A global clinical measure of fitness and frailty in elderly people

医学 虚弱指数 老年学 比例(比率) 置信区间 共病 队列 接收机工作特性 内科学 物理 量子力学
作者
Kenneth Rockwood
出处
期刊:Canadian Medical Association Journal [Canadian Medical Association]
卷期号:173 (5): 489-495 被引量:8987
标识
DOI:10.1503/cmaj.050051
摘要

BACKGROUND: There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. METHODS: We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. RESULTS: The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). INTERPRETATION: Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
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
刚刚
刚刚
陌陌完成签到,获得积分10
刚刚
哈哈完成签到,获得积分10
刚刚
阔达菠萝完成签到,获得积分10
刚刚
背后的初彤完成签到 ,获得积分10
刚刚
琛123完成签到,获得积分10
2秒前
張肉肉完成签到,获得积分10
2秒前
JamesPei应助闪闪的紫烟采纳,获得10
2秒前
fanfan发布了新的文献求助10
4秒前
阔达菠萝发布了新的文献求助30
4秒前
King16完成签到,获得积分10
4秒前
learning完成签到,获得积分10
5秒前
冷静雨梅发布了新的文献求助10
5秒前
6秒前
在水一方应助欢呼的安白采纳,获得10
7秒前
ppprotein完成签到,获得积分10
7秒前
8秒前
ice完成签到,获得积分10
8秒前
9秒前
醋酸异丙酯完成签到 ,获得积分10
10秒前
顾矜应助milkway采纳,获得10
10秒前
10秒前
11秒前
lyk2815完成签到,获得积分10
11秒前
11秒前
qinqin发布了新的文献求助10
11秒前
科研通AI6.2应助冷静雨梅采纳,获得10
12秒前
liugm发布了新的文献求助10
12秒前
Joanna完成签到 ,获得积分10
12秒前
鱼仔完成签到,获得积分10
13秒前
13秒前
14秒前
开放身影完成签到,获得积分10
14秒前
ice发布了新的文献求助10
15秒前
15秒前
15秒前
16秒前
Shafrir完成签到,获得积分10
16秒前
王方明完成签到,获得积分10
16秒前
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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Management and the Arts 310
Teaching Social and Emotional Learning in Physical Education 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7635011
求助须知:如何正确求助?哪些是违规求助? 9209019
关于积分的说明 19750752
捐赠科研通 7202945
什么是DOI,文献DOI怎么找? 3275138
关于科研通互助平台的介绍 2437001
邀请新用户注册赠送积分活动 2272151