Yannick Béjot1, Benoit Daubail2, Bénédicte Sensenbrenner2, Nicolas Legris2, Jérôme Durier2, Maurice Giroud2. 1. Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France. Electronic address: ybejot@yahoo.fr. 2. Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
Abstract
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.
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 strokepatients. Further studies are required to confirm this finding.
Authors: Daniel M Kobewka; Daniel McIsaac; Michaël Chassé; Kednapa Thavorn; Sunita Mulpuru; Luke T Lavallée; Shane English; Justin Presseau; Alan J Forster Journal: Syst Rev Date: 2017-01-17