Development and validation of a cardiometabolic multimorbidity prediction model in middle-aged and older adults - PubMed
3 hours ago
- #predictive modeling
- #aging population
- #cardiometabolic health
- Cardiometabolic multimorbidity (CMM) is prevalent among middle-aged and older adults in China, impacting quality of life and healthcare systems.
- A predictive model was developed using data from the China Health and Retirement Longitudinal Study (CHARLS) to assess the five-year risk of CMM onset.
- The study analyzed data from 5,388 participants initially free of CMM, split into training (70%) and validation (30%) sets.
- Key predictors identified include systolic blood pressure, BMI, fasting blood glucose, total cholesterol, triglycerides, uric acid, age, comorbidities, and pain.
- The logistic regression model showed superior performance with an AUC of 0.732, reliable calibration, and clinical net benefit across risk thresholds.
- The model aids in early identification of high-risk individuals, supporting targeted interventions to reduce CMM-related burdens.