Dataset Information

Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis.

ABSTRACT:

Introduction

Although severe acute respiratory syndrome coronavirus-2 infection is causing mortality in considerable proportion of coronavirus disease-2019 (COVID-19) patients, however, evidence for the association of sex, age, and comorbidities on the risk of mortality is not well-aggregated yet. It was aimed to assess the association of sex, age, and comorbidities with mortality in COVID-2019 patients.

Methods

Literatures were searched using different keywords in various databases. Relative risks (RRs) were calculated by RevMan software where statistical significance was set as p < 0.05.

Results

COVID-19 male patients were associated with significantly increased risk of mortality compared to females (RR 1.86: 95% confidence interval [CI] 1.67-2.07; p < 0.00001). Patients with age ?50 years were associated with 15.4-folds significantly increased risk of mortality compared to patients with age <50 years (RR 15.44: 95% CI 13.02-18.31; p < 0.00001). Comorbidities were also associated with significantly increased risk of mortality; kidney disease (RR 4.90: 95% CI 3.04-7.88; p < 0.00001), cereborovascular disease (RR 4.78; 95% CI 3.39-6.76; p < 0.00001), cardiovascular disease (RR 3.05: 95% CI 2.20-4.25; p < 0.00001), respiratory disease (RR 2.74: 95% CI 2.04-3.67; p < 0.00001), diabetes (RR 1.97: 95% CI 1.48-2.64; p < 0.00001), hypertension (RR 1.95: 95% CI 1.58-2.40; p < 0.00001), and cancer (RR 1.89; 95% CI 1.25-2.84; p = 0.002) but not liver disease (RR 1.64: 95% CI 0.82-3.28; p= 0.16).

Conclusion

Implementation of adequate protection and interventions for COVID-19 patients in general and in particular male patients with age ?50 years having comorbidities may significantly reduce risk of mortality associated with COVID-19.

SUBMITTER: Biswas M

PROVIDER: S-EPMC7801974 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis.

Biswas Mohitosh M Rahaman Shawonur S Biswas Tapash Kumar TK Haque Zahirul Z Ibrahim Baharudin B

Intervirology 20201209

<h4>Introduction</h4>Although severe acute respiratory syndrome coronavirus-2 infection is causing mortality in considerable proportion of coronavirus disease-2019 (COVID-19) patients, however, evidence for the association of sex, age, and comorbidities on the risk of mortality is not well-aggregated yet. It was aimed to assess the association of sex, age, and comorbidities with mortality in COVID-2019 patients.<h4>Methods</h4>Literatures were searched using different keywords in various databas ...[more]

PMID: 33296901

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Project description:BackgroundEstimating the risk of pre-existing comorbidities on coronavirus disease 2019 (COVID-19) mortality may promote the importance of targeting populations at risk to improve survival. This systematic review and meta-analysis aimed to estimate the association of pre-existing comorbidities with COVID-19 mortality.MethodsWe searched MEDLINE, SCOPUS, OVID, and Cochrane Library databases, and medrxiv.org from December 1st, 2019, to July 9th, 2020. The outcome of interest was the risk of COVID-19 mortality in patients with and without pre-existing comorbidities. We analyzed 11 comorbidities: cardiovascular diseases, hypertension, diabetes, congestive heart failure, cerebrovascular disease, chronic kidney disease, chronic liver disease, cancer, chronic obstructive pulmonary disease, asthma, and HIV/AIDS. Two reviewers independently extracted data and assessed the risk of bias. All analyses were performed using random-effects models and heterogeneity was quantified.ResultsEleven pre-existing comorbidities from 25 studies were included in the meta-analysis (n = 65, 484 patients with COVID-19; mean age; 61 years; 57% male). Overall, the between-study heterogeneity was medium, and studies had low publication bias and high quality. Cardiovascular disease (risk ratio (RR) 2.25, 95% CI = 1.60-3.17, number of studies (n) = 14), hypertension (1.82 [1.43 to 2.32], n = 13), diabetes (1.48 [1.02 to 2.15], n = 16), congestive heart failure (2.03 [1.28 to 3.21], n = 3), chronic kidney disease (3.25 [1.13 to 9.28)], n = 9) and cancer (1.47 [1.01 to 2.14), n = 10) were associated with a significantly greater risk of mortality from COVID-19.ConclusionsPatients with COVID-19 with cardiovascular disease, hypertension, diabetes, congestive heart failure, chronic kidney disease and cancer have a greater risk of mortality compared to patients with COVID-19 without these comorbidities. Tailored infection prevention and treatment strategies targeting this high-risk population might improve survival.

Project description:A COVID-19 patient often presents with multiple comorbidities and is associated with adverse outcomes. A comprehensive assessment of the prevalence of comorbidities in patients with COVID-19 is essential. This study aimed to assess the prevalence of comorbidities, severity and mortality with regard to geographic region, age, gender and smoking status in patients with COVID-19. A systematic review and multistage meta-analyses were reported using PRISMA guidelines. PubMed/MEDLINE, SCOPUS, Google Scholar and EMBASE were searched from January 2020 to October 2022. Cross-sectional studies, cohort studies, case series studies, and case-control studies on comorbidities reporting among the COVID-19 populations that were published in English were included. The pooled prevalence of various medical conditions in COVID-19 patients was calculated based on regional population size weights. Stratified analyses were performed to understand the variations in the medical conditions based on age, gender, and geographic region. A total of 190 studies comprising 105 million COVID-19 patients were included. Statistical analyses were performed using STATA software, version 16 MP (StataCorp, College Station, TX). Meta-analysis of proportion was performed to obtain pooled values of the prevalence of medical comorbidities: hypertension (39%, 95% CI 36-42, n = 170 studies), obesity (27%, 95% CI 25-30%, n = 169 studies), diabetes (27%, 95% CI 25-30%, n = 175), and asthma (8%, 95% CI 7-9%, n = 112). Moreover, the prevalence of hospitalization was 35% (95% CI 29-41%, n = 61), intensive care admissions 17% (95% CI 14-21, n = 106), and mortality 18% (95% CI 16-21%, n = 145). The prevalence of hypertension was highest in Europe at 44% (95% CI 39-47%, n = 68), obesity and diabetes at 30% (95% CI, 26-34, n = 79) and 27% (95%CI, 24-30, n = 80) in North America, and asthma in Europe at 9% (95% CI 8-11, n = 41). Obesity was high among the ≥ 50 years (30%, n = 112) age group, diabetes among Men (26%, n = 124) and observational studies reported higher mortality than case-control studies (19% vs. 14%). Random effects meta-regression found a significant association between age and diabetes (p < 0.001), hypertension (p < 0.001), asthma (p < 0.05), ICU admission (p < 0.05) and mortality (p < 0.001). Overall, a higher global prevalence of hypertension (39%) and a lower prevalence of asthma (8%), and 18% of mortality were found in patients with COVID-19. Hence, geographical regions with respective chronic medical comorbidities should accelerate regular booster dose vaccination, preferably to those patients with chronic comorbidities, to prevent and lower the severity and mortality of COVID-19 disease with novel SARS-CoV-2 variants of concern (VOC).

Project description:ObjectiveRisk factors for in-hospital mortality in confirmed COVID-19 patients have been summarized in numerous meta-analyses, but it is still unclear whether they vary according to the age, sex and health conditions of the studied populations. This study explored these variables as potential mortality predictors.MethodsA systematic review was conducted by searching the MEDLINE, Scopus, and Web of Science databases of studies available through July 27, 2020. The pooled risk was estimated with the odds ratio (p-OR) or effect size (p-ES) obtained through random-effects meta-analyses. Subgroup analyses and meta-regression were applied to explore differences by age, sex and health conditions. The MOOSE guidelines were strictly followed.ResultsThe meta-analysis included 60 studies, with a total of 51,225 patients (12,458 [24.3%] deaths) from hospitals in 13 countries. A higher in-hospital mortality risk was found for dyspnoea (p-OR = 2.5), smoking (p-OR = 1.6) and several comorbidities (p-OR range: 1.8 to 4.7) and laboratory parameters (p-ES range: 0.3 to -2.6). Age was the main source of heterogeneity, followed by sex and health condition. The following predictors were more markedly associated with mortality in studies with patients with a mean age ≤60 years: dyspnoea (p-OR = 4.3), smoking (p-OR = 2.8), kidney disease (p-OR = 3.8), hypertension (p-OR = 3.7), malignancy (p-OR = 3.7), diabetes (p-OR = 3.2), pulmonary disease (p-OR = 3.1), decreased platelet count (p-ES = -1.7), decreased haemoglobin concentration (p-ES = -0.6), increased creatinine (p-ES = 2.4), increased interleukin-6 (p-ES = 2.4) and increased cardiac troponin I (p-ES = 0.7). On the other hand, in addition to comorbidities, the most important mortality predictors in studies with older patients were albumin (p-ES = -3.1), total bilirubin (p-ES = 0.7), AST (p-ES = 1.8), ALT (p-ES = 0.4), urea nitrogen (p-ES), C-reactive protein (p-ES = 2.7), LDH (p-ES = 2.4) and ferritin (p-ES = 1.7). Obesity was associated with increased mortality only in studies with fewer chronic or critical patients (p-OR = 1.8).ConclusionThe prognostic effect of clinical conditions on COVID-19 mortality vary substantially according to the mean age of patients.Prospero registration numberCRD42020176595.

Project description:BackgroundComprehensive evidence synthesis on the associations between comorbidities and behavioural factors with hospitalisation, intensive care unit (ICU) admission, and death due to COVID-19 is required for deriving national and international recommendations on primary targets for non-pharmacological interventions (NPI) and vaccination strategies.MethodsWe performed a rapid systematic review and meta-analysis on studies and publicly accessible data to quantify associations between predisposing health conditions, demographics, behavioural factors on the one hand and hospitalisation, ICU admission, and death from COVID-19 on the other hand. We provide ranges of reported and calculated effect estimates and pooled relative risks derived from a meta-analysis and meta-regression.ResultsSeventy-five studies were included in qualitative and 74 in quantitative synthesis, with study populations ranging from 19 to 44,672 COVID-19 cases. The risk of dying from COVID-19 was significantly associated with cerebrovascular [pooled relative risk (RR) 2.7 (95% CI 1.7-4.1)] and cardiovascular [RR 3.2 (CI 2.3-4.5)] diseases, hypertension [RR 2.6 (CI 2.0-3.4)], and renal disease [RR 2.5 (CI 1.8-3.4)], with high heterogeneity in pooled estimates, partly but not solely explained by age of study participants. For some comorbidities, our meta-regression showed a decrease in effect on the severity of disease with a higher median age of the study population. Compared to death, associations between several comorbidities and hospitalisation and ICU admission were less pronounced.ConclusionsWe obtained robust estimates on the magnitude of risk for COVID-19 hospitalisation, ICU admission, and death associated with comorbidities, demographic, and behavioural risk factors and show that these estimates are modified by age of study participants. This interaction is an important finding to be kept in mind for current vaccination strategies and for the protection of individuals with high risk for a severe COVID-19 course.

Project description:Several comorbidities have been shown to be associated with coronavirus disease 2019 (COVID-19) related severity and mortality. However, considerable variation in the prevalence estimates of comorbidities and their effects on COVID-19 morbidity and mortality have been observed in prior studies. This systematic review and meta-analysis aimed to determine geographical, age, and gender related differences in the prevalence of comorbidities and associated severity and mortality rates among COVID-19 patients. We conducted a search using PubMed, Scopus, and EMBASE to include all COVID-19 studies published between January 1st, 2020 to July 24th, 2020 reporting comorbidities with severity or mortality. We included studies reporting the confirmed diagnosis of COVID-19 on human patients that also provided information on comorbidities or disease outcomes. We used DerSimonian and Laird random effects method for calculating estimates. Of 120 studies with 125,446 patients, the most prevalent comorbidity was hypertension (32%), obesity (25%), diabetes (18%), and cardiovascular disease (16%) while chronic kidney or other renal diseases (51%, 44%), cerebrovascular accident (43%, 44%), and cardiovascular disease (44%, 40%) patients had more COVID-19 severity and mortality respectively. Considerable variation in the prevalence of comorbidities and associated disease severity and mortality in different geographic regions was observed. The highest mortality was observed in studies with Latin American and European patients with any medical condition, mostly older adults (≥ 65 years), and predominantly male patients. Although the US studies observed the highest prevalence of comorbidities in COVID-19 patients, the severity of COVID-19 among each comorbid condition was highest in Asian studies whereas the mortality was highest in the European and Latin American countries. Risk stratification and effective control strategies for the COVID-19 should be done according to comorbidities, age, and gender differences specific to geographical location.

Dataset Information

Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis.

Introduction

Methods

Results

Conclusion

Publications

Association of Sex, Age, and Comorbidities with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis.

Similar Datasets

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