用于确定急性脑出血血肿扩大风险的临床预测算法（BRAIN）
Clinical prediction algorithm (BRAIN) to determine risk of hematoma growth in acute intracerebral hemorrhage.
作者信息
Wang Xia, Arima Hisatomi, Al-Shahi Salman Rustam, Woodward Mark, Heeley Emma, Stapf Christian, Lavados Pablo M, Robinson Thompson, Huang Yining, Wang Jiguang, Delcourt Candice, Anderson Craig S
机构信息
From the The George Institute for Global Health, University of Sydney, Sydney, Australia (X.W., H.A., M.W., E.H., C.D., C.S.A.); Royal Prince Alfred Hospital, Sydney, Australia (X.W., H.A., M.W., E.H., C.D., C.S.A.); Division of Clinical Neurosciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK (R.A.-S.S.); Department of Neurology, APHP-HôpitalLariboisière and DHU NeuroVasc Paris-Sorbonne, Univ Paris Diderot-Sorbonne Paris Cité, Paris, France (C.S.); Servicio de Neurología, Departamento de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago, Chile (P.M.L.); Universidad de Chile, Santiago, Chile (P.M.L.); Department of Cardiovascular Sciences and NIHR Biomedical Research Unit in Cardiovascular Disease, University of Leicester, Leicester, UK (T.R.); Department of Neurology, Peking University First Hospital, Beijing, China (Y.H.); and The Shanghai Institute of Hypertension, Rui Jin Hospital, Shanghai Jiaotong University, Shanghai, China (J.W.).
出版信息
Stroke. 2015 Feb;46(2):376-81. doi: 10.1161/STROKEAHA.114.006910. Epub 2014 Dec 11.
BACKGROUND AND PURPOSE
We developed and validated a simple algorithm to predict the risk of hematoma growth in acute spontaneous intracerebral hemorrhage (ICH) to better inform clinicians and researchers in their efforts to improve outcomes for patients.
METHODS
We analyzed data from the computed tomography substudies of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trials (INTERACT1 and 2, respectively). The study group was divided into a derivation cohort (INTERACT2, n=964) and a validation cohort (INTERACT1, n=346). Multivariable logistic regression was used to identify factors associated with clinically significant (≥6 mL) increase in hematoma volume at 24 hours after symptom onset. A parsimonious risk score was developed on the basis of regression coefficients derived from the logistic model.
RESULTS
A 24-point BRAIN score was derived from INTERACT2 (C-statistic, 0.73) based on baseline ICH volume (mL per score, ≤10=0, 10-20=5, >20=7), recurrent ICH (yes=4), anticoagulation with warfarin at symptom onset (yes=6), intraventricular extension (yes=2), and number of hours to baseline computed tomography from symptom onset (≤1=5, 1-2=4, 2-3=3, 3-4=2, 4-5=1, >5=0) predicted the probability of ICH growth (ranging from 3.4% for 0 point to 85.8% for 24 points) with good discrimination (C-statistic, 0.73) and calibration (Hosmer-Lemeshow P=0.82) in INTERACT1.
CONCLUSIONS
The simple BRAIN score predicts the probability of hematoma growth in ICH. This could be used to improve risk stratification for research and clinical practice.
CLINICAL TRIAL REGISTRATION URL
http://www.clinicaltrials.gov. Unique identifier: NCT00226096 and NCT00716079.
背景与目的
我们开发并验证了一种简单算法，用于预测急性自发性脑出血（ICH）时血肿扩大的风险，以便更好地为临床医生和研究人员提供信息，助力他们改善患者预后。
方法
我们分析了急性脑出血强化降压试验（分别为INTERACT1和INTERACT2）试点阶段和主要阶段的计算机断层扫描子研究数据。研究组分为推导队列（INTERACT2，n = 964）和验证队列（INTERACT1，n = 346）。采用多变量逻辑回归来确定与症状发作后24小时血肿体积临床显著增加（≥6 mL）相关的因素。基于从逻辑模型得出的回归系数，开发了一个简约风险评分。
结果
基于基线ICH体积（每分毫升数，≤10 = 0，10 - 20 = 5，>20 = 7）、复发性ICH（是 = 4）、症状发作时使用华法林抗凝（是 = 6）、脑室内扩展（是 = 2）以及从症状发作到基线计算机断层扫描的小时数（≤1 = 5，1 - 2 = 4，2 - 3 = 3，3 - 4 = 2，4 - 5 = 1，>5 = 0），从INTERACT2得出了一个24分的BRAIN评分（C统计量，0.73），该评分预测了ICH扩大的概率（范围从0分的3.4%到24分的85.8%），在INTERACT1中具有良好的区分度（C统计量，0.73）和校准度（Hosmer - Lemeshow P = 0.82）。
结论
简单的BRAIN评分可预测ICH时血肿扩大的概率。这可用于改善研究和临床实践中的风险分层。
临床试验注册网址
http://www.clinicaltrials.gov。唯一标识符：NCT00226096和NCT00716079。
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