On 2021-10-08 13:13:27, user Richard S wrote:
Did the authors address multicollinearity of the highly correlated independent variables in their regression models?
On 2021-10-08 13:13:27, user Richard S wrote:
Did the authors address multicollinearity of the highly correlated independent variables in their regression models?
On 2021-10-15 21:36:23, user Mary V wrote:
Please add results for the unvaccinated individuals who recovered from Covid prior to Feb 28, 2021. How does their risk of symptomatic infection during the delta uptick compare with the individuals who were fully vaccinated by Feb 28, 2021 and didn't have a positive Covid test before 6/1/21? Did one shot of the Pfizer vaccine improve the immunity of that group during the delta uptick? Other studies have shown a very strong immunity for those who have recovered from Covid symptoms. The data in this paper only supports a vaccine recommendation for people who've had asymptomatic cases of Covid. Hence the data for those who've had symptomatic cases needs to be added or your conclusion about the vaccine recommendation should be qualified.
On 2022-03-22 12:17:46, user panos101 wrote:
What's the status of this article. Has it been published?
On 2021-10-08 13:47:58, user Mazda Sabouri wrote:
The IFR formula on page 9 appears to assume that the number of excess deaths and Covid deaths are equal. Certainly possible in certain regions, but also not a proper assumption to make universally.
Also there does come a point where IFR exceeds PFR in a given region. Especially for a highly contagious virus that aggressive targets large numbers of vulnerable people each and every year. This study admits that certain regions in Iran have had 200%+ attack rates already.
On 2021-10-08 20:58:14, user AbsurdIdea wrote:
Referring to "However, if prior infection does not afford protection against some of the newer variants of concern, there is little reason to suppose that the currently available vaccines would either.": The mRNA vaccines are targeted specifically to the "spike". There appears to be no information as to what the infection used or uses to identify the virus, and thus while new variants have a "spike" and likelihood of maintained resistance there is zero evidence of what natural immunity would or would not recognise in a variant. Thus the argument provided has no substance.
On 2021-10-09 20:30:31, user j` wrote:
Are you under the impression antibodies are the immune system's only means of protection?
Have you reviewed previous studies showing robust immunity of mild infections?
On 2021-10-10 04:14:01, user kdrl nakle wrote:
Nice. So you are 20 times more likely to have COVID induced myocarditis than vaccine induced one. And on the top of that the COVID induced one will last longer.
On 2021-10-10 04:55:53, user kdrl nakle wrote:
One of many recent papers indicating that Moderna is ahead of Pfizer.
On 2021-10-10 05:19:33, user kdrl nakle wrote:
I don't know about UK but in case of US this is useless since the mitigation measures are so heavily politicized in the US to the point of absurd actions. For example Alabama, does not even report outbreaks in schools any more and does not quarantine nor test exposed students.
On 2021-10-18 00:30:55, user Prescott Comptr wrote:
hasn't there been enough time for a peer review?
On 2021-10-18 22:45:59, user Sir Henry wrote:
Table S3 of the Supplementary Materials shows 262 "severe" adverse events for the vaccine, compared to 150 for the placebo. The difference of 112 is too large to be a statistical fluke (p < 0.001) and is a multiple of the number of "severe COVID-19" cases (30) for the placebo (Table S6). In terms of "severe" outcomes (COVID-19 or adverse events), the vaccine appears significantly more dangerous than the placebo over the four month observation period.
On 2021-10-19 17:10:24, user Jeremy Gustafson wrote:
It's too bad they didn't break out a 5th group of previously infected and not vaccinated to compare their immunity similar to the study that was done in Israel.
On 2021-10-22 07:52:48, user Adrien MP wrote:
Hi,<br /> Could you make Tables 1 and 2 available in order one can take the full extent of the work presented here?<br /> Thanks
On 2021-10-24 07:24:16, user Otmar S wrote:
Dysguesia is the leading indicator which can also be seen for children regarding other studies (for example CLOCK). I can´t find the question/incidence of Dysgeusia for children in this study. I wonder why. No data?
On 2021-10-31 17:00:24, user wincap wrote:
You should include affect of vaccines triggering paraneoplastic syndrome, which occurs in 20% of cancer patients.
On 2021-11-04 18:32:24, user Libres Penseurs wrote:
By looking roughly at the numbers, the authors seemed to be right. Ottawa area population is around 1 million. If Ottawa is aligned with the rest of Canada, 78% of the population received at least 1 dose since the beginning of the vaccination campaign. On the two months stated in the study, the increase was about 10% (overall Canada data). This means that around 100 000 people were vaccinated in the Ottawa area during those two months. Ottawa have a lot of hospitals so you cannot assume that everybody with adverse reaction to the vaccine will show up at the same hospital. The authors use 1/3 of that total number (32k). The 800000 number refers only to people having received at least one dose since the beginning of the vaccination campaign. <br /> Myopericarditis cases at one hospital for a period of two month cannot be used as a numerator on this number to calculate risk.
On 2021-12-01 14:08:31, user watcher wrote:
The authors mention that vaccination efficacy might be affected by underreporting of mild symptomps. This raises another issue, which was not accounted for in the model. Asymptomatic infected individuals may still transmit the virus, but due to the lack of symptoms will not alter their behavior. It should be assumed that the more prominent symptoms are, the more individuals will reduce their contacts, to protect themselves and others. As unvaccinated infections generally result in more symptoms, these individuals will likely reduce their contacts naturally. Symptoms alter the behavior of individuals and thus transmissions, which is not accounted for in the model, but could change the outcome quite a bit.
On 2021-12-07 17:04:15, user LizzyJ wrote:
''Pandemic modeling'' is quickly becoming the astrology of mathematics & physics.
Want to get a lot of media attention and citations? Simply code up a little model and write up a paper about your unscientific predictions. As in all models, the chosen values for the parameters in this simulation are naive assumptions. There is no sufficiently high-quality or complete data on vaccine status and mode of infection (e.g. infected by a vaccinated or unvaccinated person) currently being reported by hospitals or health departments.
Pandemic modeling is an abstract and theoretical mathematical exercise with very high bias and uncertainty based on the underlying assumptions, factors included or excluded, incomplete input data, very poor data quality with big non-random gaps in the data, etc. It should not guide public policy. Only clinical studies and real-world medical data should guide policy.
On 2023-03-08 12:30:58, user Carlos Oliveira wrote:
This study has been published on Frontiers in Public Health: <br /> Routine saliva testing for SARS-CoV-2 in children: Methods for partnering with community childcare centers<br /> Frontiers in Public Health, 11, 1003158 - February 2023<br /> https://doi.org/10.3389/fpu...
On 2022-01-12 17:15:59, user Rick Sheridan wrote:
This was a laudable effort and I congratulate all of the authors and the study’s primary driver for pushing this through. Am in agreement that insight from results is likely limited by the maximum dosage as stipulated by the NNHPD guidelines. I enclose here daily quantitative PCR results from a high-quality PCR vendor during my own Jan '22 experience with high-dose hesperidin in context of a documented SC2 infection during the omicron wave.
https://emskephyto.medium.c...
As can be seen in the data log made available, subject (100 kg male) was taking multiple grams at a dose, often successively within hours of each other. Critically for DDI, no other pharmaceutical drugs were taken concurrently. For independent auditing purposes, will be happy to disclose the PCR vendor, the collector, and the hesperidin nutritional supplement brand to any relevant reachout.
With what little one has to go on from the posted results, I would offer a model that during an active infection, the minimum possible Ct value is correlated to the sustained serum hesperetin glucuronide level during the 0.5 - 2 days prior to the nasopharyngeal sampling from which Ct is determined.
Addressing the standing issue that viral load has often peaked prior to trial enrollment, this challenge remains tolerable in context of a clinical trial because one can still show an accelerated viral load reduction in the experimental group as compared with control, sufficient to demonstrate the mechanism.
Rick Sheridan<br /> EMSKE Phytochem<br /> 11-Jan 2022
On 2022-01-12 20:21:08, user Mike B wrote:
Do we know it's VOC? Dogs detect Parkinson's using same technique, perhaps from minor expression of misfolded protein. Discrimination and scent memory by dogs is much more complex than we know. <br /> Implies we could build a molecular filter to mimic dog's nose. That however, is elusive.<br /> Fantastic study. Much ??? to working dogs, especially Belgian Malinois!
On 2022-01-13 12:47:09, user kdrl nakle wrote:
On Christmass Eve Dec 24, 2021 there was 948 in ICUs in California. Yesterday CA DoH posted 1903 in ICUs. What happened? Most of that in Southern California, imagine. This flies in the face of this paper. This paper lacks multivariate analysis as most infected by Omicron were double vaccinated and most infected by Delta were unvaccinated. That way these people make sensational paper without serious research. <br /> We had 2730 deaths yesterday in the US (NYT), now the 7-day-avg is approaching the height of Delta wave, currently 1825. The peak of Delta wave was 2087 on Sep 20. I actually expect Omicron will crash this Delta record shorty as it will crash ICU overall record in no more than two days from today. Currently 24,711 in ICUs on January 11, 2022.<br /> This sad attempt to make Omicron look mild will actually cost many lives for all the people that took masks off and are believing this "mild Omicron" propaganda. Wait until you see.
On 2022-01-14 20:11:27, user Boback wrote:
Why are the event number exactly the same between vaccine arms in Table 1 in multiple places. Calculated point estimates and CI also the same for those. Did you have a coding error with events? I wouldn't expect so many exact event counts to overlap.
On 2021-12-27 21:14:28, user Danes wrote:
Any comment on the huge discrepancy in pre-risk between vaccine and COVID groups in Table 1? Does not seem to be appropriate for this type of comparison.
On 2022-01-16 16:21:39, user Titan28 wrote:
I don't see ivermectin on the list of suspect drugs. Was it not tested?
On 2022-01-18 13:58:07, user William Henry Talbot Walker wrote:
Were all of the vaccinated participants studied for pre-existing cellular response or globulin levels before the vaccines were administered?
On 2022-01-21 05:16:30, user Victor Schoenbach wrote:
I found this article both valuable and important, but I do not understand the last two sentences ("Despite the small numbers of individuals included in this study, the findings are uniquely valuable because of the early detection of Omicron infection in frequent workplace Covid-19 testing to prevent spread. In real-world antigen testing, the limit of detection was substantially lower than manufacturers have reported to the FDA based on laboratory validation.")
The first of these sentences is confusingly worded; copy editing would help.<br /> The second sentence refers to a lower limit of detection. Perhaps I do not understand the technical meaning of that term, but I would have thought that meant that the real-world sensitivity of the antigen test was higher (virus detected at a lower level), whereas the article suggests the opposite.
On 2022-01-21 14:18:29, user Rosanna wrote:
It will be interesting to know which organs are mostly affected by these autoantibodies. No mention about it is done in the manuscript. Do the authors have this information? Are lungs more affected in patients that suffered a critical COVID-19? <br /> Also, do the authors have data in male patients?
Rosanna Paciucci, Ph.D. Faculty Attending, Vall d'Hebron University Hospital, Barcelona, Spain
On 2022-01-21 21:47:18, user Brian Roberts wrote:
Thanks for this most up-to-date study. The only "sensitivity" number that matters to the clinician is how the BinaxNOW compared to the PCR for the entire group. That number was not provided. Or how they compare in symptomatic vs. asymptomatic groups, since that information is known to the clinician. How they compare in groups defined by the PCR Ct counts is all but useless, since it is unknown information at the bedside.
On 2022-01-22 13:19:19, user Torsten Selle wrote:
Is it possible to extend the measurement series to smaller aerosols (5-2µm). I am asking in regards to aerosols that cannot be stopped by ffp2 or n95 masks.
On 2022-01-24 01:15:03, user Fergal Daly wrote:
The paper uses linear regression on a non-linear variable (cases/100k). Does it apply directly to cases/100k or is it against log(cases) which should be somewhat linear?
On 2022-01-28 20:32:03, user Ranya Srour wrote:
The article is a good baseline for future studies involving suicidal ideation and bar graphs are very clear and easy to interpret. By extension, the study addresses the question: is it necessary to wait for sobriety before defining a patient as suicidal?
Maybe discuss this question directly in the discussion more; since it is the main question it may be valuable to expand on the in discussion.
On 2022-01-28 20:32:54, user Dhuha Al-Rasool wrote:
Very interesting article! It would be interesting to see the impact of THC on the SI results considering that it does not wear off as quickly as alcohol.
On 2022-01-29 14:26:08, user Alberto wrote:
Thank you for this study. It's important to have this kind of study in a country like Greece where mortality has been very high in 2021 (compared to other European and worldwide countries and compared to itself in 2020) because we can appreciate the difference between the reality observed and the projected modeling based on the data that is available about vaccination status. The resulting model, which is incompatible with the reality observed worldwide, is a good measurement of the quality of the data available. I hope this can be looked at in more <br /> detail by more people thanks to this study.
On 2022-01-30 23:47:58, user HereHere wrote:
I'm a registered massage therapist in Ontario. We received no clear advice from our regulatory college about ventilation. I was waiting and waiting and waiting. They were very slow with recommending N95s and KN95s, and to my knowledge, still have not acknowledged that surface transmission is exceedingly rare. I don't know how they coordinate with Public Health Ontario, but you would think that, given we work in close contact with patients in typically small, poorly ventilated rooms, ventilation would have been given greater consideration.
On 2022-02-01 14:15:41, user Richard Reynolds wrote:
There is another reason, the most likely one, why immune cell aggregates were not found in the meninges in this study, which is due to the nature of the tissue used. This study used formalin fixed paraffin embedded tissues which are suboptimal for studying the delicate meningeal compartment. Cells are lost from the meninges at every stage of the embedding, cutting and section mounting stages, when compared to using snap frozen blocks. When you float FFPE sections on to a water bath before mounting them on slides you can actually see with the naked eye parts of the meninges floating away from the sections. Presumably this would also results in losing various components of the meninges, including immune cells. We dont find nearly as many immune cell aggregates in the meninges when we use FFPE sections and in order to see them in the FFPE sections we needed to change out protocols substantially to much milder procedures in order to better preserve the cellular components of the meninges.
On 2022-02-01 21:24:21, user Dylan wrote:
Would have been nice to see loss of taste and smell included given their pediatric prevalence per https://link.springer.com/a...
On 2021-10-18 16:39:30, user Kim Noble wrote:
Well-thought, provoking article. Congratulations to Dr. Gõni and her team.
On 2022-02-02 07:40:56, user Gerald Zavorsky, PhD, FACSM wrote:
I have no idea why studies like these are coming out all of a sudden. Politics should not be a part of science and I think these diversity studies and social injustice studies actually do a disservice to the minority groups in the U.S. There are several studies that show racial differences in lung function. I, for one, have published one of these studies (10.1186/s12890-021-01591-7) that demonstrate differences lung function after correcting for several factors. In order for these authors to truly test the hypothesis that reference equations should not be adjusted for race (i.e., no adjustment if you are African American, Hispanic, or Asians), then you would need to perform a Kappa Statistic and ROC analysis in both whites and the other ethnic groups. In addition, in each race/ethnic group, you would need a substantial proportion of individuals with CONFIRMED DISEASE. That is, confirmed disease via CT imaging or via strict criteria (i.e., GOLD criteria). Using a subjective assessment of breathlessness is not right, in my opinion. The authors have not used the objective criteria of FEV1/FVC ratio for definitive obstruction; they only used FEV1 and FVC separately, and according to ATS/ERS guidelines, it is strictly the FEV1/FVC ratio that confirms obstruction. Then, using the LLN criteria for FEV1/FVC, then one should assess the sensitivity, specificity, positive predictive value, etc., comparing reference equations for different races in those with confirmed disease and those without the disease OR at least confirmed obstructive pattern (FEV1/FVC < LLN). That is, what is the sensitivity in detecting lung disease (or confirmed obstruction via the FEV1/FVC ratio) in blacks when using the GLI reference equation for blacks? What are the false negatives in blacks when using the black reference equation? THEN compare these results against the same group using the prediction equations for whites. This is really the only way. Subjective scores of breathlessness do not confirm the disease. All that their tables and figures show that if you use a white reference equation in blacks you can falsely over-diagnose lung disease in blacks. In this case, 870-890 blacks had falsely low FEV1 or FVC when using the white reference equation. The authors data actually go against their conclusions. First, 9% of whites were below the LLN for FEV1 when the white equation was used. Similarly, 9% of blacks were < LLN for FEV1 when the black equation was used. To me, this shows that the equations for blacks correctly identify low FEV1 values in blacks, and the reference equations in whites correctly identify low FEV1 in whites. The proportions are the same! As well, their Figure 1b, the mortality for Blacks that had an FEV1 that was normal when using black reference equation (orange line) was the SAME as when using the white reference equation for whites (blue line). This shows that the reference equations for whites used on whites are just as appropriate as the reference equation for blacks used on blacks. Indeed, if anything, Figure 1b demonstrates that using the white reference equation in blacks underscored mortality in blacks by 5% (i.e., 5% of the deaths are missed in blacks when using white reference equations). Thus, in conclusion, the authors have this all wrong and have misinterpreted the data. We should be correcting for race.
On 2021-10-18 18:05:16, user Francis Bascelli wrote:
How can I access this data on UK Biobank? The data/code section says the data can be accessed though UK Biobank, but I am having trouble finding it.
On 2022-02-02 11:42:04, user Philip Ashton wrote:
Hello,
Thanks for posting this really fascinating paper, so much food for thought!
We looked at this in our journal club today, and one practical issue that came up is that we would like to know over what period and what season sampling was done at each site and how this relates to typhoid season at each site. Because Typhi is often seasonal and this could influence the results.
Thanks again!
Phil
On 2022-02-03 03:23:31, user Chris wrote:
Do we know why the vaccines cause myocarditis yet?
On 2022-02-03 08:04:13, user dgatwood wrote:
Any chance a future update to this article could include the VE data against hospitalization *prior* to the third dose of mRNA-1273 (for comparison purposes)? Even a citation would help.
On 2022-02-03 21:59:47, user Suzy Huijghebaert wrote:
Line 148: "susceptibility of potential secondary cases was highest among the unvaccinated"<br /> Yet, some % in Table 1 striked me, and Table 9 does not really confirm that in the OR values. So I checked a few numbers, as when it comes to transmission of the omicron it is not so much sex or age that will matter, but - in real life - rather the total number of people you are in contact with, in view of the speed of transmission and the fact kids are affected by this mutants as well. Neither does it matter - economic-wise- whether the secondary case is vaccinated or not (yet, I agree an interesting aspect to study).So, how did you define the "potential cases"? The potential cases (per group of index cases) were apparently much lower in the vaccinated group than in the unvaccinated, and just proportionally correcting for that parameter, suggests that the rough highest attack rate -t as would be in real life - would have occurred with both BA1 and BA2 among the fully vaccinated (62-63%), provided they would have been in contact with as many potential cases in their households as the unvaccinated. Please clarify what induces the divergence/where the divergence with the outcomes arise from. Another question: what was the proportion of omicron cases among the people having already received vaccine, yet not considered fully vaccinated and now counted among the unvaccinated in your unvaccinated sample? Already thank you for clarifying.
On 2021-10-20 16:54:26, user helgarhein wrote:
You reported a surprising result: in the group of 51health care workers who were replete (above 75 nmol/l) only 2 took supplements. I would not have expected so many people (49) to have replete 25(OH)D levels in indoor workers in Birmingham (52ºN) in May, without supplements. However we had in the UK an unusually sunny and pleasant spring in 2020. I guess many people used their free time to go outdoors, because it was so sunny and dry, cinemas, restaurants etc were closed and socialising happened mostly outdoors. I presume that the unusual finding of so many people with excellent 25(OH)D levels could be explained by having acquired those levels in the week or two before May 2020. But maybe a longer timespan with good vitamin D supply is needed to make really all immune actions work optimally?? Could this have skewed the curve to make it look U-shaped?<br /> But, as pointed out by Dr. Gareth Davies, the most important observation was missing: the out comes of those infected, the ICU admissions and the mortality rate.<br /> Helga Rhein, ?retired GP, Edinburgh
On 2022-02-07 21:44:51, user Isaac Tian wrote:
Hello, we're the authors of citation #20. We had a few suggestions after reading your work.
A practical deployment of the network would ideally use some other silhouette imaging method such as a CT scan or an RGB photo like you suggested in the Study Limitations section. The sentences that referenced our work didn't mention our attempt to estimate total and regional body fat using a 2D RGB camera image.<br /> Our study data, composed of 2D coronal and sagittal images coupled with 2-fold DXA composition measurements, may be relevant to validating your method on non-MRI inputs. Additionally, I believe our parallel effort in estimating body composition from 2D silhouettes should be cited and compared against. We also did estimate compartmental body fat as arm, leg, and visceral fat. Our initial model was not very flexible in pose due to the smaller training set available at the time, but we have since corrected for this.
I recomputed our errors as MAEs to directly compare against your results, and assuming an adipose tissue density of 900 g / L, this came out to 121 g and 151 g for males and females, respectively. This is about 3-4x less than the magnitude of error reported in your draft. An analysis on the RMSE may be appropriate as large scale data may inflate R2.
A collaboration may be appropriate once this draft has passed peer review in which your network is used as the pre-trained initialization to fine-tune on silhouettes segmented from another imaging source, such as our Shape Up! dataset which was stratified by age and BMI. This also addresses the bias concern you mentioned as your MRI dataset has an average age of 65.
Thanks for sharing your work!
On 2022-02-15 09:24:31, user Shelly L Miller wrote:
This paper has been peer-reviewed and published here: https://www.nature.com/arti...
On 2022-02-25 06:26:07, user Abhishek Mallela wrote:
As of February 24, 2022, Figure 5 in the published version of this manuscript is missing axis labels. Please refer to the preprint version of Figure 4 for the axis labels.
On 2022-04-10 09:05:20, user dyctiostelium wrote:
The manuscript describes an analysis made from a database of suspected and confirmed COVID cases, with information about whether they had received any COVID vaccine at least 14 days prior and in the case they were, which one of 7 different vaccines.
It is stated that "vaccination status, date and specific vaccine<br /> product was collected from evaluated persons as part of epidemiological follow-up of suspected COVID-19 cases" and table S1 includes a row titled "Follow-up - person days", but the design does not seem to involve any clinical follow-up, given that the persons had either been vaccinated or not at the time their data was included in the database.
Could the authors clarify what is the source of the numbers in the row "follow-up" of figure S1?<br /> Of note, when the person-day is divided by the n of each column it gives a number of 114 days for the unvaccinated and around 200 days for the 7 different vaccines.
On 2022-04-15 17:26:22, user Young Juhn wrote:
A version of this article has been accepted for publication in the Journal of the American Medical Informatics Association (JAMIA) published by Oxford University Press. A link will be forthcoming.
On 2021-11-06 19:24:57, user Eleutherodactylus Sciagraphus wrote:
: This preprint includes data from human subjects that are under ethical scrutiny. The<br /> majority of patients enrolled were not informed nor agreed on participating in the study. The Brazilian National Comission forResearch Ethics (CONEP) has been bypassed, documents have been tampered, and the situation is now under investigation.
References supporting this statement (both in English and in Portuguese):<br /> https://brazilian.report/li...<br /> https://www.emergency-live....<br /> https://www.dire.it/14-10-2...<br /> https://www.matinaljornalis...<br /> https://g1.globo.com/rs/rio...
On 2022-06-07 10:39:46, user M. M. Welling wrote:
For the 2 patients, both were vaccinated before the PET scans. The control patents were from 2019 thus uninfected and not vaccinated for COVID-19. Neuroinflammation can be initiated by the vaccination after liposomal transfer of the mRNA through the BBB. This needs to be discussed as well.issue
On 2022-07-11 07:19:17, user Thijs Blok wrote:
Question: <br /> - A PCR can stay positive for weeks after infection, is that taking in account?<br /> - Is a throat swap executed with the selftests ?
On 2021-11-23 20:58:11, user jackbutler5555 wrote:
Did the study include all samples from the formerly infected or just those hardy and viable enough for the study?
On 2023-06-29 09:40:33, user Nensi wrote:
The idea behind this study is truly interesting and highlights the critical importance of addressing the issues surrounding poor reporting and the quality of systematic reviews.<br /> However, some things could be changed to improve the quality of this study. Below you can find some of my comments regarding your manuscript.<br /> 1) The manuscript could use extensive language editing, as there are many grammatical and spelling errors. Many language editing programmes can be very useful for these purposes (Grammarly, Instatext etc.).<br /> 2) You begin the Methods section with the aim of your study, but you state that the aim was to do a study. You can see why that does not make sense. The aim of your study was to do a study. You should report here the specific purpose or what you wanted to assess (for example, the aim was to assess the reporting quality of systematic reviews published by authors from India from 2015 to 2020).<br /> 3) In Results, you decided to report the data in text and with two figures. However, when you have so much descriptive data, it could be presented more clearly with just a table. The table allows the authors to store large amounts of data in a small place, making it easier for the readers to go through the data and understand the results. <br /> 4) Another detail about presenting the results is that they should be written in the past tense instead of the present tense you used.<br /> 5) Also, when presenting descriptive data, it is recommended to report both absolute and relative numbers (for example, „Only 20 (15%) of the reviews have been registered in PROSPERO registry“).<br /> 6) You could benefit from using STROBE reporting guidelines for observational studies (https://www.equator-network... "https://www.equator-network.org/reporting-guidelines/strobe/)"). Reporting guidelines are handy in ensuring you have reported everything that needs to be written in an article.<br /> 7) There is also much room for improvement regarding the referencing. A small detail would be the in-text referencing where you put [1] after the full stop. So the general rule would be that if you use brackets, it should be placed inside the sentence, and if you want to put the number in superscript, it should be after the sentence. That could use a bit of tidying up. <br /> 8) Additionally, regarding the referencing, you have used different styles of referencing in the reference list and some of the references are not referenced correctly or at all. There are many programmes that can help you organize and write the references (EndNote, Zotero, Mendeley etc.).<br /> 9) And one more thing for future referencing, even though a study is methodological, it should be preregistered. All studies should be preregistered to promote open science and transparency in conducting scientific research.<br /> I hope these suggestions will help. Good luck with your work!
On 2025-11-11 14:07:07, 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 authors applied metagenomic sequencing to samples from multiple wastewater treatment plants to characterize the diversity and abundance of antibiotic resistance genes. Using a standardized bioinformatics pipeline, they quantified ARG classes relative to total microbial DNA, and compared treatment efficiency across plants.
They observed that water leaving the treatment plant still harbored a broad spectrum of ARGs, including multidrug-resistance genes.
The authors describe wastewater treatment plants as both sources and potential intervention points for antibiotic resistance by emphasizing that improved engineering and coordinated antibiotic-management strategies could limit the spread of resistance genes in urban systems.
These findings indicate that monitoring of municipal wastewater may serve as a real-time surveillance tool for community-level antibiotic resistance burden and inform outbreak preparedness.
On 2020-04-03 17:14:59, user Paula Thompson wrote:
OK. While I do like to look at data, I don't understand comments abt this being too simplistic. Are the data too simple, and not fitting reality well, or are they good? Thanks for help.
On 2022-12-15 21:37:06, user Yiwen Zhu wrote:
This paper has now been published in Neuroscience & Biobehavioral Reviews Volume 143, December 2022, 104954 (doi: 10.1016/j.neubiorev.2022.104954). Please update the link if possible, thank you! <br /> - Yiwen Zhu
On 2020-04-06 01:21:26, user iggy wrote:
TLDR; Does Coronavirus lower the testosterone of those who survived it, long term? <br /> What percentage of men who had Covid-19 is affected by lowered testosterone? <br /> How much is it lowered?
On 2020-04-23 17:59:14, user El Ray wrote:
You can only measure what makes it into a sample. Comparing different assays on the same samples is the most informative approach.
On 2023-06-21 18:28:21, user Wim van Drongelen wrote:
Now published in Communications Biology doi: 10.1038/s42003-023-04696-3
On 2020-07-23 11:59:38, user Mr C S Mence wrote:
All the researchers seem to be north of the equator. Is there any data from countries south of the equator who have experience of the pandemic through their winter months
On 2020-04-24 05:20:43, user Olexiy Buyanskyy wrote:
Where is the zinc? Zelenko pointed that zinc is required!
On 2020-04-28 03:05:27, user algebra wrote:
What was the dosage given? Too little might not work, too much could be toxic
On 2020-04-21 23:43:04, user docmeehan wrote:
I'm not sure VA database born retrospective cohort analysis that declines to reveal drug dosing protocols contributes much to the science. Let's have those drug dosing protocols.
On 2020-06-08 21:08:42, user Paul Gordon wrote:
Hi, nice work. I notice that NRW-11 is reported in the supplementary tables, but is the only genome missing in GISAID. Was it withdrawn due to quality or was there an oversight in the submission? Thanks!
On 2022-01-01 14:56:50, user Jeffrey_S_Morris wrote:
Nice study! For completeness, it would be nice if table 3 included the transmissibility odds ratios for vaccination statuses stratified by variant
On 2020-06-15 02:32:20, user Sinai Immunol Review Project wrote:
Main findings<br /> Sex-based differences in the immune response have been reported for various types of infections. There is a growing body of epidemiological evidence that supports the finding that men experience more severe COVID-19 disease than women do, but the immune mechanisms underscoring such a difference remain unknown.
Here, Takahashi et al. analyze PBMCs, plasma, and nasopharyngeal swabs or saliva from 93 mild-to-moderate COVID-19 patients (n=93), comprised of 48 women (n=48) and 45 men (n=45), to characterize potential sex-based differences in the immune response to SARS-CoV-2 infection. It is important to note that patients on hydroxychloroquine and Remdesivir were not excluded from a sub-cohort of patients (n=39) evaluated as baseline measures for untampered immune responses to SARS-CoV-2 (these patients were not treated prior to first sample collection). In a second sub-cohort, 54 patients were assessed longitudinally for an undisclosed amount of time. Samples from uninfected healthcare workers were used as controls.
Viral Load (nasopharyngeal or saliva samples)<br /> No significant differences were identified between male and female patients. Still, median viral RNA was higher in male patients at first sample collection and generally throughout disease course.
Antibody production (plasma samples)<br /> Anti-SARS-CoV-2 S1 protein-specific IgG and IgM antibodies were measured in the plasma of male and female patients. Though anti-S1-IgG antibodies were higher in female patients, compared to male patients, no significant differences could be identified either in the baseline cohort or in longitudinal patients.
Cytokine analysis (plasma samples)<br /> Among baseline patients, who had not received immunomodulatory therapy prior to sample collection (except hydroxychloroquine), type I/II/III IFN levels were not significantly different between male and female patients. However, IL-8 was significantly higher in male than in female patients. Of note, among longitudinally evaluated patients, CCL5 levels were significantly higher in male than in female patients. CXCL10 levels show a similar trend, though this was not significant.
Immune cell landscape (PBMCs)<br /> Both male and female patients exhibited a reduction among T cells and an increase in B cells. No significant differences in T cell subtypes (naïve, central/effector memory, follicular, regulatory) were observed between male and female patients. Of note, however, female patients showed (1) a significantly greater proportion of CD38+HLA-DR+ activated CD8+ T cells and (2) a concomitant enrichment of PD-1+TIM-3+ terminally differentiated T cells, compared to male patients. Otherwise, no other significant differences were identified between male and female patients.
The authors subsequently interrogated the peripheral myeloid compartment. Female patients showed a greater increase in CD14+CD16+ intermediate monocytes than male patients, while both patients exhibited a marked increase in total monocytes, compared to the controls. However, male patients showed higher levels of CD14loCD16+ non-classical monocytes than female patients and their uninfected, healthy counterparts. The authors noted that this enrichment of non-classical monocytes was correlated with CCL5 levels only in male patients.
Clinical comparison<br /> Clinical outcomes were tracked for both male and female patients. Clinical scoring was used to separate each group into two sub-groups: patients that had remained stable throughout hospital stay (stabilized) and patients that had worsened since the first sample collection (deteriorated). Deteriorated male patients were significantly older than stabilized male patients; there was no significant difference in age between stabilized and deteriorated female patients. In terms of BMI, both deteriorated male and female patients tended to be higher in BMI than their respective stabilized counterparts. Interestingly, anti-S1-IgG antibodies were higher in stabilized female patients than their deteriorated counterparts, though this trend was not seen with male patients. Otherwise, no other significant differences in clinical parameters were observed.
Additional comparisons between deteriorated and stabilized patients of each sex revealed that certain innate cytokine mediators (TNFSF10 and IL-15) associated with worse outcome in female patients but not in male patients. In contrast, the proportion of CD38+HLA-DR+ activated CD8+ T cells was significantly reduced in deteriorated male patients compared to their stable counterparts, but this was not true for female patients. Indeed, poor CD8+ T cell activation and IFN? production were both negatively correlated with age in male patients, but not in female patients.
Limitations<br /> • A significant number of patients were diagnosed with underlying chronic conditions that have been previously described to associate with poorer COVID-19 outcomes or with a compromised immune system. <br /> • Approximately two-thirds of each group (men and women) were treated with tocilizumab, and nearly a sixth of each group were treated with corticosteroids. While these patients were excluded from the baseline cohort, it is unclear whether or not these patients contributed to the second cohort that was longitudinally examined.<br /> • The mean age for patients is notably higher than the mean age for the HCW control group.<br /> • Duration of hospital stay was not considered, so it is unclear how quickly certain subsets of male and female patients deteriorated. This may be a confounding variable, or at the very least, the kinetics of disease course in male and female patients is a parameter that warrants investigation.
Significance<br /> In summary, Takahashi et al. provide the first report-to-date that delineates immunological differences between male and female patients with mild-to-moderate COVID-19 disease during the initial stages of infection. For example, male patients deteriorate due to less robust T cell-mediated antiviral immunity, compared to their female counterparts. Several of the other findings substantiate previous reports, such as those of significant neutrophil chemotaxis in the lung of COVID-19 patients (and its association with poorer prognosis). This study, therefore, provides an important platform for additional inquiries into key signaling pathways and transcriptional programs that are differentially regulated between male and female COVID-19 patients by specific cell types (i.e. intermediate and non-classical monocytes, CD38+HLA-DR+ CD8+ T cells) identified in this report. These studies, alongside others, are warranted to better tailor therapies for male and female COVID-19 patients.
This review was undertaken by Matthew D. Park as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.
On 2020-07-11 04:42:51, user Tom Jarman wrote:
the authors reached the conclusion that masks do not have a significant difference in person-to-person transmission for influenza-like illnesses, yet they still recommend use of masks. What am I missing here?
On 2022-01-06 23:28:48, user Greg Nelson wrote:
This is encouraging, would love to see another paper comparing to the PCR negative population (2346 respondees - 951 with PCR positive (study population) = 1395 people) to see baseline frequency of symptoms
On 2020-08-24 05:59:23, user Jala Painter wrote:
If hydroxychloroquine is dangerous as a treatment for COVID19 will a lupus patient have to go off his Plaquenil medication if he contracts COVID19?
On 2020-08-24 17:50:51, user Puvvada Rahul krishna wrote:
We would like to withdraw the article from MedRxiv. The reason for withdrawal was plagiarism issue while publishing to other journal's
On 2020-08-25 20:28:59, user Jean Sanders wrote:
this is very valuable information; I am trying to process the data so I will be informed when we have meetings this week on school re-opening... Thank you for this fine work and the many references
On 2020-09-05 11:35:05, user Tricia Young wrote:
Thank you for providing statistics that are more consistent with what is really happening. Will this article be published?
On 2020-05-13 03:36:31, user Annalisse Mayer wrote:
But what about the people who died suddenly at home and never made it to the hospital? How many of them were smokers? Maybe being able to get to the hospital means one is better at resisting the infection
On 2022-02-12 20:26:12, user Jan Lakota wrote:
This paper is in concert with the presented findings:<br /> New diagnosis of multiple sclerosis in the setting of mRNA COVID-19 vaccine exposure
J Neuroimmunol. 2022 Jan 15;362:577785. doi: 10.1016/j.jneuroim.2021.577785.
On 2020-03-25 22:19:11, user Sinai Immunol Review Project wrote:
Title
Detectable serum SARS-CoV-2 viral load (RNAaemia) is closely associated with drastically elevated interleukin 6 (IL-6) level in critically ill COVID-19 patients
Keywords
ARDS; interleukin-6 (IL-6); procalcitonin (PCT); pro-inflammatory cytokines; SARS-CoV-2 RNAaemia
Key findings
48 adult patients diagnosed with Covid19 according to Chinese guidelines for Covid19 diagnosis and treatment version 6 were included in this study. Patients were further sub-divided into three groups based on clinical symptoms and disease severity: (1) mild, positive Covid19 qPCR with no or mild clinical symptoms (fever; respiratory; radiological abnormalities); (2) severe, at least one of the following: shortness of breath/respiratory rate >30/min, oxygen saturation SaO2<93%, Horowitz index paO2/FiO2 < 300 mmHg (indicating moderate pulmonary damage); and (3) critically ill, at least one additional complicating factor: respiratory failure with need for mechanical ventilation; systemic shock; multi-organ failure and transfer to ICU. Serum samples and throat-swaps were collected from all 48 patients enrolled. SARS-CoV-2 RNA was assessed by qPCR with positive results being defined as Ct values < 40, and serum interleukin-6 (IL-6) was quantified using a commercially available detection kit. Briefly, patient characteristics in this study confirm previous reports suggesting that higher age and comorbidities are significant risk factors of clinical severity. Of note, 5 out of 48 of patients (10.41%), all in the critically ill category, were found to have detectable serum SARS-CoV-2 RNA levels, so-called RNAaemia. Moreover, serum IL-6 levels in these patients were found to be substantially higher and this correlated with the presence of detectable SARS-CoV-2 RNA levels. The authors hypothesize that viral RNA might be released from acutely damages tissues in moribund patients during the course of Covid19 and that RNaemia along with IL-6 could potentially be used as a prognostic marker.
Potential limitations
While this group’s report generally confirms some of the major findings of a more extensive study, published in early February 2020, (Huang C et al, Lancet 2020; 395:497-506; https://www.thelancet.com/a... "https://www.thelancet.com/action/showPdf?pii=S0140-6736%2820%2930183-5)"), there are limitations that should be taken into account. First, the number of patients enrolled is relatively small; second, interpretation of these data would benefit from inclusion of information about study specifics as well as providing relevant data on the clinical course of these patients other than the fact that some were admitted to ICU (i.e. demographics on how many patients needed respiratory support, dialysis, APACHE Ii/III or other standard ICU scores as robust prognostic markers for mortality etc). It also remains unclear at which time point the serum samples were taken, i.e. whether at admission, when the diagnosis was made or during the course of the hospital stay (and potentially after onset of therapy, which could have affected both IL-6 and RNA levels). The methods section lacks important information on the qPCR protocol employed, including primers and cycling conditions used. From a technical point of view, Ct values >35 seem somewhat non-specific (although Ct <40 was defined as the CDC cutoff as well) indicating that serum RNA levels are probably very low, therefore stressing the need for highly specific primers and high qPCR efficiency. In addition, the statistical tests used (t-tests, according to the methods section) do not seem appropriate as the organ-specific data such as BUN and troponin T values seem to be not normally distributed across groups (n= 5 RNAaemia+ vs. n= 43 RNAaemia-). Given the range of standard deviations and the differences in patient sample size, it is difficult to believe that these data are statistically significantly different.
Overall relevance for the field
This study is very rudimentary and lacks a lot of relevant clinical details. However, it corroborates some previously published observations regarding RNAemia and IL-6 by another group. Generally, regarding future studies, it would be important to address the question of IL-6 and other inflammatory cytokine dynamics in relation to Covid19 disease kinetics (high levels of IL-6, IL-8 and plasma leukotriene were shown to have prognostic value at the onset of ARDS ; serum IL-2 and IL-15 have been associated with mortality; reviewed by Chen W & Ware L, Clin Transl Med. 2015).
Reviewed as part of a project by students, postdoctoral fellows and faculty at the Immunology Institute of the Icahn School of Medicine at Mount Sinai
On 2020-10-22 15:04:33, user BB_Aragon wrote:
Table 6 in the supplementary material appears to be another copy of the text. Could the author please replace this with the actual Table 6?
On 2020-04-22 11:58:50, user Hans-Ulrich ISELIN wrote:
Has anybody found a reference for the definition of the SOC (Standard of Care) applied in this study?
On 2022-10-13 01:38:32, user Renier Mendoza wrote:
Now published in the Journal of Korean Medical Science
On 2023-12-21 15:35:25, user OJ Watson wrote:
Now published at: https://www.science.org/doi...
On 2024-02-05 08:06:08, user Sydney Paltra wrote:
A peer-reviewed version of this preprint is now available under: https://doi.org/10.3390/arm...
On 2020-04-28 09:20:22, user Carlos Gaspar Reis wrote:
What hydrogen peroxide concentration was used, 3%?
On 2020-05-23 09:25:08, user Francesca Simonato wrote:
What hydrogen peroxide concentration was used?
On 2020-04-28 11:01:19, user Henry Lahore wrote:
I do not understand the author's matrix pool testing process..
On 2022-05-03 19:26:37, user Carol Taccetta, MD, FCAP wrote:
The MMIA assay used here comes from the same institution as the authors--the reference states it is under a provisional patent.
On 2022-06-24 22:44:55, user S. W. wrote:
This preprint has been published in Emerging Infectious <br /> Diseases at https://doi.org/10.3201/eid2808.220617.
On 2022-10-23 23:35:14, user Aditya Awasare wrote:
I really enjoyed reading the paper and it is amazing to see what the future of diagnosis and disease modelling could one day be. I was really curious about the criteria used for the definition and classification of signs and symptoms but could not find the attached supplemental tables. Also, since one of the factors that makes the diagnosis of neurological diseases so hard is the presence of comorbidities, can this model be extended to detect their presence? What would the training data look like for this or how would the signs and symptoms classification be modified to accommodate this?
On 2022-10-29 10:11:21, user samer singh wrote:
Published/peer-reviewed version of the study is available at Clinical and Translational Discovery https://doi.org/10.1002/ctd...
On 2022-11-10 09:21:51, user Clive Bates wrote:
Please see our post-publication peer review of this pre-print published at Qeios.
Bates, C., Youdan, B., Bonita, R., Laking, G., Sweanor, D., & Beaglehole, R. (2022). Review of: “Tobacco endgame intervention impacts on health gains and Maori:non-Maori health inequity: a simulation study of the Aotearoa-New Zealand Tobacco Action Plan.” Qeios DOI 10.32388/8WXH0J
The paper, Ouakrim et al., refers to modelling of proposed New Zealand legislation that would make deep reductions in the nicotine in cigarettes. The review notes that the authors have assumed this will lead to an 85% reduction in smoking over five years, with almost one-third of smokers quitting in each year. Our Qeios review examines the origins and credibility of that assumption.
We identify ten flaws in the modelling and stress that the smoking cessation trial on which its assumptions are largely based is not a viable proxy for assessing the impact of a market-wide regulatory intervention. The modelling does not simulate the most likely behavioural responses that would follow from such an intervention and does not address plausible unintended consequences such as illicit trade, hoarding or workarounds..
I should stress that this review of the modelling is not intended as a decisive argument against the proposed denicotinisation policy. It is, however, an argument against relying on this modelling to justify the policy. There are other considerations both for and against the policy.
Our review should be seen as a constructive contribution to sound policy-making. Decision makers should should proceed without over-reliance on modelling, knowing its limitations, possible risks and likely unintended consequences. The reveiw authors have not explicitly opposed the measure but suggested it needs to be re-evaluated: <br /> (1) with a deeper assessment of the risks of unintended consequences; <br /> (2) against a maximalist approach to voluntary tobacco harm reduction as the counterfactual (not just business as usual); <br /> (3) a better understanding of how it will work for the most disadvantaged people and communities.
On 2022-11-11 09:33:21, user S Venkata Mohan wrote:
This article was published with the following citation
Surveillance of SARS-CoV-2 genome fragment in urban, peri-urban and rural water bodies: a temporal and comparative analysis<br /> p. 0987 | Hemalatha, Manupati; Tharak, Athmakuri; Kopperi, Harishankar; Kiran, Uday; Gokulan, C. G.; Mishra, Rakesh K.; Mohan, S. Venkata doi: 10.18520/cs/v123/i8/987-994.
Due to DOI issue we are not able to link
On 2022-11-26 16:52:14, user Miles Markus wrote:
This analysis by expert mathematicians is very welcome because as they state: "Understanding the cause of recurrent vivax malaria is critical for disease control efforts …".
Homology in relation to Plasmodium vivax malarial recurrences is a core concept in this interesting paper. A complication as regards interpreting the origin of recurrences caused by homologous parasites has recently arisen because there has been a paradigm shift in our understanding of P. vivax biology. The bulk of the P. vivax parasite biomass in chronic infections is now known to be located outside the peripheral bloodstream and liver; and more recurrences might be recrudescences (as opposed to relapses – there being comparatively few hepatic hypnozoites present) than meets the eye [1].
Light should soon be shed upon the matter. This is when it becomes apparent, from experiments using humanized mice, whether or not primaquine kills non-circulating asexual stages in bone marrow [2]. The prevailing idea in the literature is that most recurrences of P. vivax malaria are relapses, which is not necessarily correct (although it could be). That conclusion has been drawn mainly from recurrence patterns following treatment of patients that included primaquine.
It is hoped that once the forthcoming new information related to parasite homology has become available via drug testing, the authors of this medRxiv article will be able to further extend their important analyses to take account thereof.
REFERENCES:<br /> 1. Markus MB. 2022. Theoretical origin of genetically homologous Plasmodium vivax malarial recurrences. Southern African Journal of Infectious Diseases 37 (1): 369. https://doi.org/10.4102/saj...<br /> 2. Markus MB. 2022. How does primaquine prevent Plasmodium vivax malarial recurrences? Trends in Parasitology 38 (11): 924–925. https://doi.org/10.1016/j.p...
On 2022-12-15 10:31:26, user RBNZ wrote:
Please make your code available on GitHub, not just the readme. Thanks.
On 2022-12-31 00:46:16, user Luis Cruz wrote:
What could explain the differences between Figure 2 from this current manuscript and Figure 4 from the manuscript published here:
On 2023-01-03 01:06:03, user Myssi Graves wrote:
How can they say it was unexpected that increased doses would increase risk when there’s decades of evidence of this with flu vax. It was an obvious outcome to anyone educated on the topic. Sadly anyone who mentioned this possibility was vilified.
On 2023-01-07 03:30:19, user loki4loki wrote:
The authors have a new definition of effectiveness. I thought a vaccine was effective if it prevented hospitalization and death. Now they have changed the goal posts. No wonder the Browns are having a bad year.
On 2023-01-17 14:50:16, user Theo Sanderson wrote:
This manuscript has been retracted. The retraction notice reads: "The authors of this article were made aware of a technical oversight which invalidate their conclusions, and alerted the editorial office so it could be withdrawn."
On 2023-01-23 00:21:16, user Stephen Akar wrote:
I am trying to access the supplementary results.
On 2023-01-26 13:02:03, user Jillian Richmond wrote:
Published online in the Journal of Investigative Dermatology https://www.jidonline.org/a...
On 2023-02-02 06:20:07, user Dr. Albert wrote:
Thank you for such an amazing paper! Your paper provides novel insight into non-invasive COVID-19 detection method, which has the potential to be implanted worldwide. To strengthen this paper even more, I would suggest some edits for your introduction/discussion section. It would be great to incorporate the advantage and disadvantage of recently used detection methods followed by how your model overcomes the caveats of pre-existing detection methods. Also, a very recent preliminary paper from University of Toronto hypothesized the application of Raman scattering along with fluorescence resonance energy transfer to detect COVID-19 using the breath! It might be worthful for you to mention about it in the paper as one of the emerging technique along with its pros and cons relating to your detection method.
Here is the link to that paper: https://www.tmrjournals.com...
On 2023-02-27 14:29:13, user Katka2507 wrote:
Thank you for sharing your data. I have a few questions. <br /> When did the patients start to complain about the symptoms indicating endophthalmitis? I could only read the information about the post catarct surgery period when you started a treatment. We also have to think of TASS.<br /> Did you counted as endophthalmitis only patients with positive cultures or all with symptoms? It is often difficult to take a vitreous sample but all of the symptoms indicate the endopthalmitis.
On 2023-03-07 04:37:46, user Ted Gunderson wrote:
July 2021 had more covid19 deaths than any other month in Rwanda.
This was after 80% of the population was injected with the covid19 vaccines.
African countries with significantly lower vaccination rates had significantly lower covid19 mortality rates.
Why doesn't this paper address this?
On 2023-03-29 21:17:46, user Kevin J. Black wrote:
The final published version appears at https://www.mdpi.com/2077-0...
On 2023-04-02 19:09:38, user GL wrote:
This systematic Review is lacking of protocol in PROSPERO. It says that follow PRISMA guidelines but it does not.
Therefore the findings are biased.
I would recommend the authors to follow more rigorously the PRISMA 2020 Guidelines or in case delete the term "systematic".
On 2023-04-14 09:15:23, user Alexander Kastaniotis wrote:
Very nice work! A comment on lipoic acid: <br /> lipoic acid does enter mitochondria, and it is used in standard mitochondrial disorder treatment cocktails, where it works as a potent antioxidant. However, in contrast to some prokaryotic lipoylation systems, mitochondria lack the machinery to activate free lipoic acid for attachment to pyruvate dehydrogenase, alpha-ketoglutarate dehydrogenase E2 subunits etc. When mitochondria are equipped with a lipoic acid activating enzyme, externally supplied lipic acid can be used for attachment. Please have a look at our work: <br /> Pietikäinen et al 2021: Genetic dissection of the mitochondrial lipoylation pathway in yeast. doi: 10.1186/s12915-021-00951-3<br /> It may also be worth noting that the complete KO of Mecr in mice causes embryonic lethality (Nair RR et al 2017; doi: 10.1093/hmg/ddx105)
On 2023-04-19 11:20:18, user Jonas Reinold wrote:
Page 6: "Current management of BD consists largely of pharmacological interventions, and the use of highly anticholinergic drugs has increased over the past 25 years (Reinold et al., 2021; Sumukadas et al., 2014)" The paper from Reinold et al is a cross-sectional study that reports prevalences of anticholinergic burden in Germany for a single year, it does not report any changes over time. The paper from Sumukadas is based on two cross-sectional analyses in 1995 and 2010 and does not say anything about an increase "over the past 25 years". Please revise the citations.
On 2023-04-27 15:33:25, user Anshu Varma wrote:
Dear Vincent Auvigne
I hope this e-mail finds you well.
My colleagues and I at the World Health Organization are<br /> intrigued by your study in France on the vaccine effectiveness of bivalent boosters compared to monovalent boosters against symptomatic SARS-coV-2 disease, among adults aged >60 years. Your work is timely, so we would be highly appreciative if you could help us improve our understanding of the study.
We acknowledge that baseline characteristics did not differ<br /> between groups, but we wonder if the recommendation for bivalent boosters and<br /> monovalent boosters may have been different and would like to know your<br /> thoughts on that.
Do you know why the bivalent booster was offered concurrently with the monovalent booster between 03/10/2022 and 06/11/2022 in the study area?
Do you know who the bivalent booster was recommended to<br /> between 03/10/2022 and 06/11/2022 in the study area?
Do you know who the monovalent booster was recommended<br /> to between 03/10/2022 and 06/11/2022 in the study area?
Thank you very much in advance and looking forward to hearing from you.
All the best
Anshu Varma
Technical Officer,<br /> COVID-19 Vaccine Effectiveness, Impact<br /> Department of Immunization, Vaccines & Biologicals (IVB)<br /> Universal Health Coverage/Lifecourse Division<br /> World Health Organization, Geneva, Switzerland<br /> varmaa@who.int
On 2023-05-18 18:59:30, user Dave Fuller wrote:
Please add peer-reviewed citation as:
Wahid KA, Lin D, Sahin O, Cislo M, Nelms BE, He R, Naser MA, Duke S, Sherer MV, Christodouleas JP, Mohamed ASR, Murphy JD, Fuller CD, Gillespie EF. Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites. Sci Data. 2023 Mar 22;10(1):161. doi: 10.1038/s41597-023-02062-w. PMID: 36949088; PMCID: PMC10033824.
Thanks!
On 2023-06-01 08:26:53, user Thomas Kesteman???????????????? @thomask@m wrote:
This preprint has generated crucial concerns about both scientific content and ethical/legal aspects.<br /> Please see the PubPeer thread for more information: https://pubpeer.com/publica...
On 2023-06-01 12:17:00, user Anne-Marthe Sanders wrote:
A peer-reviewed and published version of the article can be found at: https://www.ncbi.nlm.nih.go...
On 2023-06-14 10:46:05, user Sayomporn Sirinavin wrote:
The title of the published version was changed by adding a word "nonimmune". <br /> The revised title is:
Effect of Andrographis paniculata treatment for nonimmune patients with early-stage COVID-19 on the prevention of pneumonia: A retrospective cohort study.
On 2023-06-15 06:08:48, user Ashok Palaniappan wrote:
A peer-reviewed version of the preprint has now been published:<br /> Muthamilselvan S and Palaniappan A (2023) BrcaDx: precise identification of breast cancer from expression data using a minimal set of features. Front. Bioinform. 3:1103493. doi: 10.3389/fbinf.2023.1103493
On 2023-07-01 05:57:09, user Zhaolong Adrian Li wrote:
Published as Li ZA, Cai Y, Taylor RL, et al. Associations Between Socioeconomic Status, Obesity, Cognition, and White Matter Microstructure in Children. JAMA Netw Open. 2023;6(6):e2320276. doi:10.1001/jamanetworkopen.2023.20276
On 2023-07-24 18:51:05, user CliffHan wrote:
Please direct your questions related to AllerPops products to info@allerpops.com. Thank you. Cliff
On 2023-08-22 14:47:23, user SRamin wrote:
I wonder if there is something different about individuals who get the bivalent vaccine versus individuals who do not that may explain the outcome observed in this study. <br /> 1) For example, perhaps individuals who received the bivalent vaccine work in a "higher risk" environment (ex. Doctors and nurses with direct patient contact) and those who did not get the bivalent vaccine worked in a "lower risk environment" (housekeeping/sanitation/cafeteria workers/laundry services). Perceived occupational risk would self-select for the exposure of interest and if perceived occupation risk matches actual risk then we would expect that bivalent vaccinated individuals would experience higher incident covid-19 rates because of higher risk of exposure. I see that one of the covariates of interest was "job location" which I presume refers to the physical location of employment in Ohio, but I think it is important to collect data on employee job type (direct patient contact vs indirect patient contact) and adjust for this in the multivariate models. <br /> 2) Another potential explanation for these results could be that individuals who received the bivalent vaccine versus those who did not had perceived an added protection and were more willing to place themselves in "riskier situations" for contracting COVID (perhaps bivalent vaccine recipients are more likely to eat out at restaurants or shop in public because of perceived added protection) or they may have felt less inclined to follow other COVID-19 infection prevention methods (less likely to wear masks or wash hands because of perceived protective benefit from the vaccine).
On 2023-08-28 18:17:04, user Yiran Wang wrote:
This paper has been modified and published in the Journal of Nuclear Medicine. <br /> DOI: https://doi.org/10.2967/jnu... <br /> https://jnm.snmjournals.org...
On 2023-09-12 09:30:17, user Chris Iddon wrote:
This paper conflates SARS-CoV-2 genome copies (ie RNA) with viable virions on page 14. Data from the human challenge studies suggests that there are between 100 to 10,000+ RNA copies to a viable virion and thus the authors are overestimating the transmission potential and infection risk. Please see Killingley et al doi 10.1038/s41591-022-01780-9 and Zhou et al doi 10.1016/S2666-5247(23)00101-5<br /> Also what is the limit of detection for the RT-PCR assay? How much of the total eluate was used in a single assay?
On 2023-10-17 03:28:40, user CDSL JHSPH wrote:
Dear Dr. Bi et. al., <br /> I would like to express my appreciation for your preprint. This preprint provides valuable insight into the phenomenon of declining effectiveness of repeated flu vaccinations. n this influenza pandemic season, it is important to have in-depth research on the issue of the effectiveness of the influenza vaccine. Your study provides timely insights. You used real-world data covering multiple seasons, which demonstrates a comprehensive understanding of vaccination and infection.
However, I have some comments and questions that I hope will help improve the paper and deepen my understanding of the study. The discussion of potential causes of reduced vaccine effectiveness was insightful. However, it may be useful to discuss the practical implications of these findings for vaccination policies and recommendations. How might this research guide public health decision-making? Would age be one aspect that might influence the reduced effectiveness of repeat vaccination? As age often plays a role in immune responses. <br /> Furthermore, I encourage you to include a section on future directions, highlighting potential areas of research or specific questions that have emerged from this study. This could inspire further investigations in the field of influenza vaccine effectiveness. To enhance the clarity of your work, I also suggest incorporating a clear statement in the abstract or introduction section that succinctly outlines the problem your research aims to address. This would assist readers in swiftly understanding the primary focus of your study.<br /> Overall, your preprint is valuable and thought-provoking, and I look forward to seeing how it progresses in terms of publication and further research.
On 2023-10-24 03:42:50, user Prasad Babar wrote:
Dear Dr. Bi et al,<br /> This preprint provides valuable insights into the declining effectiveness of repeat flu vaccinations, addressing a critical issue in influenza vaccine effectiveness. The use of real-world data and the exploration of factors such as vaccination timing and prior clinical infections is commendable. The paper's significance lies in its contribution to understanding complex factors affecting vaccine efficacy.<br /> The robust methodology, including the use of observational data and logical theoretical modeling of subclinical infections, supports the paper's conclusions. However, the absence of data on subclinical infections is a notable limitation, and the paper should acknowledge this gap more explicitly and discuss its potential implications for the conclusions.<br /> While the paper is generally well-presented, a simple illustration of the modelling approach would enhance accessibility. <br /> The lessons regarding the influence of the immune system, the importance of monitoring subclinical infections, and the need for empirical studies on subclinical infection rates are valuable. Further research in these areas and the development of future research directions should be emphasized.<br /> Overall, this preprint makes a substantial contribution to the field, challenging conventional vaccine efficacy assessment and emphasizing the potential role of subclinical infections. It provides important insights while acknowledging the need for empirical data on subclinical infections and a more explicit discussion of limitations and practical implications.
On 2023-11-16 17:02:09, user Emma wrote:
this paper has now been published: https://substanceabusepolic...
On 2024-01-03 10:54:03, user Andres Ceballos wrote:
This paper has been publised on Frontiers. Cell. Infect. Microbiol journal:
Emergence and circulation of azole-resistant C. albicans, C. auris and C. parapsilosis bloodstream isolates carrying Y132F, K143R or T220L Erg11p substitutions in Colombia https://doi.org/10.3389/fci...<br /> Front. Cell. Infect. Microbiol., 21 March 2023<br /> Sec. Fungal Pathogenesis<br /> Volume 13 - 2023
On 2024-02-02 01:52:27, user Alan Olan wrote:
The article has been published at Journal of Clinical Trials and available via - https://www.longdom.org/ope...
OR
On 2024-02-09 18:56:46, user Adriano Aguzzi wrote:
It was brought to my attention that this manuscript contains an error. In Figure 2D, the band representing tau immunoreactivity is duplicated between the 2nd and the 10th lane. The raw data of the uncropped blot from which Figure 2D is derived (Supplemental Fig. S1) provides the correct images. The transposition error in Fig. 2D has no impact on the interpretation of the results and will be corrected in a future version of this manuscript. Adriano Aguzzi
On 2024-02-20 02:54:02, user disqus_y4jraNO9xU wrote:
This paper was published here https://www.nature.com/arti...
On 2024-02-26 17:16:20, user Ciarán McInerney wrote:
Please, justify why<br /> you use a 1:4 ratio for matching. Is this representative of the true<br /> prevalence? Perturbing the true prevalence is only valid for control<br /> experimental studies, not for observational studies. Note that some of the<br /> statistics you use to evaluate your predictive model are affected by the<br /> prevalence of the outcome, so arbitrarily fixing it invalidates their<br /> interpretation as real-world evaluations (specifically, NPV and PPV, which are<br /> the canonical statistics for evaluating prediction).
On 2024-03-05 20:40:49, user Calum Polwart wrote:
An interesting approach to analysis, and good use of cross sector data.
I'd be interested to know if the authors considered use the the WHO ATC defined daily doses for calculation of their prescription numbers. Ideally they should provide an explanation to the 5d course length.
A couple of minor issues:
The version of R is incorrect - it should presumably be R4.3.1 not 4.31
The red line on the histograms are very difficult to read and perhaps the darkness of the histogram fill could be reduced?
On 2024-03-12 13:07:14, user Torben Redmer wrote:
Our article has now been published at Acta Neuropathologica:
Redmer, T., Schumann, E., Peters, K. et al. MET receptor serves as a promising target in melanoma brain metastases.<br /> Acta Neuropathol 147, 44 (2024). https://doi.org/10.1007/s00...
On 2024-04-24 21:14:09, user Austin Bessire wrote:
I have personally suffered from TSW and this work is unimaginably valuable from a patient's perspective. Insight as to how there is increased expression of mitochondrial complex I helps legitimize my suffering and provide more understanding as to how I may be able to treat it. I also am grateful to see that abnormalities were induced by glucocorticoid exposure both in vitro and in a cohort of healthy controls to rule out it being solely environmentally caused.
On 2024-04-27 20:26:14, user Sarah Simpson wrote:
Thank you for this important study. I have been suffering with topical steroid withdrawal for over 20 months after 35+ years of use for my atopic dermatitis which only got worse. My skin is now finally healing after the cessation of all medication. We need more research and for doctors to know more about this iatrogenic condition
On 2024-04-29 16:25:58, user Mandy wrote:
I am a former research biochemist whose daughter suffered from this TSW. I am so profoundly grateful to see meaningful research being done in this area - this could be a first step to treatments to alleviate the symptoms of this debilitating condition, and of the ability to assess genetic or epigenetic risk factors so we can prevent it in the first place. It is particularly validating to see quantitative differences between steroid withdrawal/red skin syndrome and atopic eczema.
On 2024-04-26 22:22:12, user Sailing Pelagia wrote:
Now published in The Canadian Journal of Speech-Language Pathology and Audiology.<br /> https://www.cjslpa.ca/detai...
On 2024-05-04 17:43:46, user VINOD KUMAR CHAUHAN wrote:
This paper has been published with changes in the title of the paper. Kindly link the published paper to the preprint.<br /> Published paper link: https://bmcmedinformdecisma...
On 2024-05-06 10:22:51, user Agustín Estrada Peña wrote:
Dear author,<br /> At a first reading I could find three major gaps in this study, for which I advice a deep review:<br /> 1. If the mapping is based on human clinical cases, it ignores the reports on wild animals (serology), on questing and feeding ticks. An infection transmitted by vectors and reservoirs by wild vertebrates should be NEVER mapped using only human cases. It is simply underrated.<br /> 2. The pathogen is transmitted ONLY by Ixodes ricinus ticks (in Poland). Therefore, predicting the habitat of other tick species will dangerously bias your results, since they have quite different preferences regarding weather, vegetation, landscape, etc.<br /> 3. Several species of Borrelia burgdorferi circulate in Poland. They are reservoirs by different vertebrates, like birds, or Rodentia. If you do not account for the distribution of these reservoirs, you can not accurately map the "preferences" of each species of the pathogen to circulate. The community of vertebrates has an effect on these processes.<br /> Thank you.<br /> Agustín Estrada-Peña
On 2024-05-08 05:54:42, user Valerie Yang wrote:
https://pubmed.ncbi.nlm.nih...
This article has been published on November 9, 2023
On 2024-05-08 09:57:18, user Andrew McIntosh wrote:
Interesting YouTube discussion on the paper here from Eiko Fried and Michele Nivard: https://www.youtube.com/wat...
On 2024-06-21 10:46:13, user Mamadu Baldeh wrote:
This preprint has undergone peer review and is now published in BMC Infectious Diseases. The published article can be accessed via DOI 10.1186/s12879-024-09524-5 or directly at https://bmcinfectdis.biomed...
Please link this preprint to the published version
On 2024-08-06 18:36:26, user Cindy wrote:
I would like to include some feedback regarding data analysis (full disclosure, I work for Olink), which I hope will be beneficial to both authors and others who are analyzing similar data from Olink:<br /> We recommend calculating Limit of Detection (LOD) according to manufacturer’s guidelines, specifically LOD for Explore HT should be calculated based on actual project data rather than use of estimates of LOD from unrelated validation data. <br /> The best practice is to use Olink Analyze functionality to determine the LOD for each project (available in the latest version!). <br /> Replacing values below LOD with LOD/2 is not recommended. It will artificially inflate coefficient of variation (CV) values. Instead, apply an LOD cutoff specific to the project data. Removing values below the project-specific LOD when calculating CVs ensures a more accurate representation of data variability.<br /> I am happy to coordinate any discussions with the Olink team to facilitate.
On 2024-10-21 23:26:17, user CDSL JHSPH wrote:
I think that the background behind your research is very important to the field of tuberculosis treatment. Treating the patients so that the bacteria is out of their body while also preventing antibiotic resistance and any toxicities that the medication may cause is an important balance when deciding duration and dosage of treatments. Utilizing the dose-finding methods, such as MCP-Mod, and applying it to studying duration-ranging of TB treatments seems like a very practical method to studying this topic.
I am curious about what you plan to do with the results of this study moving forward? You have identified a method to use in duration-ranging studies for TB antibiotics, but are you planning on using this information in your own studies? Is this a topic that many researchers in the field were looking for? I am just wondering about the practicality of this study and how it will actually be used moving forward.
On 2025-01-03 16:28:46, user Karl Klein wrote:
This article has now been published in the journal Epilepsia: http://doi.org/10.1111/epi.18251
On 2025-03-06 13:21:04, user Matteo Pozzi wrote:
Here is the accepted version of the manuscript: https://www.nature.com/articles/s41598-024-79602-w
On 2025-04-04 12:04:32, user Claire Brereton wrote:
I would be very interested to know what value of R0 you derived. I cannot find the supplementary material you refer to.
On 2025-04-24 14:04:15, user Sara Uccella wrote:
published on Sleep Medicine: https://www.sciencedirect.com/science/article/pii/S1389945725002072
On 2022-07-27 11:02:06, user Karen wrote:
The SARS-CoV-2 comparison is flawed.
* You compare cases (testing and reporting-dependent, highly time-variable), not incidence rates (such as ONS estimates)<br /> * You compare cases in the general population, not the paediatric population<br /> * You plot cases on a log scale against hepatitis cases on a linear scale.
This needs revision. Indeed, when you revise it, you find that the conclusion is literally reversed.
On 2022-08-12 15:45:38, user Daniel Corcos wrote:
As I understand it, lifting the mask requirement on March 10 rather than March 3 was associated with more COVID.
On 2022-08-12 17:17:01, user Dr. Amy wrote:
An updated version of this work is now accepted and in press. The primary differences are 1) we evaluated and did find a reduction in symptoms based on adherence to a 2/day regimen. 2) The most likely reduction in severity comes from the effect of NS high volume irrigation on the nasal biome. We have added this reference by Dr. Huijghebaert and recommend interested scientists use this as the rationale for why irrigation reduced COVID severity: https://pubmed.ncbi.nlm.nih... Finally, we would like to reiterate that Povidone Iodine did not provide any benefit over the other NS regimen, and of course vaccination is the best way to reduce severity.
On 2022-09-13 08:47:26, user Gabriel Costa wrote:
Here is Gabriel, the first author. Some updates:
1 - There is an error in the prisma flowchart diagram (Fig 1), it is missing one observational study that was excluded. We had 81 RCTs, 7 phase one trials and 1 observational study (this last is missing in the figure). It was excluded due to the replication not having the same PICO components.
2 - We are conducting the direct comparison meta-analyses via R and the results with simple coding are almost the same, using MH method for all. Network and IPD meta-analyses it was not possible for this to be done.
3 - Since (2) = TRUE, we are excluding the highly cited article of the meta-analysis, making the meta-analysis a complete independent replication. We do not observe substantial differences in the effects, suggesting that the 50% cutoff was adequate and only if the trial weights 90% of the meta-analysis this dependency becomes a problem.
4 - Since (2) and (3) = TRUE, we are calculating prediction intervals as well.
5 - There is a typo in the abstract in the Methods section. "We... and potential predictors or replicability". The correct is predictors OF replicability.
An overview of the project, datasets and analysis code can be found at https://osf.io/a8zug/. As well as these updates.
Thanks for the interest,<br /> Gabriel Costa on behalf of all authors
On 2022-09-27 14:26:13, user C. Downs wrote:
Published version can be found at https://doi.org/10.1177/105...
On 2022-10-04 16:28:04, user Thomas Arend wrote:
Dear Venkata,
I have some remarks to your study.
The age bands in your tables are very big. We know elderly people were <br /> vaccinated first. Elderly people have a higher risk to die or get <br /> hospitalized from COVID-19.
In the age band > 18 yo this would lead to a pattern as in figure 5b <br /> and 5c. The hospitalization and death rates rise with the start of the <br /> vaccination process in the vaccinated group, just because the members of <br /> the group are older.
After a peak, the rates fall back to a lower level (right side of the figures).
On the other hand the unvaccinated group consists of younger people<br /> as the older people leave the group by vaccination. The rates would <br /> fall with the beginning of the vaccination process and rise later to a <br /> higher level.
This effect can be seen in the ONS data, even when you compare smaller age bands and take the start of the vaccination process into account.
An equivalent argument would be valid for differences in sex.
As I know from Germany, the vaccination rate rises with age. Older people<br /> are more likely to be vaccinated than younger people. Therefore, there <br /> is a bias between vaccinated and unvaccinated people by age and possible<br /> sex.
For risk assessment, you are comparing a group of younger unvaccinated with older vaccinated people. This is misleading. And will probably be the reason for the negative vaccine effectiveness.
The curves in figure 5b and 5c depend highly on the age and sex structure of the groups.
In table 1 you are comparing all ages. The proportion of infected people in the differs largely by age over the time.
In Germany, only ~ 20 % of the age group 60+ yo and 80+ yo got infected <br /> until now. In the age group 5 – 14 yo and 15 – 34 yo, nearly 60 % got infected until now. The incidence varied a lot during the <br /> pandemic. So different time frames differ in the age and sex structure <br /> of the infected people.
Proposals
You should report and discuss the mean and median ages of the groups with standard deviation and IQR.
You should take at least the differences in age and sex into account and<br /> transfer the populations of the groups into a standard population and <br /> calculate the hospitalization and death rates for this standard <br /> population before comparing.
Or:
Even in the age bands 60+ yo the vaccination process produces a bias<br /> by age and sex because the risks rise almost with each age year and female have a lesser risk than male. Therefore, you should <br /> only compare small age bands with a width of five years or less.
You should divide the group of unvaccinated into unvaccinated and still not infected and unvaccinated and at least one time infected. Because infection works similar to vaccination.
Without these improvements, I can't see how you will come to a valid conclusion and result.
Best regards
Thomas Arend
On 2020-05-26 06:00:43, user Hooman Noorchashm wrote:
Cyclosporine could b the critical pharmacological block for arresting progression of COVID-19 disease to critical illness. Congratulations to our Spanish colleagues. https://www.drugwatch.com/n...
On 2020-05-26 20:56:26, user Sinai Immunol Review Project wrote:
Main Findings<br /> In this study, Bouadma and authors longitudinally profiled multiple immune parameters of a fatal case of Covid-19 that quickly developed multiorgan failure. An 80-year old male patient presented with fever and diarrhea that developed into multiorgan failure and hemoptysis over the course of 24 days that resulted in death. During this time, he was treated with broad-spectrum antibacterial agents, Remdesivir, and interferon beta-1a. Peripheral naive CD4+ and CD8+ T cells remained stable throughout, but effector memory T cells continually increased. Exhausted and senescent CD4+ and CD8+ T cells, and gamma delta T cells increased following day 14. Activated and exhausted B cells peaked on day 20. After day 16, NK cells and monocytes generally declined possibly due to lung trafficking. These fluctuations in immune populations were accompanied by induction of pro-inflammatory cytokines and Th1/Th2 factors that increased on day 14. Although some cytokines decreased following day 14, cytokines associated with T cell activation, exhaustion, and apoptosis continued to increase.
Limitations<br /> It is difficult to draw broad conclusions from one patient and this longitudinal study did not start at the onset of infection and symptoms. Furthermore, these observations were done on the peripheral blood without complementary analysis of the lung where they suspect NK cells and monocytes have trafficked to.
Significance<br /> This shows that immune cells proportion, functional state, and soluble factors fluctuate throughout disease progression. This is a broad overview of potential blood biomarkers that can be used to assess progression and severity.
Credit<br /> Reviewed by Dan Fu Ruan, Evan Cody and Venu Pothula as part of a project by students, postdocs and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai
On 2020-05-27 00:52:35, user Jayanti Prasad wrote:
Please post your comments, suggestions & feeback.
On 2020-05-28 15:04:54, user Judith Levine wrote:
Small point — probably just a typo, but the use of “country” in the abstract should be corrected to “county”.
On 2020-05-28 16:49:42, user Ruth Cleary wrote:
Wondering whether Metformin Instant Release and Extended release readings were different from each other and, if so, by how much.
On 2020-05-28 22:26:40, user Andrew Cohen wrote:
NOTE: On the Supplementary Material page, the file "Supplemental Material" goes with the currently posted preprint. (The file "Supplementary Appendix" belongs to an earlier version of the preprint that was posted on medRxiv.)
On 2020-06-02 05:55:45, user OxImmuno Literature Initiative wrote:
On 2020-06-29 19:44:04, user Justin wrote:
30/10/2020 in figure 2 appears to be a typo. It should read 30/10/2019
On 2020-06-10 09:40:43, user CC wrote:
are there any subtle clotting differences between A and O blood groups that could be relevant to the coagulopathy seen in CoVID19?
On 2020-05-03 14:25:00, user Geoff Turner wrote:
Comparing diagnostic tests like this is a classic signal detection problem. What is your d'? What's the d' for the nasopharyngeal test? What's the bias of each? This is the only way to know which test is most sensitive AND simultaneously least biased.
On 2020-05-14 05:11:14, user Matthew Ward wrote:
Hi Anne, brilliant study - Well done to all the team.
Could a saliva sample prove sensitive enough for Sars-Cov-2 to be detected on a lateral flow test?
Or would the sample almost always require amplification via PCR to increase sensitivity?
Many thanks<br /> Matt
On 2020-05-06 17:35:54, user Research Explained wrote:
Our group made a general public friendly summary of this study and its strengths and weaknesses. Check it out at: https://www.researchexplain...
On 2020-05-07 00:13:23, user mpeaton wrote:
Layman question: What were the aerosols made of, and did they evaporate? I have yet to find a paper demonstrating that ANY virus is viable after being exhaled in a droplet containing NaCl, proteins etc. and then dehydrating. Though there are some that claim otherwise, such as this one: https://dx.doi.org/10.1098%...
On 2020-05-07 15:07:58, user Thomas Meunier wrote:
KEY TAKEAWAYS FROM STUDY:
The research, which has not yet undergone standard peer review evaluation, does not question the efficiency of social distancing.
The research looks specifically at the impact of police-enforced home containment policies in some European countries.
The work suggests that social distancing may be just as effective as home containment.
4.The results show that the epidemic was already in decline (that is, the number of cases was growing less and less rapidly for 2 to 3 weeks before the lockdown and kept declining at the same rate afterwards) before the full lockdown, possibly thanks to social distancing measures already in place.
On 2020-05-07 20:20:44, user Gregory Kreiss wrote:
6% positive cases for 5-19 years old versus 8.5% for 20-49 years does not look like similar but an increase of 40% for the middle ages adults!<br /> Also one of the major limitation of this study is that we do not know wether the infected children are part of household where one of the adult has been also infected (cluster effect) and if it is the case who has infected who. To be conclusive the children should have been selected randomly within the population and not part of the household members.
On 2020-05-07 20:47:41, user Dan T.A. Eisenberg wrote:
We are thinking of implementing this in my lab for research purposes and hopefully to expand testing capacity. Have you or anyone else you know of tested the stability of saliva samples for longer periods of time, adding in preservative, and/or keeping more of a cold chain (e.g. stored at +4 or -20 for some time)?
On 2020-05-08 04:39:19, user Robin H wrote:
This study is weird.
First of all : why a daily dose of 600mg of HCQ?<br /> Raoult and his team use a dose of 200mg per day to treat Covid-19. The general dose for the treatment of rheumatoid arthritis or lupus is 200 to 400mg, max 600mg if there is no response.<br /> There is a high debate about the potential cardiac toxicity of HCQ... But with this dose, we can understand that "Eight patients receiving HCQ (9.5%) experienced electrocardiogram modifications requiring HCQ discontinuation." Of course...<br /> Did the authors intend to favor the cardiac toxicity of HCQ to invalidate this treatment?... I Wonder.
Second point: when you display the characteristics of the observed populations in the first table, you should indicate the p-value concerning the comparisons. If I'm correct, the HCQ group tends to have a more severe condition BEFORE treatment, at admission. 14 HCQ-treated patients (21.9%) vs 8 control patients (12.1%) had >50% of lung affected in CT scan... There is a trend to a significant difference with a p-value of 0.08...
Then, you can't be conclusive with such bias...
On 2020-05-08 05:56:07, user Masfin Otta wrote:
Obviously, the conclusion of the paper was dead wrong: the covid-19 outbreak in Okinawa had already been completely suppressed without stringent stay-home measures by 28 April and we are not seeing 20,000 deaths but only 5 so far. Perhaps, the total number of the cases was not on the exponential line, particularly after the middle of April, 2-3 weeks after the start of the outbreak as Professor Michael Levitt of Stanford observed from the outbreaks of China, Italy and Iran. Another discussion may be that Rt might have been much lower than assumed and the outbreak died out without many new cases imported from the mainland or perhaps Europe and North America where the epidemic is much much severe than the mainland.
On 2020-05-09 23:51:12, user Sinai Immunol Review Project wrote:
Main findings<br /> The humoral response to SARS-CoV-2 infection has been largely studied in the context of antibody distribution in the peripheral blood of COVID-19 patients. However, little has been explored that evaluates immunophenotyping of B cells in patients with different clinical courses of COVID-19. Here, Woodruff et al. investigated B cell populations by spectral flow cytometry to understand the protective and non-protective humoral responses using PBMCs from 9 critically ill and 8 mild patients with COVID-19.
Comparing CD45+ hematopoietic cells from 22 healthy controls and 17 COVID-19 patients, the authors found an expansion of CD19+ B cells in COVID-19 patients with a significant increase in CD138+ antibody-secreting cells (ASCs) among other B cell subpopulations: transitional, naive, double-negative, and memory. Interestingly, a greater abundance of these mature, CD138+ ASCs, which are often associated with protection during a vaccine-induced response, was found in COVID-19 patients with worse outcomes. Previously, this group described, in flaring systemic lupus erythematosus (SLE), an activated IgD-CD27-double negative B cell population that they characterized as part of an extra-follicular (EF) response. The comparison of the PBMCs across COVID-19 samples revealed two clusters: one that strongly upregulated the EF response pathway (EF-CoV), and one with a low EF response but a high transitional B cell signal (Tr-CoV).
Within the EF-CoV cluster, ASC expansion correlated with enriched ASC maturation and an increase in the active naïve (IgD+CD11c+) and a subset of the double-negative (DN2: IgMlo IgD- CD11c+ CD21-) cell compartments. The composition of the double-negative component with skewing to the ASC-associated DN2 group in the EF-CoV cluster appeared identical to the B cell landscape of patients with active SLE. Similar to the increase in IL-6 and IP-10 during active SLE, association with upregulated IL-6 and IP-10 and poor prognosis for COVID-19 was also found in this study. Higher serum IL-6 and IP-10, a CXCR3 ligand, and expression of CXCR3 by B cell subpopulations belonging to the EF-CoV cluster, supports the notion that peripheral homing of B cells to inflamed tissue sites, as described in both the lung and kidneys, takes place in COVID-19 patients.
A minor subset of B cells in the EF-CoV cluster were CD21lo transitional B cells. These cells were enriched in the Tr-CoV cluster and associated with mild disease. They shared several B cell immaturity markers, such as high levels of CD10 and CD38, and expressed high levels of surface IgM and muted surface IgD, which indicate extrafollicular homing. A longitudinal comparison of two ICU patients in each cluster (two EF-CoV patients and two Tr-CoV patients) revealed that the paucity of CD21lo transitional B cells in the EF-CoV was associated with higher severity of disease and a decrease in PaO2/FiO2 ratio (a measure of gas exchange efficiency). EF-CoV patients had higher levels of CRP, which correlated with a low frequency of transitional B cells, a high number of DN2 B cells, and elevated serum IL-6. Importantly, these patients faced poorer outcomes.
Limitations<br /> Aside from the small sample size in the primary study and in the longitudinal follow-up, this report relies on surface markers to assess B cell heterogeneity in COVID-19 patients and characterize potential autoimmune subpopulations that are also present in SLE patients. However, there are limitations to the scope of coverage that flow cytometric analyses can provide. Single-cell RNA sequencing (scRNAseq) can provide a broader expression profile to distinguish subsets based on transcriptomic expression, as opposed to relying on existing, classical categorizations as done in this study. Therefore, higher granularity in the evaluation of cell-type heterogeneity may yield more precise assessments of cell-type similarities and differences between COVID-19 and autoimmune disease.
Importantly, the characterizations of B cell subpopulations in this study have largely been correlative. Trends with clinical outcome or existing prognostic markers are insufficient to define the roles that these cell types may play in the pathogenesis of COVID-19. Without additional studies (and accounting for the general lymphopenia already reported in COVID-19 patients), it is unclear whether these phenotypes are by-products of abnormal or absent T cell help or actual reactions to/consequences of SARS-CoV-2 infection.
Lastly, since this report identified similar B cell subsets in both critically ill COVID-19 patients and SLE patients, additional serological studies exploring any evidence of autoreactivity in EF-CoV patients with high IL-6 are warranted.
Significance<br /> Using a specialized flow cytometry panel for B cell analysis, the authors provide a description of the B cell landscape in COVID-19 patients. Understanding the role of potentially pathogenic B cell modules could be crucial for designing immuno-modulatory therapies that target pro-inflammatory or potentially autoimmune phenotypes seen with SARS-CoV-2 infections.
Reviewed by Matthew D. Park and Miyo Ota as part of a project by students, postdocs, and faculty at the Immunology Institute of the Icahn School of Medicine, Mount Sinai.
On 2020-05-11 11:49:19, user Medicos Lk wrote:
According to the data four SARS-CoV2 virus strains are circulating among Sri Lankan Covid-19 infected patients.
On 2020-05-11 12:28:29, user Sinai Immunol Review Project wrote:
The main finding of the article: <br /> This study analyzed the effects of the arterial hypertension and of the use of renin-angiotensin-aldosterone system (RAAS) inhibitors on mortality and recovery in patients with Covid-19. Through medical records, the authors performed a multicenter retrospective study of 3017 COVID-19 patients hospitalized within the Hackensack Meridian Health network in New Jersey. Among these patients, 52.5% presented a diagnosis of hypertension. The authors showed a significantly increase (2.7 times) of the mortality in patients with hypertension compared to Covid-19 patients without hypertension. However, when adjusted for age, the effect of hypertension in mortality decreased, as the incidence of hypertension was higher in older populations. In addition, when other clinical or demographic conditions were taken into account, no effect of hypertension on mortality was found. <br /> In relation to the RAAS inhibitors, angiotensin converting enzyme 1 (ACE1) inhibitors and angiotensin-receptor blockers (ARBs) were used in 22.8% and 18% of hypertensive patients. The use of ACE1 inhibitors and ARBs were found not to have detrimental effects and perhaps offer some protection to hypertensive patients in comparison with other anti-hypertensive agents. Hospital discharge rates were 9% higher for hypertensive patients prescribed RAAS inhibitors compared to other anti-hypertensive agents.
Critical analysis of the study: <br /> The manuscript needs a better scientific writing, especially more in-depth details on the description of the patient population, clinical parameters, treatments used, other co-morbidities. The implications for COVID-19 disease of the upregulated cascade of vasoactive peptides belonging to RAAS on hypertensive patients, the relationship between the use of RAAS inhibitors on cytokine storm, plasma angiotensin II and ACE2 activity, could be better discussed. There is no information on which ARBs or other anti-hypertensive agents were used, despite being an important information given the different pharmacological characteristics of each one.
The importance and implications for the current epidemics: <br /> While there is still uncertainty on the effect of RAAS inhibitors on Covid-19 severity in hypertensive patients, this manuscript demonstrates that ACE1 inhibitors and ARBs therapy are not detrimental, and can even be protective in hypertensive individuals. These results thus support the recommendations of the guidelines for maintaining therapy with these classes of drugs in hypertensive SARS-CoV-19 patients.
Reviewed by Bruna Gazzi de Lima Seolin.
On 2020-05-12 21:48:21, user Clive Bates wrote:
I think the conclusions are radically overstated given the method. The authors summarise:
? Current e-cigarette use is positively associated with COVID-19 infections.<br /> ? Current e-cigarette use is positively associated with COVID-19 deaths.<br /> ? This study emphasizes the importance of studying the susceptibility of current e-cigarette users to COVID-19 infection and death.
It would be more accurate to say "statewide prevalence of vaping is correlated with COVID-19 infections and deaths". The study did not discover if e-cigarette use is associated with COVID-19 because it did not actually measure this: "we did not have data on what proportion of those who actually contracted COVID-19 or died from COVID-19 were vapers".
It is a "helicopter view" of the situation using variables covering millions of people in gigantic aggregations, and looking at the progression of the epidemic at different stages as it moves unevenly through the different states over time. There are so many factors that determine the progression of the epidemic, it is hard to imagine how any vaping signal could be detected among the roaring cacophony of confounders and noise.
Luckily, we can also assess the usefulness of the method in the investigation of new associations that have not so far been established (e.g. vaping) by seeing how well it discovers associations that have been already well-established by other research. For example obesity and male sex have been found to be risk factors for COVID-19. But the big finding in this study (see Figure 1) is that obesity and, especially, being male appear to be protective, thus overturning the broad consensus. That would be the big news and should feature heavily in the conclusions if the authors were confident in the method. The trouble is that it could equally lead observers to dismiss the method used as self-evidently flawed. No such objection can be raised about vaping, however, because there is little other data available and therefore no reality-check is possible. So to act with integrity, the authors have a choice: stand by the method and challenge the consensus on male sex and obesity risk factors or accept that if the method does not reveal well-established associations then it should not be used to look for novel ones.
Other than pure chance, the second most likely explanation for the result is that vaping is a marker for some larger scale confounding phenomenon (poverty, hospitality trade, housing density, urbanisation, cosmopolitan, early spread of the virus etc) that is contributory to COVID-19 susceptibility but that cannot be fully adjusted for by the variables available to the authors. It would require heroic assumptions to draw any conclusions about vaping from an analysis like this.
On 2020-05-13 10:08:28, user Benjamin Hartley wrote:
Hi, Can you clarify the meaning of the theta "infection" parameter in equation 1 (years 2015-2019) which multiplies the death rate? Is this a typo, or set to 1?
On 2020-05-13 13:19:20, user T Christopher Bond wrote:
Looking for an explanation of the total numbers and the comparator group in Table 4 (ICI vs ?).
On 2020-05-13 18:50:12, user John wrote:
Lack of Vitamin D has been implicated, paler skin produces more, and there are potential genetic factors too, watching this may help https://youtu.be/Ja-jhcXMGj0
On 2020-05-14 12:31:40, user Riccardo Pecori wrote:
Very nice work. A couple of questions for the authors: <br /> 1 - in the self-collected samples (Triton experiment) what is the volume of PBS in which the swabs are rinsed? <br /> 2 - would it be possible to get the written instructions for self-sampling? It would be beneficial for the standardization of the sampling.
On 2020-05-14 17:42:03, user MiCo BioMed wrote:
This paper makes a false claim, because the authors didn't follow MiCo Biomed's PCR test instruction.. The authors used an RNA extraction kit manufactured by Invitrogen, which is incompatible with MiCo BioMed's PCR kit. MiCo BioMed's PCR kit instruction clearly tells users to use only MiCo Biomed's RNA extraction kit.
On 2020-05-15 16:11:42, user David Simons wrote:
Please in future versions of this article consider reporting a descriptive analysis by your outcomes of interest. Saying current smokers had a 5 times greater risk of ITU admission or 10 times greater risk of death is not helpful when you are not reporting the absolute numbers.
On 2020-05-15 16:48:46, user Will Wiegman wrote:
A combo of severe Thiocyanate and Iodine Deficiencies shuts down the pitting function of the spleen making it impossible for the body to eliminate the viruses trapped inside of mature red blood cells with no nucleus for the virus to use to replicate.
https://www.ncbi.nlm.nih.go...
https://pubmed.ncbi.nlm.nih...
Paragraph 4:<br /> https://pubmed.ncbi.nlm.nih...
On 2020-05-15 22:28:30, user Sally Elghamrawy wrote:
Any one need the dataset ,,,just send to me.
On 2020-05-18 02:17:06, user welko welko wrote:
There were 33 positive IgG among 1,000 serum samples 33 per 1000<br /> so...<br /> 330 per 10,000<br /> 3300 per 100,000<br /> 4950 per 150,000<br /> From your data I calculated; its 3.3% not 33%:Give Kobe a break
On 2020-05-19 16:06:56, user Jared Roach wrote:
The main point of this article is really good. The more variance there is in the infectiousness of individuals, the greater the probability of complete elimination. Indeed, if there is zero variance, then elimination will never occur. This assumes a fairly simple model (e.g., SIS compartmental model). The article would benefit from a few references to classical epidemiological models that the assumptions are based on. The point about animal reservoirs in the last paragraph should be more strongly emphasized. We know this virus originally came from bats, and we know that dogs and felines can be infected. So it seems very likely that there will be animal reservoirs. This point should be emphasized, with references.
On 2020-05-19 20:06:13, user Achint Chaudhary wrote:
I have gone through this and similar articles recently published.I found some issues on which I am bit skeptical about approach followed by the authors:
Data Augmentation (using SMOTE) is done before splitting the data into Train-Test sets, which will leak information from train set to test set.
Data balance is achieved on Test set also, I agree that class balanced data set will led to a better classifier, but reporting metric values on a test set with different class ratio from real world testing is an issue to be raised
XGBoost is shown to be the best known algorithm in this article, but XGBoost algorithm is already known to handle class imbalance, so why do we need SMOTE at first place. Would not it be right if experiments without data augmentation would be also shown
On 2020-05-20 06:25:22, user Bob wrote:
How do the authors reconcile a lower bound of 0.02 IFR with the fact that 0.026% of Americans have already died from SARS-CoV-2? Kind of difficult to have an IFR lower than that.
On 2020-05-23 11:05:15, user John Jacobson wrote:
It would be great to see more of a discussion on how many of the recorded deaths from COVID-19 are directly attributable to Sars-CoV-2. Is the current ~96K US deaths the true death toll of direct deaths from Covid-19 or does this number include significant number of deaths from other causes, but list Covid-19 in death certificate (e.g. a patient with renal failure or end-stage liver cancer or head trauma picks up nosocomial infection and is recorded as part of covid burden)? This would surely reduce IFR estimates if accurately known. Is testing for Covid-19 more widespread than for routine influenza A or B infections? Seems likely in the current climate in the midst of a pandemic, which might be another caveat when comparing. Important to factor in both of these points to get a greater appreciation and context of the current pandemic?
On 2020-05-20 06:50:14, user Chris Valle-Riestra wrote:
Thank you, I can see that this is a very important finding for understanding the development of the epidemic in any nation, region, or city. That heterogeneity in susceptibility would have this effect can be understood intuitively, as soon as one really starts to think about it. Determining an average R nought for an entire nation, and making projections based on that alone, plainly doesn't tell the whole story.
A simple thought experiment will demonstrate this. If an entire population is split into two sub-populations of equal size, and the individuals in one of the sub-populations all have low susceptibility, effective R just for that sub-population can be well below 1.0, in spite of a generally high virulence of the virus. Very few in this sub-population will ever become infected. The other half of the full population will be highly susceptible, and a substantial majority of that sub-population would be expected to become infected over time. Adding it all up, something well under 50% of the total population will ultimately become infected, and herd immunity will have been achieved.
Recent small serological studies around the U.S. have typically indicated a middle-of-the-road level of infection, ranging between perhaps 6 and 30 percent from place to place, many weeks into the epidemic. This has struck me as perplexing. Based on the usual naive model of the development of an epidemic, one would have thought it likely to find either (1) a very low level of infection, such as under 5 percent, implying great success in suppression efforts, or (2) infection levels moving steadily past 50 percent, implying a high R nought that suppression efforts were inadequate to suppress. Basically, either suppression would work or it wouldn't. It would be surprising to find that that the virus had enough power to infect a major fraction of the population, carrying a big head of steam going forward, and yet be able to be halted that late in the game.
Your finding points to a likely explanation for this phenomenon. It suggests to me a likelihood that the epidemic in the U.S. has been working its way through the most susceptible sub-populations, not successfully checked, but that it has made little progress in infecting less susceptible sub-populations.
I think it should be recognized that to the degree that an individual's susceptibility is based on his social conditions, that may change over time. An individual living far out in the country may have little connectivity, and therefore little susceptibility. If he moves into the heart of a city, that may change. This implies that herd immunity is likely to "erode" over time. COVID-19 is likely to remain endemic and to continue to cause a low level of disease, serious and otherwise, for a long time to come.
Be that as it may, there's a strong likelihood that public health officials and political leaders have been seriously misinterpreting the progress of epidemic. This has major implications for public policy choices. Further research is urgently needed, and decision makers need to develop a more nuanced understanding. They are currently making weighty decisions based upon a probably badly flawed model.
On 2020-05-21 01:11:37, user Brian Richard Allen wrote:
Be interesting to see how New Zealand:- whose authoritarian government has effectively prevented its subjects from acquiring herd immunity;- will fare when its borders are opened and tourists -- and the virus -- flow in.
On 2020-05-21 01:21:24, user Morat Gurgeh wrote:
This whole affair has been entirely unedifying. I do not know the truth of the allegations published in Buzzfeed, but then neither does anyone else commenting here, on Twitter and elsewhere. There are a lot of people, including senior academics, who should be ashamed of their behaviour.
Turning to the central controversy, it is entirely possible and indeed likely for different populations to have different IFRs. The fact that the IFR in NYC appears to be significantly higher than reported here does not “debunk” this work and indeed is not even inconsistent with these results.
NYC was hit early by the virus, when protocols for managing infected patients were still developing and mistakes were made. In addition, those most susceptible to COVID-19 (e.g. the old) were much less likely to be voluntarily shielding. Catastrophic errors have been made in many countries in care homes. So the likelihood of those over 80 being infected was likely much higher than in this study. Given the incredibly steep fatality gradient with age, this alone could explain the IFR differences.
I think the main take home message of this paper is this: the lives of healthy, working age people should return largely to normal while those groups identified at elevated risk should continue to shield. Amongst the young, we should treat infection by SARS-CoV-2 as more akin to measles than Ebola.
We need most of the healthy, young population to develop what immunity they can to this virus so that we can properly protect those most susceptible.
On 2020-05-21 20:00:27, user Babak Javid wrote:
Please note that the Supplementary File refers to the earlier version of this manuscript and is no longer current. Unfortunately, it cannot be removed for clarity!
On 2020-05-22 23:43:28, user Malcolm Semple wrote:
Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study<br /> BMJ 2020; 369 doi: https://doi.org/10.1136/bmj... (Published 22 May 2020)<br /> Cite this as: BMJ 2020;369:m1985
On 2020-05-24 09:26:14, user Count Iblis wrote:
The natural vitamin D levels are way higher than the average levels found in populations living in the civilized world. Biologically normal vitamin D levels are between 120 nmol/l and 250 nmol/l. Levels below 100 nmol/l are from a natural biological point of view extremely low, but such levels are the norm in the civilized World, even in the tropics as people there too spend most of the day indoors.
Studies like this that look into the correlation between vitamin D levels naturally found in society and harmful effects of COVID-19 effect are interesting, but they cannot detect all of the effects of the severe vitamin D deprivation of the western population. It's similar to a study into the effects of exercise on heart disease if you're studying a population of couch potatoes. You may detect a difference between those couch potatoes that don't sit all day long on the couch and those that hardly get up at all during the day. But the large effects on heart health that kick in when you run for more than half an hour a day, cannot be extracted from such a study.
On 2020-05-25 11:34:54, user Rogelio Macías-Ordóñez wrote:
Even after countless revisions prior tu submission to medRxiv we found a minor mistake in the sentence (lines 375-378):
"A group of five countries (Brazil Fig 4, México, India, Peru and Russia) with IFR values below 1% and an already high death toll (above 1,000) may experience a high number of casualties if, as our estimates suggest, they experience 68-82% more deaths in the next 23 days."
It should say "...64-82% more deaths in the next 23 days." since 64% is the lowest value (for Brazil) among those countries in Table 1.
On 2020-07-17 13:12:12, user Liam Golding wrote:
What is the detection limit of this assay? I assume it's >log0.
On 2020-07-18 00:57:36, user Kamran Kadkhoda wrote:
Despite other reports such high seroprevalence in healthcare setting highly suggests false positivity. Ideally all positives should have been confirmed by neuralization assay. Since most were mild/moderate/asymptomatic and they admit 50% were confirmed this is an attestation to high false positivity of their screen test. I refer them to the large Wuhan study with 2% sero-prevalence as they confirmed all cases with neuralization. Most positives found here are probably from common CoVs...for the record specificity of 100% is a mathematical impossibility.
On 2020-07-18 08:58:40, user disqus_LHZMcrKY6P wrote:
LAMP has great potential as a screening tool, the limit of detection (100,000 c/ml ?) is at least 10 times less than most commercial and LDT assay based on traditional RT PCR methods. I note the authors suggest "If such a test were to be used for community screening outside of CLIA-certified diagnostic labs, effective interventions could be taken immediately while awaiting confirmatory tests at partner CLIA labs" When used in this way it Is a very good screening tool. It would be important in times of global supply issues and economical impact of testing versus impact to balance implications of duplication of swab collection.<br /> Those using and commissioning tests must be aware of the limitations of all assays and use them appropriately. It is very attractive to use tests that are high throughput and low cost. This assay would be well suited during peaks of pandemics where negative results are followed up by CLIA testing.
On 2020-07-18 09:38:23, user disqus_LHZMcrKY6P wrote:
Thank you for this informative paper, the statistical probabilities of result significance in the event of a negative result are very important in terms of the application of the test. Is there possibility to follow-up negative lamp results in both asymptomatic contacts and symptomatic cases with laboratory based assays RT-pcr assays (with LOD< 1000 cp/ml) and repeat LAMP assay at say 4-7 days later to evidence the statistical probabilities with true outcome? Do the authors recommend that LAMP assay result is routinely followed up with a more sensitive test for negative results?<br /> I cannot see units for analytical sensitivity is this copies/ml, per reaction or per swab? This is important for selecting a confirmatory test that has a more sensitive limit of detection and for comparing results across assay and finally for understanding the % of samples that would not be detected if this was performed as a single test based on current knowledge of viral loads in samples.<br /> The natural history of covid19 disease makes the means that interpretation of significance of low viral loads is reliant on a number of factors specific to the individual, while it is true that a low viral load is less likely to be infective, we cannot be sure at which stage of infectious course the individual is at and therefore low viral loads cannot be ruled as insignificant in terms of infectious potential nor clinical outcome.
On 2020-07-18 11:59:14, user Kevin wrote:
This paper appears to be a good quantitative assessment of the relative risk between full flights and flights with empty middle seats (~44% reduction with empty middle seats).
I believe the author’s attempt to quantify the overall probability of contracting COVID while flying to be highly flawed.
First, the Lancet study states its mask values are from (at worst) 12-ply cotton masks, and this paper assumes 100% mask compliance. Twitter is full of photos of non-compliant airline passengers, and with no federal regulations defining and requiring mask compliance, the author’s assumption skews the assessment.
Second, the author states he makes no attempt to account for duration of exposure. I assume the author believes this is acceptable, since as stated in the paper “the air in the aircraft cabin is constantly refreshed, so the cabin does not constitute a closed indoor space.” Unfortunately, FAA Regulation 25.831 (a) specifies a minimum fresh air volume requirement, but allows that to be mixed with filtered recirculated air. So while better than a room with no fresh air being circulated, it is not the same as standing in an open field. Again, not taking exposure time into account likely skews the outcome to make air travel appear safer than it is.
Third, and this may be the most important, the author does nothing to account for arguably the highest risk activities while aboard an aircraft: boarding and de-planing. As soon as the seatbelt light goes off, passengers jump out of their seats and crowd the aisle, huffing and puffing as they pull their suitcases out of the overhead bin, all while pressed up against fellow travelers. Boarding is a similar mess, but can at least be controlled through passenger metering at the gate and entry door. If the paper doesn’t consider the highest risk activities associated with flying, it can’t attempt to assign an overall probability to air travel.
In summary, this is not a comprehensive analysis of the probability of contracting COVID while flying, and the overall probabilities should not be presented and discussed since the underlying assumptions are both incomplete and likely flawed. This paper does appear to do good work comparing the transmission probability due to passenger proximity (QL), and should concentrate the findings in that area.
On 2020-07-19 10:16:32, user Shahar Seifer wrote:
The density of virions in aerosols may be different than the density in saliva. The argument on probability of transmission is based on the assumption that the two values are the same, which is doubtful.
On 2020-07-19 10:54:36, user C Ilie wrote:
The best way to test a theoretical model is to run an experiment. But, what if the experiment already took place? Princess Diamond Cruise analysis found the infection rate was below 20%. <br /> https://www.linkedin.com/pu...
On 2020-07-19 14:36:08, user Ulrich Müller-Sedgwick wrote:
Great to see this paper published with interesting results. I was the lead clinician for the CPFT Adult ADHD Clinic until March 2017 (when I moved to London). How should we screen for hoarding symptoms? Is there a screening version of longer questionnaires or 1-2 questions that we can ask in our clinical interview, especially in patients with procrastination as a main symptom?
On 2020-07-20 05:20:08, user Curbina wrote:
I have wondered if China published total mortality data that could be used as it has been done elsewhere to estimate excess mortality during the pandemic. This article is the closest to that so far.
On 2020-07-21 15:54:39, user OxImmuno Literature Initiative wrote: