Objective:To systematically review risk prediction models for sarcopenia in community-dwelling older adults.Methods:Literature on risk prediction models for sarcopenia in community-dwelling older adults was retrieved from China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Embase, Cochrane Library, and Web of Science. The search period was from database inception to October 24, 2024. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies using the Prediction Model Risk of Bias Assessment Tool (PROBAST) .Results:A total of 17 articles were included, encompassing 24 risk prediction models for sarcopenia in community-dwelling older adults. The area under the receiver operating characteristic curve ( AUC) reported in 16 studies ranged from 0.710 to 0.983. Age, sex, body mass index, body weight, calf circumference, and physical activity habits were the most frequently identified predictors. The overall risk of bias in the 17 articles was high, while applicability was generally good. Conclusions:Although the risk prediction models for sarcopenia in community-dwelling older adults show good predictive performance, methodological flaws in model development and a high risk of bias are prevalent. Future studies should strictly adhere to the PROBAST framework, optimize model construction and validation processes, and improve data handling strategies to enhance model performance and applicability.

Objective:To systematically review risk prediction models for sarcopenia in community-dwelling older adults.Methods:Literature on risk prediction models for sarcopenia in community-dwelling older adults was retrieved from China National Knowledge Infrastructure, Wanfang Data, China Biology Medicine disc, VIP, PubMed, Embase, Cochrane Library, and Web of Science. The search period was from database inception to October 24, 2024. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies using the Prediction Model Risk of Bias Assessment Tool (PROBAST) .Results:A total of 17 articles were included, encompassing 24 risk prediction models for sarcopenia in community-dwelling older adults. The area under the receiver operating characteristic curve ( AUC) reported in 16 studies ranged from 0.710 to 0.983. Age, sex, body mass index, body weight, calf circumference, and physical activity habits were the most frequently identified predictors. The overall risk of bias in the 17 articles was high, while applicability was generally good. Conclusions:Although the risk prediction models for sarcopenia in community-dwelling older adults show good predictive performance, methodological flaws in model development and a high risk of bias are prevalent. Future studies should strictly adhere to the PROBAST framework, optimize model construction and validation processes, and improve data handling strategies to enhance model performance and applicability.

With the increasing number of adolescents with chronic diseases surviving into adulthood, various problems have arisen in the transition from a sheltered pediatric environment to an adult medical independent environment. In this context, transitional care has emerged, which plays an important role in increasing disease knowledge, enhancing self-management abilities, reducing admission and visit rates, and improving the quality of life for adolescents with chronic diseases. This paper reviews the overview, implementation methods, strategies, and suggestions for transitional care for adolescents with chronic diseases, so as to provide reference and guidance for standardizing and promoting transitional care for adolescents with chronic diseases.