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  1. May 2023
    1. Does Early Treatment of Exacerbation ImproveOutcome in Chronic Obstructive Pulmonary Disease?

      Does Early Treatment of Exacerbation Improve Outcome in Chronic Obstructive Pulmonary Disease?

  2. Dec 2022
    1. For example, a benefit–harm analysis forroflumilast as preventive therapy for COPD exacerbationsreported that benefits of roflumilast outweighed itspotential harm when patients have severe exacerbationrisk of at least 22% over a year.24 Using data from thisbenefit–harm analysis, the accompanying web app ofACCEPT can be used to inform therapeutic decisions onuse of roflumilast for a given patient. Another example isin the potential use of preventative daily azithromycintherapy in COPD. Azithromycin reduces annual exacer-bation rate by 27%.8

      Por qué es importante estimar el riesgo?



  3. Nov 2022
    1. Lung function didnot decrease significantly during the prodromal period, but byDay 0, PEFR had fallen from baseline by a median 8.6 (IQR 0to 22.9) L/min, FEV1 by 24.0 (IQR 216.1 to 84.3) ml, and FVCby 76.0 (IQR 240.4 to 216.4) ml. The declines in lung func-tion, whether measured by PEFR, FEV1, or FVC, were allhighly significant (p , 0.001). Significantly greater decreasesin PEFR were seen when the exacerbation was associated withsymptoms of increased dyspnea (r 5 20.12 [n 5 449]; p 50.014), colds (r 5 20.09 [n 5 449]; p 5 0.047), or increasedwheeze (r 5 20.12 [n 5 449]; p 5 0.009), but not with othersymptoms.
    2. Before onset of exacerbation there was deterioration inthe symptoms of dyspnea, sore throat, cough, and symptoms of acommon cold (all p , 0.05), but not lung function.

      La función pulmonar no cambia días antes de la exacerbación



    1. The bad news is that this study suggests that the EXACT seems to be relatively insensitive in detectingexacerbation events. Only 34 (27%) out of 128 of London diary card exacerbations exceeded the EXACTthreshold for an exacerbation event (defined as a 12-point increase in EXACT score above baseline for twoconsecutive days or a 9-point increase for three days). Even more worryingly, of the 85 London COPDCohort diary card-defined exacerbations that were treated with oral antibiotics and/or corticosteroids by thestudy team during the 2-year study period, only 34% were picked up using EXACT.

      Bad news for EXACT

    2. The results of the study are certainly mixed. The good news is that mean EXACT scores did increase, asexpected, during exacerbation events relative to the stable state, and that the time taken for EXACT scores toreturn to baseline was significantly correlated to both diary-card symptom recovery time and lung functionrecovery. This information suggests that EXACT can be used to measure the duration of COPDexacerbation events.

      Usar EXACT en ambos estudios. La ventaja es que EXACT da información sobre la severidad y la duración de la exacerbación.



    1. The EXACT has previously been used in conjunction with a personal digital assistant [14, 24] or smartphone[25].

      25 Halpin DM, Laing-Morton T, Spedding S, et al. A randomised controlled trial of the effect of automated interactive calling combined with a health risk forecast on frequency and severity of exacerbations of COPD assessed clinically and using EXACT PRO. Prim Care Respir J 2011; 20: 324–331

    2. Thus, this study has highlightedimportant potential limitations of the EXACT in its ability to independently identify events that were capturedby physician review (HCU) or London COPD cohort diary cards.

      London COPD cohort diary card

    3. Patients completed a paper version of the EXACT at least once under supervision in the clinic and wereinstructed to complete the EXACT diary each evening before bedtime, based on their symptomsexperienced that day.

      How EXACT was administrated

    4. Exacerbation duration was defined as the number of days after onset that worsening symptoms persisted.The last day of recorded worsening symptoms before two consecutive symptom-free days defined the end ofthe exacerbation

      Definición de duración de exacerbación

    5. The exacerbations of chronic pulmonary disease tool (EXACT) is a PRO daily symptom diary developed tocapture frequency, severity and duration of exacerbations in clinical trials of COPD [14].

      Leer EXACT

      14 Leidy NK, Wilcox TK, Jones PW, et al. Standardizing measurement of chronic obstructive pulmonary disease exacerbations. Reliability and validity of a patient-reported diary. Am J Respir Crit Care Med 2011; 183: 323–329

    6. An exacerbation was defined as an increase in respiratorysymptoms for two consecutive days, with at least one major symptom (dyspnoea, sputum purulence orsputum volume) plus either another major or a minor symptom (wheeze, cold, sore throat and cough), thefirst of which was defined as the day of onset of the exacerbation.

      Exacerbation assessment



    1. The PaCO2 is currently obtained invasively by tak-ing blood samples at discrete time instants. To motivate animprovement, this paper justifies PaCO 2 monitoring forCOPD patients continuously and noninvasively by transcuta-neous CO2 measurements (PtcCO2).

      Should we used PaCO2?

    2. Pulse oximeters, however, cannot detect changes in the arte-rial carbon dioxide (CO2) partial pressure (PaCO2), which weargue is one of the most significant parameters for COPDpatients

      Si tenemos medidas con su tiempo (dependiendo de cuanto tiempo), podríamos restar el segundo posterior al anterior y finalmente hacer un promedio de las medidas por hora o por día.



    1. A previousstudy [13] has suggested that symptoms tend to worsen duringthe 7 days immediately before an exacerbation episode.

      13 Donaldson GC, Wedzicha JA. COPD exacerbations .1: Epidemiology. Thorax 2006 Feb;61(2):164-168 [FREE Full text] [doi: 10.1136/thx.2005.041806] [Medline: 16443707]



    1. Here, we present a case of COPD exacerbation detected using RPM ina clinical setting. The RPM system (Spire Health, 2021) has been vali-dated for use with chronic respiratory disease patients [9,10] and iscomprised of: (1) Health Tags, undergarment waistband-adhered phys-iologic monitors which include photoplethysmography, activity, andrespiratory force sensors, (2) an in-home stationary device to collect andupload sensor data, and (3) a web dashboard to display patient data andnotifications to clinicians.

      Parece mucho a TOLIFE. Tienen una app y han medido varias variables fisiológicas

      9 Mark Holt, et al., Ambulatory monitoring of respiratory effort using a clothing-adhered biosensor, in: IEEE International Symposium on Medical Measurements and Applications (MeMeA), IEEE, 2018.

      10 Neema Moraveji, et al., Long-term, ambulatory respiratory monitoring of COPD patients using garment-adhered sensors, in: IEEE International Symposium on Medical Measurements and Applications (MeMeA), IEEE, 2019.

    2. Case

      Caso muy interesante. Es lo que queremos que pase en nuestro pacientes. Solo se han evaluado dos variables: RR y PR. Se mide como porcentaje de cambio y se establece un umbral que está descrito en los gráficos.

    3. Seemungal et al. reported a 7-day prodrome prior to diagnosis ofexacerbation [6]. With this in mind, the use of respiratory RPM has thepotential to reduce COPD treatment delays leading to improved care.Increased respiratory rate has demonstrated predictive ability for ex-acerbations of COPD [7,8]. Shah et al. observed an increased respiratoryrate in the 5 days preceding hospitalization for COPD exacerbations,highlighting the window of opportunity for intervention [7].

      Detalles importantes:

      Seemungal determinó un periodo prodrómico de 7 días. Sin embargo, hay que recordar que las exacerbaciones tienen diferentes presentaciones.

      RR parece ser un predictor importante. Se eleva 5 días antes de la hospitalización

      6 T.A. Seemungal, G.C. Donaldson, A. Bhowmik, D.J. Jeffries, J.A. Wedzicha, Time course and recovery of exacerbations in patients with chronic obstructive pulmonary disease, Am. J. Respir. Crit. Care Med. 161 (5) (2000 May) 1608–1613, https://doi.org/10.1164/ajrccm.161.5.9908022. PMID: 10806163.

      7 S.A. Shah, C. Velardo, A. Farmer, L. Tarassenko, Exacerbations in chronic obstructive pulmonary disease: identification and prediction using a digital Health system, J. Med. Internet Res. 19 (3) (2017) e69, https://doi.org/10.2196/ jmir.7207. Published 2017 Mar 7.

      8 A.M. Ya ̃nez, D. Guerrero, R. P ́erez de Alejo, F. Garcia-Rio, J.L. Alvarez-Sala, M. Calle-Rubio, R.M. de Molina, M. Valle Falcones, P. Ussetti, J. Sauleda, E. Z. García, J.M. Rodríguez-Gonz ́alez-Moro, M. Franco Gay, M. Torrent, A. Agustí, Monitoring breathing rate at home allows early identification of COPD exacerbations, Chest 142 (6) (2012) 1524–1529.

    1. Acute changes in lung function (forcedexpiratory volume in 1 s (FEV 1)) or the FEV1/forced vital capacity ratio are not sensitive, and do notcorrelate well with AECOPD [57, 58].

      Acute changes in lung function FEV1 and FEV1/FVC are not sensitive and dote correlate wll with AECOPD

      57 Stevenson NJ, Walker PP, Costello RW, et al. Lung mechanics and dyspnea during exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2005; 172: 1510–1516

      58 Parker CM, Voduc N, Aaron SD, et al. Physiological changes during symptom recovery from moderate exacerbations of COPD. Eur Respir J 2005; 26: 420–428.

    2. Studies that have assessed the incidence of symptom-based AECOPDs compared to event-based AECOPDsin the same patients followed over time suggest that observed exacerbation rates are much higher ifsymptom-based definitions are used. The Investigating New Standards for Prophylaxis in ReducingExacerbations (INSPIRE) study compared the incidence of AECOPD using symptom-based definitions anda treatment-based definition and found that the incidence rate was three AECOPDs per patient-year if asymptom-based definition was used and 1.5 AECOPDs per patient-year if an event-based definition wasused, suggesting that 50% of symptom-defined COPD exacerbations are not treated by physicians [27].

      Dato importante. Symptom-based son más diagnosticadas que las event-based.

      27 Wedzicha JA, Calverley PM, Seemungal TA, et al. The prevention of chronic obstructive pulmonary disease exacerbations by salmeterol/fluticasone propionate or tiotropium bromide. Am J Respir Crit Care Med 2008; 177: 19–26.

    3. A further advantage is that validated tools to capture symptom-basedAECOPDs exist and include patient diary cards [18] and the validated Exacerbation of ChronicPulmonary Disease Tool (EXACT) [19].

      18 Quint JK, Donaldson GC, Hurst JR, et al. Predictive accuracy of patient-reported exacerbation frequency in COPD. Eur Respir J 2011; 37: 501–507.

      19 Leidy NK, Murray LT. Patient-reported outcome (PRO) measures for clinical trials of COPD: the EXACT and E-RS. COPD 2013; 10: 393–398.

    4. Advantages and disadvantages of event-based definitions of AECOPD
    5. Advantages and disadvantages of symptom-based definitions of AECOPD
    6. The 2018 GOLD document defines COPD exacerbation as “an acute worsening ofrespiratory symptoms that results in additional therapy”. Exacerbations are classified as 1) mild if they aretreated with short-acting bronchodilators only; 2) moderate if they are treated with short-actingbronchodilators plus antibiotics and/or oral corticosteroids; or 3) severe if the patient visits the emergencyroom or requires hospitalisation because of an exacerbation [16].

      Acoording ot the 2018 GOLD Guideline

    7. Symptom-based definitions rely on patient-reported worsening of respiratory symptoms either to ahealthcare practitioner or within a symptom diary.

      Esto es lo que NO queremos hacer. Tal vez symotom-based hay que descartarlo

    1. ecause of global variability in the available resources to treat patients and local customsaffecting the criteria for hospital visits and admissions, there is substantial variability in reported ECOPD outcomes.(11)

      Importantísimo leer

      • Halpin DMG, Rabe AP, Loke WJ, et al. Epidemiology, Healthcare Resource Utilization, and Mortality of Asthma and COPD in COVID-19: A Systematic Literature Review and Meta-Analyses. J Asthma Allergy 2022; 15: 811-25
    2. Short-termexposure to fine (PM2.5) and coarse (PM10) particulate matter is associated with increased hospitalizations, ER visits,and outpatient visits,(16) as well as increased mortality of COPD exacerbations.(15,17,18)
    3. Currently, exacerbations are classified after the event has occurred as:► Mild (treated with short acting bronchodilators only, SABDs)► Moderate (treated with SABDs and oral corticosteroids ± antibiotics) or► Severe (patient requires hospitalization or visits the emergency room). Severe exacerbations may also beassociated with acute respiratory failure.

      Claramente se describe cuáles son las exacerbaciones severas. Hospitalizaciones o emergencias.

    4. Currently, exacerbations are classified after the event has occurred as:► Mild (treated with short acting bronchodilators only, SABDs)► Moderate (treated with SABDs and oral corticosteroids ± antibiotics) or► Severe (patient requires hospitalization or visits the emergency room). Severe exacerbations may also beassociated with acute respiratory failure.

      Claramente se describe cuáles son las exacerbaciones severas. Hospitalizaciones o emergencias.

    1. Frequently used definitions and diagnostic criteria for COPD exacerbations

      Exacerbation definitions



    1. It should be noted that the use of a fixed FEV1/FVC ratio (< 0.7) to define airflowobstruction may result in over-diagnosis of COPD in the elderly,(30,31) and under-diagnosis in young adults,(31

      Importante para el reclutamiento de pacientes



    1. Another limitation is that our study did not assess potentialmicrobiological pathogens that may have been associated withindividual exacerbations. It is tempting to speculate that suddenexacerbations may be those that are caused by infections (eitherviral or bacterial respiratory tract infections).
    2. We employed a generalised esti-mating equation (GEE) logistic model with an exchangeablewithin-patient correlation structure to account for individualpatients having multiple exacerbations.

      Análisis estadístico

    3. An openingwas defined as the first day of a positive symptom score indi-cating worsening of respiratory symptoms from baseline (ie,a symptom score $1 point)

      Lo que nosotros podríamos hacer, es establecer umbrales para que cuando cierto numero de medidas superen este umbral, salte la alarma.

    4. This prodrome phase is ofgreat interest, as knowledge of exacerbation onsetcan help physicians to time early therapeuticinterventions appropriately. 7


      Wilkinson T, Donaldson GC, Hurst JR, et al. Early therapy improves outcomes of exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2004;169:1298e303.

    5. However, it should be stressed thataction plans that contain only minimal or no patient self-management education have not been shown to reduce urgenthealthcare utilisation for COPD. 12

      Importante recalcar que las intervenciones que no involucran acciones propias del paciente, no reducen la utilización del sistema sanitario

      12 Walters JA, Turnock AC, Walters EH, et al. Action plans with limited patient education only for exacerbations of chronic obstructive pulmonary disease. Cochrane Database Syst Rev 2010;(5):CD005074

    6. Previous studies suggest that prompt treatment ofexacerbations is associated with better clinical outcomes.

      Importante para justificar el hecho de querer predecir exacerbaciones

      7 Wilkinson T, Donaldson GC, Hurst JR, et al. Early therapy improves outcomes of exacerbations of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2004;169:1298e303.

    7. One implication isthat COPD action plans, with provision of prespecifiedprescriptions for antibiotics and oral steroids, may be appro-priate to ensure prompt and appropriate management of exac-erbations. 10

      Qué podrían hacer los médicos que saben que se enfrentan a una probable exacerbación en los próximo días?

    8. The onset, or prodrome,of COPD exacerbations is a subject that has received very littlestudy to date.

      Algo que deberíamos utilizar para sustentar nuestro estudio

    1. Thefindings show that patients who receive prompt therapy afterthe onset of their exacerbation are likely to recover more rapidlythan those who delay reporting and thus initiation of treatment.Furthermore, patients who habitually fail to seek therapy fortheir exacerbations have poorer health-related quality of lifeand are more likely to be hospitalized for the management ofan exacerbation

      Esto es importante pero cabe recalcar que nosotros queremos intervenir al paciente antes de que tenga la exacerbacion

    2. patients withCOPD often have poor understanding of their disease and symp-toms, with the result that exacerbations are often not reportedto healthcare professionals for treatment (2).

      Importante que el DIT tenga contenido educativo y que pueda servir como una manera de que el paciente participe activamente en con su enfermedad



    1. The relative importance of the eosinophilia re-mains to be determined, but several eosinophil products maycause inflammatory damage to the airway (eosinophil peroxi-dase, major basic protein, eosinophil cationic protein, metallo-proteinases, platelet activating factor, and cysteinyl leukotrienes)(75) and, together with histamine, can cause bronchospasm

      Eosinophilia puede causar broncoespasmo en conjunto con otros factores

    2. Patients with mild to moderate COPD exacerbations show anincreased number of eosinophils in their bronchial mucosa (72).Although this suggests an “asthmatic profile,” the observed eo-sinophils are not degranulated (as they would be in asthma) andare not associated with increased IL-5 expression (72).

      Por qué los eosinófilos aumentan y cómo son diferentes a el perfil de los pacientes con asma

    3. The lower airways of 25 to 50% of patients with COPD arecolonized by bacteria, especially noncapsulated Haemophilusinfluenzae, Streptococcus pneumoniae, and Moraxella catarrhalis.

      Ver listado de bacterias

    4. Recent studies have shown that about one-half of COPD exacer-bations are associated with viral infections, the majority of whichare due to rhinovirus (32–36).

      Casi 50% de las exacerbaciones son por infecciones virales, y dentro de ellas, las provocadas por rhinovirus.

    5. Lung function changes, such as decreases in peak expiratoryflow rate (PEFR) or FEV1 immediately before exacerbation, aregenerally small and not useful in predicting exacerbations, butlarger decreases in PEFR are associated with dyspnea, longerrecovery time after exacerbations, and the presence of symptom-atic colds (11).

      Importante. Los cambios en el FEV1 inmediatamente antes de las exacerbaciones no son útiles para predecir exacerbaciones.

      11 Seemungal TA, Donaldson GC, Bhowmik A, Jeffries DJ, Wedzicha JA. Time course and recovery of exacerbations in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2000;161:1608–1613. (lo tenemos)

    6. There have now been several large population studies (8–10)showing that the number and severity of exacerbations are lowerin patients with mild to moderate COPD (FEV1  50% pre-dicted), whereas in severe disease the rate of COPD exacerba-tions may increase to 1.5 to 2.5/patient/yr.

      Nos puede servir como parámetro para elegir a nuestros pacientes, enfocándonos en aquellos que tienen una estadío moderado/grave.

    1. Weobserved that an established machine-learning method (GB) narrowlyoutperformed other prediction algorithmsand resulted in a prediction model with ahigh discrimination power (AUC = 0.82),which also showed robust calibration in thevalidation data.

      GB machine learning was the best

    2. The primary outcome was the occurrence ofat least one COPD-related hospitalizationwithin the 2-month period after the indexdate (the outcome window).
    3. A history of previous exacerbations isconsidered the best predictor of futureexacerbations and forms the current basis ofrisk stratification in guidelines (22, 23).
      1. Vestbo J, Hurd SS, Agust ́ı AG, Jones PW, Vogelmeier C, Anzueto A, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2013;187:347–365.

      2. Kerkhof M, Freeman D, Jones R, Chisholm A, Price DB; Respiratory Effectiveness Group. Predicting frequent COPD exacerbations using primary care data. Int J Chron Obstruct Pulmon Dis 2015;10: 2439–2450

    4. In particular, we comparedlogistic regression (LR), random forest (RF),neural network (NN), and gradient-boosting (GB) methods (20).
    5. Adistinct advantage of this approach is thatrisk prediction can be performed remotelyand can be made arbitrarily complex toimprove its accuracy. In this “populationsurveillance” approach, individuals who areidentified as high-risk can then be contactedfor preventive disease management.

      Ventajas de realizar predicciones con datos medidos de manera continua.

    6. Most previous risk-predictionmodels for COPD exacerbations weredeveloped for use at point of care (5–8);however, an alternative approach is to useroutinely collected health data (9).
      1. Collier R. WHO guidelines on ethical public health surveillance. CMAJ 2017;189:E977
    1. Using the definition of exacerba-tion based on health care utilization, they foundthat the degree of airflow obstruction, health-related quality of life, an elevated white-cellcount, and a history of gastroesophageal refluxwere independently associated with increasedexacerbation frequency in the entire cohort;however, a history of previous exacerbationsbest predicted the subsequent occurrence of ex-acerbations in all stages of COPD severity.

      Predictores de COPD

    2. Whendefined on the basis of health care utilization,exacerbations are classified as moderate or, ifhospitalization ensues, as severe, with those epi-sodes managed by patients themselves relegatedto the mild category.3
      1. Celli BR, MacNee W, American Thoracic Society/European3. Respiratory Society Task Force. Standards for the diagnosis and management of patients with COPD: a summary of the ATS/ERS position paper. Eur Respir J 2004;23:932-46

      Podríamos leer uno más actualizado

    3. Consequently, confirmation that an “exacerba-tion” has actually occurred requires not only theworsening of the patient’s respiratory symptomsbut also the prescription of additional treatmentby a health care provider



    1. Stepwise logisticregression is commonly used for variable selection 16 and this method was prespecified during the study design
    2. he outcome was the occurrence of AECOPD (ie occurrence versus no occurrence)

      Muy parecido a lo que sería nuestro outcome. Poner interés en como hacen el modelo predictivo.



    1. In contrast, in this study,we focused on exacerbation risk prediction for discharged COPDpatients, because their health condition is likely to be lessaccessible.
    2. These resultsshowed that physiological and environmental data are morepowerful predictors than questionnaire data.
    3. When only lifestyle or environmental dataare automatically uploaded daily, the system still predictswhether AECOPD will occur within the next 7 days.
    4. For model comparison with machine learning–basedclassification, we selected the following classifiers: decisiontrees [15], random forests [16], k-nearest neighbor clustering[17], linear discriminant analysis, and adaptive boosting [18]
    5. Classification algorithms for this study were selected accordingto previously published studies on COPD such as those of Wanget al [13] and Rahman et al [14].
      1. Wang C, Chen X, Du L, Zhan Q, Yang T, Fang Z. Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease. Comput Methods Programs Biomed 2020 May;188:105267. [doi: 10.1016/j.cmpb.2019.105267] [Medline: 31841787]

      2. Rahman MJ, Nemati E, Rahman MM, Nathan V, Vatanparvar K, Kuang J. Automated assessment of pulmonary patients using heart rate variability from everyday wearables. Smart Health 2020 Mar;15:100081. [doi: 10.1016/j.smhl.2019.100081]

    1. severe exacerbationswere those that required an emergency departmentvisit or admission to hospital. 3,8–10

      exacerbaciones severas

      3 Vogelmeier CF, Criner GJ, Martinez FJ, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 Report. GOLD Executive Summary. Am J Respir Crit Care Med 2017; 195: 557–82.

      8 Albert RK, Connett J, Bailey WC, et al. Azithromycin for prevention of exacerbations of COPD. N Engl J Med 2011; 365: 689–98.

      9 Criner GJ, Connett JE, Aaron SD, et al. Simvastatin for the prevention of exacerbations in moderate-to-severe COPD. N Engl J Med 2014; 370: 2201–10.

      10 Aaron SD, Vandemheen KL, Fergusson D, et al. Tiotropium in combination with placebo, salmeterol, or fluticasone–salmeterol for treatment of chronic obstructive pulmonary disease: a randomized trial. Ann Intern Med 2007; 146: 545.

    2. In reporting our prediction model, we followedrecommendations set by the Transparent Reporting of aMultivariable Prediction Model for Individual Prognosisor Diagnosis (TRIPOD) statement.

      Es necesarion que nosotros hagamos esto?

      1. Collins GS, Reitsma JB, Altman DG, Moons K. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement. BMC Med 2015; 13: 1
    3. Inclinical practice, a history of two or more exacerbationsand one severe exacerbation per year is used toguide therapeutic choices for exacerbation prevention.3

      Esto es lo que en la práctica clínica se considera para guiar el tratamiento en exacerbaciones

      Vogelmeier CF, Criner GJ, Martinez FJ, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 Report. GOLD Executive Summary. Am J Respir Crit Care Med 2017; 195: 557–82.

    4. Neither the developmental nor the validation datasetsincluded patients with mild (GOLD 1) severity and, assuch, we could not establish the accuracy of predictionsfor this subgroup.

      Mencionar en nuestros estudios

    5. Azithromycin reduces annual exacer-bation rate by 27%.8


    6. The Acute COPD Exacerbation Prediction Tool (ACCEPT):a modelling study

      The Acute COPD Exacerbation Prediction Tool (ACCEPT):a modelling study

    7. ACCEPT can combine predicted risk with effectestimates from randomised trials to enable personalisedtreatment.

      esto sería interesante recalcar en el ensayo clínico

    8. We used a joint accelerated failure time and logistic modelto characterise rate and severity of exacerbations. We havepreviously published details of this approach elsewhere.14

      análisis estadístico

    9. A 2017 systematic review of clinical prediction modelsfor COPD exacerbations found that only two models18,19 ofthe 27 reviewed reported on any external validation. Whenavailability of predictors and practical applicability werealso considered, none of the models were deemed readyfor clinical implementation.6

      es posible que nuestro estudio sea difícil de aplicar por el uso de sensores

    10. ACCEPT predicts rate and severity of exacerbations.

      Este es el outcome de ACCEPT. Nosotros definitivamente tenemos que hacer una clasificación.

    11. For example, ACCEPT can predict thenumber of exacerbations at a given time period, time tonext exacerbation, and probability of having a specificnumber of non-severe or severe exacerbations within agiven follow-up time (up to 1 year). By contrast, logisticregression models, used in most previous clinicalprediction models, predict the probability of having at leastone exacerbation in a single timeframe.6

      Aquí hay un versus muy claro. Esto hay que estudiarlo a fondo

    12. Outcomes of interest were rates of exacerbations andsevere exacerbations over 1 year.

      tasa de exacerbaciones y exacerbaciones severas en un año

    1. A Cochrane review [ 31 ] has summarized the impact of remote monitoring technologyfor people with COPD.

      Janjua, S.; Carter, D.; Threapleton, C.J.; Prigmore, S.; Disler, R.T. Telehealth Interventions: Remote Monitoring and Consultations for People with Chronic Obstructive Pulmonary Disease (COPD). Cochrane Database Syst. Rev. 2021, 7, CD013196.

    2. An increase in respiratory rates and thepercentage of respiratory cycles triggered by the patients nearly systematically precededexacerbation in patients with COPD treated by home NIV [ 25].

      Características de monitorización a distancia que pueden describir las exacerbaciones

    3. mean decrease of 700 steps per day was associated with an increasein the EXACT score indicating the start of an exacerbation [21 ].

      relación actividad física exacerbaciones

    4. The COPD “frequent exacerbator” phenotype is consistently defined by atleast two treated exacerbations per year and is associated with poor long-term outcomesand an accelerated decline in lung function

      Fenotipo de frequent exacerbator

    5. COPD exacerbations are more common in females, patients with car-diometabolic or psychiatric comorbidities—in particular depression—and at the mostsevere spectrum of the disease. A history of prior exacerbations has been demonstrated tohave by far the strongest association with the risk of future exacerbations [7,8]

      sex-related factors that are related to copd exacerbatoins

    1. In conclusion, our study confirms the obser-vation that exacerbations become more frequentand more severe as the severity of underlyingCOPD increases and shows that the most impor-tant determinant of frequent exacerbations is ahistory of exacerbations.

      Una vez más, la importancia de las exacerbaciones previas

    2. Wedefined frequent exacerbations as two or moreexacerbations in a year because this definition co-incides with current health care utilization crite-ria for frequent exacerbations.

      Definition of frequent exacerbator

    3. The casedefinition of an exacerbation was a functional one,based on the decision by a patient’s primary cli-nician or by study personnel to prescribe antibi-otics or systemic corticosteroids, alone or in com-bination.

      Definition of exacerbation



    1. We show that the combination of a low dailystep count and high CRP or IL-6 level isassociated with an increased rate of AEsand COPD-related hospitalizations

      Biomarcadores con pasos en predecir hospitalizaciones



    1. Results ofthe logistic regression and ROC analysis showed that theinfluences of the BODE index and the GOLD stage on exac-erbation risk during the first year of follow-up was similar.

      El efecto predictor del BODE y el GOLD es el mismo sobre las exacerbaciones, pero este efecto fue evaluado en una regresión simple.

    2. Adjusted multiple logistic regression models were alsoperformed, including independent variables associated with exac-erbation (P  0.20) in the univariate analysis

      Statistical analysis for prediction

    1. Exacerbations were gradedaccording to either: treatment in primary care, emer-gency room visit, or hospitalization. The BODE indexwas a good predictor of both the number and the sever-ity of exacerbations in COPD, especially in those exacer-bations that required hospital admission

      La relación del BODE y las exacerbaciones.

    2. Recently, Williams et al. sug-gested that the incremental shuttle walking test (ISWT)could be substituted for the 6MWT as an alternativemeasure of exercise capacity within the index and intro-duced the i-BODE (4). As field exercise tests, the ISWTand 6MWT are closely related (5, 6), though ISWT isconsidered to be closer to a maximal exercise test (7),whereas the 6MWT reflects a more functional exerciseperformance

      Diferencias entre el ISWT vs 6MWT.

    3. The BODE index has been found to be better than forcedexpiratory volume in 1 second (FEV1 ) in predicting the risk of death and hos-pitalization among patients with COPD (2, 3).

      Relación del BODE index con las hospitalizaciones y la mortalidad. Mejor predictor que el FEV1



    1. Another potential limitation is thechanges in treatment of COPD over thestudy period.

      Deberíamos analizar esto en nuestro estudio.

    2. The principal finding of this study isthat simultaneously elevated levels ofCRP, fibrinogen, and leukocytes wereassociated with increased risk of fre-quent exacerbations in individuals withstable COPD.

      Lo que demuestra el estudio.

    3. First, we analyzedrisk of having frequent exacerbationsduring the first year of follow-up usinglogistic regression

      statistical analysis for prediction

    4. Frequent ex-acerbations were defined as 2 or moreexacerbations less than 1 year apart.

      Podemos nosotros añadir esto a nuestros objetivos?

    5. An exacerbation of COPD was de-fined as a short-course treatment withoral corticosteroids alone or in combi-nation with an antibiotic or as a hos-pital admission due to COPD

      Definición de exacerbación

    6. However, some patients with COPDalso have evidence of low-grade sys-temic inflammation with increased lev-els of such inflammatory biomarkers

      Hay marcadores biológicos que pueden estar elevados en condiciones estables y que pueden estar relacionados con outcomes negativos. Estos son:

      • CRP
      • Fibrinógeno
      • Leucocitos

      Podemos solicitar estos en las visitas? o de verdad solo queremos información de los sensores?

    7. However, when predicting risk of fu-ture exacerbations based on previousevents, the positive predictive value re-mains low,9 indicating that additionaldeterminants of exacerbation suscep-tibility remain to be identified

      Esto contrasta con la información del paper de Mullerova:

      Hospitalized Exacerbations of COPD. Risk Factors and Outcomes in the ECLIPSE Cohort.

      Es un argumento interesante a debatir en nuestro estudio

    1. Finally, the ECLIPSE study wasconducted in multiple countries, which may have dif-ferent policies for hospitalizations and may follow(slightly) different treatment strategies. To explore thispossibility, we analyzed the subset of data collectedfrom three countries contributing the majority ofpatients (United States, United Kingdom, and Norway)and did not find significant differences among thesecountries in incidence of hospitalized exacerbations(e-Table 2), suggesting that if anything, this effect islikely small.

      Un análisis que nosotros también podemos hacer

    2. On theother hand, we acknowledge that our results may notbe immediately generalizable to the entire primarycare population of patients with COPD because inour study, patients were recruited mainly from pulmo-nary clinics.

      Una limitación que nosotros también tenemos

    3. In a subgroup of patients without recent hospitalizedexacerbation at baseline, fibrinogen was identified asan additional risk factor of future risk of hospital admis-sions for COPD exacerbations. Inflammatory pathwaysplay a prominent role in exacerbations of COPD.Fibrinogen has been recognized to independently contrib-ute to clinically important outcomes in COPD, includinghospitalization for COPD. 46,47 Our results indicate fibrin-ogen levels are predictive of the future hospitalizedexacerbations in the absence of information on past his-tory of these events. Plasma fibrinogen is under regula-tory qualification as a risk factor for mortality andhospitalization in COPD.48

      Relación del fibrinógeno con las hospitalizaciones por EPOC

    4. following an exacerbation 29-32 ; inactivity associatedwith hospitalization may cause muscle mass loss anddysfunction33; comorbidities may develop or worsen dueto treatment side effects (eg, systemic steroids inducinghyperglycemia and/or muscle weakness)34; patients maybe exposed to nosocomial infections35; and hospitaliza-tion may cause and/or aggravate depression.36

      ¿Por qué las hospitalizaciones son negativas para los pacientes con EPOC?

    5. We found that a previous hospitalized exacerbation inthe past year was the strongest predictor of future exac-erbations requiring hospitalization.

      Predictor más importante de exacerbaciones severas

    6. (1) COPD exacerba-tions requiring hospital admission are relatively fre-quent events occurring in about 30% of patients duringthe 3-year follow-up; (2) past history of hospitalizedexacerbations is most predictive of future events, andother risk factors include the severity of airflow limita-tion, poor health status, radiologic evidence of emphy-sema, older age, and presence of systemic inflammation;and (3) a history of hospitalized exacerbations heraldspoor survival

      Resumen de resultados

    7. (1) baseline differences between patients with and withouthospitalized exacerbation during follow-up were tested using analysisof variance or Wilcoxon rank-sum test for continuous variables, andx2 test for categorical variables; (2) the incidence (first hospitalizedexacerbation during the prospective follow-up) and recurrence (secondhospitalized exacerbation during the prospective follow-up) of hos-pitalized exacerbations was summarized as a rate per person per year(PPPY), using a sum of individual patient’s person-time in the studyand standardized per year, accompanied by 95% CIs; (3) factors asso-ciated with first hospitalized (and recurrent) exacerbations during the3-year follow-up, were explored using Cox proportional hazards models,adjusted for a wide range of demographics, and clinical and biologicmarkers.

      Statistical analysis

    8. Subjects were followed-up at 3 months, 6 months, and every 6 monthsthereafter for a maximum of 3 years. All patients had their vital statusconfirmed 3 years after recruitment.Information on COPD exacerbations was collected at scheduled visitsby investigators using the case report forms and based on either sub-jects’ recall of exacerbation events or available medical records for exac-erbation events, supplemented by monthly phone calls. For the purposeof the current analysis, we focused on those exacerbation episodes thatrequired hospital admission (hospitalized exacerbation).

      Seguimiento de pacientes parecido a la propuesta de TOLIFE.

    9. Exacerbations of COPD accel-erate disease progression5-7

      Interesante de leer

      1. Tanabe N , Muro S , Hirai T , et al . Impact of exacerbations on emphysema progression in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2011 ; 183 ( 12 ): 1653 - 1659 .

      2. Donaldson GC , Seemungal TA , Bhowmik A , Wedzicha JA . Relationship between exacerbation frequency and lung function decline in chronic obstructive pulmonary disease. Thorax. 2002 ; 57 ( 10 ): 847 - 852.

      3. Vestbo J , Edwards LD , Scanlon PD , et al ; ECLIPSE Investigators . Changes in forced expiratory volume in 1 second over time in COPD. N Engl J Med. 2011 ; 365 ( 13 ): 1184 - 1192 .

    1. logisticmultivariate regression tests

      Statistical analysis

    2. xacerbation wasdefined on the basis of symptom-based diagnosis such asincreased cough and sputum production, a change of sputumcolor, and worsening of dyspnea from a stable state andbeyond-normal day-to-day variations, i.e., showing acute onsetand necessitating a change in regular medication, in accor-dance with a previous report [21]. Moderate exacerbationsrequired a prescription for antibiotics and/or systemic corticos-teroids, and severe exacerbations required hospitalization [22].

      Definición de exacerbación

      1. Calverley PM, Anderson JA, Celli B, et al. Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease. N Engl J Med 2007;356:775–89
    1. the CODEX indexis the most useful in predicting survival, hospital read-missions, and a combination of the two in the short andmedium term in patients hospitalized for AECOPD.

      De nuevo, la importancia del CODEX

    2. Multicomponent scales have been developed toimprove prognosis prediction in COPD, and they haveproved to be better predictors of survival than anyisolated variable.

      Lo importante de esto es que podamos hacer las escalas con las medidas de los sensores. Leer la continuación del párrafo. Destaca que el BODE fue desarrollado para pacientes sin comorbilidades, pero que esta el BODEX y el DOSE.

      Si se van a usar los indices es importante que haya una frecuencia de visitas cada 3 meses, por ejemplo, porque se los obtiene a través de variables que hay que medirse en las visitas.

      Pensar en que se quieren hacer modelos predictivos tomando en cuenta solo la información de los sensores. Sería bueno contar con estos indices de manera automática con la información que se obtiene de los sensores.

    3. This newly proposed CODEX index is essentially anevolution of the BODE and BODEX indexes, retain-ing their cutoffs for dyspnea, obstruction, and previousexacerbations, but replacing BMI with comorbiditymeasured using the original Charlson index modifiedby age.

      Importante considerar esta variante de los indices previos.

    4. Second, we reportedthe usefulness of this CODEX index in evaluating therisk of readmission, as well as the composite end point(readmission and/or mortality).

      Evaluar incluir CODEX

    5. Time-dependentvariables from hospital discharge were analyzed with Cox logisticregression and Kaplan-Meier statistics.

      Cox logistic regression

    6. Full methodology is avail-able elsewhere and is summarized in e-Appendix 1. 16,17

      Methods supplement

    1. The mostcommon statistical method was logistic regression (11 out of 25 different statistical methods analysed)followed by Cox regression (10), and correlation analysis between an index (or a multivariable regressionequation) with the outcome (three). Finally, Poisson regression model, negative binomial regression modeland random forest model were each used once.

      Métodos estadísticos. Leer los papers que están siendo estudiados

      Bertens (29) Ya lo tienes

      Motegi (43) Motegi T, Jones RC, Ishii T, et al. A comparison of three multidimensional indices of COPD severity as predictors of future exacerbations. Int J COPD 2013; 8: 259–271.

      Almagro (23) Almagro P, Soriano JB, Cabrera FJ, et al. Short- and medium-term prognosis in patients hospitalized for COPD exacerbation: the CODEX index. Chest 2014; 145: 972–980.

      Suetomo (48) Suetomo M, Kawayama T, Kinoshita T, et al. COPD assessment tests scores are associated with exacerbated chronic obstructive pulmonary disease in Japanese patients. Respir Investig 2014; 52: 288–295

      Mullerova (45) Müllerova H, Maselli DJ, Locantore N, et al. Hospitalized Exacerbations of COPD. Chest 2015; 147: 999–1007.

      Thomsen (50) Thomsen M, Ingebrigtsen TS, Marott JL, et al. Inflammatory biomarkers and exacerbations in chronic obstructive pulmonary disease. JAMA 2013; 309: 2353–2361.

      Moberg (42) Moberg M, Vestbo J, Martinez G, et al. Validation of the i-BODE index as a predictor of hospitalization and mortality in patients with COPD Participating in pulmonary rehabilitation. COPD 2014; 11: 381–387.

      Takahashi (49) Takahashi T, Muro S, Tanabe N, et al. Relationship between periodontitis-related antibody and frequent exacerbations in chronic obstructive pulmonary disease. PLoS One 2012; 7: e40570.

      Faganello (33) Faganello MM, Tanni SE, Sanchez FF, et al. BODE index and GOLD staging as predictors of 1-year exacerbation risk in chronic obstructive pulmonary disease. Am J Med Sci 2010; 339: 10–14

      Garcia-Aymerich (34) Garcia-Aymerich J, Farrero E, Félez MA, et al. Risk factors of readmission to hospital for a COPD exacerbation: a prospective study. Thorax 2003; 58: 100–105.

      Ko (39) Ko FW, Tam W, Tung AH, et al. A longitudinal study of serial BODE indices in predicting mortality and readmissions for COPD. Respir Med 2011; 105: 266–273.

      Echave (32) Echave-Sustaeta J, Comeche Casanova L, Garcia Lujan R, et al. Prognosis following acute exacerbation of COPD treated with non-invasive mechanical ventilation. Arch Bronconeumol 2010; 46: 405–410.

      Lee (40) Lee SD, Huang MS, Kang J, et al. The COPD assessment test (CAT) assists prediction of COPD exacerbations in high-risk patients. Respir Med 2014; 108: 600–608.

      Moy (44) Moy ML, Teylan M, Danilack VA, et al. An index of daily step count and systemic inflammation predicts clinical outcomes in chronic obstructive pulmonary disease. Ann Am Thorac Soc 2014; 11: 149–157

      Hurst (36) Hurst JR, Vestbo J, Anzueto A, et al. Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med 2010; 363: 1128–1138

      Amalakuhan (28) Amalakuhan B, Kiljanek L, Parvathaneni A, et al. A prediction model for COPD readmissions: catching up, catching our breath, and improving a national problem. J Community Hosp Intern Med Perspect 2012; 2: 9915.

    2. In order to come up with high-quality prediction models for exacerbations in COPD patients, a standardmethodology for developing the models should be adopted [55]

      Leer cita 55

      Moons KG, Kengne AP, Woodward M, et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 2012; 98: 683–690.



    1. CODEX was designed to predict mortality and hospitalreadmission in 3–12 months after discharge of patients hospi-talized for AECOPD.6

      CODEX Leer

      Almagro P, Soriano JB, Cabrera FJ, et al; Working Group on COPD, Spanish Society of Internal Medicine. Short- and medium-term prognosis in patients hospitalized for COPD exacerbation: the CODEX index. Chest. 2014;145(5):972–980.

    2. BODE2 (body mass index [BMI], airflow obstruction, dyspnea, andexercise capacity), BODEX3 (BMI, airflow obstruction, dyspnea, and previous severeexacerbations), ADO4 (age, dyspnea, and airflow obstruction), and DOSE5 (dyspnea,airflow obstruction, smoking status, and exacerbation frequency

      ¿Se pueden incluir estas variables?

    1. When the recordings met criteria number 1 a red lineappeared on the corresponding day of the patient’s time-score plot (Fig. 2) and an electronic mail message wasautomatically sent to the research team.

      Ideas of how alerts may work

    2. To establish a baseline all patients entered an exacer-bation-free run-in period of 14 days where they recordedsymptom score and lung function as described above.Baseline for each symptom score and FEV 1 was the medianand the mean value respectively of the 14-day run-in periodrecordings

      exacerbation free run in period of 14 days.

      Podemos aplicarlo en nuestro estudio? Hacer pasar a los pacientes por un periodo de 2 semanas sin exacerbaciones y empezar a contar desde ahí.

    3. . AECOPD was, therefore, regarded to be present ifat least one of the following criteria was encountered:1. An increase of at least 1 degree of 2 symptom scoresand/or a decline in FEV 1  10% from baseline for 2successive days.2. A patient presenting with symptoms they felt to bethose of AECOPD and sought help that resulted in thembeing given a course of antibiotics and/or prednisolone.

      Nosotros registraremos los ingresos

    1. Conventional threshold-basedalgorithms, adopted in the majority of reviewed stud-ies (n ¼ 12), show poor performance in early detect-ing respiratory exacerbations or identifying severityand duration in COPD, 13,53 with the best reportedaccuracy being 73% of exacerbations detected. 52 ; bestsensitivity/specificity 66%/93%55 24 h before hospi-talization.

      Estudio donde se creó una alarma.

      1. Pinnock H, Hanley J, McCloughan L, et al. Effective ness of telemonitoring integrated into existing clinical services on hospital admission for exacerbation of chronic obstructive pulmonary disease: researcher blind, multicentre, randomised controlled trial. BMJ 2013; 347: f6070

      2. Halpin DMG, Laing-Morton T, Spedding S, et al. A randomised controlled trial of the effect of automated interactive calling combined with a health risk forecast on frequency and severity of exacerbations of COPD assessed clinically and using EXACT PRO. Prim Care Respir J 2011; 20: 324–331.

      3. Sund ZM, Powell T, Greenwood R, et al. Remote daily real-time monitoring in patients with COPD – a feasibility study using a novel device. Respir Med 2009; 103: 1320–1328.

      4. Yanez AM, Guerrero D, Perez De Alejo R, et al. Monitoring breathing rate at home allows early identification of COPD exacerbations. Chest 2012; 142:1524–1529.

    2. Whilst the 7-day recall scoresand the daily diary scores have been found to beequivalent in detecting changes over time of theimpact of COPD symptoms, only daily data seemto be suitable if the outcome of interest is detectingthe onset of exacerbations. 85

      Importante que la medida de los sensores sea diaria. Problemas técnicos tienen que verse por adelantado.

    3. In COPD, physiological measurements have notproved to be able to predict deteriorations, eitherbecause they change late in the time course ofexacerbation, they cannot be measured reliably orbecause therapeutic interventions during the experi-ment alter the outcomes hindering the accuracy ofalgorithms. 17

      Posibles inconvenientes de obtener medidas fisiológicas.

    4. One study used a com-promise solution, 56 whereby the patient with a lowrisk of exacerbation monitored on a weekly basis andwhen risk increased according to the predictivemodel, reporting tasks could be scheduled daily toensure timely detection.

      ¿Se puede hacer esto? Sería importante conversar los posibles problemas técnicos de los sensores

    5. A common limitation in the selected studies was theexamination of a relatively small group of patientswho presented a high rate of exacerbations. Winterperiods were extensively selected for trials becauseexacerbations are more likely than in other sea-sons. 51 Although this may have enabled recruit-ment of ‘at-risk’ populations it may have affectedgeneralizability of results.

      Esto es importante preguntar a Judith

    6. EXACT-PRO was specifically designed and validated fordetecting COPD exacerbation

      La ventaja de exact es que es el único cuestionario validado para detectar exacerbaciones

    7. (EXACT)

      Sería necesario recoger EXACT??

    8. An ‘event-based’ definition of an exacerbation, 70including self-administration of medication orunscheduled visits to emergency units and/or admis-sions, was used in nine studies (n ¼ 6 in COPD andn ¼ 3 in asthma studies). Symptom-based definitionsof exacerbation (e.g. Anthonisen criteria 71 ) were usedin seven COPD studies.

      Criterios de exacerbaciones

    9. Exacerbation criteria

      Diferentes criterios de exacerbaciones

    10. Common classification algorithms for supervisedlearning in the healthcare field include artificialneural networks, 36 decision trees, 37 random forests, 38Bayesian networks, 39 k-nearest neighbors,40 supportvector machines, 41 linear discriminant analysis, 42 k-means clustering 43 and logistic regression. 44

      Haremos un classification. Evaluar la posibilidad de regresión de Cox.

      • Artificial neural networks
      • Decision trees
      • Random forests
      • Bayesian networks
      • k-nearest neighbors
      • Support vector machines
      • Linear discriminant analysis
      • k-means clustering
      • Logistic regression
    1. Cox proportional hazards modeling would alsohave been a valid approach for risk estimation, but we choselogistic regression analysis because we considered each exac-erbation within our predefined time frame of 2 years to beof equal importance, regardless of whether this exacerbationoccurred early or late in the follow-up period.

      Esto es importante. Comparación entre logística y regresión de cox

    2. We used logistic regression modeling to estimate the riskof occurrence of COPD exacerbations within the proceeding24 months.

      Análisis estadístico

    3. We were not able to include all potential predictorsavailable from the literature, such as exercise capacity, theSt George’s Respiratory Questionnaire, oxygen therapy,and gastroesophageal reflux

      Variables a incluir

    4. Unfortunately, wecould not evaluate the widely accepted BODE index,5 becausewe did not perform a 6-minute walking test in any of ourcohorts.

      Nosotros podemos contar con el BODE?

    5. For both cohorts we used the same “operational” definitionfor exacerbation of COPD, that is, symptomatic deteriorationrequiring pulsed oral steroid use or hospitalization.15–1

      Se pueden utilizar ambas definiciones?

    6. For both cohorts we used the same “operational” definitionfor exacerbation of COPD, that is, symptomatic deteriorationrequiring pulsed oral steroid use or hospitalization.15–1

      Se pueden utilizar ambas definiciones?

    1. The primary composite outcome was death or admissionsfrom the baseline data collection until 60 months. Thesecondary outcome was exacerbations from the baselinedata collection until 60 months.

      Sería lo mejor dejar de seguir a los pacientes después de la primera exacerbación?



    1. Seven out of nine studies foundin the literature confirmed the finding that female patientshave a higher number of total exacerbations.15–17,19,21,22,31

      Dato curioso. Sería interesante revisarlo

    2. Five different prediction models for the annual exacerba-tion rate were estimated using negative binomial regression2

      nb regression. Han hecho 5 modelos, pero en el sentido de que han utilizado diferentes variables como predictoras

    3. Participants were asked to use the following definition foran exacerbation: a moderate exacerbation was defined asan increase in symptoms requiring a visit to a health careprovider and a course of antibiotics and/or oral steroids.A severe exacerbation was defined as an exacerbation requir-ing hospitalization.

      Parecido a lo que queremos medir

    1. History of Exacerbations

      Tratar de conseguir esta información

    2. The test set AUROC of 0.86 was relatively high,18–24 butour models may be of limited value for prediction ofsevere exacerbations due to high false positive rate

      Tener cuidado con esto.

    3. These methods included logistic regression with multipleregularization methods (lasso, ridge and elastic net), ran-dom forest and gradient boosted trees models (XGBoost).

      Regularization methods and XGboosted random and boosted trees

    4. This set of models(along with support vector machines and neural networks,which were not taken into consideration being more chal-lenging to interpret) are considered gold standard formachine learning classification studies done on tabulardata. Resampling was applied during cross-validation,making sure that only training folds of each cross-valida-tion iteration are affected, and the effect of resampling istested on the non-resampled test fold in each cross-valida-tion iteration.

      Procesos estadísticos que acompañan a los modelo predictivos.

    5. The prediction period was divided into non-overlap-ping 10-day prediction windows for each patient (Figure3). Before the start of each 10-day prediction window,lookback periods of 10, 30, 60, 90,180, 365 days or theentire patient history were set up depending on the vari-able. For details refer to Supplemental Table 1.

      Esto es muy importante. Esto es una opción de cómo nosotros podríamos evaluar las exacerbaciones

    1. Seasonality isknown to affect COPD exacerbations, most frequently occur-ring in the winter months,37–39 which is likely to reflect anincreased prevalence of respiratory infections, reduced immu-nity, altered environmental conditions, and physiologicalresponses during these months.40,41

      effect of seasonality on exacerbacions

    2. Timing of Re-Exacerbation RiskTo understand the timing and dynamics of re-exacerbationrisk, and to evaluate the choice of cut points for early andlate re-exacerbations, Kaplan–Meier cumulative incidencecurves of time to first re-exacerbation amongst all patientsin cohort A were plotted.

      Timing and dynamics de las exacerbaciones

    3. The cut-off pointfor early and late re-exacerbations was chosen based on clinicaljudgment, and was informed by an analysis of dailyre-hospitalization risk in the US.18 The 90-day cut-off pointwas also chosen based on clinical development support for anAECOPD therapy. Patients were classed as having nore-exacerbations if they did not re-exacerbate within the180-day period after the index date.

      Considerar que las hospitalizaciones son un equivalente a las exacerbaciones severas ya que estas requieren hospitalizarse. Depende de cómo las vayamos a medir

    4. Re-exacerbations were defined a priori as either early (occur-ring within 1–90 days after the index date) or late (occurringbetween 91–180 days after the index date

      re exacerbaciones

    5. This included start date, end (reso-lution) date, treatment (oral corticosteroid/antibiotics),severity (including hospitalization), and outcome (includ-ing death). Data was collected at scheduled visits (baselineand 3, 6, 12, 18, 24, 30, and 36 months), using an electro-nic case-report form and based on either patients’ recall ofexacerbation events or available medical records forexacerbation events, and was supplemented by monthlyphone calls to ECLIPSE participants

      Puede servir para guiar nuestro diseño

    6. First, we aimed to develop and validatea predictive model capable of identifying factors potentiallypredictive of experiencing early, late, or no re-exacerbationwithin 180 days.

      Ligado al objetivo del CSA

    1. A challenge in COPD is the variation between patients and how to set alarm limits for anindividual patient. Of the 16 articles included in this review, only eight studies (three at high riskof bias, one at low quality and two at moderate quality) [ 5, 13, 14 ,18 – 21, 25] mentioned that they hadcustomised the alarm limits for each individual. Methods used were reported in six out of the eightstudies


    1. Exacerbations were defined as subject-reported worsen-ing in respiratory health, requiring therapy with systemic cortico-steroids and/or antibiotics. Frequent exacerbations were definedas 2 or more exacerbations in 1 year, and severe exacerbations weredefined as those leading to hospitalization or emergency room vis-its [9]




    1. Acute exacerbationreadmission within 30 days due to the short acute exacer-bation cycle, not only severely damages lung function andincreases the risk of death, but also occupies a large num-ber of medical resources [4]

      short exacerbation cycle?

    2. Our study assumes that the SVM model can achieve acertain prediction effect in predicting the risk of readmis-sion in COPD patients, and the results have certain refer-ence value. Therefore, it is proposed to use SVM to builda 30-day acute exacerbation readmission risk predictionmodel for elderly COPD patients, and evaluate its predic-tion effect, so as to provide a basis for early identificationof patients with high risk of readmission in the future.

      SVM for the prediction analysis

    1. such as bloodeosinophil count, chronic bronchitis, gastroesophagealreflux, socioeconomic status, and insurance coverageimprove risk prediction remains to be investigated.

      Considerar estas variables a medir.

      • Blood eosinphil count
      • Chronic bronchitis
      • Gastroesophageal reflux
      • SES (cómo lo vamos a medir?)
      • Insurance coverage

      Tal vez no sea lo más importante porque queremos que el modelo esté construído con variables a partir de los sensores

    2. Second, ACCEPT does not advance ourunderstanding of how various risk factors operatein combination. Many variables appear to be simplymarkers of severity rather than biological predictors ofreal risk. The authors address one of these: contrary toestablished literature, current smoking confers reducedrisk of exacerbation, probably because patients withsevere disease and high frequency of exacerbations aremore likely to have quit smoking.

      Dos cosas importantes: - Nosotros tenemos que resaltar que no medidos marcadores de severidad. - Resaltan la posible confusión entre fumar y un riesgo reducido de exacerbaciones

    3. Finally, preventionof severe exacerbations is needed before they occur,and performance of this risk tool in individuals whohave never had an exacerbation is not clear and needsto be tested.

      Cómo evaluaremos a los pacientes que no han tenido exacerbaciones?

    4. First, although ACCEPTshowed good-to-excellent discrimination overalland appears superior to exacerbation history alone,improvement in risk prediction was smaller in thosewith previous history of exacerbations than in thosewithout.

      Esto también es importante. Es importante porque nosotros deberíamos dividir el desempeño del modelo según varias poblaciones de interés. Por ejemplo, en este caso, han comparado el desempeño del modelo en población con y sin exacerbaciones previas.

    5. Thus, the major improvement in risk prediction withACCEPT appears to be for severe exacerbations.

      Esto es importante porque es justamente lo que nosotros queremos.

    6. Usinga joint survival–logistic model, this risk tool providesan individualised risk estimate for exacerbations in thesubsequent year and their severity, as well as the rate offuture events.

      Este documento es un comentario al estudio del ACCEPT. Nosotros podemos hacer lo mismo, pero teniendo en cuenta un mes(?) como referencia.


      Podemos dividir el tratamiento según la familia de fármacos que esté recibiendo el paciente. Así como la base de datos de Urban Training.

      • Beta adrenergic
      • Muscarinic
      • Oral Glucocorticoid
      • Inhaled glucocorticoid
      • Antimicrobial therapy (antibiotics, antiviral)
    2. More than 80percent of exacerbations of COPD can be managed on an outpatient basis, sometimes afterinitial treatment in the office or emergency department.

      Debido a este hecho: ¿Deberíamos hacer un check list sobre la toma de decisiones para ingresar o no a los pacientes con exacerbaciones? El hecho de que no ingresen a pacientes que debieron, puede aumentar el riesgo de exacerbaciones?

      Variables a considerar para ingresar a un paciente con COPD - Inadequate response to outpatient or emergency department management - Onset of new signs (eg, cyanosis, altered mental status, peripheral edema) - Marked increase in intensity of symptoms over baseline (eg, new onset resting dyspnea) accompanied by increased oxygen requirement or signs of respiratory distress - Severe underlying COPD (eg, forced expiratory volume in one second [FEV ] ≤50 percent of predicted) - History of frequent exacerbations or prior hospitalization for exacerbations - Serious comorbidities including pneumonia, cardiac arrhythmia, heart failure, diabetes mellitus, renal failure, or liver failure - Frailty - Insufficient home support


      ¿Sería bueno crear una variable: viral infections? Y tal vez las demás infecciones virales del COVID.

    1. Vitamin D supplementation — Adhering to current guidelines regarding vitamin Dsupplementation in patients with a 25-hydroxyvitamin D level <20 or 30 ng/mL (50 or 75nmol/L) reduces COPD exacerbations in addition to benefits in reducing falls and fractures

      Otra variables que se podría añadir. Revisarlo bien porque el resultado de los metaanálisis son mixtos

    2. Noninvasive ventilation — For patients who require noninvasive ventilation (NIV) during ahospitalization for a COPD exacerbations and who remain hypercapnic, nocturnal NIV athome significantly reduces the risk of rehospitalization

      Importante porque puede afectar a el riesgo de hospitalización y depende de como queramos medir las exacerbaciones

    3. Prophylactic azithromycin

      Para pacientes con exacerbaciones recurrentes (>= a 2 por año) la administación profiláctica de azitromicina puede ayudar a reducir la frecuencia de exacerbaciones.

    4. defined as "an acuteevent characterized by a worsening of the patient's respiratory symptoms that is beyondnormal day-to-day variations and leads to a change in medication

      Definition of exacerbation according to GOLD guidelines


      Sección de prevención de exacerbaciones de COPD en uptodate. Importante leer que la sección comienza con medidas para reducir la exacerbaciones. Estas medidas pueden ser incluidas cómo variables a preguntar.

      Irán señaladas, pero igual: - Smoking cessation - Proper use of medications - Vaccination against seasonal influenza - Vaccination against COVID - Pneumococcal vaccination

    6. Pulmonary rehabilitation

      Posible variables a añadir: tiempo en rehabilitación pulmonar? ha estado en rehabilitación pulmonar en el ultimo año? Más de 6 meses en el último año? Cuántos meses en el último año?

    7. Smoking cessation (see "Overview of smoking cessation management in adults")•Proper use of medications (including inhaler technique) ( table 5 and table 6and table 7 and table 8) (see "The use of inhaler devices in adults")•Vaccination against seasonal influenza (see "Seasonal influenza vaccination inadults")•Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)(see "COVID-19: Vaccines")•Pneumococcal vaccination ( figure 1) (see "Pneumococcal vaccination in adults")

      Posibles variables a añadir.

    1. Use of the ubiquitous proportional hazardsmodel, with time to first exacerbation as the outcome, is acommon mode of inference in contemporary clinical trialsof COPD. While it is robust in estimating treatment effectin randomized controlled trials, this analytical method fallsshort of providing other features, such as background rateof exacerbations or the shape of the incidence function, toenable predictions about the rate and (absolute or relative)duration of time to future events for a given patient. Asmentioned by Cox et al. (11), making such informative pre-dictions has been hindered by the widespread use of semi-parametric proportional hazards models.

      desventajas del proportinal hazards

    2. In the present work, we used a joint para-metric recurrent-event and logistic regression model toenable full quantification of exacerbation incidence andseverity and their correlation

      objetivo del análisis estadístico



    1. Patients were contacted by telephone by atrained clinical research assistant at months 1, 2, and 3 afterrecruitment and were asked about potential hospitalizationsbecause of ECOPD. Whenever this was identified, hospital,data of admission, and reason for hospitalization were recordedusing standardized questionnaires. The attending pulmonolo-gist of each patient, blinded to the respiratory results, reviewedall available information and validated the episode of ECOPDhospitalization

      llamada de teléfono al mes 1, 2 , 3 después del reclutamiento

    2. First, weanalyzed individual changes in mean respiratory frequency usingtime series analysis of breathing rate in each patient whorequired ECOPD hospitalization during follow-up. This timeseries included 5 baseline days and the 5 days that precededhospitalization. Baseline was defined as the first 5 consecutivefollow-up days with valid recorded data and a minimum com-pliance with oxygen therapy of 4 h/d, before any exacerbationhad occurred. Individual changes were analyzed using the YoungC statistic, which is appropriate for the study of changing trendsin short series with a small number of measures. 16 Second, weanalyzed the change in mean respiratory frequency between the5 baseline days and the 5 days that preceded hospitalization ofall individual time series considered together using analysis ofvariance for repeated measures. Third, we analyzed the discrimi-nating power of the change in the mean respiratory frequency topredict ECOPD hospitalizations using receiver operating char-acteristic (ROC) curves in two different potentially relevantclinical scenarios (increase of breathing rate from baseline to24 or 48 h before hospitalization).

      time series

    3. Patients were contacted by telephone by atrained clinical research assistant at months 1, 2, and 3 afterrecruitment and were asked about potential hospitalizationsbecause of ECOPD. Whenever this was identified, hospital,data of admission, and reason for hospitalization were recordedusing standardized questionnaires. The attending pulmonolo-gist of each patient, blinded to the respiratory results, reviewedall available information and validated the episode of ECOPDhospitalization.

      Llamadas de teléfono 1, 2, 3 días después del reclutamiento