Updating and Validating the Charlson Comorbidity Index and Score for Risk Adjustment in Hospital Discharge Abstracts Using Data From 6 Countries

医学 查尔森共病指数 共病 索引(排版) 急诊医学 出院 内科学 计算机科学 万维网
作者
Hude Quan,Bing Li,Chantal Marie Couris,Kiyohide Fushimi,Patrick Graham,P Hider,Jean‐Marie Januel,Vijaya Sundararajan
出处
期刊:American Journal of Epidemiology [Oxford University Press]
卷期号:173 (6): 676-682 被引量:4773
标识
DOI:10.1093/aje/kwq433
摘要

With advances in the effectiveness of treatment and disease management, the contribution of chronic comorbid diseases (comorbidities) found within the Charlson comorbidity index to mortality is likely to have changed since development of the index in 1984. The authors reevaluated the Charlson index and reassigned weights to each condition by identifying and following patients to observe mortality within 1 year after hospital discharge. They applied the updated index and weights to hospital discharge data from 6 countries and tested for their ability to predict in-hospital mortality. Compared with the original Charlson weights, weights generated from the Calgary, Alberta, Canada, data (2004) were 0 for 5 comorbidities, decreased for 3 comorbidities, increased for 4 comorbidities, and did not change for 5 comorbidities. The C statistics for discriminating in-hospital mortality between the new score generated from the 12 comorbidities and the Charlson score were 0.825 (new) and 0.808 (old), respectively, in Australian data (2008), 0.828 and 0.825 in Canadian data (2008), 0.878 and 0.882 in French data (2004), 0.727 and 0.723 in Japanese data (2008), 0.831 and 0.836 in New Zealand data (2008), and 0.869 and 0.876 in Swiss data (2008). The updated index of 12 comorbidities showed good-to-excellent discrimination in predicting in-hospital mortality in data from 6 countries and may be more appropriate for use with more recent administrative data.
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
哈喽发布了新的文献求助10
1秒前
SHUAI完成签到,获得积分10
2秒前
Hello应助zz采纳,获得10
3秒前
HMONEY应助董董采纳,获得10
3秒前
盖世英雄的小超人完成签到,获得积分10
8秒前
9秒前
12秒前
凡平完成签到,获得积分10
13秒前
禾沐发布了新的文献求助10
15秒前
15秒前
NexusExplorer应助第七个星球采纳,获得10
16秒前
如意2023完成签到 ,获得积分10
17秒前
liu完成签到,获得积分10
20秒前
称心寒松发布了新的文献求助10
20秒前
zzjjhh完成签到,获得积分10
22秒前
DLL完成签到 ,获得积分10
22秒前
GAOBIN000发布了新的文献求助10
23秒前
23秒前
26秒前
栗子完成签到,获得积分10
27秒前
搜集达人应助舒适乐儿采纳,获得10
30秒前
xmy发布了新的文献求助10
32秒前
令狐绝音发布了新的文献求助30
36秒前
心动nofear完成签到,获得积分20
37秒前
姜sir完成签到 ,获得积分10
40秒前
40秒前
43秒前
lu完成签到,获得积分10
43秒前
橘白应助涵涵采纳,获得10
45秒前
46秒前
47秒前
猪猪hero应助心动nofear采纳,获得10
47秒前
CH发布了新的文献求助10
47秒前
文天烽完成签到,获得积分10
48秒前
48秒前
49秒前
wzlcarrot发布了新的文献求助10
52秒前
sunshine发布了新的文献求助10
54秒前
yy应助第七个星球采纳,获得10
54秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Animal Physiology 2000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Machine Learning Methods in Geoscience 1000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3741430
求助须知:如何正确求助?哪些是违规求助? 3284094
关于积分的说明 10038212
捐赠科研通 3000880
什么是DOI,文献DOI怎么找? 1646852
邀请新用户注册赠送积分活动 783919
科研通“疑难数据库(出版商)”最低求助积分说明 750478