Risk-Stratifying COVID-19 Patients the Right Way

2D speckle-tracking echocardiography as a prognostic imaging modality for COVID-19 adverse outcomes

2D speckle-tracking echocardiography (2D-STE) has been used to assess cardiac recovery during the COVID-19 patient follow-ups within the pandemic. The novel role of STE in predicting adverse outcomes of COVID-19 has received attention due to its high sensitivity in identifying subclinical myocardial dysfunction. We reviewed the studies on using 2D-STE to assess COVID-19 prognosis. A literature search was conducted on PubMed and Scopus for eligible articles, 24 of which discussed using prognostic 2D-STE for COVID-19 patients. 2D-STE predicts cardiovascular impairments more rapidly and precisely than conventional echocardiography. The 2D-STE technique presents an independent prognostic factor in COVID-19 infection. 2D-STE could be considered a time-efficient and accurate risk predictor of all-cause mortality in COVID-19 patients.

[Right ventricular systolic dysfunction as a predictor of adverse outcome in patients with COVID-19]

Aim To analyze survival of patients with COVID-19 based on echocardiographic (EchoCG) criteria for evaluation of the right ventricular (RV) systolic function.Material and methods Data of patients were retrospectively evaluated at the Center for Medical Care of Patients with Coronavirus Infection. Among 142 primarily evaluated patients with documented COVID-19, 110 patients (men/women, 63/47; mean age, 62.3 ± 15.3 years) met inclusion/exclusion criteria. More than 30 EchoCG parameters were analyzed, and baseline data (comorbidities, oxygen saturation, laboratory data, complications, outcomes, etc.) were evaluated. ROC-analysis was used for evaluating the diagnostic significance of different EchoCG parameters for prediction of a specific outcome and its probability. Dependence of the overall survival of patients on different EchoCG parameters was analyzed with the Cox proportional hazards model. For assessing the predictive value of EchoCG parameters for patient stratification by risk of an adverse outcome, a predictive model was developed using the CHAID method.Results The in-hospital death rate of patients included into the study was 15.5 %, and the death rate for this period of in-hospital observation was 12 %. Based on the single-factor analysis of EchoCG parameters, a multifactor model was developed using the method of Cox regression. The model included two predictors for an unfavorable outcome, estimated pulmonary artery systolic pressure (EPASP) and maximal indexed right atrial volume (RAi), and a preventive factor, right ventricular global longitudinal strain (LS RV). Base risks for fatal outcome were determined with an account of the follow-up time. According to the obtained values, an increase in EPASP by 1 mm Hg was associated with increases in the risk of fatal outcome by 8.6 % and in the RA(i) volume by 1 ml/5.8 %. LS RV demonstrated an inverse correlation; a 1% increase in LS RV was associated with a 13.4% decrease in the risk for an unfavorable outcome. According to the ROC analysis, the most significant determinants of the outcome were the tricuspid annular plane systolic excursion (TAPSE) (AUC, 0.84 ± 0.06; cut-off, 18 mm) and EPASP (AUC, 0.86 ± 0.05; cut-off, 42 mm Hg). Evaluating the effects of different EchoCG predictors, that characterized the condition of the right heart, provided a classification tree. Six final decisions were determined in the model, two of which were assigned to the category of reduced risk for fatal outcome and four were assigned to the category of increased risk. Sensitivity of the classification tree model was 94.1 % and specificity was 89.2 %. Overall diagnostic significance was 90.0±2.9 %.Conclusion The presented models for statistical treatment of EchoCG parameters reflect the requirement for a comprehensive analysis of EchoCG parameters based on a combination of standard methods for EchoCG evaluation and current technologies of noninvasive visualization. According to the study results, the new EchoCG marker, LS RV, allows identifying the signs of right ventricular dysfunction (particularly in combination with pulmonary hemodynamic indexes), may enhance the early risk stratification in patients with COVID-19, and help making clinical decisions for patients with different acute cardiorespiratory diseases.