title: iScore for predicting institutional care after ischemic stroke: a population-based study.
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.
authors.affiliation: Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France. Electronic address: ybejot@yahoo.fr.
authors.forename: Yannick
authors.initials: Y
authors.lastname: Béjot
authors.affiliation: Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
authors.forename: Benoit
authors.initials: B
authors.lastname: Daubail
authors.affiliation: Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
authors.forename: Bénédicte
authors.initials: B
authors.lastname: Sensenbrenner
authors.affiliation: Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Legris
authors.affiliation: Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Durier
authors.affiliation: Dijon Stroke Registry, EA4184, Department of Neurology, University Hospital and Medical School of Dijon, University of Burgundy, Dijon, France.
authors.forename: Maurice
authors.initials: M
authors.lastname: Giroud
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002545:Brain Ischemia / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology / Q000523:psychology / Q000628:therapy*; D003661:Decision Support Techniques; D005260:Female; D005602:France / Q000453:epidemiology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009735:Nursing Homes; D010347:Patient Care Planning; D010351:Patient Discharge; D011237:Predictive Value of Tests; D011379:Prognosis; D012042:Registries; D012047:Rehabilitation Centers; D018570:Risk Assessment; D012307:Risk Factors; D020521:Stroke / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology / Q000523:psychology / Q000601:surgery*
keywords: Stroke; discharge planning; epidemiology; predictors; stroke outcome; stroke registry