Prognostic significance of cardiac dysfunction markers in comorbid patients with chronic heart failure

Background. The results of numerous studies have demonstrated a strong relationship between cardiovascular mortality and cardiac biomarker levels. However, a significant number of these studies were devoted to assessing the prediction of cardiovascular events during the acute period of COVID-19. Therefore, the search for markers for predicting the unfavorable course of chronic heart failure in patients with type 2 diabetes mellitus (SD2) and CKD who have undergone COVID-19 is relevant.

Objective. Purpose of the study was to prediction of the unfavorable course of chronic heart failure in comorbid patients who have undergone COVID-19.

Materials and methods. The study included 181 patients with verified cardiovascular pathology and chronic heart failure with preserved ejection fraction of NYHA functional class 1-3, suffering from type 2 DM and CKD, which were divided into two groups: group 1 included 135 patients who had suffered COVID-19 not earlier than 3-6 months ago, in group 2 (n = 46) COVID there was no history of-19. The duration of the study was 18 months. Quality of life was determined using the Kansas and Minnesota Questionnaire, ECHOCG hemodynamics, glomerular filtration rate, cardiac dysfunction biomarkers NT-proBNP and sST2.

Results. The results of the study showed that the reduced clinical and functional status of patients who had recovered from COVID-19 was confirmed by the results of TSC (p = 0.0004) and the total SJC score (p < 0.001). Low indicators of the physical component of health affected the summary assessment of quality of life in patients undergoing COVID-19 according to the results of the KCCQ questionnaires (55.81 points versus 62.86 points in the comparison group, p < 0.001) and MLHFQ (43.0 points versus 38.0 points in the comparison group, p = 0.002). In the first group, more significant adverse changes in the indicators of remodeling of the left heart and hemodynamic disorders were identified, which corresponded to significantly higher concentrations of markers of myocardial dysfunction. Using multivariate logistic regression analysis, a basic statistical model 1 was built to predict the probability of HF decompensation and cardiovascular death (CVD) in patients with chronic heart failure, diabetes mellitus type II and chronic kidney disease who underwent COVID-19. According to the obtained results, the most significant parameters for assessing the probability of CCT of Model 1 were the number of points on the clinical assessment scale, stroke volume, left ventricular mass index, NT-proBNP concentration. This model, sensitivity and specificity of which was 85.6%, 79.2% respectively, had a fairly high prognostic potential (AUC – 0.856; 95% CI: 0.717-0.994; p < 0.001). The inclusion of sST2 in the original model resulted in an increase in the area under the ROC curve (AUC – 0.91; 95% CI: 0,812-0,992; р < 0,001). Thus compared to the baseline model including NT-proBNP concentration, the addition of sST2 increases the predictive power of the model with respect to the risk of CCT in patients with CHFsEF with diabetes mellitus and chronic kidney desease who have had COVID-19. The results of the calculations confirm the high quality of the model with a sensitivity of 93.3%, specificity of 78.9% and accuracy of 86.1%. Comorbid patients with chronic heart failure who underwent COVID-19 have more severe clinical manifestations, structural and functional disorders of the heart and kidneys, higher concentrations of biomarkers of cardiac dysfunction NT-proBNP and sST2. Soluble ST2 outperforms NT-proBNP in predictive properties and is a priority for assessing the risk of heart failure decompensation and mortality in patients with comorbid pathology who underwent COVID-19.

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