Anderson C S, Jamrozik K D, Broadhurst R J, Stewart-Wynne E G
Department of Medicine, Flinders University of South Australia, Bedford Park.
Stroke. 1994 Oct;25(10):1935-44. doi: 10.1161/01.str.25.10.1935.
Few studies have evaluated the factors influencing or predicting long-term survival after stroke in an unselected series of patients in whom the underlying cerebrovascular pathology is clearly defined. Moreover, the relative importance of risk factors for stroke, including sociodemographic and premorbid variables, has not been described in detail.
The study cohort consisted of 492 patients with stroke who were registered with a population-based study of acute cerebrovascular disease undertaken in Perth, Western Australia, during an 18-month period in 1989 and 1990. Objective evidence of the pathological basis of the stroke was obtained in 86% of cases, and all deaths among patients during a follow-up of 1 year were reviewed.
One hundred twenty patients (24%) died within 28 days of the onset of stroke. Among the different subtypes of stroke, the 1-year case fatality (mean, 38%) varied from 6% and 16% for boundary zone infarction and lacunar infarction, respectively, to 42% and 46% for subarachnoid hemorrhage and primary intracerebral hemorrhage, respectively. Using Cox proportional-hazards analysis, a predictive model was developed on 321 patients with acute stroke (test sample). The best model contained five baseline variables that were independent predictors of death within 1 year: coma (relative risk [RR], 3.0; 95% confidence interval [CI], 1.1 to 8.4), urinary incontinence (RR, 3.9; 95% CI, 1.4 to 10.6), cardiac failure (RR, 6.5; 95% CI, 2.8 to 15.1), severe paresis (RR, 4.9; 95% CI, 1.6 to 15.5), and atrial fibrillation (RR, 2.0; 95% CI, 1.1 to 3.5). The sensitivity, specificity, and negative predictive value of this model for predicting death were 90%, 83%, and 95%, respectively. When applied to a second randomly selected validation sample of 171 events, sensitivity was 94%, specificity 62%, and negative predictive value 92%, indicating stability of the model.
Although the case fatality, timing, and cause of death vary considerably among the different pathological subtypes of stroke, simple clinical measures that reflect the severity of the neurological deficit and associated cardiac disease at onset independently predict death by 1 year and may help to direct management.
在一系列未经过筛选且明确界定潜在脑血管病理状况的患者中,很少有研究评估影响或预测卒中后长期生存的因素。此外,包括社会人口统计学和病前变量在内的卒中危险因素的相对重要性尚未得到详细描述。
研究队列包括492例卒中患者,这些患者是在1989年和1990年为期18个月的西澳大利亚珀斯开展的一项基于人群的急性脑血管病研究中登记的。86%的病例获得了卒中病理基础的客观证据,并且对患者随访1年期间的所有死亡情况进行了回顾。
120例患者(24%)在卒中发病后28天内死亡。在不同亚型的卒中中,1年病死率(平均38%)从边界区梗死和腔隙性梗死的6%和16%,分别到蛛网膜下腔出血和原发性脑出血的42%和46%不等。使用Cox比例风险分析,在321例急性卒中患者(测试样本)中建立了一个预测模型。最佳模型包含五个基线变量,这些变量是1年内死亡的独立预测因素:昏迷(相对风险[RR],3.0;95%置信区间[CI],1.1至8.4)、尿失禁(RR,3.9;95%CI,1.4至10.6)、心力衰竭(RR,6.5;95%CI,2.8至15.1)、严重瘫痪(RR,4.9;95%CI,1.6至15.5)和心房颤动(RR,2.0;95%CI,1.1至3.5)。该模型预测死亡的敏感性、特异性和阴性预测值分别为90%、83%和95%。当应用于第二个随机选择的171例事件的验证样本时,敏感性为94%,特异性为62%,阴性预测值为92%,表明该模型具有稳定性。
尽管不同病理亚型卒中的病死率、死亡时间和原因差异很大,但反映发病时神经功能缺损严重程度和相关心脏病的简单临床指标可独立预测1年内的死亡,并可能有助于指导治疗。