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. 2020 Dec 7;15(12):e0243191. doi: 10.1371/journal.pone.0243191

Prevalence and predictors of death and severe disease in patients hospitalized due to COVID-19: A comprehensive systematic review and meta-analysis of 77 studies and 38,000 patients

Kunchok Dorjee 1,*, Hyunju Kim 2, Elizabeth Bonomo 1, Rinchen Dolma 3
Editor: Davide Bolignano4
PMCID: PMC7721151  PMID: 33284825

Abstract

Introduction

Progression of COVID-19 to severe disease and death is insufficiently understood.

Objective

Summarize the prevalence of risk factors and adverse outcomes and determine their associations in COVID-19 patients who were hospitalized.

Methods

We searched Medline, Embase and Web of Science for case-series and observational studies of hospitalized COVID-19 patients through August 31, 2020. Data were analyzed by fixed-effects meta-analysis using Shore’s adjusted confidence intervals to address heterogeneity.

Results

Seventy-seven studies comprising 38906 hospitalized patients met inclusion criteria; 21468 from the US-Europe and 9740 from China. Overall prevalence of death [% (95% CI)] from COVID-19 was 20% (18–23%); 23% (19–27%) in the US and Europe and 11% (7–16%) for China. Of those that died, 85% were aged≥60 years, 66% were males, and 66%, 44%, 39%, 37%, and 27% had hypertension, smoking history, diabetes, heart disease, and chronic kidney disease (CKD), respectively. The case fatality risk [%(95% CI)] were 52% (46–60) for heart disease, 51% (43–59) for COPD, 48% (37–63) for chronic kidney disease (CKD), 39% for chronic liver disease (CLD), 28% (23–36%) for hypertension, and 24% (17–33%) for diabetes. Summary relative risk (sRR) of death were higher for age≥60 years [sRR = 3.6; 95% CI: 3.0–4.4], males [1.3; 1.2–1.4], smoking history [1.3; 1.1–1.6], COPD [1.7; 1.4–2.0], hypertension [1.8; 1.6–2.0], diabetes [1.5; 1.4–1.7], heart disease [2.1; 1.8–2.4], CKD [2.5; 2.1–3.0]. The prevalence of hypertension (55%), diabetes (33%), smoking history (23%) and heart disease (17%) among the COVID-19 hospitalized patients in the US were substantially higher than that of the general US population, suggesting increased susceptibility to infection or disease progression for the individuals with comorbidities.

Conclusions

Public health screening for COVID-19 can be prioritized based on risk-groups. Appropriately addressing the modifiable risk factors such as smoking, hypertension, and diabetes could reduce morbidity and mortality due to COVID-19; public messaging can be accordingly adapted.

Introduction

Coronavirus disease-19 (COVID-19) caused by severe acute respiratory syndrome- coronavirus-2 (SARS-CoV-2) that first emerged in Wuhan, China in late December 2019 has spread with such rapidity and efficiency that in less than 10 months, it has caused more than 36 million cases and million deaths globally [1]. Driven by an urgency to solve the crisis, studies are being published at an unprecedented pace. However, across the publications, prevalence of death, severe disease and their association with epidemiological risk factors have greatly varied [2, 3], with studies showing conflicting results for association of key risk factors such as sex [48], smoking [912], hypertension [4, 7, 8, 13, 14] and diabetes [4, 7, 8, 13, 14] with COVID-19 disease severity and death. Whether or how cardiovascular risk factors, especially prior hypertension, diabetes and heart disease are associated with acquisition of SARS-CoV-2 and progression to severe disease or death is not understood well [1518]. Meta-analyses conducted so far on prevalence of epidemiological risk factors and association with disease progression were mostly based on studies from China [9, 11, 1820] and many of the analyses on prevalence estimates included studies focused on critically ill patients [9, 19], which can overestimate the prevalence and affect generalizability of results. To our knowledge, none of the analyses were restricted to hospitalized COVID-19 patients. Restricting our analysis to hospitalized patients provides an efficient sampling frame to investigate disease progression in relation to risk factors.

Therefore, we undertook a comprehensive systematic review and meta-analysis to investigate the association between key epidemiological factors–age, gender, smoking, hypertension, diabetes, heart disease, chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD) and chronic liver disease (CLD)–and progression to death and severe disease in patients hospitalized due to COVID-19. We additionally compared the 1) the prevalence of risk factors and death in the US-Europe with that of China; 2) the prevalence of co-morbidities at baseline with the general population prevalence, and 3) prevalence of cardiovascular disease, COPD and CKD at baseline with corresponding organ injuries (acute cardiac injury, acute lung injury, and acute kidney injury) during hospital admission.

Methods

Literature search, study selection and data abstraction

We searched Medline, Embase, Web of Science and the WHO COVID-19 database to identify studies published through August 31, 2020 that investigated the risk of severe disease or death in hospitalized patients with confirmed COVID-19 disease. We used search terms, ‘coronavirus disease 19’, ‘COVID-19’, ‘severe acute respiratory syndrome coronavirus 2’ and ‘SARS-CoV-2’ for COVID-19 and the string ((characteristics) OR (risk factors) OR (epidemiology) OR (prevalence) OR (intensive care) OR (ventilator) OR (mechanical ventilator) OR (mortality) OR (survivor*) OR (smoking) OR (smoker*)) AND ((COVID-19) OR (COVID) OR (coronavirus)) for studies published between December 15, 2019 and August 31, 2020. We started the search on March 18, 2020 with biweekly search thereafter and final search on August 31, 2020. We included case series and observational studies that described the prevalence of death or severe disease in adult population stratified by risk factors: age, sex, hypertension, diabetes, heart disease, COPD, CKD and CLD. We excluded studies that included non-consecutive patients or exclusively focused on pregnant women, children, and elderly patients. We excluded studies that exclusively studied critically ill patients from calculation of prevalence of death but included them for calculating the association of risk factors with death. Screening of abstracts and full-text reviews were conducted using Covidence (Melbourne, Australia).

Risk factors and outcomes

Primary outcomes were prevalence of death and association of risk factors with death. We extracted data on death as recorded in the publications. We measured prevalence of severe disease and association with risk factors as secondary outcomes. We defined outcome as severe disease for any of 1) the study classified COVID-19 disease as severe or critical, 2) intensive care unit (ICU) admission, 3) acute respiratory distress syndrome, or 4) mechanical ventilation. Severe disease was defined by studies as respiratory rate≥30 per minute, oxygen saturation≤93%, and PaO2/FiO2<300 and/or lung infiltrates>50% within 24–48 hours [3]. Critical illness was defined as respiratory failure, shock and/or multiple organ dysfunction or failure [3]. Heart disease as a pre-existing condition was broadly defined by most studies as ‘cardiovascular disease’ (CVD). Additional outcomes were acute cardiac and kidney injury in the hospitalized patients that were defined as such by the studies.

Statistical analysis

We calculated and reported summary estimates from fixed-effects models [21]. We assessed heterogeneity across studies using Cochran’s Q-test (χ2 p value <0.10) [22] and I2 statistics (I2 >30%) [23]. In the presence of heterogeneity, we adjusted the confidence intervals for between-study heterogeneity using the method described by Shore et al. [24]. We presented the results from random effects meta-analysis as well. The meta-analysis was performed in Microsoft® Excel 2020 (Microsoft Corporation, Redmond, WA). We analyzed publication bias using funnel plots and Egger’s tests. Quality of each study was assessed using the Newcastle-Ottawa assessment scales using the PRISMA guidelines. We calculated the following as a part of our analyses: 1) prevalence of severe disease or death, 2) prevalence of risk factors, and 3) relative risk for the association of age, sex, and comorbidities with outcome. When not reported or when unadjusted odds ratio was presented, we calculated the relative risk (95% CI) using the frequencies provided. Adjusted estimates were used where available. Case fatality risk (and case severity risk) for a specific risk factor was calculated as number of deaths (or severe disease) in patients with a risk factor out of all patients possessing the risk factor.

Results

Study characteristics

Initial search yielded 30133 citations. Articles were then screened (Fig 1). We identified 410 articles for full text review, of which 77 studies met inclusion criteria (Table 1) [48, 13, 14, 2594]. The studies were conducted in: China (n = 35), USA (n = 18), Europe (n = 10), rest of Asia (n = 5) and Africa (n = 1). Two studies were prospective, five cross-sectional, and remaining retrospective in nature.

Fig 1. PRISMA flow diagram for selection of studies.

Fig 1

Table 1. Characteristics of studies to determine prevalence of risk factors and death or severe disease and their associations in patients hospitalized for COVID-19 globally.

Author, year of publication (journal) Country Region Study Period Study Design Size Epidemiological Risk Factor Outcome Measures of Association
Aggarwal S et al., 2020 (Diagnosis) USA Des Moines 3-1-2020 to 4-4-2020 Retrospective 16 Age, sex, smoking, substance use, obesity, HTN, DM, CVD, COPD, CKD, Cancer Prevalence of death and primary end point (death, shock, or ICU admission). Association of risk factors with outcome Unadjusted RR calculated
Argenziano M. G et al., 2020 (BMJ) USA New York City 3-11-2020 to 4-6-2020 Retrospective 1,000 Age, sex, ethnicity, obesity, smoking, HTN, DM, CVD, COPD, CKD, cancer, HIV, viral hepatitis, cirrhosis Association of risk factors with disease severity and death. Adjusted HR
Brill S. E et al., 2020 (BMC Medicine) UK Barnet 3-10-2020 to 4-8-2020 Retrospective 450 Age, race, sex, smoking, HTN, DM, CVD, immunosuppression Prevalence of death. Unadjusted RR calculated
Association of comorbidities with disease severity.
Cao Z et al., 2020 (PLOS ONE) China Beijing 1-21-2020 to 2-12-2020 Retrospective 80 Sex, age, HTN, CVD, DM, COPD, smoking Association of risk factors with disease severity. Unadjusted RR calculated
CDC (MMWR) USA National 2-12-2020 to 3-28-2020 Retrospective 5285 Age, Current Smoker, DM, CVD, COPD, CKD, CLD Prevalence of ICU admission. Association of risk factors with severe disease (ICU admission). Unadjusted RR calculated
Chen G et al., 2020 (Journal of Clinical Investigation) China Wuhan December 2019 to 01-27-2020 Retrospective 21 Age, sex, Huanan sea food market exposure, HTN, DM Prevalence of severe disease. Compared moderate and severe cases based on risk factors. Unadjusted RR calculated
Chen J et al., 2020 (Journal of Infection) China Shanghai 1-20-2020 to 2-6-2020 Retrospective 249 Age, sex Prevalence of ICU admission. Association of age and sex with ICU admission. Adjusted OR reported for age and sex
Chen Q et al., 2020 (Infection) China Zhejiang province 1-1-2020 to 3-11-2020 Retrospective 145 Age, sex, smoking, exposure history, BMI, HTN, DM, COPD, CKD, Solid tumor, Heart disease, HIV infection Prevalence of severe disease. Association of risk factors with severe disease. Unadjusted RR calculated
Chen T et al., 2020 (BMJ) China Wuhan, Hubei 1-13-2020 to 2-28-2020 Retrospective 274 Age, sex, sea food market exposure, contact history, smoking HTN, DM, CVD, CHF, heart failure, cancer, HBV, HIV, CKD Association of risk factors with death. Unadjusted RR calculated
Compared death and recovered group. Presently hospitalized patients excluded from study.
Chilimuri S et al., 2020 (West J Emerg Med) USA New York City 3-9-2020 to 4-9-2020 Retrospective 375 Age, sex, ethnicity, HTN, DM, CVD, COPD, CKD, HIV/AIDS, CLD Association of risk factors with disease severity and death. Adjusted OR
reported for age, sex and comorbidities
Ciceri F et al., 2020 (Clinical Immunology) Italy Milan 2-25-2020 to 5-1-2020 Retrospective 410 Age, sex, ethnicity, BMI, HTN, CVD, DM, COPD, CKD, cancer Prevalence of death. Adjusted HR
Association of risk factors with disease severity.
Cummings MJ et al., 2020 (The Lancet) USA New York City 3-2-2020 to 4-1-2020 Prospective 257 Age, sex, race, BMI, HTN, DM, chronic cardiac disease (CHD and CHF), CKD, smoking history, COPD, cancer, HIV, cirrhosis Association of risk factors with death. Adjusted HR
Deng Y et al., 2020 (Chin Med J) China Wuhan 1-1-2020 to 2-21-2020 Retrospective 116 out of 964 Age, sex, HTN, DM, Heart Disease, Cancer Association of risk factors with death. Unadjusted RR calculated
Compared death and recovered group.
Presently hospitalized patients excluded from study.
Du R-H et al., 2020 (ERJ) China Wuhan, Hubei 1-25-2020 to 2-7-2020 Retrospective 179 Age, sex, HTN, DM, CVD, TB, cancer, CKD or CLD Prevalence of death. Association of risk factors with death. Adjusted OR for age≥65 and CVD. Unadjusted RR calculated for other variables
Escalera-Antezana et al., 2020(Infez Med) Bolivia Nationwide 3-2-2020 to 3-29-2020 Retrospective 107 Age, HTN, CVD, DM, obesity, sex Prevalence of death. Adjusted OR
Association of risk factors with disease severity. reported for age, sex and risk factors
Feng Y et al., 2020 (AJRCCM) China Wuhan, Shanghai, Anhui province 1-1-2020 to 2-15-2020 Retrospective 476 Age, age groups, sex, Wuhan exposure, smoking, alcohol, HTN, anti-hypertensives, CVD, DM, cancer, COPD, CKD Prevalence of death. Association of risk factors with severe disease. Adjusted HR for HTN, CVD, DM. Unadjusted RR calculated for other variables
Ferguson J et al., 2020 (EID) USA Northern California 03-13-2020 to 04-11-2020 Retrospective 72 Sex, race, smoking, HTN, DM, CKD, Heart Disease, COPD Prevalence of ICU admission. Association of risk factors with severe disease (ICU admission). Unadjusted RR calculated
Galloway J.B et al., 2020 (Journal of Infection) UK London 3-1-2020 to 4-17-2020 Retrospective 1,157 Age, sex, ethnicity, cancer, CKD, DM, HTN, CVD, COPD Prevalence of death. Adjusted HR reported for age and sex
Association of risk factors with disease severity.
Garibaldi B et al., 2020 (Ann Intern Med) USA Maryland 3-4-2020 to 6-27-2020 Retrospective 832 Age, sex, alcohol, smoking, BMI, cancer, CVD, COPD, HTN, liver disease, CKD, HIV/AIDS DM Association of risk factors with disease severity. Adjusted HR
Washington DC
reported for age, ethnicity and BMI
Giacomelli A et al., 2020 (Pharmacol Res) Italy Milan 2-21-2020 to 4-20-2020 Prospective 233 Sex, age, smoking, obesity Prevalence of death. Adjusted HR
Association of risk factors with disease severity. reported for sex, age, and obesity
Gold J et al, 2020 (MMWR) USA Georgia 3-1-2020 to 3-30-2020 Retrospective 305 Age, sex, race, HTN, DM, Heart Disease, COPD, CKD, Cancer Prevalence of patient characteristics, death, and ICU. Unadjusted RR calculated
Goyal P et al. 2020 (NEJM) USA New York City 3-3-2020 to 3-27-2020 Retrospective 393 Age, sex, race, smoking, HTN, DM, COPD, Heart Disease, Asthma Prevalence of severe disease (mechanical ventilation). Association of risk factors with severe disease. Unadjusted RR calculated
Gregoriano C et al.,2020 (Swiss Medical Weekly) Switzerland Aarau 2-26-2020 to 4-30-2020 Retrospective 99 Age, sex, smoking, HTN, cancer, CVD, COPD, obesity, DM, rheumatic disease, organ transplant recipient, obstructive sleep apnea Prevalence of disease endpoints (transfer to ICU and in-hospital mortalities). Unadjusted OR
Association of comorbidities with disease endpoints.
Guan et al., 2020 (NEJM) China Nationwide 12-11-2019 to 01-31-2020 Retrospective 1099 Age, sex, smoking, exposure to transmission source, HTN, DM, CHD, CKD, COPD, Cancer, HBV, cerebrovascular disease, immunodeficiency Prevalence of death, composite outcome, ((Death/MV/ICU) and severe disease. Association with severe disease and composite outcome. Unadjusted RR calculated
Guan Wei-Jie, 2020(ERJ) China Nationwide 12-11-2019 to 1-31-2020 Retrospective 1590 Age, sex, smoking, CKD, COPD, HTN, DM, CVD, Cancer, HBV Prevalence of patient characteristics, death and composite outcome (Death, ICU, MV). Adjusted HR
Hewitt J et al., 2020 (Lancet) UK Nationwide (UK), 2-27-2020 to 4-28-2020 Prospective 1,564 Age, sex, smoking, DM, HTN, CVD, CKD Prevalence of death. Adjusted HR
Italy Modena (Italy) Association of risk factors with disease severity.
Hsu H. E et al., 2020 (Morbidity and Mortality Weekly Report) USA Boston 3-1-2020 to 5-18-2020 Retrospective 2,729 Age, sex, ethnicity, COPD, cancer, CKD, cirrhosis, CVD, DM, HIV/AIDS, HTN, obesity, substance use disorder Association of risk factors with disease severity. Unadjusted RR calculated
Hu L et al., 2020 (CID) China Wuhan 1-8-2020 to 2-20-2020 Retrospective 323 Age, sex, current smoker, HTN, DM, CVD, COPD, CKD, CLD, Cancer Prevalence of severe (severe and critical) disease. Association of risk factors with disease severity. Unadjusted RR calculated
Huang C et al., 2020 (The Lancet) China Wuhan 12-16-2020 to 1-2-2020 Prospective 41 Age, sex, Huanan seafood market exposure, smoking, HTN, DM, CKD, COPD, CVD, Cancer, CLD Association of risk factors with severe disease (ICU care). Unadjusted RR calculated
Hur K et al., 2020 (Otolaryngol Head Neck Surg) USA Chicago 3-1-2020 to 4-8-2020 Retrospective 486 Age, sex, BMI, smoking, HTN, DM, CVD, COPD, cancer, immunosuppression, CKD, Association of risk factors with disease severity. Adjusted HR (for age, sex, ethnicity BMI, HTN, smoking)
Iaccarino G et al., 2020 (Hypertension) Italy Nationwide 3-9-2020 to 4-9-2020 Cross-sectional 1,591 Age, sex, HTN, obesity, DM, COPD, CKD, CVD, cancer Prevalence of death. Adjusted OR
Association of risk factors with disease severity.
Inciardi R et el., 2020 (Eur Heart J) Italy Lombardy 3-4-2020 to 3-25-2020 Retrospective 99 Sex, smoking, HTN, DM, coronary artery disease, COPD, CKD, cancer Prevalence of death. Association of risk factors with death. Unadjusted RR calculated
Jang J.G et al., 2020 (Journal of Korean Medical Science) South Korea Daegu 2-19-2020 to 4-15-2020 Retrospective 110 Age, sex, CVD, cerebrovascular disease, COPD, dementia, DM, HTN, connective tissue disease liver disease, malignancy, Parkinson’s disease Association of risk factors with disease severity and death. Adjusted OR
Javanian M et al., 2020 (Rom J Intern Med) Iran Mazandaran province 2-25-2020 to 3-12-2020 Retrospective 100 Age, sex, HTN, DM, CVD, CKD, cancer, CLD Prevalence of death. Association of risk factors with death. Unadjusted RR calculated
Kalligeros M et al., 2020 (Obesity Journal) USA Rhode Island 2-17-2020 to 4-5-2020 Retrospective 103 Age, sex, ethnicity, smoking, BMI (obesity), cancer, CKD, cirrhosis, DM, heart disease (CVD), HTN, lung disease (COPD), transplant Association of risk factors with disease severity. Adjusted OR
(for age, sex, ethnicity, BMI, DM, HTN, heart disease, lung disease)
Khalil K et al., 2020 (Journal of Infection) UK London 3-7-2020 to 4-7-2020 Prospective 220 Age, sex, ethnicity, smoking, COPD, CVD, HTN, hyperlipidemia, DM, CKD, CVA, dementia, liver disease, cancer Prevalence of death. Unadjusted RR calculated
Association of risk factors with disease severity.
Khamis F et al., 2020 (Journal of Infection and Public Health) Oman Muscat 2-24- 2020 to 4-24-2020 Retrospective 63 Age, sex, smoking, substance use, HTN, DM, CKD, CVD Prevalence of severe disease and death. Unadjusted RR calculated
Association of risk factors with disease severity.
Lendorf M.E et al., 2020 (Danish Medical Journal) Denmark North Zealand 3-1-2020 to 5-18-2020 Retrospective 111 Age, sex, BMI, cancer, HTN, CVD, COPD, immunosuppression, CKD, DM, smoking Association of risk factors with disease severity and death. Unadjusted RR calculated
Li X et al., 2020 (J Allergy Clin Immunol) China (Wuhan, Hubei) Wuhan, Hubei 1-26-2020 to 2-5-2020 Retrospective 548 Age, sex, smoking, HTN, DM, Heart Disease, CKD, Cancer, COPD Prevalence of death and severe disease. Unadjusted RR calculated
Association of risk factors with severe disease.
Liu S et al., 2020 (BMC Infectious Diseases) China Jiangsu Province 1-10-2020 to 3-15-2020 Retrospective 625 Sex, age, HTN, DM, CVD Association of risk factors with disease severity. Adjusted OR
(for age and HTN)
Liu W et al. 2020 (Chin Med J) China Wuhan 12-30-2019 to 01-15-2020 Retrospective 78 Age, sex, smoking history, exposure to Huanan seafood market, HTN, diabetes, COPD, cancer Compared progression group and stabilization group. Progression group defined by progression to severe or critical disease or death. Unadjusted RR calculated
Nikpouraghdam M et al., 2020 (J Clin Virol) Iran Tehran 2-19-2020 to 4-15-2020 Retrospective 2,964 Age, sex, DM, COPD, HTN, CVD, CKD, cancer Prevalence of death. Adjusted OR
Association of risk factors with disease severity.
Nowak B et al., 2020 (Pol Arch Intern Med) Poland Warsaw 3-16-2020 to 4-7-2020 Retrospective 169 Sex, smoking, HTN, DM, CVD, COPD, CKD, AKI, cancer Prevalence of death. Association of risk factors with death. Unadjusted RR calculated
Okoh A.K et al., 2020 (Int J Equity Health) USA Newark 3-10-2020 to 4-20-2020 Retrospective 251 Age, sex, ethnicity, BMI, HTN, DM, CVD, COPD, HIV, CKD, cancer Prevalence of death. Adjusted OR
Association of risk factors with disease severity and death.
Palaiodimos L et al., 2020 (Metabolism) USA New York 3-9-2020 to 3-22-2020 Retrospective 200 Age, sex, race, smoking, HTN, DM, coronary artery disease, COPD, CKD, cancer Prevalence of death. Association of risk factors with death. Adjusted OR (provided by the study)
Pellaud C et al., 2020 (Swiss Medical Weekly) Switzerland Fribourg 3-1-2020 to 5-10-2020 Retrospective 196 Sex, age, HTN, DM, obesity, CVD, COPD, cancer, immunosuppression, smoking Prevalence of death. Unadjusted RR calculated
Association of risk factors with disease severity.
Richardson S et al., 2020 (JAMA) USA New York 3-1-2020 to 4-4-2020 Retrospective 5700 Age, sex, race, smoking, HTN, DM, COPD, asthma, coronary artery disease, kidney disease, liver disease, obesity, cancer Prevalence of ICU admission and death. Unadjusted RR calculated
Association of risk factors with death.
Rivera-Izquierdo M et al., 2020 (PLOS ONE) Spain Granada 3-16-2020 to 4-10-2020 Retrospective 238 Sex, age, smoking, HTN, DM, CVD, COPD, CKD, active neoplasia, medications Prevalence of death. Adjusted HR
Association of risk factors with disease severity.
Shabrawishi M et al., 2020 (Plos One) Saudi Arabia Mecca 3-12-2020 to 4-8-2020 Retrospective 150 Age, sex, HTN, DM, CVD, CKD, hypothyroidism, cancer, CVA, COPD, CLD Association of risk factors with disease severity and death. Unadjusted RR calculated
Shahriarirad R et al., 2020 (BMC Infectious Diseases) Iran Fars Province 2-20-2020 to 3-20-2020 Multicenter Retrospective 113 Age, sex, HTN, DM, CVD, COPD, CKD, malignancy, other immunosuppressive diseases Prevalence of death. Unadjusted RR calculated
Association of risk factors with disease severity.
Shekhar R et al., 2020 (Infectious Diseases) USA New Mexico 1-19-2020 to 4-24-2020 Cohort 50 Age, sex, HTN, DM, COPD, alcoholic cirrhosis, alcohol use, obesity Association of risk factors with disease severity. Unadjusted RR calculated
Shi Y et al., 2020 (Crit Care) China Zhejiang province Not specified to 02-11-2020 Retrospective 487 Age, sex, smoking, HTN, DM, CKD, CVD, CLD, cancer Prevalence of and association of risk factors with severe disease Unadjusted RR calculated
Suleyman G et al., 2020 (JAMA Network) USA Metropolitan Detroit 3-9-2020 to 3-27-2020 Retrospective 463 Age, sex, ethnicity, COPD, obstructive sleep apnea, DM, HTN, CVD, CKD, cancer, rheumatologic disease, organ transplant, obesity, smoking Association of risk factors with disease severity. Adjusted OR
Sun L et al., 2020 (Journal of Medical Virology) China Beijing 1-20-2020 to 2-15-2020 Retrospective 55 Age, sex, exposure, HTN, DM, CVD, Lung Disease, CKD, CLD Prevalence of severe disease. Association of risk factors with severe disease. Unadjusted RR calculated
Tambe M et al., 2020 (Indian J Public Health) India Pune 3-31-2020 to 4-24-2020 Cross-Sectional 197 Age, sex, HTN, DM, COPD, CVS, ALD, CKD Association of risk factors with disease severity and death. Unadjusted RR calculated
Tian S et al., 2020 (Journal of Infection) China Beijing 1-20-2020 to 2-10-2020 Retrospective 262 Age, sex, contact history, exposure to Wuhan. Prevalence of death. Association of severe disease with risk factors. Unadjusted RR calculated
Tomlins J et al., 2020 (Journal of Infection) UK Bristol 3-10-2020 to 3-30-2020 Retrospective 95 Age, sex, HTN, DM, COPD, CVD, cancer, renal disease, gastrointestinal disease, neurological disease Prevalence of death. Association of risk factors with death. Unadjusted RR calculated
Turcotte J.J et al., 2020 (PLOS ONE) USA Maryland 3-1-2020 to 4-12-2020 Retrospective 117 Age, BMI, sex, DM, obstructive sleep apnea, COPD, CVD, CKD, HTN, smoking, alcohol use, liver disease Association of risk factors with disease severity and death. Adjusted OR
Wan S et al., 2020 (Journal of Medical Virology) China Northeast Chongqing 1-23-2020 to 2-8-2020 Retrospective 135 Age, sex, smoking, CKD, COPD, HTN, DM, CVD, Cancer, CLD, exposure, travel history Prevalence of severe disease. Association of risk factors with severe disease. Unadjusted RR calculated
Wang D et al., 2020 (JAMA) China Wuhan 1-1-2020 to 1-28-2020 Retrospective 138 Age, sex, Huanan Seafood Market Exposure, HTN, DM, CVD, COPD, Cancer, CKD, CLD, HIV Prevalence of death and ICU admission. Unadjusted RR calculated
Association of risk factors with severe disease (ICU care)
Wang R et al., 2020 (Internal Journal of Infectious Diseases) China Fuyang 1-20-2020 to 02-09-2020 Retrospective 125 Age, sex, CVD, Cancer Prevalence of critical disease. Association of age, sex, and smoking with critical disease. Unadjusted RR calculated
Wang Z et al., 2020 (CID) China Wuhan 1-16-2020 to 01-29-2020 Retrospective 69 Age, sex, HTN, DM, CVD, COPD, Cancer, HBV, Asthma Prevalence of death and severe disease (SpO2<90%). Association of risk factors with severe disease. Unadjusted RR calculated
Wei Y et al., 2020 (BMC Infectious Diseases) China Hubei Province 1-27-2020 to 3-22-2020 Retrospective 276 Age, sex, smoking, obesity, HTN, COPD, CVD, DM, cerebrovascular disease, cancer Association of risk factors with disease severity. Unadjusted RR calculated
Wu C et al., 2020 (JAMA Intern Med) China Wuhan 12-15-2019 to 01-26-2020 Retrospective 201 Age, sex, HTN, DM, CVD, CKD, Chronic Lung Disease, Cancer, CLD, Sea Food Market Exposure. Prevalence of ARDS, ICU admission and death. Association of risk factors with severe disease (ARDS) and death. Unadjusted RR calculated
Yang X et al, 2020 (Lancet Respir Med) China Wuhan 12-24-2019 to 1-26-2020 Retrospective 52 Age, sex, exposure, COPD, diabetes, chronic cardiac disease, smoking, malnutrition Association of risk factors with death. Unadjusted RR calculated
Yao Q et al., 2020 (Pol Arch Intern) China Huanggang, Hubei 1-30-2020 to 2-11-2020 Retrospective 108 Age, sex, smoking, HTN, DM, CVD, CLD, cancer Prevalence of severe disease and death. Unadjusted RR calculated
Association of risk factors with severe disease and death.
Young BE et al., 2020 (JAMA) Singapore Singapore 1-23-2020 to 2-3-2020 Retrospective 18 Age, sex Prevalence of severe disease (receiving supplemental O2). Association of severe disease with age and sex. Unadjusted RR calculated
Yu T et al., 2020 (Clinical Therapeutics) China Guangdong January to February 2020 Cross-sectional 95 Age, sex, current smoker Prevalence of ARDS. Unadjusted RR calculated
Association of age, sex, and smoking with ARDS.
Yu X et al., 2020 (Transboundary and Emerging Diseases) China Shanghai Up to 2-19-2020 Retrospective 333 Age, sex, BMI, smoking, alcohol, exposure, HTN, DM, CVD Prevalence of death and severe disease (Severe/critical pneumonia). Association of risk factors with severe disease. Adjusted OR for age group, sex, CVD, DM, HTN.
Zhan T et al., 2020 (J Int Med Res) China Wuhan 1-12-2020 to 3-8-2020 Retrospective 405 Age, sex, smoking, alcohol history, CVD, gastrointestinal disease, COPD, CKD, CLD Association of risk factors with disease severity. Unadjusted RR calculated
Zhang G et al., 2020 BMC Respiratory Research) China Wuhan 1-16-2020 to 2-25-2020 Retrospective 95 Age, sex Prevalence of severe disease, composite end point, and death. Association with severe disease. Unadjusted RR calculated
Zhang J et al., 2020 (Clin Microbiol Infect) China Wuhan 1-11-2020 to 2-6-2020 Retrospective 663 Age, sex, COPD, CVD, gastrointestinal disease, CKD, cancer Prevalence of death. Adjusted OR
Association of risk factors with disease severity.
Zhang JJ et al., 2020 (Allergy) China Wuhan 1-16-2020 to 2-3-2020 Retrospective 140 Age, sex, current smoker, past smoker, exposure history, HTN, DM, CVD, COPD, CKD, CLD Prevalence of severe disease. Association of risk factors with severe disease (ICU admission). Unadjusted RR calculated
Zhao X-Y et al., 2020 (BMC Inf Dis) China Hubei (Non-Wuhan) 1-16-2020 to 2-10-2020 Retrospective 91 Age, sex, DM, COPD, Cancer, Kidney disease Prevalence of death. Association of risk factors with severe disease Unadjusted RR calculated
Zheng S et al., 2020 (BMJ) China Zhejiang province 1-19-2020 to 2-15-2020 Retrospective 96 Age, sex, HTN, DM, CVD, lung disease, Liver disease, renal disease, malignancy, viral Load, immunocompromise Prevalence of death and severe disease. Unadjusted RR calculated
Association of risk factors with severe disease.
Zheng Y et al., 2020 (Pharmacological Research) China Shiyan, Hubei 1-16-2020 to 2-4-2020 Retrospective 73 Age, sex, exposure, smoking history, DM, CVD Prevalence of severe (severe/ critical) disease. Association of smoking and diabetes with severe disease. Unadjusted RR calculated
Zhou F et al., 2020 (The Lancet) China Wuhan 12-29-2019 to 1-31-2020 Retrospective 191 Age, sex, current smoking, exposure history, HTN, DM, CVD, COPD, cancer, CKD Prevalence of severe disease (ICU admission) and death. Association of risk factors with death. Adjusted OR for age and CVD. Unadjusted RR calculated for other variables.

CVD, cardiovascular disease; CKD, chronic kidney disease; CLD, chronic liver disease; COPD, chronic obstructive pulmonary disease; HTN, hypertension; DM, diabetes mellitus; ICU, intensive care unit; BMI, body mass index; HIV, human immunodeficiency virus; AIDS, acquired immunodeficiency syndrome; RR, relative risk; HR, hazard ratio; OR, odds ratio.

Population and demographics

There were 38,906 total COVID-19 hospitalized patients including 21468 patients from the US and Europe (87% from the US), and 9740 patients from China. Median age was 59 years [IQR: 57–62 years; I2 = 58%; n = 62 studies] and 48% [95% CI: 44–53%; I2 = 98%; n = 41] were aged≥60. Fifty-nine percent [95% CI: 57–60%; I2 = 98%; n = 75] of the patients were males.

Prevalence of death and severe disease

We calculated an overall prevalence of death of 20% [95% CI: 18–23%; I2 = 96%; n = 60], ranging from 1% to 38% across the studies, and of severe disease of 28% [95% CI: 24–33%; I2 = 98%; n = 60] for all patients hospitalized due to COVID-19 (Tables 2 and 3). Data on prevalence of death, severe disease, and risk factors (S1 Table), and association of the risk factors with death (S2 Table) and severe disease (S3 Table) for the individual studies are presented in the supplemental tables.

Table 2. Pooled prevalence of death stratified by epidemiological risk factors in COVID-19 patients hospitalized between December 2019-August 2020.

Risk factor or Outcome Overall prevalence of risk across studies Pooled Prevalence of Death (Case Fatality Risk) and Risk Factor Summary Relative Risk of Death
No. of studies Pooled prevalence of risk factor and death, No. of studies *Case fatality risk (Prevalence of death in risk group), #Prevalence of risk factor in persons who died, No. of studies Fixed Effects Random Effects# Heterogeneity
Summary relative risk; 95% CI (Shore adjusted) sRR; (95% CI) I2; c2; p value
% (95% CI) % (95% CI) % (95% CI)
Death 60 20 (18–23) N/A N/A N/A N/A N/A N/A N/A
Age ≥ 60 years 41 48 (44–53) 18 35 (28–43) 85 (80–89) 24 3.61 (2.96–4.39) 1.29 (1.03–1.62) 77%; 99; p<0.01
Male 75 59 (57–60) 31 26 (21–32) 66 (64–69) 36 1.31 (1.22–1.40) 1.34 (1.24–1.45) 18%; 43; p = 0.17
Smoking history 41 26 (22–31) 11 27 (24–32) 44 (38–50) 13 1.28 (1.06–1.55) 1.41 (1.12–1.78) 68%; 37; p<0.01
Current smoker 21 10 (7–13) 7 21 (14–29) 13 (7–24) 8 1.43 (91–2.26) 1.53 (95–2.45) 78%; 32; p<0.01
COPD 52 9 (8–11) 20 51 (36–71) 12 (7–19) 22 1.70 (1.42–2.04) 1.74 (1.43–2.13) 66%; 61; p<0.01
Hypertension 64 50 (46–54) 29 28 (23–36) 66 (61–70) 32 1.76 (1.58–1.96) 1.88 (1.66–2.13) 56%; 70; p<0.01
Diabetes 67 28 (25–31) 29 24 (17–33) 39 (35–44) 33 1.50 (1.35–1.66) 1.60 (1.42–1.79) 58%; 77; p<0.01
Cardiovascular disease 65 17 (15–20) 29 52 (46–60) 37 (32–43) 34 2.08 (1.81–2.39) 2.25 (1.92–2.64) 69%; 106; p<0.01
Chronic kidney disease 47 13 (11–16) 18 48 (37–63) 27 (21–34) 23 2.52 (2.11–3.00) 2.39 (1.91–2.99) 72%; 79; p<0.01
Chronic Liver Disease 31 2(2–3) 8 39(31–50) 6 (4–8) 9 2.65(1.88–3.75) 1.99 (1.26–3.16) 77%; 35; p<0.01

*Case fatality risk of represent total number of people that died in the specific risk group divided by total population in the risk group.

# Prevalence of risk group in dead represent total number of people having the risk group divided by total population that died.

Table 3. Pooled prevalence of severe disease stratified by epidemiological risk factors in COVID-19 patients.

Risk group or outcome Prevalence of Severe Disease (Case Severity Risk) and Risk Factors Summary Relative Risk of Severe Disease
No. of studies Prevalence of severe disease and case severity risk*, % (95% CI) *Prevalence of risk factor in people with severe disease, % (95% CI) No. of studies Fixed Effects Random Effects# Heterogeneity
sRR; 95% CI (Shore adjusted) sRR; (95% CI) I2; c2; p value
Severe disease 25 20 (16–25) N/A N/A N/A N/A N/A
Age ≥ 60 years 26 48 (39–59) 56 (52–61) 29 1.57 (1.36–1.80) 1.76 (1.50–2.07) 85%; 184; p<0.01
Male 45 40 (34–47) 63 (61–66) 47 1.26 (1.18–1.35) 1.33 (1.22–1.44) 38%; 75; p<0.01
Smoking history 27 39 (34–46) 26 (21–32) 27 1.29 (1.18–1.42) 1.32 (1.18–1.47) 33%; 39; p = 0.05
Current smoker 13 38 (28–53) 13 (9–20) 15 1.52 (1.21–1.91) 1.25 (94–1.66) 75%;56; p<0.01
COPD 24 43 (35–52) 14 (12–17) 29 1.71 (1.49–1.97) 1.83 (1.54–2.18) 84%;179; p<0.01
Hypertension 39 44 (37–53) 55 (50–61) 40 1.46 (1.28,1.65) 1.54 (1.33,1.78) 77%;168; p<0.01
Diabetes 43 43 (38–49) 33 (30–38) 44 1.48 (1.35–1.63) 1.64 (1.47–1.82) 59%;104; p<0.01
Cardiovascular disease 37 56 (48–65) 28 (24–33) 38 1.54 (1.39–1.72) 1.74 (1.52–1.98) 77%;164; p<0.01
Chronic kidney disease 22 36 (33–40) 26 (19–37) 27 1.56 (1.31–1.86) 1.42 (1.15–1.76) 85%; 176; p<0.01
Chronic Liver Disease 12 43(32–57) 5 (3–7) 15 1.63 (1.23–2.15) 1.66 (1.16–2.36) 82%; 76; p<0.01

*Case severity risk represent total number of people developing severe disease in the specific risk group divided by total population in that risk group.

# Prevalence of risk factor in severe disease represent total number of people with the risk factor divided by total population with severe disease.

Predictors of death and severe disease (Tables 2 and 3)

Age and sex

Median age for people who died was 79 years [IQR: 77–80; I2 = 89%; n = 28] and who had severe disease was 61 years [IQR: 59–63; I2 = 48%; n = 26]. Eighty-five percent [95% CI: 80–89; I2 = 76%; n = 18] of the deaths were in people aged ≥ 60 years and 66% [95% CI: 64–69; n = 34] were in males. The CFR (95% CI) was 35% (28–43%) for age≥60 years and 26% (21–32%) for males. Patients aged≥60 years [summary relative risk (sRR): 3.61; 95% CI: 2.96–4.39; I2 = 77%; n = 24] and males [sRR: 1.34; 95% CI: 1.22–1.40; I2 = 18%; n = 36] had higher risk of death. The risk of severe disease was similarly higher for age>60 [sRR: 1.57; 95% CI: 1.36–1.80; I2 = 85%; n = 29] and males [sRR: 1.26; 95% CI: 1.18–1.35; I2 = 38%; n = 47].

Hypertension

The prevalence of hypertension in the COVID-19 patients was 50% [95% CI: 46–54% I2 = 98%; n = 64], with a CFR in hypertensive patients of 28% [95% CI: 23–36%; I2 = 97%; n = 29] and a CSR of 44% [95% CI: 37–53%; I2 = 95%; n = 39]. Of the COVID-19 patients that died, 66% [95% CI: 61–70%; I2 = 83%; n = 29] had hypertension. Hypertensives had higher relative risk of death [sRR: 1.76; 95% CI: 1.58–1.96; I2 = 56%; n = 32] and severe disease [sRR: 1.46; 95% CI: 1.28–1.65; I2 = 77%; n = 40] compared to non-hypertensives (Fig 2A).

Fig 2. Association of hypertension, diabetes and heart disease with death in COVID-19 patients.

Fig 2

Diabetes

The prevalence of diabetes was 28% [95% CI: 25–31%; I2 = 97%; n = 67] with a CFR of 24% [95% CI: 17–33%; I2 = 98%; n = 29] and CSR of 43% [95% CI: 38–49%; I2 = 99%; n = 30] in the diabetics. Of the COVID-19 patients that died, 33% [95% CI: 32–44%; I2 = 83%; n = 29] were diabetics. Diabetics had higher relative risk of death [sRR: 1.50; 95% CI: 1.35–1.66; I2 = 58%; n = 33] and severe disease [sRR: 1.48; 95% CI: 1.35–1.63; I2 = 59%; n = 44] compared to non-diabetics (Fig 2B).

Cardiovascular disease

The pooled prevalence of CVD was 17% [95% CI: 15–20%; I2 = 96%; n = 65] with a CFR of 52% [95% CI: 46–60%; I2 = 81%; n = 29] and CSR of 56% [95% CI: 48–65%; I2 = 91%; n = 37] among cardiac patients. Of the patients that died, 37% [95% CI: 32–43%; I2 = 83%; n = 29] had CVD. Patients with CVD had higher relative risk of death [sRR: 2.08; 95% CI: 1.81–2.39; I2 = 69%; n = 34] and severe disease [sRR: 1.54; 95% CI: 1.39–1.72; I2 = 77%; n = 38] compared to patients without CVD (Fig 2C).

Smoking and COPD

The prevalence of any history of smoking in the patients was 26% [95% CI: 22–31%; I2 = 98%; n = 41]. For patients with smoking history, the CFR was 27% [95% CI: 24–32%; I2 = 61%; n = 11] and CSR was 39% [95% CI: 34–46; I2 = 78%; n = 27]. Compared to never smokers, patients with smoking history had higher relative risk of death [sRR: 1.28; 95% CI: 1.06–1.55; I2 = 68%; n = 13] and severe COVID-19 disease [sRR: 1.29; 95% CI: 1.18–1.42; I2 = 33%; n = 27] (Fig 3A). The prevalence of COPD was 9% [95% CI: 8–11%; I2 = 94%; n = 52]. Patients with COPD had a CFR of 51% [95% CI: 43–59%; I2 = 0%; n = 21]; CSR of 43% [95% CI: 35–52%; I2 = 84%; n = 24]; a sRR of death of 1.70 [95% CI: 1.42–2.04; I2 = 66%; n = 22] and of severe disease of 1.71 [95% CI: 1.49–1.97; I2 = 84%; n = 29] (Fig 3B).

Fig 3. Association of smoking, chronic obstructive pulmonary disease, chronic kidney disease and chronic liver disease with death in COVID-19 patients.

Fig 3

Chronic kidney disease

The prevalence of CKD was 13% [95% CI: 11–16%; I2 = 96%; n = 47] with a CFR of 48% [95% CI: 37–63%; I2 = 89%; n = 18] and CSR of 36% [95% CI: 33–40%; I2 = 56%; n = 22] in CKD patients. CKD was present in 27% [95% CI: 21–34%; I2 = 79%; n = 18] of all COVID-19 patients that died. CKD patients had higher relative risk of death [sRR: 2.52; 95% CI: 2.11–3.00; I2 = 72%; n = 23] and severe disease [sRR: 1.56; 95% CI: 1.31–1.86; I2 = 85%; n = 27] compared to non-CKD patients (Fig 3C).

Chronic liver disease

The prevalence of CLD was 2% [95% CI: 2–3%; I2 = 72%; n = 31] with a CFR of 39% [95% CI: 31–50%; I2 = 0%; n = 8] and CSR of 43% [95% CI: 32–57%; I2 = 5%; n = 12] in CLD patients. CLD was present in 6% [95% CI: 4–8%; I2 = 0%; n = 8] of the COVID-19 patients who died. Patients with CLD had higher relative risk of death [sRR: 2.65; 95% CI: 1.88–3.75; I2 = 77%; n = 9] and severe disease [sRR: 1.63; 95% CI: 1.23–2.15; I2 = 82%; n = 15] compared to non-CKD patients (Fig 3D).

COVID-19 related organ system injury

To understand how pre-existing health conditions may be correlated with the risk of specific organ injury, we calculated the prevalence of acute injury to lung, heart and kidney for studies that reported prevalence of both the pre-existing condition(s) and corresponding organ injury (Fig 4A). Pooled across 12 studies [14, 25, 32, 45, 48, 49, 52, 54, 60, 62, 79], the prevalence of COPD at baseline was 6% [95% CI: 4–11%] and the proportion of patients developing ARDS during hospitalization was 48% [32–73%]. The pooled prevalence of baseline CVD (n = 13 studies) was 11% [95% CI: 9–15%] and that of acute cardiac injury (ACI) during hospitalization was 21% [95% CI: 15–28%] [6, 14, 25, 32, 35, 43, 48, 49, 54, 79, 84]. The prevalence of CKD (n = 12 studies) was 14% [95% CI: 8–26%] and that of acute kidney injury during hospitalization (AKI) was 27% [95% CI: 21–34%] [6, 14, 25, 32, 45, 48, 65, 79].

Fig 4. Prevalence of acute organ injuries during hospital stay and regional difference in prevalence of death and comorbidities in patients hospitalized for COVID-19.

Fig 4

ARDS, acute respiratory distress syndrome; COPD, chronic obstructive pulmonary disease; ACI, acute cardiac injury; CVD, cardiovascular disease; AKI, acute kidney injury; CKD, chronic kidney disease; HTN, hypertension.

Regional difference in prevalence of death and risk factors

Upon sub-group analysis, we noted significantly higher prevalence of death and risk factors among COVID-19 patients in the US and Europe than in China (Fig 4B). The prevalence of death was 23% [95% CI: 19–27%; I2 = 97%; n = 29] in the US and Europe, and 11% [95% CI: 7–16%; I2 = 94%; n = 24] in China. Prevalence of severe disease was 20% [95% CI: 16–25%; I2 = 98%; n = 25] for US and Europe, and 39% [95% CI: 32–47%; I2 = 97%; n = 30] for China. Median age of patients was 65 years [IQR: 63–67 years; I2 = 0%; n = 24] for the US and Europe and 55 years [IQR: 52–58 years; I2 = 57%; n = 27] for China. Fifty-two percent [95% CI: 46–59%; I2 = 98%; n = 16] of the patients hospitalized were aged ≥60 years in the US and Europe as compared to 36% [95% CI: 30–43%; I2 = 96%; n = 22] for China. The prevalence of co-morbidities between US-Europe and China differed as follows: 1) US-Europe: HTN = 55% [95% CI: 52–57%]; diabetes = 31% [95% CI: 29–34]; CVD = 18% [95% CI: 15–21%]; smoking history = 15% [95% CI: 11–21%]; COPD = 9% [95% CI: 6–13%] and 2) China: HTN = 23% [95% CI: 20–26%]; diabetes = 12% [95% CI: 10–14%]; CVD = 16% [95% CI: 12–22%]; smoking history = 11% [95% CI: 9–13%]; CKD = 2.3% [95 CI: 1.6–3.4%] and COPD = 4% [95 CI: 3–5%].

Comorbidities in COVID-19 patients and the general populations in the US and China

In order to gain some understanding of whether patients with comorbidities are at higher risk of COVID-19 infection or hospitalization, we compared the prevalence of comorbidities between COVID-19 patients hospitalized in the US and the prevalence of comorbidities in the general US population. We observed that the prevalence of hypertension (55%), diabetes (33%), CVD (17%), and smoking history (23%) were substantially higher in the COVID-19 patients than in the general US population (Fig 4C). For the Chinese population, the overall prevalence of hypertension (23%) and diabetes (12%) in the COVID-19 patients were similar to that of the general Chinese population. However, the prevalence of smoking history (11%), COPD (4%), CKD (2%), and heart disease (16%) in the COVID-19 patients hospitalized in China were unexpectedly lower as compared to their corresponding prevalence in the general Chinese population (Fig 4D).

Sensitivity analyses

The positive associations of age≥65 years, male sex, smoking history, COPD, hypertension and diabetes with the risk of death in the COVID-19 patients were relatively homogenous (I2<70%). However, we carried out sensitivity analyses to assess the effects of outliers. For the risk of death for hypertension and smoking history, we removed the study by Yao et al. [86] which showed significantly higher risk compared to other studies; the results for both hypertension [sRR = 1.74; 95% CI: 1.58–1.94] and smoking [sRR:1.24; 95% CI: 1.08–1.42] remained significant. Guan et al. [13] had published a second study with additional patients and reported adjusted estimates for COPD, diabetes and hypertension. We used the adjusted risk estimates for the analyses. For the risk of death with other risk factors (CVD, CKD, and CLD) for Guan et al. [45], we conducted sensitivity analyses by using the counts only from the original study. The results [sRR (95% CI)] were similar as: CVD = 2.06 [95 CI: 1.80–2.36], CKD = 2.48 [95% CI: 2.09–2.94] and CLD = 2.67 [95% CI: 1.85–3.85].

Small study effects and quality assessment

We observed asymmetry in the funnel plot for studies that reported prevalence of death in COVID-19 patients (Egger’s test p = 0.001) (S1 Fig). On further analysis, the plot remained asymmetrical when restricted to studies from China (Egger’s p = 0.003) but was symmetrical for studies from US-Europe (Egger’s p = 0.160). We observed symmetrical funnel plots with no bias for pooled prevalence severe disease (Egger’s p = 0.128). On average, prospective or retrospective studies scored a score of 6 out of 9 and cross-sectional studies scored 6 out of 10. Many studies did not get a full score because they did not adjust for confounders (age, sex, or other risk factors) or patients remained hospitalized even after the follow-up ended, suggesting inadequate follow-up period (S4 Table).

Discussion

We carried out a comprehensive systematic review and meta-analysis of 77 studies that included 38906 hospitalized patients to investigate the prevalence and risk factors for death and severe disease in COVID-19 patients. We calculated an overall prevalence of death of 20% and severe disease of 28%. Nearly 50% of the patients admitted to hospitals due to COVID-19 were ≥60 years of age and 59% were males. We observed high prevalence of hypertension and diabetes of 50% and 28%, respectively, for the patients. The risk factors were more prevalent in patients who died and were distributed as: age ≥60 years: 85%; males: 66%; hypertension: 66%; diabetes: 39%; heart disease: 37%; CKD: 27%; smoking history: 44%; COPD: 12%, and CLD: 9%. In comparison with the overall prevalence of death of 20% for all COVID-19 hospitalized patients, the CFR was higher for male patients (26%) and for patients having the following risk factors: age≥60 years (35%), heart disease (52%), COPD (51%), CKD (48%), CLD (39%), hypertension (28%), diabetes (24%), and smoking history (27%). The elevation in the risk of death was statistically significant for age ≥60 (sRR = 3.6; 95% CI: 3.0–4.4), male sex 1.3 (95% CI: 1.2–1.4), smoking history (sRR = 1.3; 95% CI: 1.1–1.6), COPD (sRR = 1.7; 95% CI: 1.4–2.0), heart disease (sRR = 2.1; 95% CI: 1.8–2.4), CKD (sRR = 2.5; 95% CI: 2.1–3.0), hypertension (sRR = 1.8; 95% CI: 1.7–2.1), and diabetes (sRR = 1.5; 95% CI: 1.4–1.7). All of the risk factors we analyzed were positively associated with progression to severe disease as well. The results suggest that older age, male sex and the co-morbidities increase the risk of progression to severe disease and death in COVID-19 patients.

We observed significant difference in the prevalence of death between US-Europe (23%) and China (11%). This lower risk of death from COVID-19 for the hospitalized patients in China may be explained by the lower median age as well as lower prevalence of co-morbidities for COVID-19 patients in China. However, this >200% lower prevalence of death in China is incommensurate with our finding of a higher prevalence of severe disease observed for patients in China (39%) as compared to patients in the US-Europe (20%). Notably, we observed asymmetry in the funnel plot and a statistically significant tests for publication bias or small study effects for the prevalence of death for studies from China that could suggest selective outcome reporting. As such, while the lower median age and prevalence of co-morbidities for COVID-19 patients in China may explain the lower prevalence of death, it is also possible that a selective under-reporting of death had occurred for studies from China. The death toll in China was initially under-reported and later updated on April 17, 2020 [95].

Whether or not cigarette smoking has been associated with SARS-CoV-2 acquisition or progression to severe disease has been strongly debated with studies showing both positive, null, and inverse association between smoking and COVID-19 [10, 11, 9698]. We found that patients with any history of smoking have both a higher risk of death (RR: 1.28; 95% CI: 1.06–1.55) and severe disease (1.29; 95% CI: 1.18–1.42). The case fatality risk for those with smoking history (27%) was also higher than the overall CFR of 20%. Whereas a higher COVID-19 mortality and morbidity among smokers may be due its causal association with COPD and CVD, Cai et al. [99] has also observed upregulation of pulmonary Angiotensin Converting Enzyme 2 (ACE2) gene expression and hence, pulmonary ACE2 receptors in smokers suggesting a direct effect of smoking on COVID-19 susceptibility and disease progression. ACE2 receptors are used by SARS-CoV-2 to translocate intracellularly [15, 100104].

Our results of higher risk of death and severe disease associated with hypertension, diabetes and CVD in COVID-19 patients concurred with most studies conducted to date including studies that specifically investigated these associations [14, 65, 105, 106]. However, it is unclear if cardiovascular risk factors including smoking, hypertension, diabetes, heart disease and CKD increases the susceptibility toward SARS-CoV-2 infection in the population [15, 100, 101, 107]. On one hand, angiotensin-converting enzyme 2 (ACE2)–by blocking the renin angiotensin aldosterone system (RAAS) and decreasing or countering the vasoconstrictive, proinflammatory and profibrotic properties of angiotensin-II through catalysis of angiotensin-II to angiotensin-(1–7)–have been shown to exert cardiovascular protective effect and prevent acute lung injury from SARS-CoV-2 [15, 100, 101]. However, on the other hand, a possible greater expression of ACE2, the functional receptor mediating cellular entry of SARS-CoV-2 in humans, in patients with cardiovascular disease and other comorbidities can lead to increased susceptibility towards infection with SARS-CoV-2 [108, 109]. In this context, it would be reasonable to posit that a substantially higher prevalence of cardiovascular comorbidities in the hospitalized patients compared to the prevalence in the general population may suggest elevated risk of acquisition of SARS-CoV-2 for patients with cardiovascular risk factors. To this end, we found that the prevalence of smoking history (23%), hypertension (55%), diabetes (33%) and heart disease (17%) in the hospitalized COVID-19 patients in the US were substantially higher than the corresponding prevalence of smoking (14%) [110], hypertension (29%) [111], diabetes (13%) [112] and heart disease (9%) [113] in the general US population that could suggest an association between these comorbidities and risk of SARS-CoV-2 infection or disease progression. However, we note that if the prevalence of these comorbidities in the asymptomatic individuals with COVID-19 in the general population is similar to that of their prevalence in the non-COVID-19 general population, then this difference–the higher prevalence of comorbidities in the hospitalized patients compared to the general population–could simply imply a higher risk of symptomatic infection or hospitalization for individuals having SARS-CoV-2 infection. The prevalence of other risk factors i.e. COPD (9%) and CKD (15%) in the COVID-19 patients in the US was similar to the overall prevalence of COPD (7%) [114] and CKD (15%) [115] in the country. Generally, we noted a lower prevalence of comorbidities for patients in China. The prevalence of hypertension (23%) and diabetes (12%) in the hospitalized patients in China, which were lower than that of the US, approximate the respective prevalence of hypertension (23%) [116] and diabetes (15%) [117] in the general population of China. A previous meta-analysis also noted this observation [19]. Surprisingly, the prevalence of smoking (11%) in the COVID-19 patients hospitalized in China are inexplicably lower than the corresponding prevalence of smoking (23%) among COVID-19 patients in the US despite a higher prevalence of smoking (47% in Chinese males) [118] in the general Chinese population is significantly higher than that of the US. The prevalence of CVD (16%), COPD (4%) and CKD (2%) among COVID-19 patients in China are substantially lower than the corresponding prevalence of CVD (21%) [119], COPD (14%) [120], and CKD (11%) [121] in the general Chinese population. Given these discrepancies, we are unsure whether the lower prevalence of comorbidities noted for the COVID-19 patients in China are representative of the true prevalence. There was a great sense of urgency and a race to publish data in the early phase of the outbreak. As such, there exists the possibility of substantial under-recording of data on covariables. Had there been under-reporting, the implication would be a higher true prevalence estimate. We do not see reason for any systematic difference in reporting of risk factors based on outcome, or vice-versa, and hence, our summary relative risk estimates for association of risk factors with death or severe disease should not have been affected.

We assessed if patients with specific co-morbidities at baseline had higher risk of specific organ injury from SARS-CoV-2 during hospitalization. While the available data did not allow direct assessment of this relation, we compared the prevalence of comorbidities with the prevalence of corresponding organ system injury for studies that reported both baseline comorbidity and corresponding organ injury. We observed that the risk of acute lung injury/ARDS (48%), ACI (21%), and AKI (27%) were substantially higher than the baseline prevalence of COPD (6%), heart disease (11%) and CKD (14%), respectively. The higher prevalence of acute organ injury than the prevalence of baseline comorbidity simply indicates that ARDS, ACI and AKI were also occurring in patients who did not have a corresponding comorbidity at baseline in addition to people having the comorbidities.

Most studies reported only frequencies of risk factors and did not present adjusted measures for disease severity or death. Given this limitation, the risk ratio we calculated from the frequencies are largely unadjusted estimates. Future studies could additionally present, at the least, age- and sex-adjusted measures for association of risk of comorbidities with death or severe disease. Many studies reported odds ratio for the measure of association between pre-existing conditions and risk of severe disease or death. Odds ratio poorly approximates risk ratio when the disease prevalence is high at baseline. For example, Zhou et al. [14] calculated an odds ratio of 5.4 (95% CI: 0.96–30.4) for risk of death from COPD in COVID-19 patients whereas the risk ratio we calculated from the frequencies presented is RR = 2.47 (95% CI: 1.34–4.55). Prevalence of severe disease or death in COVID-19 patients was high in several studies. Similarly, several meta-analyses calculated odds ratios instead of risk ratios to summarize the risk of disease severity or death in association with risk factors such as smoking, diabetes, hypertension and cardiovascular disease [10, 11, 18], often to be interpreted by media and even by researchers as a measure of relative risk. Lack of rigor in research design, analysis and interpretation could generate inconsistent and ungeneralizable results across studies leading to controversy and confusion around serious public health issues such as that existing for association (or not) of smoking with COVID-19 disease acquisition, severity or death. As publications evolve at a pace that could be overwhelming for researchers and practitioners, we attempted to present a meaningful summary and inference for association of risk factors with death or severe disease from literatures published globally. Additionally, we provide an epidemiological framework for the risk of infection by SARS-CoV-2 based on presence of cardiovascular risk factors. This analysis can inform public health measures for COVID-19 screening and prevention, risk stratification and management of patients in clinical practice, analysis and presentation strategies for research data and inspire etiological investigations.

Conclusion

Epidemiological risk factors for progression of COVID-19 to severe disease and death and for acquisition of SARS-CoV-2, the causal agent for COVID-19, based on presence of pre-existing conditions have been insufficiently understood. Meta-analysis of 77 studies including 39023 COVID-19 patients hospitalized globally revealed case fatality risk of 52% for those having heart disease, 51% for COPD, 48% for CKD, 39% for CLD, 28% for hypertension, 27% for smoking history, 24% for diabetes, 35% for age≥60 years, and 26% for males. Of all the patients who died, an overwhelming majority (85%) were in people aged≥60 years. Also, of the people who died, 66% were males, 66% had hypertension, 44% had history of smoking, 39% had diabetes, 37% had CVD, 27% had CKD, and 6% had CLD. All of the above risk factors were significantly associated with death and severe disease in the patients hospitalized for COVID-19. The prevalence of ARDS was 48%, ACI 21%, and AKI 28% in the hospitalized patients. A higher prevalence of hypertension, diabetes, smoking and heart disease in the COVID-19 inpatients as compared to that of the general population could imply a higher risk of SARS-CoV-2 infection or disease progression for patients having these risk factors. These findings could inform public health strategies for targeted screening and appropriate control of modifiable risk factors such as smoking, hypertension, and diabetes to reduce morbidity and mortality. Finally, based on the published literature, there were vast differences in the prevalence of death and risk factors for the populations in China and in US-Europe that should be further investigated.

Supporting information

S1 Table. Prevalence of death, severe disease and risk factors in COVID-19 patients (December 2019-August 2020).

(DOCX)

S2 Table. Prevalence of death stratified by risk factors in COVID-19 patients (December 2019-August 2020).

(DOCX)

S3 Table. Prevalence of severe disease stratified by risk factors in COVID-19 patients (Dec 2019-August 2020).

(DOCX)

S4 Table. Newcastle-Ottawa quality assessment (modified) for studies#.

#Award of Points: Selection: points were awarded based on representativeness of the exposed group and unexposed group (2 points), ascertainment of exposures (1 point), and demonstration that outcome of interest was not present at the start of the study (1 point). Comparability (2 points): points were awarded based on whether the analyses were adjusted for age, sex, and other risk factors (2 points for adjustment to age and sex). Outcome (3points): points were awarded based on ascertainment of outcome through record linkage or independent blind assessment (1 points); duration of follow-up (1 point) (hospitalization till discharge); and adequacy of follow up for study population (complete follow up for the patients (vs whether patients were currently under treatment at the time of study report) (1 point), or if the patients currently under admission are excluded from outcome assessment (1 point).

(DOCX)

S1 Fig. Publication bias or small study effects for prevalence of death and severe disease.

(TIF)

S1 Checklist. PRISMA 2009 checklist.

(DOC)

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

Dr. Dorjee is supported by grants from the US National Institute of Allergy and Infectious Diseases of the National Institute of Health (Grant # K01AI148583); Johns Hopkins Alliance for a Healthier World (Grant # 80045453); STOP TB PARTNERSHIP TB REACH (Grant # 134126); the Pittsfield Anti-TB Association and dedicated private philanthropists.

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Decision Letter 0

Davide Bolignano

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

21 Aug 2020

PONE-D-20-19976

Epidemiological Risk Factors Associated with Death and Severe Disease in Patients Suffering From COVID-19: A Comprehensive Systematic Review and Meta-analysis

PLOS ONE

Dear Dr. Dorjee,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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We look forward to receiving your revised manuscript.

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Davide Bolignano, MD, PhD

Academic Editor

PLOS ONE

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'Funding: Dr. Dorjee is supported by grants from private philanthropists; the Johns Hopkins Alliance for Healthier World (Grant # 80045453); National Institute of Allergy and Infectious Diseases of the National Institute of Health (Grant # K01AI148583); the United Nations STOP TB PARTNERSHIP TB REACH (Grant # 134126); and the Pittsfield Anti-tuberculosis Association (PATA).'

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors showed results from systematic literature review regarding SARS-C0-V2 and outcomes.

They used PRISMa methodology; the article is presented in an intelligible fashion and is written in standard English.

In general the manuscript has typical content as for review with accepted style. My points are listed below. Conclusions and limitations are acceptable.

-some typhos exist needing correction: e.g. once angiotensin begins with capital letter other time with small letter

- citations are missing journel pages, for the instance ref.6, 7.

Reviewer #2: In this manuscript the Authors present the results of a fixed- effects meta-analysis designed to investigate the association between clinical/epidemiological risk factors and progression to death in patients hospitalized due to COVID-19. A total of 44 studies were included in the analysis, comprising 20594 hospitalized patients mainly from China and US and small cohorts from Italy, UK, Iran and Singapore. Despite the heterogeneity of the studies and the lack of adjusted measures for disease severity or death, the rationale behind the study is interesting and overall the paper is original and well written. The comparison between the prevalence of comorbidities/risk factors in hospitalized COVID-19 patients and in the general population is well summarized.

We feel that the Authors should blunt the link with cardiovascular diseases as the statement “…suggesting either a tendency for SARS-CoV-2 to more effectively establish infection in cardiovascular patients or to cause more severe disease among them prompting hospitalization” (page 20) does not seem quite convincing. This also suggests that the Discussion should better elaborate on the proportion of asymptomatic individuals and the interactions of comorbidities.

**********

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Reviewer #1: Yes: Mariusz Kusztal

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Dec 7;15(12):e0243191. doi: 10.1371/journal.pone.0243191.r002

Author response to Decision Letter 0


13 Oct 2020

A letter with detailed response to the feedback from editors and revised are being submitted herewith this submission.

Attachment

Submitted filename: Response_To_Reviewers.docx

Decision Letter 1

Davide Bolignano

30 Oct 2020

PONE-D-20-19976R1

Prevalence and Predictors of Death and Severe Disease in Patients Hospitalized Due To COVID-19: A Comprehensive Systematic Review and Meta-analysis of 77 Studies and 38,000 patients.

PLOS ONE

Dear Dr. Dorjee,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 14 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Davide Bolignano, MD, PhD

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors responded to all queries sufficiently. In recent version it is publishable in PLOS one.

Reviewer #2: In this Manuscript the Authors present a Systematic Review and Meta-analysis of prevalence and predictors of death and severe disease in patients hospitalized due to COVID-19. They performed a fixed-effects meta-analysis using Shore’s adjusted confidence intervals to address heterogeneity. The paper is technically sound, well presented and adequately discussed.

Occasional formatting errors should be fixed.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Decision Letter 2

Davide Bolignano

18 Nov 2020

Prevalence and Predictors of Death and Severe Disease in Patients Hospitalized Due To COVID-19: A Comprehensive Systematic Review and Meta-analysis of 77 Studies and 38,000 patients.

PONE-D-20-19976R2

Dear Dr. Dorjee,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Davide Bolignano, MD, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: In my opinion all suggestions regarding manuscript improvement has been adressed. The paper in the current form can be published

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Acceptance letter

Davide Bolignano

24 Nov 2020

PONE-D-20-19976R2

Prevalence and Predictors of Death and Severe Disease in Patients Hospitalized Due To COVID-19: A Comprehensive Systematic Review and Meta-analysis of 77 Studies and 38,000 patients.

Dear Dr. Dorjee:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Davide Bolignano

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Prevalence of death, severe disease and risk factors in COVID-19 patients (December 2019-August 2020).

    (DOCX)

    S2 Table. Prevalence of death stratified by risk factors in COVID-19 patients (December 2019-August 2020).

    (DOCX)

    S3 Table. Prevalence of severe disease stratified by risk factors in COVID-19 patients (Dec 2019-August 2020).

    (DOCX)

    S4 Table. Newcastle-Ottawa quality assessment (modified) for studies#.

    #Award of Points: Selection: points were awarded based on representativeness of the exposed group and unexposed group (2 points), ascertainment of exposures (1 point), and demonstration that outcome of interest was not present at the start of the study (1 point). Comparability (2 points): points were awarded based on whether the analyses were adjusted for age, sex, and other risk factors (2 points for adjustment to age and sex). Outcome (3points): points were awarded based on ascertainment of outcome through record linkage or independent blind assessment (1 points); duration of follow-up (1 point) (hospitalization till discharge); and adequacy of follow up for study population (complete follow up for the patients (vs whether patients were currently under treatment at the time of study report) (1 point), or if the patients currently under admission are excluded from outcome assessment (1 point).

    (DOCX)

    S1 Fig. Publication bias or small study effects for prevalence of death and severe disease.

    (TIF)

    S1 Checklist. PRISMA 2009 checklist.

    (DOC)

    Attachment

    Submitted filename: Response_To_Reviewers.docx

    Attachment

    Submitted filename: Response_To_Reviewers.docx

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting information files.


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