Cardiopulmonary predictors of mortality in patients with COVID-19: What are the findings?

BACKGROUND

Since 2019, coronavirus disease 2019 (COVID-19) has been the leading cause of mortality worldwide.

AIMS

To determine independent predictors of mortality in COVID-19, and identify any associations between pulmonary disease severity and cardiac involvement.

METHODS

Clinical, 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.

RESULTS

The 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.

CONCLUSIONS

Our 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.