Elevated Cardiac Troponin I as a Mortality Predictor in Hospitalised COVID-19 Patients.

Background and

Objectives

SARS-CoV-2 affects multiple organ systems, including the cardiovascular system, leading to immediate and long-term cardiovascular complications. Acute myocardial injury is one of the earliest and most common cardiac issues in the acute phase of COVID-19. This study aimed to evaluate the prognostic value of cardiac troponin I (cTnI) levels in predicting in-hospital mortality among hospitalised COVID-19 patients. Materials and

Methods

A retrospective observational cohort study included 2019 adult patients hospitalised with a confirmed COVID-19 infection stratified by cTnI levels on admission into three groups: <19 ng/L (1416 patients), 19-100 ng/L (431 patients), and >100 ng/L (172 patients). Myocardial injury was defined as blood serum cTnI levels increased above the 99th percentile upper reference limit. Depersonalised datasets were extracted from digital health records. Statistical analysis included multivariable binary logistic and Cox proportional hazards regressions.

Results

Overall, 29.87% of patients experienced acute myocardial injury, which development was associated with age, male sex, chronic heart failure, arterial hypertension, obesity, and chronic kidney disease. Among patients with cTnI levels of 19-100 ng/L, the odds ratio for requiring invasive mechanical ventilation was 3.18 (95% CI 2.11-4.79) and, for those with cTnI > 100 ng/L, 5.38 (95% CI 3.26-8.88). The hazard ratio for in-hospital mortality for patients with cTnI levels of 19-100 ng/L was 2.58 (95% CI 1.83-3.62) and, for those with cTnI > 100 ng/L, 2.97 (95% CI 2.01-4.39) compared to patients with normal cTnI levels.

Conclusions

Increased cardiac troponin I, indicating myocardial injury, on admission is associated with a more adverse clinical disease course, including a higher likelihood of requiring invasive mechanical ventilation and increased risk of in-hospital mortality. This indicates cardiac troponin I to be a beneficial biomarker for clinicians trying to identify high-risk COVID-19 patients, choosing the optimal monitoring and treatment strategy for these patients.