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• W4383896247 abstract "Abstract Background Sarcopenia is a progressive age-related disease that can cause a range of adverse health-related outcomes in the elderly and an increased risk of death in the short term in those with severe sarcopenia. The aim of this study was to construct and validate a predictive model for the risk of sarcopenia in the elderly in China. Methods This study used the data from the 2015 China Health and Retirement Longitudinal Study (CHARLS), a high-quality microdata representing households and individuals aged 45 years and older in China. Sixty-five indicators, including sociodemographic, health-related and biochemical indicators, were analyzed in this study. Results A total of 3454 older adults from the 2015 CHARLS database were included in the final analysis. A total of 997 (28.8%) had symptoms of sarcopenia. Multivariate logistic regression analysis showed that Sex, BMI, MSBP, MDBP and Pain were predictors of sarcopenia in the elderly. These factors were used to construct the Nomogram model, which had good consistency and accuracy. The AUC value of the prediction model in the training set was 0.77 (95% CI = 0.75-0.7901); The AUC value in the validation set was 0.76 (95%CI = 0.7287–0.7904). Hosmer-Lemeshow test values were P = 0.5041 and P = 0.2668 respectively (P > 0.05). The calibration curves showed a significant agreement between the nomogram model and the actual observations. ROC and DCA showed that the nomogram had good predictive performance.. Conclusion The prediction model of the risk of sarcopenia in Chinese elderly people constructed in this study has a certain predictive effect, and can provide a reference for early screening and intervention by clinical staff." @default.
• W4383896247 created "2023-07-12" @default.
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• W4383896247 date "2023-07-11" @default.
• W4383896247 modified "2023-10-16" @default.
• W4383896247 title "Construction and validation of a predictive model for the risk of sarcopenia in the elderly in China" @default.
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• W4383896247 doi "https://doi.org/10.21203/rs.3.rs-3106392/v1" @default.
• W4383896247 hasPublicationYear "2023" @default.
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