SynthesisGlobal heart2020
The Relationship of COVID-19 Severity with Cardiovascular Disease and Its Traditional Risk Factors: A Systematic Review and Meta-Analysis.
Synthesis in Global heart, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers, 9 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
102 citing papers in PubMed, 9 syntheses or guidelines pooled it, 164 citations in OpenAlex.
- Pooled it
- Adjunctive therapy with lipid-lowering agents in COVID-19: a systematic review and meta-analysis of randomized controlled trials.Lipids in health and disease · 2023Pooled it
- Pre-existing health conditions and severe COVID-19 outcomes: an umbrella review approach and meta-analysis of global evidence.BMC medicine · 2021Pooled it
- Cardiovascular risk factors, cardiovascular disease, and COVID-19: an umbrella review of systematic reviews.European heart journal. Quality of care & clinical outcomes · 2021Pooled it
- Covid-19 and non-communicable diseases: evidence from a systematic literature review.BMC public health · 2021Pooled it
- ACC Health Policy Statement on Cardiovascular Disease Considerations for COVID-19 Vaccine Prioritization: A Report of the American College of Cardiology Solution Set Oversight Committee.Journal of the American College of Cardiology · 2021Guideline
- The potential association between common comorbidities and severity and mortality of coronavirus disease 2019: A pooled analysis.Clinical cardiology · 2020Pooled it
- Pooled it
- Polypharmacy among COVID-19 patients: A systematic review.Journal of the American Pharmacists Association : JAPhAPooled it
- COVID-19 mortality in patients on anticoagulants and antiplatelet agents.British journal of haematology · 2020Trial
- Life's Essential 8 and Risk of Severe COVID-19 Among Adults Without Clinical Cardiovascular Disease: The C4R Study.Journal of the American Heart Association · 2026Article
- Analysis of an AI-powered system for vaccination screening, monitoring, and management in adults aged 50 and above.Frontiers in public health · 2026Article
- A narrative review of heterogeneity in SARS-CoV-2 infection outcomes and vaccine efficacy: strategizing pandemic preparedness in Africa.Frontiers in public health · 2026Review
- Machine learning identifies clinical and sociodemographic factors contributing to post-COVID hospitalization and cardiovascular risk in patients with peripheral artery disease.Scientific reports · 2025Article
- A Retrospective Observational Study on COVID-19 Patients Receiving Treatment with Nirmatrelvir/Ritonavir (PAXLOVID).Pulmonary therapy · 2025Article
- Consideration of Cardiovascular Morbidities in the Relationship between Ambient Air Pollution Exposure and Individual-Level Adverse COVID-19 Outcomes: A Systematic Review.Current epidemiology reports · 2025Article
- Risk factors for disease progression and clinical outcomes in patients with COVID-19 in Taiwan: a nationwide population-based cohort study.BMC pulmonary medicine · 2025Article
- Retrospective analysis of risk factors associated with mortality in hospitalized COVID-19 patients.Journal of family medicine and primary care · 2024Article
- Intelligent cardiovascular disease diagnosis using deep learning enhanced neural network with ant colony optimization.Scientific reports · 2024Article
- Cardiovascular risk and the COVID-19 pandemic: a population-based and case‒control studies.Population health metrics · 2024Article
42 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex.
methodsWe performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data (≥10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses.
resultsOf the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >~5 in >60-65 versus <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR = 1.73, [95% CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ~2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19.
conclusionsDespite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be informative for predicting the risk of severe COVID-19.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.