Is Health-Related Quality of Life Improving After Stroke?
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Recent innovations in diagnosis, management, and rehabilitation have resulted in measurable improvements in clinical and functional outcomes after acute stroke. However, whether gains in health-related quality of life after stroke have also occurred is not well characterized. Using 2 Canadian population surveys, the purpose of this study was to identify changes in health-related quality of life in individuals with stroke from 1996 to 2005. METHODS: Data from the public use files of the National Population Health Survey, Cycle 2 (1996), and the Canadian Community Health Survey, Cycle 3.1. (2005), were used. A total of 847 individuals with stroke were included. Self-reported information on health status based on the Health Utilities Index Mark 3 was used to generate single-attribute and overall health-related quality of life scores. Analysis of covariance and multiple logistic regression were used to determine the relationship between survey year and poststroke impairment adjusting for demographic variables and clinical comorbidities. RESULTS: A statistically significant and clinically important reduction in mean overall Health Utilities Index Mark 3 scores was observed for respondents with stroke from 1996 to 2005. In addition, 2 of the 8 single-attribute Health Utilities Index Mark 3 domains showed a significant change between survey years. Significantly more individuals with stroke reported dexterity and cognitive impairment in 2005 compared with respondents in 1996, indicating reduced health-related quality of life for these domains. CONCLUSIONS: Despite improvements in medical management, quality of life is not improving after stroke in the Canadian population. These findings are useful to generate hypotheses about the impact of advances in management on quality of life after stroke and identify specific domains that may benefit from future study in stroke populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".