A.05 Five-year clinical and health economic outcomes in patients with late functional improvement post-stroke: A population-based cohort study
Bibliographic record
Abstract
Background: We recently demonstrated that late functional improvement between 3-12 months post-stroke occurs in about one-fourth of patients with ischaemic stroke. It is unknown whether this improvement is associated with better long-term clinical or health-economic outcomes. Methods: In a prospective, population-based cohort of 1-year ischaemic stroke survivors (Oxford Vascular Study;2002-2014), we determined changes in functional status (modified Rankin Scale[mRS], Rivermead Mobility Index[RMI], Barthel Index[BI]) from 3-12 months post-stroke. We examined the association of late improvement (by ≥1 mRS grades, ≥1 RMI points, and/or ≥2 BI points) with 5-year mortality, institutionalization (Cox regressions), and health/social-care costs (generalized linear models), adjusted for age/sex/3-month disability/stroke subtype. Results: Among 1,288 1-year survivors, 1,135 had 3-month mRS>0, with 319(28.1%) demonstrating late improvement. 1-year survivors with late mRS improvement had lower 5-year mortality (aHR:0.68,95%CI 0.51-0.91,p=0.009), institutionalization (aHR:0.48,0.33-0.72,p<0.001), and costs (margin -$17,369,-25,271 to -9,469,p<0.001). These associations remained on excluding patients with recurrent strokes during follow-up (e.g. 5-year death/institutionalization aHR:0.59,0.44-0.79,p<0.001) and on examining late improvement per RMI and/or BI (e.g. 5-year death/institutionalization aHR:0.67,0.53-0.84,p=0.001). Conclusions: Late functional improvement post-stroke is associated with lower 5-year mortality, institutionalization, and costs. These findings should motivate patients and clinicians to maximize late recovery and encourage payers to consider access to rehabilitative services for at least 1-year post-stroke.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".