Myint Phyo Kyaw, Clark Allan B, Kwok Chun Shing, Davis John, Durairaj Ramesh, Dixit Anand K, Sharma Anil K, Ford Gary A, Potter John F
Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, Norfolk, UK; Stroke Research Group, Norfolk and Norwich University Hospital, Norwich, Norfolk, UK; Clinical Gerontology Unit, University of Cambridge, Cambridge, Cambridgeshire, UK.
Int J Stroke. 2014 Apr;9(3):278-83. doi: 10.1111/ijs.12088. Epub 2013 Jul 9.
Previous prognostic scoring systems in predicting stroke mortality are complex, require multiple measures that vary with time and failed to produce a simple scoring system.
AIMS/HYPOTHESIS: The study aims to derive and internally validate a stroke prognostic scoring system to predict early mortality and hospital length of stay.
Data from a U.K. multicenter stroke register were examined (1997-2010). Using a prior hypothesis based on our and others observations, we selected five patient-related factors (age, gender, stroke subtype, clinical classification, and prestroke disability) as candidate prognostic indicators. An 8-point score was derived based on multiple logistic regression model using four out of five variables. Performance of the model was assessed by plotting the estimated probability of in-hospital death against the actual probability by testing for overfitting (calibration) and area under the curve methods (discrimination).
The total sample consisted of 12,355 acute stroke patients (ischemic stroke 91.0%). The score predicted both in-patient and seven-day mortality. The crude in-patient mortality were 1.57%, 4.02%, 10.65%, 21.41%, 46.60%, 62.72%, and 75.81% for those who scored 0, 1, 2, 3, 4, 5, and 6, respectively. The calibration of the model revealed no evidence of overfitting (estimated overfitting 0.001). The area under the curve values for both in-hospital and seven-day mortality were 0.79. The score predicted length of stay with a higher score was associated with longer median length of stay in those discharged alive and shorter median length of stay in those who died (P for both <0.001).
A simple 8-point clinical score is highly predictive of acute stroke mortality and length of hospital stay. It could be used as prognostic tool in service planning and also to risk-stratify patients to use these outcomes as markers of stroke care quality across institutions.
以往用于预测卒中死亡率的预后评分系统较为复杂,需要多种随时间变化的测量指标,且未能产生一个简单的评分系统。
目的/假设:本研究旨在推导并进行内部验证一个卒中预后评分系统,以预测早期死亡率和住院时间。
研究了来自英国多中心卒中登记处的数据(1997 - 2010年)。基于我们自己和他人的观察结果提出一个先验假设,我们选择了五个与患者相关的因素(年龄、性别、卒中亚型、临床分类和卒中前残疾状况)作为候选预后指标。使用五个变量中的四个,基于多元逻辑回归模型得出一个8分制评分。通过绘制估计的院内死亡概率与实际概率的关系图,采用过拟合检验(校准)和曲线下面积法(区分度)来评估模型的性能。
总样本包括12355例急性卒中患者(缺血性卒中占91.0%)。该评分可预测住院期间和七天死亡率。评分为0、1、2、3、4、5和6分的患者,其粗住院死亡率分别为1.57%、4.02%、10.65%、21.41%、46.60%、62.72%和75.81%。模型校准显示没有过拟合的证据(估计过拟合为0.001)。院内和七天死亡率的曲线下面积值均为0.79。该评分可预测住院时间,评分越高,存活出院者的中位住院时间越长,死亡者的中位住院时间越短(两者P值均<0.001)。
一个简单的8分制临床评分对急性卒中死亡率和住院时间具有高度预测性。它可作为服务规划中的预后工具,也可用于对患者进行风险分层,将这些结果用作各机构卒中护理质量的指标。