[Comparison of three different organ failure assessment score systems in predicting outcome of severe sepsis].

作者
Xiaopan Luo,Haihong Wang,Shuangfei Hu,Shuijing Wu,Guo-hao Xie,Baoli Cheng,Chen Zhou,Xiangming Fang
出处
期刊:PubMed [National Institutes of Health]
卷期号:47 (1): 48-50 被引量:9
链接
标识
摘要

OBJECTIVE: To compare multiple organ dysfunction score (MODS), the sequential organ failure assessment (SOFA) and the logistic organ dysfunction score (LODS) in predicting hospital mortality in severe sepsis. METHODS: Four hundred and three patients admitted to the ICU from December 2004 to November 2007 with a diagnosis of severe sepsis were enrolled in this study. Their MODS, SOFA, LODS and Acute Physiology and Chronic Health Evaluation (APACHE) II at admission and the highest score during hospitalization were respectively recorded and collected in regard to mortality. The discrimination of three multiple organ dysfunction score systems were assessed by the areas under the receiver operating characteristic curves (AUC). RESULTS: The AUC of admission scores was 0.811 for LODS, 0.787 for SOFA, 0.725 for MODS, and 0.770 for APACHE II in predicting hospital mortality. All maximum scores had better power of discrimination than the admission scores (P < 0.01). The power of discrimination of LODS and SOFA were better than the MODS, either the admission or the highest, respectively (P < 0.01). However, no significant difference was observed between the LODS and the SOFA regarding mortality prediction (P > 0.05). The AUC value for the APACHE II score was much lower compared to LODS (P < 0.01). However, there was no difference in AUC value among APACHE II, SOFA and MODS (P > 0.05). CONCLUSION: LODS, SOFA and MODS show a good discrimination power, while maximum LODS is of the highest discrimination power to predict the outcome of patient with severe sepsis.

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
汉堡包的应助被本汪自有喵计采纳,获得10
2秒前
kiki发布了新的文献求助10
2秒前
2秒前
化学废材发布了新的文献求助10
2秒前
酷酷的乐萱完成签到,获得积分20
3秒前
化学废材发布了新的文献求助10
3秒前
化学废材发布了新的文献求助10
3秒前
化学废材发布了新的文献求助10
3秒前
5秒前
哈哈完成签到 ,获得积分10
5秒前
6秒前
Lin发布了新的文献求助10
6秒前
化学废材发布了新的文献求助10
7秒前
7秒前
化学废材发布了新的文献求助10
7秒前
化学废材发布了新的文献求助10
7秒前
8秒前
9秒前
10秒前
11秒前
化学废材发布了新的文献求助10
11秒前
化学废材发布了新的文献求助10
11秒前
化学废材发布了新的文献求助10
11秒前
12秒前
15秒前
lijing发布了新的文献求助10
15秒前
化学废材发布了新的文献求助10
15秒前
常裤子发布了新的文献求助10
16秒前
17秒前
HJJHJH发布了新的文献求助10
17秒前
ViVi水泥要干喽完成签到,获得积分10
19秒前
lijing完成签到,获得积分10
20秒前
20秒前
Lin完成签到,获得积分10
21秒前
21秒前
21秒前
饼太发布了新的文献求助10
23秒前
23秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
A Will for the Machine: Computerization, Automation, and the Arts in South Africa 400
Decentring Leadership 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7808415
求助须知:如何正确求助?哪些是违规求助? 9340903
关于积分的说明 20504200
捐赠科研通 7400656
什么是DOI,文献DOI怎么找? 3328820
关于科研通互助平台的介绍 2475533
邀请新用户注册赠送积分活动 2347140