BackgroundCoronavirus disease 2019 is an evolving infectious disease that dramatically spread all over the world in the early part of 2020. No studies have yet summarized the potential severity and mortality risks caused by COVID-19 in patients with chronic obstructive pulmonary disease (COPD), and we update information in smokers. MethodsWe systematically searched electronic databases from inception to March 24, 2020. Data were extracted by two independent authors in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Study quality was assessed using a modified version of the Newcastle-Ottawa Scale. We synthesized a narrative from eligible studies and conducted a meta-analysis using a random-effects model to calculate pooled prevalence rates and 95% confidence intervals (95%CI). ResultsIn total, 123 abstracts were screened and 61 full-text manuscripts were reviewed. A total of 15 studies met the inclusion criteria, which included a total of 2473 confirmed COVID-19 patients. All studies were included in the meta-analysis. The crude case fatality rate of COVID-19 was 7.4%. The pooled prevalence rates of COPD patients and smokers in COVID-19 cases were 2% (95% CI, 1%-3%) and 9% (95% CI, 4%-14%) respectively. COPD patients were at a higher risk of more severe disease (risk of severity = 63%, (22/35) PLOS ONEPLOS ONE | https://doi.

JSA: Conception, design, data acquisition, analysis, interpretation, drafting manuscript for intellectually important content, and approval of final version; TO: Data acquisition and approval of final version; AMA: Analysis, interpretation and approval of final version; MA: Analysis, interpretation and approval of final version; SM: Analysis, interpretation and approval of final version; AA: data acquisition, analysis and approval of final version; SQ: interpretation and approval of final version; SM: interpretation, and approval of final version.; JRH: Conception, design, analysis, interpretation, and approval of final version.

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IMPORTANCEMost of the global morbidity and mortality in chronic obstructive pulmonary disease (COPD) occurs in low-and middle-income countries (LMICs), with significant economic effects.OBJECTIVE To assess the discriminative accuracy of 3 instruments using questionnaires and peak expiratory flow (PEF) to screen for COPD in 3 LMIC settings. DESIGN, SETTING, AND PARTICIPANTSA cross-sectional analysis of discriminative accuracy, conducted between January 2018 and March 2020 in semiurban Bhaktapur, Nepal; urban Lima, Peru; and rural Nakaseke, Uganda, using a random age-and sex-stratified sample of the population 40 years or older.EXPOSURES Three screening tools, the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE; range, 0-6; high risk indicated by a score of 5 or more or score 2-5 with low PEF [<250 L/min for females and <350 L/min for males]), the COPD in LMICs Assessment questionnaire (COLA-6; range, 0-5; high risk indicated by a score of 4 or more), and the Lung Function Questionnaire (LFQ; range, 0-25; high risk indicated by a score of 18 or less) were assessed against a reference standard diagnosis of COPD using quality-assured postbronchodilator spirometry. CAPTURE and COLA-6 include a measure of PEF. MAIN OUTCOMES AND MEASURESThe primary outcome was discriminative accuracy of the tools in identifying COPD as measured by area under receiver operating characteristic curves (AUCs) with 95% CIs. Secondary outcomes included sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS Among 10 709 adults who consented to participate in the study (mean age, 56.3 years (SD, 11.7); 50% female), 35% had ever smoked, and 30% were currently exposed to biomass smoke. The unweighted prevalence of COPD at the 3 sites was 18.2% (642/3534 participants) in Nepal, 2.7% (97/3550) in Peru, and 7.4% (264/3580) in Uganda. Among 1000 COPD cases, 49.3% had clinically important disease (Global Initiative for Chronic Obstructive Lung Disease classification B-D), 16.4% had severe or very severe airflow obstruction (forced expiratory volume in 1 second <50% predicted), and 95.3% of cases were previously undiagnosed. The AUC for the screening instruments ranged from 0.717 (95% CI, 0.677-0.774) for LFQ in Peru to 0.791 (95% CI, 0.770-0.809) for COLA-6 in Nepal. The sensitivity ranged from 34.8% (95% CI, 25.3%-45.2%) for COLA-6 in Nepal to 64.2% (95% CI, 60.3%-67.9%) for CAPTURE in Nepal. The mean time to administer the instruments was 7.6 minutes (SD 1.11), and data completeness was 99.5%. CONCLUSIONS AND RELEVANCEThis study demonstrated that screening instruments for COPD were feasible to administer in 3 low-and middle-income settings. Further research is needed to assess instrument performance in other low-and middle-income settings and to determine whether implementation is associated with improved clinical outcomes.

BackgroundChronic obstructive pulmonary disease (COPD) is the end result of a susceptible individual being exposed to sufficiently deleterious environmental stimuli. More than 90% of COPD-related deaths occur in low- and middle-income countries (LMICs). LMICs face unique challenges in managing COPD; for example, deficient primary care systems present challenges for proper diagnosis and management. Formal diagnosis of COPD requires quality-assured spirometry, which is often limited to urban health centres. Similarly, standard treatment options for COPD remain limited where few providers are trained to manage COPD. The Global Excellence in COPD Outcomes (GECo) studies aim to assess the performance of a COPD case-finding questionnaire with and without peak expiratory flow (PEF) to diagnose COPD, and inform the effectiveness and implementation of COPD self-management Action Plans in LMIC settings. The ultimate goal is to develop simple, low-cost models of care that can be implemented in LMICs. This study will be carried out in Nepal, Peru and Uganda, three distinct LMIC settings.Methods/designWe aim to assess the diagnostic accuracy of a simple questionnaire with and without PEF to case-find COPD (GECo1), and examine the effectiveness, cost-effectiveness and implementation of a community-health-worker-supported self-management Action Plan strategy for managing exacerbations of COPD (GECo2). To achieve the first aim, we will enrol a randomly selected sample of up to 10,500 adults aged ≥ 40 years across our three sites, with the goal to enrol 240 participants with moderate-to-severe COPD in to GECo2. We will apply two case-finding questionnaires (Lung Function Questionnaire and CAPTURE) with and without PEF and compare performance against spirometry. We will report ROC areas, sensitivity and specificity. Individuals who are identified as having COPD grades B–D will be invited to enrol in an effectiveness-implementation hybrid randomised trial of a multi-faceted COPD self-management Action Plan intervention delivered by CHWs. The intervention group will receive (1) COPD education, (2) facilitated-self management Action Plans for COPD exacerbations and (3) monthly visits by community health workers. The control group will receive COPD education and standard of care treatment provided by local health providers. Beginning at baseline, we will measure quality of life with the EuroQol-5D (EQ-5D) and St. George’s Respiratory Questionnaire (SGRQ) every 3 months over a period of 1 year. The primary endpoint is SGRQ at 12 months. Quality-adjusted life years (QALYs) using the Short-Form 36 version 2 will also be calculated. We will additionally assess the acceptability and feasibility of implementing COPD Action Plans in each setting among providers and individuals with COPD.DiscussionThis study should provide evidence to inform the use of pragmatic models of COPD diagnosis and management in LMIC settings.Trial registrationNCT03359915 (GECo1). Registered on 2 December 2017 and NCT03365713 (GECo2). Registered on 7 December 2017. T...

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CONSORT 2010 checklist of information to include when reporting a randomised trial* Section/Topic Item No Checklist item Reported on page No Title and abstract 1 a I d e n t i f i c a t i o n a s a r a n d o m i s e d t r i a l i n t h e t i t le 1b Structured summary of trial design, methods, results, and conclusions (for specific guidance see CONSORT for abstracts)

Background Low- and middle-income countries (LMICs) account for >90% of deaths and illness episodes related to COPD; however, this condition is commonly underdiagnosed in these settings. Case-finding instruments for COPD may improve diagnosis and identify individuals that need treatment, but few have been validated in resource-limited settings. Methods We conducted a population-based cross-sectional study in Uganda to assess the diagnostic accuracy of a respiratory symptom, exposure and functional questionnaire in combination with peak expiratory flow for COPD diagnosis using post-bronchodilator FEV 1 /FVC z-score below the 5th percentile as the gold standard. We included locally relevant exposure questions and statistical learning techniques to identify the most important risk factors for COPD. We used 80% of the data to develop the case-finding instrument and validated it in the remaining 20%. We evaluated for calibration and discrimination using standard approaches. The final score, COLA (COPD in LMICs Assessment), included seven questions, age and pre-bronchodilator peak expiratory flow. Results We analyzed data from 1,173 participants (average age 47 years, 46.9% male, 4.5% with COPD) with acceptable and reproducible spirometry. The seven questions yielded a cross-validated area-under-the-curve [AUC] of 0.68 (95% CI 0.61–0.75) with higher scores conferring greater odds of COPD. The inclusion of peak expiratory flow and age improved prediction in a validation sample (AUC=0.83, 95% CI 0.78–0.88) with a positive predictive value of 50% and a negative predictive value of 96%. The final instrument (COLA) included seven questions, age and pre-bronchodilator peak expiratory flow. Conclusion COLA predicted COPD in urban and rural settings in Uganda has high calibration and discrimination, and could serve as a simple, low-cost screening tool in resource-limited settings.