Myocardial injury determination improves risk stratification and predicts mortality in COVID-19 patients

Despite being associated with worse prognosis in patients with COVID-19, systematic determination of myocardial injury is not recommended. The aim of the study was to study the effect of myocardial injury assessment on risk stratification of COVID-19 patients.

Seven hundred seven consecutive adult patients admitted to a large tertiary hospital with confirmed COVID-19 were included. Demographic data, comorbidities, laboratory results and clinical outcomes were recorded. Charlson comorbidity index (CCI) was calculated in order to quantify the degree of comorbidities. Independent association of cardiac troponin I (cTnI) increase with outcomes was evaluated by multivariate regression analyses and area under curve. In addition, propensity-score matching was performed to assemble a cohort of patients with similar baseline characteristics.

In the matched cohort (mean age 66.76 ± 15.7 years, 37.3% females), cTnI increase above the upper limit was present in 20.9% of the population and was associated with worse clinical outcomes, including all-cause mortality within 30 days (45.1% vs. 23.2%; p = 0.005). The addition of cTnI to a multivariate prediction model showed a significant improvement in the area under the time-dependent receiver operating characteristic curve (0.775 vs. 0.756, DC-statistic = 0.019; 95% confidence interval 0.001-0.037). Use of renin-angiotensin-aldosterone system inhibitors was not associated with mortality after adjusting by baseline risk factors.

Myocardial injury is independently associated with adverse outcomes irrespective of baseline comorbidities and its addition to multivariate regression models significantly improves their performance in predicting mortality. The determination of myocardial injury biomarkers on hospital admission and its combination with CCI can classify patients in three risk groups (high, intermediate and low) with a clearly distinct 30-day mortality.