亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Development and Validation of a Nomogram for Predicting Sarcopenia in Community-Dwelling Older Adults

列线图 肌萎缩 医学 接收机工作特性 逻辑回归 老年学 多元分析 体质指数 风险评估 婚姻状况 物理疗法 内科学 环境卫生 人口 计算机安全 计算机科学
作者
Yihan Mo,Yi-Dong Su,Xin Dong,Jing Zhong,Chen Yang,Wenyu Deng,Xuemei Yao,Beibei Liu,Xiuhua Wang
出处
期刊:Journal of the American Medical Directors Association [Elsevier]
卷期号:23 (5): 715-721.e5 被引量:42
标识
DOI:10.1016/j.jamda.2021.11.023
摘要

Objective To establish and validate a nomogram that predicts the risk of sarcopenia for community-dwelling older residents. Design Retrospective study. Setting and Participants A total of 1050 community-dwelling older adults. Methods Data from a survey of community-dwelling older residents (≥60 years old) in Hunan, China, from June to September 2019 were retrospectively analyzed. The survey included general demographic information, diet, and exercise habits. Sarcopenia diagnosis was according to 2019 Asian Working Group for Sarcopenia criteria. Participants were randomly divided into the development group and validation groups. Independent risk factors were screened by multivariate logistic regression analysis. Based on the independent risk factors, a nomogram model was developed to predict the risk of sarcopenia for community-dwelling older adults. Both in the development and validation sets, the discrimination, calibration, and clinical practicability of the nomogram were verified using receiver operating characteristic curve analysis, Hosmer-Lemeshow test, and decision curve analysis, respectively. Results Sarcopenia was identified in 263 (25.0%) participants. Age, body mass index, marital status, regular physical activity habit, uninterrupted sedentary time, and dietary diversity score were significant contributors to sarcopenia risk. A nomogram for predicting sarcopenia in community-dwelling older adults was developed using these factors. Receiver operating characteristic curve analysis showed that the area under the curve was 0.827 (95% CI 0.792-0.860) and 0.755 (95% CI 0.680-0.837) in the development and validation sets, respectively. The Hosmer-Lemeshow test yielded P values of .609 and .565, respectively, for the 2 sets. The nomogram demonstrated a high net benefit in the clinical decision curve in both sets. Conclusions and Implications This study developed and validated a risk prediction nomogram for sarcopenia among community-dwelling older adults. Sarcopenia risk was classified as low (<11%), moderate (11%-70%), and high (>70%). This nomogram provides an accurate visual tool to medical staff, caregivers, and older adults for prediction, early intervention, and graded management of sarcopenia.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
俏以完成签到,获得积分10
19秒前
体贴静竹完成签到 ,获得积分10
36秒前
44秒前
星辰大海应助科研通管家采纳,获得10
1分钟前
清晨仪仪发布了新的文献求助10
1分钟前
1分钟前
朴素尔阳发布了新的文献求助10
1分钟前
1分钟前
webmaster完成签到,获得积分10
2分钟前
向东是大海完成签到,获得积分10
2分钟前
2分钟前
CC发布了新的文献求助10
3分钟前
万能图书馆应助清晨仪仪采纳,获得30
3分钟前
Yihan完成签到,获得积分10
3分钟前
科研王者发布了新的文献求助10
3分钟前
老万的小迷弟完成签到,获得积分10
3分钟前
JoeyJin完成签到,获得积分10
3分钟前
我是老大应助科研王者采纳,获得10
3分钟前
4分钟前
yeeeee发布了新的文献求助10
4分钟前
ttkx发布了新的文献求助10
4分钟前
CipherSage应助yeeeee采纳,获得10
4分钟前
量子星尘发布了新的文献求助10
4分钟前
5分钟前
5分钟前
artos发布了新的文献求助30
5分钟前
Lucas应助科研通管家采纳,获得10
5分钟前
科研通AI6应助artos采纳,获得10
6分钟前
华仔应助CC采纳,获得30
6分钟前
6分钟前
CC发布了新的文献求助30
6分钟前
执着梦柏完成签到 ,获得积分10
6分钟前
7分钟前
7分钟前
SciGPT应助科研通管家采纳,获得10
7分钟前
8分钟前
清晨仪仪发布了新的文献求助30
8分钟前
8分钟前
步念发布了新的文献求助30
8分钟前
科研通AI6应助步念采纳,获得30
8分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Basic And Clinical Science Course 2025-2026 3000
《药学类医疗服务价格项目立项指南(征求意见稿)》 880
花の香りの秘密―遺伝子情報から機能性まで 800
3rd Edition Group Dynamics in Exercise and Sport Psychology New Perspectives Edited By Mark R. Beauchamp, Mark Eys Copyright 2025 600
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
nephSAP® Nephrology Self-Assessment Program - Hypertension The American Society of Nephrology 550
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5622241
求助须知:如何正确求助?哪些是违规求助? 4707275
关于积分的说明 14938986
捐赠科研通 4769648
什么是DOI,文献DOI怎么找? 2552255
邀请新用户注册赠送积分活动 1514348
关于科研通互助平台的介绍 1475053