Tseng Hung-Pin, Lin Feng-Jenq, Chen Pi-Tzu, Mou Chih-Hsin, Lee Siu-Pak, Chang Chun-Yuan, Chen An-Chih, Liu Chung-Hsiang, Yeh Chung-Hsin, Tsai Song-Yen, Hsiao Yu-Jen, Lin Ching-Huang, Hsu Shih-Pin, Yu Shih-Chieh, Hsu Chung-Y, Sung Fung-Chang
Department of Neurology, Lotung Pohai Hospital, Lotung, Ilan, Taiwan.
Department of Applied Economics and Management, National Ilan University, Ilan, Taiwan.
J Stroke Cerebrovasc Dis. 2015 Jun;24(6):1179-86. doi: 10.1016/j.jstrokecerebrovasdis.2015.01.010. Epub 2015 Apr 3.
Discharge disposition planning is vital for poststroke patients. We investigated clinical factors associated with discharging patients to nursing homes, using the Taiwan Stroke Registry data collected from 39 major hospitals.
We randomly assigned 21,575 stroke inpatients registered from 2006 to 2008 into derivation and validation groups at a 3-to-1 ratio. We used the derivation group to develop a prediction model by measuring cumulative risk scores associated with potential predictors: age, sex, hypertension, diabetes mellitus, heart diseases, stroke history, snoring, main caregivers, stroke types, and National Institutes of Health Stroke Scale (NIHSS). Probability of nursing home care and odds ratio (OR) of nursing home care relative to home care by cumulative risk scores were measured for the prediction. The area under the receiver operating characteristic curve (AUROC) was used to assess the model discrimination against the validation group.
Except for hypertension, all remaining potential predictors were significant independent predictors associated with stroke patient disposition to nursing home care after discharge from hospitals. The risk sharply increased with age and NIHSS. Patients with a cumulative risk score of 15 or more had an OR of 86.4 for the nursing home disposition. The AUROC plots showed similar areas under curves for the derivation group (.86, 95% confidence interval [CI], .85-.87) and for the validation group (.84, 95% CI, .83-.86).
The cumulative risk score is an easy-to-estimate tool for preparing stroke patients and their family for disposition on discharge.
出院处置规划对中风患者至关重要。我们利用从39家主要医院收集的台湾中风登记数据,调查了与患者出院后入住疗养院相关的临床因素。
我们将2006年至2008年登记的21575名中风住院患者按3:1的比例随机分为推导组和验证组。我们使用推导组通过测量与潜在预测因素相关的累积风险评分来建立预测模型,这些因素包括年龄、性别、高血压、糖尿病、心脏病、中风病史、打鼾、主要照顾者、中风类型以及美国国立卫生研究院卒中量表(NIHSS)。通过累积风险评分测量入住疗养院护理的概率以及相对于居家护理的入住疗养院护理优势比(OR),以进行预测。采用受试者工作特征曲线下面积(AUROC)评估模型对验证组的区分能力。
除高血压外,所有其余潜在预测因素都是与中风患者出院后入住疗养院护理相关的显著独立预测因素。风险随年龄和NIHSS急剧增加。累积风险评分为15分或更高的患者入住疗养院处置的OR为86.4。AUROC图显示推导组(.86,95%置信区间[CI],.85-.87)和验证组(.84,95%CI,.83-.86)的曲线下面积相似。
累积风险评分是一种易于估计的工具,可帮助中风患者及其家属为出院处置做好准备。