Béjot Yannick, Daubail Benoit, Sensenbrenner Bénédicte, Legris Nicolas, Durier Jérôme, Giroud Maurice
Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
J Stroke Cerebrovasc Dis. 2015 Mar;24(3):694-8. doi: 10.1016/j.jstrokecerebrovasdis.2014.11.010. Epub 2015 Jan 16.
We assessed whether the iScore could predict the need for poststroke institutional care.
Patients with acute ischemic stroke living in Dijon, France, were recorded between 2006 and 2011, using a population-based stroke registry. The iScore was calculated for each patient. A logistic regression model was used to assess the performance of the iScore for predicting the need for placement in a care institution. The discrimination and calibration of the model were assessed using the c statistic and the Hosmer-Lemeshow goodness-of-fit test, respectively.
Of the 1199 patients recorded, 124 were excluded because of early death and 95 because of missing for variables included in the iScore. Of the remaining 980 patients, 522 (53.3%) returned home and 458 (46.7%) required placement in a care institution. The median iScore was 123 (interquartile range, 97-148), and the proportion of patients who required placement in a care institution increased with each quintile of risk score. The discrimination of the model was good with a c statistic of .75 (95% confidence interval, .72-.78), as was calibration (P = .35).
The iScore could be useful for predicting the need for placement in a care institution in ischemic stroke patients. Further studies are required to confirm this finding.
我们评估了iScore是否能够预测中风后机构护理的需求。
2006年至2011年期间，使用基于人群的中风登记系统记录了居住在法国第戎的急性缺血性中风患者。为每位患者计算iScore。使用逻辑回归模型评估iScore预测入住护理机构需求的性能。分别使用c统计量和Hosmer-Lemeshow拟合优度检验评估模型的辨别力和校准度。
在记录的1199例患者中，124例因早期死亡被排除，95例因iScore中包含的变量缺失被排除。在其余980例患者中，522例（53.3%）回家，458例（46.7%）需要入住护理机构。iScore的中位数为123（四分位间距，97-148），需要入住护理机构的患者比例随风险评分的每一个五分位数增加。模型的辨别力良好，c统计量为0.75（95%置信区间，0.72-0.78），校准度也良好（P = 0.35）。
iScore可能有助于预测缺血性中风患者入住护理机构的需求。需要进一步研究来证实这一发现。
