ESC Heart Failure (Aug 2022)
Role of depressive symptoms in the prognosis of heart failure and its potential clinical predictors
Abstract
Abstract Aims This study aims to analyse the factors associated with prognosis in hospitalized patients with heart failure, particularly the role of depressive symptoms, and to develop a prediction model for depressive symptoms based on clinical characteristics in hospitalized patients with heart failure. Methods and results Baseline information was collected at admission, and patients were followed up after discharge. The endpoint events were being hospitalized for heart failure or all‐cause death. Depressive symptoms were evaluated and defined via the Patient Health Questionnaire (PHQ)‐2 and PHQ‐9. The bidirectional elimination was used to screen independent predictors of heart failure with depression symptoms. The least absolute shrinkage and selection operator (LASSO) optimized the predictor variables, and the prediction model was constructed. The model was internally validated by the bootstrap sampling method (Bootstrap), and its performance was assessed by discrimination and calibration. The mean age of patients with heart failure was 69.43 ± 12.15 years, and the proportion of males was 66.67%. The prevalence of depressive symptoms in hospitalized patients with heart failure was 46.83%, and the prevalence of moderate/severe depressive symptoms was 11.62%. Eighty cases (30.30%) were readmitted for heart failure, and 13 cases (4.92%) were all‐cause deaths. Depressive symptoms (HR = 2.43, 95% CI: 1.55–3.80) and the PHQ‐9 score (HR = 1.11, 95% CI: 1.06–1.16) were both independent risk factors for endpoint events (P < 0.001). For heart failure patients combined with depressive symptoms, obesity (OR = 0.27, 95% CI: 0.09–0.77, P = 0.015), N‐terminal brain natriuretic peptide precursor (NT‐proBNP) level (lnNT‐proBNP: OR = 1.55, 95% CI: 1.20–2.01, P < 0.001) and red blood cell distribution width (RDW) (OR = 1.26, 95% CI: 1.08–1.47, P = 0.004) were the independent factors. Six variables, including cardiovascular disease hospitalization history, obesity, renal insufficiency, NT‐proBNP level, neutrophil ratio and RDW, were included to construct the prediction model. The area under the curve (AUC) was 0.730 in the original data, and the calibration curve was approximately distributed along the reference line in Bootstrap (500 resamplings), indicating the high level of discrimination and calibration of this model. Conclusions Depressive symptoms and the PHQ‐9 score are both independent risk factors for the prognosis of hospitalized patients with heart failure. In hospitalized patients with heart failure, the risk prediction model developed in this study has good predictive power for depressive symptoms.
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