Predictors of Mortality Following Aortic Valve Replacement in Aortic Stenosis Patients

Abstract

Background: Understanding of the risk factors for the development of adverse outcomes after aortic valve replacement is necessary to develop timely preventive measures and to improve the results of surgical treatment. Methods: We analyzed patients with aortic stenosis (n = 742) who underwent surgical treatment in the period 2014–2020. The average age was 63 (57;69) years—men 58%, women 42%. Results: The hospital mortality rate was 3% (22 patients). The following statistically significant threshold values (cut-off points) were obtained in the ROC analysis: aortic cross-clamp time > 93 min AUC (CI) 0.676 (0.640–0.710), p = 0.010; cardiopulmonary bypass time > 144 min AUC (CI) 0.809 (0.778–0.837), p < 0.0001, hemoglobin before op <120 g/L. AUC (CI) 0.762 (0.728–0.793), p < 0.0001, hematocrit before op <39% AUC (CI) 0.755 (0.721–0.786), p < 0.001, end-diastolic dimension index >2.39 AUC (CI) 0.647 (0.607–0.686), p = 0.014, end-systolic dimension index >1.68 AUC (CI) 0.657 (0.617–0.695), p = 0.009. Statistically significant independent predictors of hospital mortality were identified: BMI > 30 kg/m2 (OR 2.84; CI 1.15–7.01), ischemic heart disease (OR 3.65; CI 1.01–13.2), diabetes (OR 3.88; CI 1.38–10.9), frequent ventricular ectopy before operation (OR 9.78; CI 1.91–50.2), mitral valve repair (OR 4.47; CI 1.76–11.3), tricuspid valve repair (OR 3.06; CI 1.09–8.58), 3 and more procedures (OR 4.44; CI 1.67–11.8). Conclusions: The hospital mortality rate was 3%. The main indicators associated with the risk of death were: diabetes, overweight (body mass index more than 30 kg/m2), frequent ventricular ectopy before surgery, hemoglobin level below 120 g/L, hematocrit level below 39%, longer cardiopulmonary bypass time and aortic cross-clamp time, additional mitral and tricuspid valve interventions.

The Role of «Novel» Biomarkers of Systemic Inflammation in the Development of Early Hospital Events after Aortic Valve Replacement in Patients with Aortic Stenosis

“…When performing the univariate and multivariate logistic regression analyses, we also added clinical and operational predictors of a lethal outcome that we found earlier in this cohort of patients [ 13 ] ( Table 4 ).…”

“…An ROC analysis was performed to determine threshold values for systemic inflammation indices associated with the primary and secondary endpoints of the study (Table 3 and Figure 1). When performing the univariate and multivariate logistic regression analyses, we also added clinical and operational predictors of a lethal outcome that we found earlier in this cohort of patients [13] (Table 4). When performing the univariate and multivariate logistic regression analyses, we also added clinical and operational predictors of a lethal outcome that we found earlier in this cohort of patients [13] (Table 4).…”

“…Hemodynamically, these were patients with predominant aortic valve stenosis. Previously, we identified the clinical predictors of mortality in the early postoperative period in this cohort of patients [ 13 ].…”

Benchmarking Time-Frequency Representations of PCG Signals for Classification Valvular Heart Diseases Using Deep Features and Machine Learning

“…Mitral stenosis (MS) is a common disease that causes a large number of diseases throughout the world. This disease is more recurrent in developing countries, but in developed countries it is becoming more common in atypical forms [7] and it is characterized by a low-pitched, diastolic rumble that is best heard at the apex with the patient in the left lateral decubitus position. Mitral valve prolapse (MVP) is a frequent condition that affects 2-3% of the general population and it is characterized by a mid-to-late systolic click followed by a late systolic murmur that is best heard at the apex and radiates to the axilla [3,8].…”