Development and validation of a risk prediction model for physical frailty in older adults who are disabled.

Physical frailty is highly prevalent among the older adults who are disabled. The aim of this study was to explore the risk factors for physical frailty in older adults who are disabled and construct a nomogram prediction model. The data source was the China Health and Retirement Longitudinal Study (CHARLS). The prediction model was validated with a cohort of 1183 older adults who are disabled. The results showed that sleep quality, depression, fatigue, and chronic disease were the best predictive factors. These factors were used to construct the nomogram model, which showed good concordance and accuracy. The prediction model yielded an Area under the curve (AUC) value of 0.760. Calibration curves showed significant agreement between the nomogram model and actual observations. Receiver operating characteristic (ROC) and Decision curve analysis (DCA) showed that the nomogram had good predictive performance. The nomogram is contributed to the screening of specific populations by clinicians.