Journal of Clinical and Nursing Research, Journal Year: 2024, Volume and Issue: 8(11), P. 246 - 264

Published: Nov. 27, 2024

Background: China is rapidly aging, increasing the burden on families, society, and public health services. The of elderly individuals tends to deteriorate with age, chronic conditions like frailty become more prevalent, driving up use healthcare Early screening intervention for are crucial in managing this demographic shift. While tools Fried Frailty Phenotype Index assess communities, they resource-intensive only indicate status without predicting risk or providing management recommendations. This study aims develop a prediction model using real-world data, which can support early detection high-risk community settings. Objectives: To analyze prevalence its influencing factors community-dwelling elderly, construct nomogram, validate clinical utility. Methods: A cross-sectional survey 420 Shanghai center was conducted (August 2022–March 2023). Data from various assessment were used build through logistic regression, validation 180 additional participants. model’s predictive performance evaluated ROC, AUC, calibration curves, decision curve analysis (DCA). Results: 7.4%. Independent included social support, malnutrition, fatigue, sarcopenia, reduced grip strength, sleep duration. achieved an AUC 0.968 training set 0.939 set, indicating high discrimination calibration. DCA confirmed Conclusion: highlights rate 7.4% among Shanghai, key identified. validated provides accurate clinically effective assessment, supporting targeted interventions prevent

Language: Английский