Incremental prognostic value of biventricular longitudinal strain and high-sensitivity troponin I in COVID-19 patients

Background Whether the combination of ventricular strain with high-sensitivity troponin I (hs-TNI) has an incremental prognostic value in coronavirus disease 2019 (COVID-19) patients has not been evaluated. The study aimed to evaluate the prognostic value of biventricular longitudinal strain and its combination with hs-TNI in COVID-19 patients. Methods A total of 160 COVID-19 patients who underwent both echocardiography and hs-TNI testing were enrolled in our study. COVID-19 patients were divided into two groups (critical and non-critical) according to severity-of-illness. The clinical characteristics, cardiac structure and function were compared between the two groups. The prognostic value of biventricular longitudinal strain and its combination with hs-TNI were evaluated by logistic regression analyses and receiver operating characteristic curves. Left ventricular longitudinal strain (LV LS) and right ventricular free wall longitudinal strain (RVFWLS) were determined by 2D speckle-tracking echocardiography. Results The LV LS and RVFWLS both were significantly lower in critical patients than non-critical patients (LV LS: -16.6 +/- 2.4 vs -17.9 +/- 3.0, P = .003; RVFWLS :-18.8 +/- 3.6 vs -23.9 +/- 4.4, P). During a median follow-up of 60 days, 23 (14.4%) patients died. The multivariant analysis revealed that LV LS and RVFWLS [Odd ratio (95% confidence interval): 1.533 (1.131-2.079), P = .006; 1.267 (1.036-1.551), P = .021, respectively] were the independent predictors of higher mortality. Further, receiver-operating characteristic analysis revealed that the accuracy for predicting death was greater for the combination of hs-TNI levels with LV LS than separate LV LS (AUC: .91 vs .77, P = .001), and the combination of hs-TNI levels with RVFWLS than RVFWLS alone (AUC: .89 vs .83, P = .041). Conclusions Our study highlights that the combination of ventricular longitudinal strain with hs-TNI can provide higher accuracy for predicting mortality in COVID-19 patients, which may enhance risk stratification in COVID-19 patients.