Рациональная фармакотерапия в кардиологии (Jul 2024)
Digital model for predicting the risk of developing acute decompensated heart failure
Abstract
Aim. Development and external validation of a risk prediction model for acute decompensated heart failure (ADHF) in patients with low left ventricular ejection fraction.Material and methods. The model development group was represented by patients with heart failure with reduced ejection fraction (HFrEF) included in a registry observational study from 2015 to 2019, a total of 260 patients, age 59 (53; 66) years, 214 (82.3%) — men. External validation of the model was carried out in a cohort of independent prospective observation of 94 patients with HFrEF from the same registry for the period from 2020 to 2021, median age 66 (52;73) years, of which 73 (77.6%) were men. The prospective follow-up period was 4.6 (2.3; 4.9) years in the internal validation group, 2.5 (1.7; 2.9) years in the external validation group. Data were obtained on the status of patients, causes of death, and the frequency of hospitalizations for ADHF. The actual and predicted incidence of ADHF using the evaluated prognostic model was compared.Results. During the observation period in the internal validation group, ADHF developed in 69 (26.5%) patients, and 47 (18.1%) died due to ADHF. The prognostic regression model included LA enlargement of more than 45 mm, male gender, left ventricular ejection fraction less than 35%, absence of renin-angiotensin system blocker and amiodarone. When performing ROC analysis, the area under the ROC curve (AUC) of the created model was 0.8, sensitivity model — 69.2%, specificity — 80%, accuracy — 75.3%. In the external validation group, 34 (36.2%) cases of ADHF were registered; mortality from ADHF in the external validation group was 15.9%, which is comparable to the development group (p > 0.05). The diagnostic value of the developed model during external validation showed to be high and was comparable to the results obtained in the development group: the area under the ROC curve (AUC) was 0.8, sensitivity — 73.3%, specificity — 82.5%, accuracy 76.1%, (p=0.102, McNeil test).Conclusion. The developed regression model has sufficient statistical power to predict the risk of ADHF in patients with low left ventricular ejection fraction in the long term, which is confirmed by external validation.
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