Clinical determinants of the severity of COVID-19: A systematic review and meta-analysis.
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ABSTRACT: Objective
We aimed to systematically identify the possible risk factors responsible for severe cases.Methods
We searched PubMed, Embase, Web of science and Cochrane Library for epidemiological studies of confirmed COVID-19, which include information about clinical characteristics and severity of patients' disease. We analyzed the potential associations between clinical characteristics and severe cases.Results
We identified a total of 41 eligible studies including 21060 patients with COVID-19. Severe cases were potentially associated with advanced age (Standard Mean Difference (SMD) = 1.73, 95% CI: 1.34-2.12), male gender (Odds Ratio (OR) = 1.51, 95% CI:1.33-1.71), obesity (OR = 1.89, 95% CI: 1.44-2.46), history of smoking (OR = 1.40, 95% CI:1.06-1.85), hypertension (OR = 2.42, 95% CI: 2.03-2.88), diabetes (OR = 2.40, 95% CI: 1.98-2.91), coronary heart disease (OR: 2.87, 95% CI: 2.22-3.71), chronic kidney disease (CKD) (OR = 2.97, 95% CI: 1.63-5.41), cerebrovascular disease (OR = 2.47, 95% CI: 1.54-3.97), chronic obstructive pulmonary disease (COPD) (OR = 2.88, 95% CI: 1.89-4.38), malignancy (OR = 2.60, 95% CI: 2.00-3.40), and chronic liver disease (OR = 1.51, 95% CI: 1.06-2.17). Acute respiratory distress syndrome (ARDS) (OR = 39.59, 95% CI: 19.99-78.41), shock (OR = 21.50, 95% CI: 10.49-44.06) and acute kidney injury (AKI) (OR = 8.84, 95% CI: 4.34-18.00) were most likely to prevent recovery. In summary, patients with severe conditions had a higher rate of comorbidities and complications than patients with non-severe conditions.Conclusion
Patients who were male, with advanced age, obesity, a history of smoking, hypertension, diabetes, malignancy, coronary heart disease, hypertension, chronic liver disease, COPD, or CKD are more likely to develop severe COVID-19 symptoms. ARDS, shock and AKI were thought to be the main hinderances to recovery.
SUBMITTER: Li X
PROVIDER: S-EPMC8092779 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundA systematic review and meta-analysis of available studies was performed to investigate the clinical characteristics that can predict COVID-19 disease severity.Materials and methodsDatabases including PubMed, Embase, and Web of Science were searched from December 31, 2019, to May 24, 2020. Random-effects meta-analysis was used for summarizing the Pooled odds ratio (pOR) of individual clinical characteristics to describe their association with severe COVID-19 disease.ResultsA total of 3895 articles were identified, and finally, 22 studies comprising 4380 patients were included. Severe disease was more common in males than females (pOR: 1.36, 95% confidence interval [CI]: 1.08-1.70). Clinical features that were associated with significantly higher odds of severe disease were abdominal pain (pOR: 6.58, 95% CI: 1.56-27.67), breathlessness (pOR: 3.94, 95% CI: 2.55-6.07), and hemoptysis (pOR: 3.35, 95% CI: 1.05-10.74). pOR was highest for chronic obstructive pulmonary disease (pOR: 2.92, 95% CI: 1.70-5.02), followed by obesity (pOR: 2.84, 95% CI: 1.19-6.77), malignancy (pOR: 2.38, 95% CI: 1.25-4.52), diabetes (pOR: 2.29, 95% CI: 1.56-3.39), hypertension (pOR: 1.72, 95% CI: 1.23-2.42), cardiovascular disease (pOR: 1.61, 95% CI: 1.31-1.98) and chronic kidney disease (pOR: 1.46, 95% CI: 1.06-2.02), for predicting severe COVID-19.ConclusionOur analysis describes the association of specific symptoms and comorbidities with severe COVID-19 disease. Knowledge of these clinical determinants will assist the clinicians in the risk-stratification of these patients for better triage and clinical management.
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Project description:Background:Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SAR2-COV-2) and was first identified in Wuhan, China, in December of 2019, but quickly spread to the rest of the world, causing a pandemic. While some studies have found no link between smoking status and severe COVID-19, others demonstrated a significant one. The present study aimed to determine the relationship between smoking and clinical COVID-19 severity via a systematic meta-analysis approach. Methods:We searched the Google Scholar, PubMed, Scopus, Web of Science, and Embase databases to identify clinical studies suitable for inclusion in this meta-analysis. Studies reporting smoking status and comparing nonsevere and severe patients were included. Nonsevere cases were described as mild, common type, nonintensive care unit (ICU) treatment, survivors, and severe cases as critical, need for ICU, refractory, and nonsurvivors. Results:A total of 16 articles detailing 11322 COVID-19 patients were included. Our meta-analysis revealed a relationship between a history of smoking and severe COVID-19 cases (OR = 2.17; 95% CI: 1.37-3.46; P < .001). Additionally, we found an association between the current smoking status and severe COVID-19 (OR = 1.51; 95% CI: 1.12-2.05; P < .008). In 10.7% (978/9067) of nonsmokers, COVID-19 was severe, while in active smokers, severe COVID-19 occurred in 21.2% (65/305) of cases. Conclusion:Active smoking and a history of smoking are clearly associated with severe COVID-19. The SARS-COV-2 epidemic should serve as an impetus for patients and those at risk to maintain good health practices and discontinue smoking. The trial is registered with the International Prospective Register of Systematic Reviews (PROSPERO) CRD42020180173.
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Project description:BackgroundCOVID-19 has spread widely worldwide, causing millions of deaths. We aim to explore the association of immunological features with COVID-19 severity.MethodsWe conducted a meta-analysis to estimate mean difference (MD) of immune cells and cytokines levels with COVID-19 severity in PubMed, Web of Science, Scopus, the Cochrane Library and the grey literature.ResultsA total of 21 studies with 2033 COVID-19 patients were included. Compared with mild cases, severe cases showed significantly lower levels of immune cells including CD3+ T cell (× 106, MD, - 413.87; 95%CI, - 611.39 to - 216.34), CD4+ T cell (× 106, MD, - 203.56; 95%CI, - 277.94 to - 129.18), CD8+ T cell (× 106, MD, - 128.88; 95%CI, - 163.97 to - 93.79), B cell (× 106/L; MD, - 23.87; 95%CI, - 43.97 to - 3.78) and NK cell (× 106/L; MD, - 57.12; 95%CI, - 81.18 to - 33.06), and significantly higher levels of cytokines including TNF-α (pg/ml; MD, 0.34; 95%CI, 0.09 to 0.59), IL-5 (pg/ml; MD, 14.2; 95%CI, 3.99 to 24.4), IL-6 (pg/ml; MD, 13.07; 95%CI, 9.80 to 16.35), and IL-10 (pg/ml; MD, 2.04; 95%CI, 1.32 to 2.75), and significantly higher levels of chemokines as MCP-1 (SMD, 3.41; 95%CI, 2.42 to 4.40), IP-10 (SMD, 2.82; 95%CI, 1.20 to 4.45) and eotaxin (SMD, 1.55; 95%CI, 0.05 to 3.05). However, no significant difference was found in other indicators such as Treg cell (× 106, MD, - 0.13; 95%CI, - 1.40 to 1.14), CD4+/CD8+ ratio (MD, 0.26; 95%CI, - 0.02 to 0.55), IFN-γ (pg/ml; MD, 0.26; 95%CI, - 0.05 to 0.56), IL-2 (pg/ml; MD, 0.05; 95%CI, - 0.49 to 0.60), IL-4 (pg/ml; MD, - 0.03; 95%CI, - 0.68 to 0.62), GM-CSF (SMD, 0.44; 95%CI, - 0.46 to 1.35), and RANTES (SMD, 0.94; 95%CI, - 2.88 to 4.75).ConclusionOur meta-analysis revealed significantly lower levels of immune cells (CD3+ T, CD4+ T, CD8+ T, B and NK cells), higher levels of cytokines (TNF-α, IL-5, IL-6 and IL-10) and higher levels of chemokines (MCP-1, IP-10 and eotaxin) in severe cases in comparison to mild cases of COVID-19. Measurement of immunological features could help assess disease severity for effective triage of COVID-19 patients.
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Project description:Various comorbidities represent risk factors for severe coronavirus disease 2019 (COVID-19). The impact of smoking on COVID-19 severity has been previously reported in several meta-analyses limited by small sample sizes and poor methodology. We aimed to rigorously and definitively quantify the effects of smoking on COVID-19 severity. MEDLINE, Embase, CENTRAL, and Web of Science were searched between 1 December 2019 and 2 June 2020. Studies reporting smoking status of hospitalized patients with different severities of disease and/or at least one clinical endpoint of interest (disease progression, intensive care unit admission, need for mechanical ventilation, and mortality) were included. Data were pooled using a random-effects model. This study was registered on PROSPERO: CRD42020180920. We analyzed 47 eligible studies reporting on 32 849 hospitalized COVID-19 patients, with 8417 (25.6%) reporting a smoking history, comprising 1501 current smokers, 5676 former smokers, and 1240 unspecified smokers. Current smokers had an increased risk of severe COVID-19 (risk ratios [RR]: 1.80; 95% confidence interval [CI]: 1.14-2.85; P = .012), and severe or critical COVID-19 (RR: 1.98; CI: 1.16-3.38; P = .012). Patients with a smoking history had a significantly increased risk of severe COVID-19 (RR: 1.31; CI: 1.12-1.54; P = .001), severe or critical COVID-19 (RR: 1.35; CI: 1.19-1.53; P < .0001), in-hospital mortality (RR: 1.26; CI: 1.20-1.32; P < .0001), disease progression (RR: 2.18; CI: 1.06-4.49; P = .035), and need for mechanical ventilation (RR: 1.20; CI: 1.01-1.42; P = .043). Patients with any smoking history are vulnerable to severe COVID-19 and worse in-hospital outcomes. In the absence of current targeted therapies, preventative, and supportive strategies to reduce morbidity and mortality in current and former smokers are crucial.
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Project description:BackgroundVaccination is the promising strategy to control the coronavirus disease 2019 (COVID-19) pandemic. However, the success of this strategy will rely mainly on the rate of vaccine acceptance among the general population. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of COVID-19 vaccine acceptance and its determinants in Ethiopia.MethodsWe searched PubMed, Scopus, Google Scholar, African Journals Online, and Web of Sciences database to retrieve related articles. Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines were used for this study. Funnel plot and Eggers test were done to assess publication bias. Cochrane Q-test and I2 statistic were done to chick evidence of heterogeneity. Subgroup analysis was computed based on the study region and the study population. Data were extracted using a Microsoft Excel spreadsheet and analyzed using STATA version 14 statistical software. Weighted inverse variance random effect model was run to estimate the pooled prevalence of COVID-19 vaccine acceptance.ResultsA total of 12 studies with 5,029 study participants were included. The pooled prevalence of COVID-19 vaccine acceptance in Ethiopia was 51.64% (95%CI; 43.95%-59.34%). Being male (AOR = 4.46, 1.19-16.77, I2 = 88%), having secondary and above educational status (AOR = 3.97, 1.94-8.12, I2 = 69%), good knowledge (AOR = 3.36, 1.71-6.61, I2 = 93%), and positive attitude (AOR = 5.40, 2.43-12.00, I2 = 87%) were determinants of COVID-19 vaccine acceptance in Ethiopia.ConclusionThe pooled prevalence of COVID-19 vaccine acceptance was low. Being male, having secondary and above educational status, good knowledge, and positive attitude were the determinants of COVID-19 vaccine acceptance. High level of COVID-19 vaccine acceptance among the general population is crucial to achieve herd immunity in the community. Therefore, policymakers, vaccine campaign program planners, and stakeholders should target to improve public awareness of vaccination that enhances vaccine acceptance and in turn helps to control the pandemic.
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Project description:BackgroundWhile the risk of severe complications of Middle East respiratory syndrome (MERS) and its determinants have been explored in previous studies, a systematic analysis of published articles with different designs and populations has yet to be conducted. The present study aimed to systematically review the risk of death associated with MERS as well as risk factors for associated complications.MethodsPubMed and Web of Science databases were searched for clinical and epidemiological studies on confirmed cases of MERS. Eligible articles reported clinical outcomes, especially severe complications or death associated with MERS. Risks of admission to intensive care unit (ICU), mechanical ventilation and death were estimated. Subsequently, potential associations between MERS-associated death and age, sex, underlying medical conditions and study design were explored.ResultsA total of 25 eligible articles were identified. The case fatality risk ranged from 14.5 to 100%, with the pooled estimate at 39.1%. The risks of ICU admission and mechanical ventilation ranged from 44.4 to 100% and from 25.0 to 100%, with pooled estimates at 78.2 and 73.0%, respectively. These risks showed a substantial heterogeneity among the identified studies, and appeared to be the highest in case studies focusing on ICU cases. We identified older age, male sex and underlying medical conditions, including diabetes mellitus, renal disease, respiratory disease, heart disease and hypertension, as clinical predictors of death associated with MERS. In ICU case studies, the expected odds ratios (OR) of death among patients with underlying heart disease or renal disease to patients without such comorbidities were 0.6 (95% Confidence Interval (CI): 0.1, 4.3) and 0.6 (95% CI: 0.0, 2.1), respectively, while the ORs were 3.8 (95% CI: 3.4, 4.2) and 2.4 (95% CI: 2.0, 2.9), respectively, in studies with other types of designs.ConclusionsThe heterogeneity for the risk of death and severe manifestations was substantially high among the studies, and varying study designs was one of the underlying reasons for this heterogeneity. A statistical estimation of the risk of MERS death and identification of risk factors must be conducted, particularly considering the study design and potential biases associated with case detection and diagnosis.
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