthened the nephrological portion of the manuscript.

      We sincerely appreciate the Reviewers’ and Editors’ comments and criticisms, which helped to improve the manuscript. We submit this revision mostly as a final opportunity to thank the Reviewers and Editors for giving so much of their time. We thank you.

    1. On 2020-05-16 02:45:51, user Sinai Immunol Review Project wrote:

      Functional alteration of innate T cells in critically ill Covid-19 patients

      Jouan Y et al., medRxic 2020.05.03.20089300; doi: https://doi.org/10.1101/202...

      Keywords<br /> • Innate T cells (MAIT, iNT, ?? T cells)

      • Critically ill COVID-19 patients

      • SARS-CoV-2

      Main findings<br /> Innate T cells are a heterogeneous group of immune cells, including mucosal-associated invariant T cells (MAIT), NKT cells (NKT) and ?? T cells, which differ from conventional T cells based on their unique features considered characteristic of both the innate and adaptive immune system. In this preprint, Jouan et al. aimed to address the potential contribution of innate T cells to COVID-19 lung immunopathology. SARS-CoV-2 PCR-positive ICU patients, diagnosed with severe COVID-19 according to clinical symptoms, were enrolled in a prospective study on average within 10 days of disease onset, and were immunologically followed up for two weeks. Of 30 patients, 24 presented with ARDS with the need for invasive mechanical ventilation either at the time of ICU admission (n=20) or later on (n=4); to maintain sufficient systemic oxygenation, one patient further required extracorporeal membrane oxygenation (ECMO), whereas another patient succumbed to disease two days post study inclusion. By the end of the observation period, 15 individuals could be discharged from ICU, while 9/14 ICU patients remained on invasive mechanical ventilation. Similar to several recent reports, the authors observed COVID-19-associated mild to severe lymphopenia, which correlated with disease severity, as well as concomitantly higher neutrophil-to-lymphocyte ratios when compared to age- and sex-matched healthy controls (n=20). Likewise, albeit relatively low overall, plasma levels of the proinflammatory cytokines IL-1?, IL-6, IL-1R? and IFN-?2, a marker of the antiviral type I IFN response, were found to be higher in COVID-19 patients vs. healthy individuals (n=10). Of particular note, these cytokines were further increased in endotracheal aspirate (ETA) supernatants relative to whole blood samples obtained from the same patients (n=20), suggesting locally enhanced airway inflammation at the time of ICU admission. Moreover, analyzing relative frequencies of circulating innate T cells in COVID-19 ICU patients (n=30) vs. age-/sex-matched healthy controls (n=20), the authors report a profound decrease in MAIT (ca. 6-fold; identified by 5-OP-RU loaded MR1 tetramer vs. unloaded control tetramer) as well as in iNKT cells (ca. 7 fold; identified by PBS-57 glycolipid-loaded CD1d tetramer vs. unloaded control tetramer), while ?? T cell frequencies remained largely stable (with the exception of a slight decrease in the V?2 subset as well as a likely increase in the V?3 subset). Interestingly, both MAIT and ?? T cell were detected in early ETA samples of 12/21 ICU patients on invasive mechanical ventilation, whereas iNKT cells were seemingly absent. Of importance, relative MAIT but not ?? T numbers were increased in ETA specimens when compared to whole blood samples obtained from the same donors, suggesting enhanced airway recruitment in contrast to potential extravasation processes as a result of inflammation-induced capillary leakage. Accordingly, the presence of innate T cells was restricted to ETA samples containing high levels of chemo-attractive CXCL10 and CXCL12. Moreover, very basic phenotypic analysis of blood-circulating innate T cells by flow cytometry revealed increased activation based on enhanced expression of CD69 and PD-1 in COVID-19 vs. healthy controls, as well as a potential trend towards exhaustion based on continuous PD-1 expression observed after repeated sampling. Enhanced levels of CD69 and PD-1 were further associated with high levels of plasma Il-18, which has been previously linked to innate T cell activation in viral infections (https://www.jimmunol.org/co... "https://www.jimmunol.org/content/194/8/3890)"). In line with the above observations, innate T cell-expressed activation markers were found to be higher at the presumable site of inflammation as compared to peripheral circulation. Additionally, functional analysis of circulating MAIT, iNKT, and ?? T cell in COVID-19 vs. healthy controls showed substantially reduced IFN? along with slightly increased production of IL-17a following stimulation with PMA/Ionomycin, corroborating a potential tendency of peripheral cellular exhaustion. Conversely, both IFN? and IL-17a were increased in ETA over plasma samples in COVID-19 ICU patients and levels of both cytokines were equally higher in those ETA specimens containing innate T cells suggesting that these cells contribute to local airway proinflammatory cytokine production. Most importantly, while repeated sampling revealed a further decrease of CD69+ activated circulatory MAIT, iNKT, and ?? T in COVID-19 over time, the authors observed that higher frequencies of activated circulatory MAIT and iNKT cells on day 7 correlated moderately with increased PaO2/FiO2 ratios, indicative of preserved lung oxygenation, thus suggesting that activation of innate T cells in early COVID-19 may be used as a predictor of disease severity.

      Limitations<br /> Technical/biological<br /> In addition to the relatively small study size, it remains somewhat unclear how many ICU patients were included in some experiments pertaining to ETA sample collection. Furthermore, a more stringent clinical characterization of enrolled patients (in addition to basic information presented in table 1) would add further impact to the observations made here regarding the potential role of innate T cells in critical COVID-19 as well as regarding any further association with ARDS severity, death or clinical course in general. To adequately address some of these questions, larger studies including patients across all clinical stages as well as early-onset and longitudinal sampling will be needed. Similarly, it would be of great interest to further examine kinetics of both potential innate T cell migration to inflamed airways and general function by means of repeated sampling. Additionally, extended flow-cytometric phenotyping of both circulatory and airway innate T cells will be needed to further characterize these populations beyond their basic activation status. In this context, general gating strategies should be included in the supplemental.

      General<br /> Throughout the manuscript, some references pertaining to specific figures or their content are incorrect. For example, supplementary figure 1A shows a COVID-19 lung CT scan, but no healthy control scan as suggested by the complementary figure legend. Data on plasma and ETA IL-1R? levels are displayed in figure 1 E & F, not in supplementary figure 1B as stated in the manuscript. Supplementary figure 1B does not exist. Similarly, some of the literature references seem to have been mixed up (cf. reference 16 on the role of MAIT cells in diabetes and obesity vs. on the role of type I IFN responses as cited in manuscript; reference 23 is missing).

      Significance<br /> Innate T cells have been previously shown to mediate potent antiviral immune mechanisms in both mouse and human studies (reviewed in https://link.springer.com/c... "https://link.springer.com/content/pdf/10.1007/s11684-017-0606-8.pdf)"). Observations made here generally corroborate limited data reported in two recent preprints (https://www.biorxiv.org/con... https://www.medrxiv.org/con... "https://www.medrxiv.org/content/10.1101/2020.04.05.20046433v1.full.pdf)") on activation status and frequencies of ?? T in COVID-19 patients. Notably, this preprint by Jouan et al. is first to assess basic functional changes of circulatory innate T cells (including MAIT, iNKT and ?? T subsets) as well as frequencies and limited phenotypic analysis of airway innate T cells in critical COVID-19. Further studies including larger cohorts of patients of variable disease are now needed to conclusively determine the role of innate T cells in COVID-19 immunopathology.

      This review was undertaken by Verena van der Heide as part of a project by students, postdocs and faculty at the Precision Immunology Institute of the Icahn School of Medicine at Mount Sinai.

    1. On 2022-03-01 06:21:04, user Nun Daled Yud wrote:

      It would be useful to measure the protection of good ventilation in the form of windows and doors that can be open especially in primary care consulting suites and waiting rooms . Many have no windows and the carbon dioxide concentration is likely high . Carbon Dioxide meter readings would be interesting . Meanwhile all new clinics and long term care facilities ought be designed to improve ventilation -safety and security is an issue as is energy cost but there may be benefit as respiratory virus are effective through the air and creativity ought be better .

    1. On 2022-03-01 12:10:22, user Eric Fauman wrote:

      There's a reason we use 5e-8 for detection of significant GWAS hits and that's because below that you're swamped with associations that are likely not real. You shouldn't do pathway enrichment on genes identified from SNPs at 1e-6; the results are likely meaningless.

    1. On 2022-03-01 17:11:24, user Rogerblack wrote:

      An interesting paper, there are some unclarities in the paper that I'd like to see addressed.

      ' Full-time sick leave was reported by 9.4% of test-positives and 6.5% of test-negatives (RD=3.20, 95% CI 2.88-3.47%),' This whole paragraph is unclear, and the interpretation depends critically on the question asked.

      Does 'Full time sick leave' here mean leave from full time work, or does it mean having to abstain from work, be it part-time or full time. Similarly, does 'part-time sick leave' mean reduction in hours worked due to illness or having to abstain from part-time work.

      I find unfortunate the seeming lack of a question around severity. I have had a post-viral disease for the past 40 years. For most of that time, I would have ticked a 'fatigued' box.

      This simple binary conceals that during that time, this has meant fatigue that means I can't do normal activities after 8 hours work, to bedbound.

      A plea, to this team and others.<br /> Please ask about impact on normal role.<br /> 'Have you had to at this time give up caring/work/educational responsibilities due to illness' (for example)<br /> I have had most of the symptoms mentioned in figure 1, at varying severities for the past decades, with prevalance and severity varying.<br /> I DO NOT CARE ABOUT ANY OF THEM.

      I care about if I can

      A) Perform normal activies as before illness onset.<br /> B) Have to pick between normal activies and drop some I am no longer able to do.<br /> C) Have to give up many normal activies and only able to do some.<br /> D) Extremely limited ability to do normal activities.<br /> E) Self-care only.<br /> F) Unable to perform self-care to a reasonable quality.<br /> (For the last weeks, E)

    1. On 2022-03-01 21:32:30, user Maurizio Rainisio wrote:

      Computing NNT would have highlighted that to spare one hospitalization over the 4 months duration of the vaccination protection would require approximately 15,000 full treatments for the 5-11 kids and 7,000 for the 12-17. Adding an NNT column to table 1 would be of great help.

    2. On 2022-03-02 17:00:41, user Carol Taccetta, MD, FCAP wrote:

      Re the severe disease (hospitalizations), I posed a question to the corresponding author: does Table 11 from NY's Pediatric COVID-19 update (link below) reflect admitted FOR covid or all comers (admitted FOR + WITH covid)? There appears to be a similar table (Table 1) in this pre-print.

      Table 11 is described within the link below as "Examining new hospital admissions with laboratory-confirmed COVID-19, per Table 11:", yet it does not specify a differentiation between admitted for and admitted with covid-19:

      https://coronavirus.health....

    1. On 2022-03-13 07:22:25, user Hanjun Lee wrote:

      Dear Dr. Colson,

      Thanks a lot for sharing this preprint and for your work regarding the virology of SARS-CoV-2. I would like to ask regarding the possibility of Amplicon-related artifacts in the Nanopore sequencing data. One of your key results that surprised me the most was the identification of a recombination event at p.156–179 of the SARS-CoV-2 Spike protein. However, looking into the Artic amplicon panel (ARTIC nCoV-2019 Amplicon Panel v4.1) that has been utilized during the amplification step, I have a fear that the recombination event at p.156–179 may be the consequence of primer set #73's preference toward a specific variant. The Artic amplicon panel that has been utilized has 99 different primer sets. While many regions are covered by more than two primer sets, some regions are covered by a single primer set. If a region is covered by a single primer set, this makes it harder to distinguish true hybrid "deltamicron" or "deltacron" genomes from a co-infection or co-incorporation of delta and omicron genomes. Spike protein's p.125–178, which has a very great overlap with the p.156–179 region that has been identified by the authors, is one such region; it is covered by ARTIC's 73rd primer set, but is just outside of the regions covered by the 72nd and 74th primer sets. Do the authors think it is possible that the 3' end of the recombination event (p.178 or 179) might be the starting site of the forward primer of the 74th primer set, not a bona fide recombination locus? Or do the authors think there is enough evidence that can outlaw such a possibility?

      Again, thank you so much for your work, and stay safe.

    1. On 2022-05-18 16:21:05, user Carly Boye wrote:

      Great presentation at #BoG2022! The scale of this study was very impressive. I was interested in your idea that BCRs might affect DD risk through noncoding mechanisms by disrupting lincRNA genes. I typically study smaller variants (such as SNPs) and it made me wonder if SNPs could potentially disrupt an interaction between lincRNA and DNA, and if this would affect transcription (and then if it could lead to DDs). Also, will your model be available once this work is published?

    1. On 2022-05-23 16:01:08, user John Dough wrote:

      Very nice work. I have a suggestion that is a relatively easy fix. I suggest you change from gender to sex. Gender is a social construct while sex is biological and my understanding is you studied sex here.

    1. On 2022-06-14 12:08:52, user Robert Clark wrote:

      In Fig. 3, it is notable that for the severe cases, the ivermectin group had a factor of 1.79 advantage on the scale of faster time to recovery. The question arises in this subgroup analysis of whether this is a real effect?

      A good way to check is to also look at the hospitalizations, emergency room visits, urgent care, etc. numbers specifically for the severe cases. Note that its expected that a large proportion of these should come from the severe cases. Then does IVM have such a clear advantage for the severe cases here as well?

      Robert Clark

    1. On 2022-06-17 14:00:48, user Todd Lee wrote:

      The authors are to be commended on a very important comparative effectiveness trial. Thank you! From a reporting standpoint:

      Additional details worthy of reporting in Table 1 are the presence of "do not resuscitate orders" which would prevent intubation and the administration of co-interventions like remdesivir which may impact both the need for ventilation and mortality (CATCO, CMAJ 2022). Could the authors provide this information?

      Additionally, the composite outcome is non-inferior. Yet, the composite contains two clinical outcomes which (a) differ in importance in that death is worse than ventilation and (b) may be related along a causal pathway in that patients who are ventilated are more likely to die. Could the authors revise the manuscript text or tables to include each component of the composite outcome separately by Day 28 or report death in the "adverse events"?

      Additionally, could post-hoc subgroup analyses be performed by age, gender, vaccine status, and CRP greater than and less than 75 (recovery criteria).

      I appreciate these were not pre-specified outcomes on clinicaltrials.gov, but they are essential to peer review and to contextualizing these results with the existing literature.

    1. On 2022-06-23 08:44:59, user Andrew Fischer Lees wrote:

      This is interesting work. Your 4th limitation is the biggest issue from a clinical side (I say this as a clinician). 99% of the time I order a hemoglobin it is as part of a CBC. Sometimes I order the hemoglobin because I want the Hb, but sometimes I order it because I want the WBC, or the platelets, or all of these things. There is not a great reason to order just WBC if that is all I care about, because the same reagents are used in the lab to process the sample, so the extra tests are "free information", that is, the marginal cost is zero.<br /> Your stability model should really be executed at the level of the CBC bundle. Asking clinicians to not order a Hb when the marginal cost is zero doesn't really save any money for the system or lab draws for the patient. But If the whole CBC is predictably stable, in that situation it would make sense to surface that information to the clinician in the form of Clinical Decision Support.

    1. On 2022-08-05 06:55:12, user Robert Clark wrote:

      The quite key question however remains unaddressed: how does vaccination status effect rebound?<br /> Because of the evidence overtime the vaccine reduces immune response, the correlation to number of shots and time since vaccination should also be made in regards to rebound.

      Robert Clark

    1. On 2020-04-02 00:27:40, user Sinai Immunol Review Project wrote:

      Summary:<br /> The authors of this study provide a comprehensive phenotypic analysis of the adaptive immune cell pool in 38 COVID-19 patients with mild or no symptoms in comparison to 18 healthy donors. Using flow cytometry of circulating PBMC, the authors found that the total lymphocyte count in COVID-19 patients was slightly reduced. This is in striking contrast to severe patients in which severe lymphopenia is common and correlates with severity of disease. The relative CD19 cell count including particularly Germinal Center B cell (GCB) counts were significantly increased in COVID-19 patients. With respect to T cells, the authors describe no substantial differences in CD4 and CD8 T cell counts. However, when analyzing T cell subsets, the authors discovered significantly increased expression of CD25 and PD-1 as markers of late activation and exhaustion in CD8+ T cells, respectively. Moreover, the amount of naïve CD4 T cells as well as of T follicular helper (Tfh) cells were significantly increased in COVID-19 patients.

      In an attempt to find correlations between patient characteristics and the status of the adaptive immune system, the authors applied Person’s correlation coefficient and found no major impact of age on CD8+ T cell activation as well as on Tfh and GCB-like T cell differentiation.

      Summing up, the authors performed a thorough phenotypic analysis of B and T cell subsets in COVID-19 patients giving a promising insight into the status of the adaptive immune system in their patient cohort with mild symptoms.

      Critical analysis:<br /> The strength of this study is the in-depth multiparameter analysis of adaptive immune cells in a reasonably sized cohort of 38 patients and 18 healthy controls. The assumption that COVID-19 patients with mild disease show an appropriate antigen-specific response due to an increase of Tfh and GCB cells is justified by the data.

      Implications of the findings in the context of current epidemics:<br /> The study clearly shows that patients with mild-disease have increased Tfh and GCB and understanding the specificity of this response and how they correlate with disease course will be interesting to explore. Defining patient groups at risk for severe courses is crucial in order to be able to intervene early using experimental therapeutic strategies.

    1. On 2022-08-13 18:37:14, user Christian Fiala, MD, PhD wrote:

      Is there any information as to the requirements and/or use of face masks by pregnant women during the pandemic in the region?

    1. On 2022-08-15 10:05:00, user james hurley wrote:

      I congratulate the authors on their protocol for a ‘Systematic Review and Meta-Analysis of Selective Decontamination of the Digestive Tract in Invasively Ventilated Patients’ [1]. That there are already over 40 published articles with “Systematic Review”, “Meta-Analysis” and “Selective Digestive Decontamination” in the title indicate that this is a vexed topic and the definitive publication is yet to appear. <br /> A simple reading of recent Cochrane reviews appears to indicate that SDD lowers both infection incidence and mortality in this patient group, whereas four other interventions do not [2-7]. However, what are the substantial areas of doubt and how can these be best addressed [8]?<br /> May I make some suggestions that might increase the chance that their proposed Systematic Review might be definitive?<br /> Firstly, is the mechanism of action of how Selective Decontamination of the Digestive Tract decrease infection and mortality in invasively ventilated patients understood? Are the animal studies undertaken in mice in the early 1980’s, from which the term ‘Selective Decontamination’ originated, still regarded as valid? Is the term “Selective Digestive Decontamination” a triple misnomer? Several have proposed that the term ‘Control of Gut overgrowth’ as a more accurate term to describe the presumed mechanism [9, 10].<br /> Second, is it true to state that the “Uncertainty about the effectiveness of SDD is due to concerns about the generalisability of RCTs with limited internal and external validity.”? Why did the use of SDD fall out of favour among neutropenic patients in the 1990’s? Is there a potential for rebound infections? Will this proposed systematic review address the question of rebound? Is there a possibility that SDD is ineffective among ICU patients? Is there a possibility that SDD and the rebound effect on its withdrawal is harmful? <br /> Thirdly, the authors will need to confront data inconsistencies between various versions of the published SDD trials that appear in the two Cochrane reviews of this topic [2, 3]. The earlier review obtained ‘Intention to treat’ data from several of the authors of the primary SDD studies which differs from the ‘on treatment’ data as published. The latter often excluded patients who died before completing the four days regarded as necessary to achieve ‘Selective Decontamination’. As a consequence, there is both survivorship bias and an underestimation of infection and mortality incidences in the ‘on treatment’ data. In addition, will the authors use the original data for the study groups as randomly allocated or will they use the adjusted data as published?<br /> Fourth, the authors propose a subgroup analysis comparing the results for “Individual patient vs unit level randomisation (i.e. cluster and cluster/cluster-cross-over).” However, their hypothesis is that the effect is unidirectional, i.e. they expect a benefit to be “,…greater in individual patient randomised trials compared to unit level randomised trials.” This expectation is a restatement of the ‘Stoutenbeek’ postulate, stated in the first SDD study undertaken in the ICU setting, that there would be a contextual effect of using SDD in the ICU context and that this effect would be beneficial to any concurrent control groups patients and, as a consequence, bias downwards the estimates of the SDD intervention within individual patient randomised trials [11, 12]. Stated otherwise, this postulate implies a herd effect similar to that of herd protection from vaccination within a population. <br /> This postulate creates several difficulties for this proposed systematic review. By raising this postulate, does this invalidate the Stable Unit Treatment Value Assumption (SUTVA) that is fundamental to valid estimates of effect size from concurrent controlled trials? If the SUTVA is questioned here, will this invalidate the estimates from the proposed systematic review? Moreover, given this postulate and proposed subgroup test, will the test be one-sided, with the expectation that the effect is uni-directional [only beneficial effect possible], or two sided?<br /> There is evidence that the results of individual [i.e. concurrent control] patient randomised trials of SDD differ to those of unit level [or historical control; i.e. non-concurrent controls] randomised trials and that the SUTVA is questionable for these studies. This has only been addressed in first and second meta-analyses on this topic both published 25 years ago [13, 14]. These indicate that the effect is greater in the former, i.e. contrary to the direction postulated by Stoutenbeek. There is further and more recent evidence for this discrepancy. On the one hand, the three largest subsequently published studies of SDD versus either standard care or SOD, which were all undertaken using unit level randomization [i.e. and non-concurrent controls], showed absolute differences in bacteremia and mortality [before any statistical adjustments] of less than 5 percentage points [15-17]. On the other hand, the most recent Cochrane review of the studies of SDD in this population, which included mostly trials using individual patient randomization [i.e. and concurrent controls], showed absolute differences in pneumonia and mortality of five percentage points or greater [3]. <br /> Will the proposed protocol use the unadjusted data or the adjusted data from these trials? Does the data adjustment account for the Stoutenbeek effect?<br /> Finally, to provide a definitive review, the authors will need to explain why event rates [pneumonia, bacteremia, candidemia and mortality] are generally higher among control groups within trials using individual patient randomization [i.e. with concurrent controls] versus control groups within trials using unit level randomization [i.e. with non-concurrent controls], versus control groups from studies of interventions other that SDD, and versus groups of studies without an intervention. Moreover, why is it that the event rates in the SDD intervention groups are similar to intervention groups from studies of interventions other that SDD in this patient group? The higher event rates are apparent in closer scrutiny of the summary results of the five Cochrane reviews [3-7]. On the one hand, the median control group event rates for pneumonia and mortality [18] are highest within the control groups of studies of SDD versus control groups of studies of other interventions and yet, on the other hand, the event rates for the intervention groups are paradoxically similar to intervention groups of studies of other interventions.<br /> I wish the authors well and hope that they succeed in providing the definitive systematic review of this topic over the arc of time [19].<br /> References<br /> 1. Hammond NE, Myburgh J, Di Tanna GL, Garside T, Vlok R, Mahendran S, Adigbli D, Finfer S, Goodman F, Guyatt G, Venkatesh B. Selective Decontamination of the Digestive Tract in Invasively Ventilated Patients in an Intensive Care Unit: A protocol for a Systematic Review and Meta-Analysis. medRxiv. 2022 Jan 1.<br /> 2. Liberati A, D'Amico R, Pifferi, et al: Antibiotic prophylaxis to reduce respiratory tract infections and mortality in adults receiving intensive care. Cochrane Database Syst Rev 2009; 4: CD000022.<br /> 3. Minozzi S, Pieri S, Brazzi L, Pecoraro V, Montrucchio G, D'Amico R. Topical antibiotic prophylaxis to reduce respiratory tract infections and mortality in adults receiving mechanical ventilation. Cochrane Database of Systematic Reviews 2021, Issue 1. Art. No.: CD000022.<br /> 4. Wang L, Li X, Yang Z, Tang X, Yuan Q, Deng L, Sun X. Semi-recumbent position versus supine position for the prevention of ventilator-associated pneumonia in adults requiring mechanical ventilation. Cochrane Database Syst Rev 2016(1). DOI: 10.1002/14651858.CD009946.pub2.<br /> 5. Gillies D, Todd DA, Foster JP, Batuwitage BT. Heat and moisture exchangers versus heated humidifiers for mechanically ventilated adults and children. Cochrane Database Syst Rev. 2017(9). DOI: 10.1002/14651858.CD004711.pub3.<br /> 6. Bo L, Li J, Tao T, Bai Y, Ye X, Hotchkiss RS, Kollef MH, Crooks NH, Deng X. Probiotics for preventing ventilator-associated pneumonia. Cochrane Database Syst Rev. 2014(10). DOI: 10.1002/14651858.CD009066.pub2.<br /> 7. Zhao T, Wu X, Zhang Q, Li C, Worthington HV, Hua F. Oral hygiene care for critically ill patients to prevent ventilator-associated pneumonia. Cochrane Database Syst Rev. 2020(12).<br /> 8. Hurley JC Selective digestive decontamination, a seemingly effective regimen with individual benefit or a flawed concept with population harm? Crit Care. 2021;25(1).<br /> 9. Silvestri L, Miguel A, van Saene HK. Selective decontamination of the digestive tract: the mechanism of action is control of gut overgrowth. Intensive Care Med. 2012;38(11):1738-50.<br /> 10. Hurley JC (2020) Structural equation modeling the “control of gut overgrowth” in the prevention of ICU-acquired Gram-negative infection. Crit Care 24(1):1-2.<br /> 11. Stoutenbeek CP, Van Saene HK, Miranda DR, et al: The effect of selective decontamination of the digestive tract on colonisation and infection rate in multiple trauma patients. Intensive Care Med 1984; 10(4):185-192.<br /> 12. Hurley JC. Incidences of Pseudomonas aeruginosa-associated ventilator-associated pneumonia within studies of respiratory tract applications of polymyxin: testing the Stoutenbeek concurrency postulates. Antimicrob Agents Chemother. 2018;62(8):e00291-18.<br /> 13. Vandenbroucke-Grauls CM, Vandenbroucke JP. Effect of selective decontamination of the digestive tract on respiratory tract infections and mortality in the intensive care unit. The Lancet. 1991;338:859-62.<br /> 14. Hurley JC. Prophylaxis with enteral antibiotics in ventilated patients: selective decontamination or selective cross-infection?. Antimicrobial agents and chemotherapy. 1995;39(4):941-7.<br /> 15. de Smet AMGA, Kluytmans JAJW, Cooper BS, et al: Decontamination of the digestive tract and oropharynx in ICU patients. N Engl J Med 2009, 360:20–31.<br /> 16. Oostdijk EA, Kesecioglu J, Schultz MJ, Visser CE, De Jonge E, van Essen EH, Bernards AT, Purmer I, Brimicombe R, Bergmans D, van Tiel F. Notice of retraction and replacement: Oostdijk et al. effects of decontamination of the oropharynx and intestinal tract on antibiotic resistance in ICUs: a randomized clinical trial. JAMA 2014; 312 (14): 1429-1437. JAMA 2017; 317(15):1583-4.<br /> 17. Wittekamp BH, Plantinga NL, Cooper BS, et al: Decontamination strategies and bloodstream infections with antibiotic-resistant microorganisms in ventilated patients: a randomized clinical trial. JAMA 2018;320(20):2087-2098. <br /> 18. Hurley JC Discrepancies in Control Group Mortality Rates Within Studies Assessing Topical Antibiotic Strategies to Prevent Ventilator-Associated Pneumonia: An Umbrella Review. Critical care explorations. 2020;2(1).<br /> 19. Pizzo PA. Management of patients with fever and neutropenia through the arc of time: a narrative review. Ann Intern Med. 2019;170(6):389–97.

    1. On 2020-04-24 15:20:42, user Lawrence Mayer wrote:

      Again I suggest readers that want to see discussion of these papers and others in Clinical Epidemiology and Science consider joining or group if they have healthcare or Science credentials.

      Clinical Epidemiological Discussion of COVID19 Pandemic Group<br /> https/facebook.com/groups/covidnerds

    1. On 2020-04-25 04:04:36, user Deevish N D wrote:

      The radiometer used in this study - UV513 AB detects a peak wavelength of 365 nm as per its manual. But the actual germicidal wavelength is around 254 nm. I believe the dose needed for UV disinfection has been under-reported in this article. Authors please correct me if am wrong.