Construction and Validation of Frailty Risk Prediction Model for Community-Dwelling Elderly Individuals With Chronic...

Area of Science:

• Gerontology and Public Health
• Chronic Disease Management
• Predictive Modeling in Healthcare

Background:

• Frailty is a significant concern in community-dwelling elderly with chronic diseases.
• Early identification and intervention are crucial for managing frailty and its complications.
• Existing prediction models may not fully capture the multifactorial nature of frailty in this population.

Purpose of the Study:

• To identify key influencing factors of frailty in community-dwelling elderly individuals with chronic diseases.
• To develop and internally validate a risk prediction model for frailty in this demographic.
• To provide a tool for early screening and personalized prevention.

Main Methods:

• Cross-sectional study design involving 678 elderly individuals with chronic diseases.
• Data collected using questionnaires including Tilburg Frailty Indicator (TFI), General Self-efficacy Scale (GSES), and Physical Resilience Instrument for Older Adults (PRIFOR).
• Binary logistic regression and LASSO regression used to identify predictors; nomogram and AUC analysis for model validation.

Main Results:

• Key predictors of frailty included religion, living arrangement, regular exercise, chronic disease duration, medication count, health status, general self-efficacy, and physical resilience.
• The developed prediction model demonstrated satisfactory discrimination and calibration.
• Internal validation confirmed the model's good predictive performance.

Conclusions:

• The frailty prediction model shows good discrimination, calibration, and clinical utility.
• It serves as a scientific basis for preventing and early screening of frailty in elderly individuals with chronic diseases.
• The model supports community healthcare professionals in risk assessment and personalized care planning to delay frailty and complications.