PREDICTING SURVIVAL FOR 1 YEAR AMONG DIFFERENT SUBTYPES OF STROKE - RESULTS FROM THE PERTH-COMMUNITY-STROKE STUDY
PREDICTING SURVIVAL FOR 1 YEAR AMONG DIFFERENT SUBTYPES OF STROKE - RESULTS FROM THE PERTH-COMMUNITY-STROKE STUDY
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DOI：
10.1161/01.str.25.10.1935
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发表时间：
1994-10-01
期刊：
影响因子：
8.3
通讯作者：
STEWARTWYNNE, EG
中科院分区：
文献类型：
--
作者：
ANDERSON, CS;JAMROZIK, KD;STEWARTWYNNE, EG
研究背景与目的很少有研究评估影响或预测脑卒中后长期生存的因素，这些患者的基础脑血管病变明确。此外，中风的危险因素，包括社会人口统计学和发病前变量的相对重要性，还没有被详细描述。方法该研究队列包括492例中风患者谁登记的人口为基础的研究急性脑血管疾病进行了在珀斯，西澳大利亚州，在18个月的时间在1989年和1990年。中风的病理基础的客观证据中获得的86%的情况下，和所有的死亡患者在随访1年reviewed.Results 120例（24%）中风发病后28天内死亡。在不同亚型的卒中中，1年病死率（平均38%）从交界区梗死和腔隙性梗死的6%和16%分别变化到蛛网膜下腔出血和原发性脑出血的42%和46%。采用考克斯比例风险分析，对321例急性卒中患者（测试样本）建立了预测模型。最佳模型包含5个基线变量，这些变量是1年内死亡的独立预测因子：（相对风险[RR]，3.0; 95%置信区间[CI]，1.1 - 8.4），尿失禁（RR，3.9; 95% CI，1.4 - 10.6），心力衰竭（RR，6.5; 95% CI，2.8 - 15.1）、重度轻瘫（RR，4.9; 95% CI，1.6 - 15.5）和房颤（RR，2.0; 95% CI，1.1 - 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验证样本的171个事件，灵敏度为94%，特异性62%，和阴性预测值92%，表明stabilityofmodel.Conclusions虽然病死率，时间，死亡原因之间的不同病理亚型的中风，反映神经功能缺损和相关心脏病发作时严重程度的简单临床指标可独立预测1年内的死亡，并有助于指导治疗。
Background oud Purpose 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.Methods 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.Results 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.Conclusions 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.