iScore for Predicting Institutional Care after Ischemic Stroke: A Population-Based Study

• Published in: Journal of stroke and cerebrovascular diseases 2015-03, Vol.24 (3), p.694-698
• Main Authors: Béjot, Yannick, MD, PhD, Daubail, Benoit, MD, Sensenbrenner, Bénédicte, MD, Legris, Nicolas, MD, Durier, Jérôme, MSc, Giroud, Maurice, MD, PhD
• Format: Article
• Language: English
• Subjects: Aged; Aged, 80 and over; Brain Ischemia - diagnosis; Brain Ischemia - epidemiology; Brain Ischemia - physiopathology; Brain Ischemia - psychology; Brain Ischemia - therapy; Cardiovascular; Decision Support Techniques; discharge planning; epidemiology; Female; France - epidemiology; Humans; Logistic Models; Male; Middle Aged; Neurology; Nursing Homes; Patient Care Planning; Patient Discharge; Predictive Value of Tests; predictors; Prognosis; Registries; Rehabilitation Centers; Risk Assessment; Risk Factors; Stroke; Stroke - diagnosis; Stroke - epidemiology; Stroke - physiopathology; Stroke - psychology; Stroke - surgery; stroke outcome; stroke registry
• ISSN: 1052-3057; 1532-8511
• DOI: 10.1016/j.jstrokecerebrovasdis.2014.11.010

Background We assessed whether the iScore could predict the need for poststroke institutional care. Methods 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. Results 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). Conclusions 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.