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Updated: Feb 7, 2026

Gathering Self-Initiated Rat Behavioral Data to Characterize Post-Stroke Deficits
Published on: March 15, 2024
Dependency and health utilities in stroke: Data to inform cost-effectiveness analyses
Myzoon Ali1, Rachael MacIsaac1, Terence J Quinn2
1Institutes of Cardiovascular and Medical Sciences, Queen Elizabeth University Hospital, Glasgow, UK.
Introduction:
Health utilities (HU) assign preference weights to specific health states and are required for cost-effectiveness analyses. Existing HU for stroke inadequately reflect the spectrum of post-stroke disability. Using international stroke trial data, we calculated HU stratified by disability to improve precision in future cost-effectiveness analyses.
Materials And Methods:
We used European Quality of Life Score (EQ-5D-3L) data from the Virtual International Stroke Trials Archive (VISTA) to calculate HU, stratified by modified Rankin Scale scores (mRS) at 3 months. We applied published value sets to generate HU, and validated these using ordinary least squares regression, adjusting for age and baseline National Institutes of Health Stroke Scale (NIHSS) scores.
Results:
We included 3858 patients with acute ischemic stroke in our analysis (mean age: 67.5 ± 12.5, baseline NIHSS: 12 ± 5). We derived HU using value sets from 13 countries and observed significant international variation in HU distributions (Wilcoxon signed-rank test p < 0.0001, compared with UK values). For mRS = 0, mean HU ranged from 0.88 to 0.95; for mRS = 5, mean HU ranged from -0.48 to 0.22. OLS regression generated comparable HU (for mRS = 0, HU ranged from 0.9 to 0.95; for mRS = 5, HU ranged from -0.33 to 0.15). Patients' mRS scores at 3 months accounted for 65-71% of variation in the generated HU.
Conclusion:
We have generated HU stratified by dependency level, using a common trial endpoint, and describing expected variability when applying diverse value sets to an international population. These will improve future cost-effectiveness analyses. However, care should be taken to select appropriate value sets.
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