Population-based study of home-time by stroke type and correlation with modified Rankin score. (7th November 2017)

• Record Type: Journal Article
• Authors: Yu, Amy Y.X.; Rogers, Edwin; Wang, Meng; Sajobi, Tolulope T.; Coutts, Shelagh B.; Menon, Bijoy K.; Hill, Michael D.; Smith, Eric E.
• Is Part Of: Neurology. Volume 89:Number 19(2017)
• Publication Date: 2017-11-07
• Subjects: Neurology -- Periodicals; Neurology -- Periodicals; Neurologie -- Périodiques; 616.8
• DOI: 10.1212/WNL.0000000000004631
• Languages: English
• ISSNs: 0028-3878

Abstract

Abstract : Objective: To describe home-time, stratified by stroke type, in a complete population and to determine its correlation with modified Rankin Scale (mRS) scores. Methods: We used linked administrative data to derive home-time in all patients admitted for a cerebrovascular event in Alberta, Canada, between 2012 and 2016. Home-time is the number of days spent outside a health institution in the first 90 days after index hospitalization. We used negative binomial regression, adjusted for age, sex, Charlson comorbidity index, and hospital location, to determine the association between home-time and stroke type. In 552 patients enrolled in 4 acute ischemic stroke clinical trials, we used multivariable ordinal logistic regression analysis to determine the association between home-time and mRS score at 90 days. Results: Among 15, 644 patients (n = 10, 428 with ischemic stroke, n = 1, 415 with intracerebral hemorrhage, n = 760 with subarachnoid hemorrhage, n = 3, 041 with TIA), patients with TIA have the longest home-time, almost triple the number of days at home compared to patients with intracerebral hemorrhage (incidence rate ratio 2.85, 95% confidence interval [CI] 2.58–3.15). Among clinical trial ischemic stroke patients, longer home-time was associated with a lower mRS score at 90 days (adjusted common odds ratio 1.04, 95% CI 1.04–1.05). Conclusions: We showed that home-time is an objective and graded indicator that is correlated with disability after stroke. It is obtainable from administrative data, applicable to different stroke types, and a valuable outcome indicator in population-based health services research.