Development and Validation of a Risk Score in Chinese Patients With Chronic Heart Failure

Area of Science:

• Cardiology
• Biostatistics
• Clinical Risk Prediction

Background:

• Acute exacerbations of chronic heart failure significantly increase the risk of major adverse cardiovascular events (MACE).
• Accurate assessment of heart failure severity is crucial for predicting MACE and guiding treatment.
• Existing risk stratification methods may not fully capture the complexity of heart failure severity and associated risks.

Purpose of the Study:

• To develop and validate a novel risk score for evaluating heart failure severity.
• To assess the relationship between the developed risk score and the incidence of MACE.
• To identify key clinical and laboratory predictors of heart failure severity and MACE risk.

Main Methods:

• A retrospective observational study of 5,777 heart failure patients.
• Data randomly split into training (70%) and validation (30%) sets.
• Least Absolute Shrinkage and Selection Operator (Lasso) logistic regression used for predictor selection and risk score development.
• Receiver Operating Characteristic (ROC) and calibration curves assessed model performance.

Main Results:

• A risk score was developed using body-mass index (BMI), ejection fraction (EF), serum creatinine, hemoglobin, C-reactive protein (CRP), and neutrophil lymphocyte ratio (NLR).
• The risk score demonstrated good discrimination (AUC 0.770 in training, 0.756 in validation) and calibration.
• Higher risk scores correlated with increased MACE incidence, longer hospital stays, and higher treatment costs (P < 0.001).

Conclusions:

• A validated risk score incorporating BMI, EF, serum creatinine, hemoglobin, CRP, and NLR effectively classifies heart failure severity.
• This risk score is closely associated with the risk of major adverse cardiovascular events (MACE).
• The developed risk score can aid clinicians in stratifying heart failure patients and anticipating adverse outcomes.