Savadi-Oskouei D, Sadeghi-Bazargani H, Hashemilar M, DeAngelis T
Neuroscience Research Center, Tabriz University of Medical Sciences, Imam Reza University Hospital, Golgasht Ave., Tabriz, Iran.
Pak J Biol Sci. 2010 May 1;13(9):443-7. doi: 10.3923/pjbs.2010.443.447.
Symptomatological prediction of Intracerebral haemorrhage (ICH) mortality is a simple and effective method compared to pathological predictors. In this study we considered consciousness level as an easily measurable predictor and compared it to haemorrhage location, intraventricular penetration and haemorrhage size derived from Computerized Tomography (CT) to predict mortality using a parametric survival analysis model. Two hundred and thirty eight ICH patients from a neurology hospital ward were enrolled into this comparative study. Patient history was documented with respect to mortality and a questionnaire outlining background variables and medical history was completed for them. Consciousness level was clinically evaluated by a physician while haemorrhage size and location were determined via computerized tomographic scanning reports. Data were entered into the computer and analyzed according to the Weibull parametric survival analysis model using STATA 8 statistical software. Males constituted 47.1% of the 238 patients, 52.9% were females. The age range of the patients varied from 13 to 88 years, with a mean age of 62.4 +/- 13.6 (Mean +/- SD). Half of the patients survived more than 20 days. Using the Weibull regression model, the only significant independent symptomatological predictor of mortality was found to be the level of consciousness. Cumulative hazard during the 90 days was compared for different levels of consciousness. Application of Weibull to pathological predictors of ICH mortality showed that the two independent predictors were haemorrhage size and intraventricular penetration. Results of statistical modelling didn't provide evidence of priority for pathological predictors of survival compared to easily measurable levels of consciousness as a symptomatological predictor. Easily measurable symptoms of level of consciousness can be used as a survival predictor of stroke due to intra-cerebral haemorrhage when compared to pathological indicators.
与病理预测指标相比,脑出血(ICH)死亡率的症状学预测是一种简单有效的方法。在本研究中,我们将意识水平视为易于测量的预测指标,并将其与计算机断层扫描(CT)得出的出血部位、脑室穿透情况和出血大小进行比较,使用参数生存分析模型预测死亡率。来自一家神经内科医院病房的238例ICH患者被纳入这项比较研究。记录了患者的死亡病史,并为他们完成了一份概述背景变量和病史的问卷。意识水平由医生进行临床评估,而出血大小和部位则通过计算机断层扫描报告确定。数据输入计算机,并使用STATA 8统计软件根据威布尔参数生存分析模型进行分析。238例患者中男性占47.1%,女性占52.9%。患者年龄范围为13至88岁,平均年龄为62.4 +/- 13.6(均值 +/- 标准差)。一半的患者存活超过20天。使用威布尔回归模型,发现唯一显著的独立症状学死亡预测指标是意识水平。比较了不同意识水平在90天内的累积风险。将威布尔模型应用于ICH死亡率的病理预测指标,结果显示两个独立预测指标是出血大小和脑室穿透情况。统计建模结果没有提供证据表明与易于测量的意识水平这一症状学预测指标相比,病理生存预测指标具有优先性。与病理指标相比,易于测量的意识水平症状可作为脑内出血性卒中的生存预测指标。