Stroke:天坛医院研发新量表用于预测脑梗死后相关院内肺炎

2013-03-21 geniusgodyu 丁香园

天坛医院研发了新的卒中相关肺炎预测量表 急性缺血性卒中常导致患者吞咽困难、进食呛咳、肢体瘫痪卧床,易发生肺部感染。为此,天坛医院的王拥军教授等人进行了一项研究,研发一种新的风险评分(急性缺血性卒中相关肺炎评分AIS-APS)用以预测急性缺血性卒中住院患者出现卒中相关肺炎的风险,并加以验证。研究结果在线发表在2013年3月12日的Stroke杂志上。研究结果显示:AIS-APS是预测急性缺血性


天坛医院研发了新的卒中相关肺炎预测量表
急性缺血性卒中常导致患者吞咽困难、进食呛咳、肢体瘫痪卧床,易发生肺部感染。为此,天坛医院的王拥军教授等人进行了一项研究,研发一种新的风险评分(急性缺血性卒中相关肺炎评分AIS-APS)用以预测急性缺血性卒中住院患者出现卒中相关肺炎的风险,并加以验证。研究结果在线发表在2013年3月12日的Stroke杂志上。研究结果显示:AIS-APS是预测急性缺血性卒中后卒中相关院内肺炎的实用风险评分量表。
AI-APS是以中国国家卒中注册为基础研发的。研究中将符合纳入标准的患者分入推导组(60%)和内部验证组(40%)。使用中国前瞻性颅内动脉粥样硬化研究进行外部验证。使用多变量logistic回归获得急性缺血性卒中后院内卒中相关肺炎的独立危险因素,使用β系数产生AIS-APS的得分点系统。分别使用受者操作特性曲线的曲线下面积和Hosmer-Lemeshow拟合优度检验评估模型的区分度及校正情况。
研究结果显示:推导组(n=8820)、内部验证组(n=5882)和外部验证组(n=3037)的总体急性缺血性卒中后卒中相关院内肺炎的发生率分别为11.4%,11.3%和7.3%。34分的AIS-APS 量表根据一系列独立预测因素研发,这些独立预测因素包括:年龄、心房颤动史、梗阻性心脏衰竭、慢性阻塞性肺疾病、吸烟、卒中前自理能力、吞咽困难、入院时的NIHSS得分、Glasgow昏迷量表得分、卒中亚型(Oxfordshire)及血糖。AIS-APS对内部验证组(0.785; 95%可信区间:0.766–0.803)和外部验证组(0.792; 95%可信区间:0.761–0.823)显示出良好的区分度(受者操作特性曲线下面积)。AIS-APS在内部验证组(P=0.22)和外部验证组(P=0.30)中校正良好(Hosmer–Lemeshow 检验)。在和之前的3个评分量表进行比较时发现:对于急性缺血性卒中后卒中相关院内肺炎,AIS-APS的区分度显著更优(所有的P<0.0001)。
该研究发现:AIS-APS是预测急性缺血性卒中后卒中相关院内肺炎的实用风险评分量表。

Background and Purpose
To develop and validate a risk score (acute ischemic stroke-associated pneumonia score [AIS-APS]) for predicting in-hospital stroke-associated pneumonia (SAP) after AIS.
Methods
The AIS-APS was developed based on the China National Stroke Registry, in which eligible patients were randomly classified into derivation (60%) and internal validation cohort (40%). External validation was performed using the prospective Chinese Intracranial Atherosclerosis Study. Independent predictors of in-hospital SAP after AIS were obtained using multivariable logistic regression, and β-coefficients were used to generate point scoring system of the AIS-APS. The area under the receiver operating characteristic curve and the Hosmer–Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively.
Results
The overall in-hospital SAP after AIS was 11.4%, 11.3%, and 7.3% in the derivation (n=8820), internal (n=5882) and external (n=3037) validation cohort, respectively. A 34-point AIS-APS was developed from the set of independent predictors including age, history of atrial fibrillation, congestive heart failure, chronic obstructive pulmonary disease and current smoking, prestroke dependence, dysphagia, admission National Institutes of Health Stroke Scale score, Glasgow Coma Scale score, stroke subtype (Oxfordshire), and blood glucose. The AIS-APS showed good discrimination (area under the receiver operating characteristic curve) in the internal (0.785; 95% confidence interval, 0.766–0.803) and external (0.792; 95% confidence interval, 0.761–0.823) validation cohort. The AIS-APS was well calibrated (Hosmer–Lemeshow test) in the internal (P=0.22) and external (P=0.30) validation cohort. When compared with 3 prior scores, the AIS-APS showed significantly better discrimination with regard to in-hospital SAP after AIS (all P<0.0001).
Conclusions
The AIS-APS is a valid risk score for predicting in-hospital SAP after AIS.

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    2013-03-30 匿名用户

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    2013-03-23 lqvr
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    2013-03-23 karmond

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