ArticleArchives of cardiovascular diseases
Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings?
Article in Archives of cardiovascular diseases. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Myocardial Injury and Predictors of In-Hospital Mortality in Severe or Critical COVID-19: A Single-Center Observational Cohort Study.Medicina (Kaunas, Lithuania) · 2026Observational
- Impact of CHA₂DS₂-VA score on COVID-19 disease-related outcomes.BMC cardiovascular disorders · 2025Article
- Association of Cardiovascular Risk Factors With Major and Minor Electrocardiographic Abnormalities: A Report From the Cross-Sectional Phase of Tehran Cohort Study.Health science reports · 2025Article
- A Nomogram for Predicting Survival in Patients with SARS-CoV-2 Omicron Variant Pneumonia Based on Admission Data.Infection and drug resistance · 2025Article
- Machine learning approaches to predict the need for intensive care unit admission among Iranian COVID-19 patients based on ICD-10: A cross-sectional study.Health science reports · 2024Article
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Authors and funding
10 authors.
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Abstract
backgroundSince 2019, coronavirus disease 2019 (COVID-19) has been the leading cause of mortality worldwide.
aimsTo determine independent predictors of mortality in COVID-19, and identify any associations between pulmonary disease severity and cardiac involvement.
methodsClinical, laboratory, electrocardiography and computed tomography (CT) imaging data were collected from 389 consecutive patients with COVID-19. Patients were divided into alive and deceased groups. Independent predictors of mortality were identified. Kaplan-Meier analysis was performed, based on patients having a troponin concentration>99th percentile (cardiac injury) and a CT severity score ≥18.
resultsThe mortality rate was 29.3%. Cardiac injury (odds ratio [OR] 2.19, 95% confidence interval [CI] 1.14-4.18; P=0.018), CT score ≥18 (OR 2.24, 95% CI 1.15-4.34; P=0.017), localized ST depression (OR 3.77, 95% CI 1.33-10.67; P=0.012), hemiblocks (OR 3.09, 95% CI 1.47-6.48; P=0.003) and history of leukaemia/lymphoma (OR 3.76, 95% CI 1.37-10.29; P=0.010) were identified as independent predictors of mortality. Additionally, patients with cardiac injury and CT score ≥ 18 were identified to have a significantly shorter survival time (mean 14.21 days, 95% CI 10.45-17.98 days) than all other subgroups. There were no associations between CT severity score and electrocardiogram or cardiac injury in our results.
conclusionsOur findings suggest that using CT imaging and electrocardiogram characteristics together can provide a better means of predicting mortality in patients with COVID-19. We identified cardiac injury, CT score ≥18, presence of left or right hemiblocks on initial electrocardiogram, localized ST depression and history of haematological malignancies as independent predictors of mortality in patients with COVID-19.
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