Health State Utility Values in People With Stroke: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background Health state utility values are commonly used to provide summary measures of health‐related quality of life in studies of stroke. Contemporaneous summaries are needed as a benchmark to contextualize future observational studies and inform the effectiveness of interventions aimed at improving post‐stroke quality of life. Methods and Results We conducted a systematic search of the literature using Medline, EMBASE, and Web of Science from January 1995 until October 2020 using search terms for stroke, health‐related quality of life, and indirect health utility metrics. We calculated pooled estimates of health utility values for EQ‐5D‐3L, EQ‐5D‐5L, AQoL, HUI2, HUI3, 15D, and SF‐6D using random effects models. For the EQ‐5D‐3L we conducted stratified meta‐analyses and meta‐regression by key subgroups. We screened 14 251 abstracts and 111 studies met our inclusion criteria (sample size range 11 to 12 447). EQ‐5D‐3L was reported in 78% of studies (study n=87; patient n=56 976). The pooled estimate for EQ‐5D‐3L at ≥3 months following stroke was 0.65 (95% CI, 0.63–0.67), which was ≈20% below population norms. There was high heterogeneity (I 2 >90%) between studies, and estimates differed by study size, case definition of stroke, and country of study. Women, older individuals, those with hemorrhagic stroke, and patients prior to discharge had lower pooled EQ‐5D‐3L estimates. Conclusions Pooled estimates of health utility for stroke survivors were substantially below population averages. We provide reference values for health utility in stroke to support future clinical and economic studies and identify subgroups with lower healthy utility. Registration URL: https://www.crd.york.ac.uk/prospero/ . Unique Identifier: CRD42020215942.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.064 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".