ABSTRACT
Background: Troponin seems to be a biological marker of interest in the risk-stratification of COVID 19 at admission, but few studies focus on exploring its prognostic abilities during hospitalization. Aim(s): To assess the ability of troponin levels at admission and during follow-up to predict in-hospital mortality in COVID-19 patients. Method(s): Troponin was measured at admission and throughout hospitalization amongst COVID-19 patients. We explored the prognostic ability of baseline troponin and kinetics on COVID-19 patients outcomes using logistic regression and Cox model. Result(s): Amongst 399 patients enrolled with confirmed COVID-19, 247 had at least 2 troponin measurements during hospitalization and 319 (80%) survived, while 80 (20%) died during hospitalization. Elevated troponin upon arrival was significantly associated with mortality (Odds Ratio (OR) 5.65 (95% CI 3.24 -9.88);p < 0.01). Patients with an elevated troponin level and underlying cardiovascular diseases were more likely to experience death than those without elevated troponin nor cardiovascular history (Hazard Ratio 4.62 (1.96-10.91);p < 0.001). There seems to be a level-dependent association between troponin level and in-hospital mortality (p < 0.01). To assess the ability of troponin monitoring during the first 10 days of hospitalization to predict in-hospital mortality we analyzed the ratio of troponin (ROT) between the highest level of troponin and the baseline troponin measurement. An increase over 75% of the ROT was not significantly associated with in hospital mortality (OR 1.02 (95% CI 1.01-1.04);p = 0.12). During follow-up, there was no significant differences of in-mortality between patients with constant elevated troponin throughout hospitalization and those who went from a normal to an elevated troponin (p = 0.15). Conclusion(s): For COVID-19 patients, troponin seems to be a relevant factor for in-hospital mortality and risk-stratification at admission but its monitoring during follow-up does not appear to be valuable in predicting disease progression.