Stroke Rehabilitation: An International Perspective
Bibliographic record
Abstract
There is a revolution underway in stroke rehabilitation. International comparative studies coupled with an impressive evidence base have provided a platform from which an ideal system for stroke rehabilitation can be envisioned. Using the concepts of structure and process of care, different systems of stroke rehabilitation can be compared and evaluated against best evidence. Two structures of care are examined: specialized interdisciplinary stroke rehabilitation units and outpatient programs. Although specialized interdisciplinary stroke rehabilitation units remain the "gold standard" of care, access to them is often limited. Outpatient programs are essential to stroke rehabilitation systems of care; however, while some countries are investing in outpatient programs, others are scaling back. Even though structures of care have been shown to affect processes of care, it is the processes of care that have proven to be more influential in altering patient outcomes. Four key processes of care are examined: time to admission, intensity of therapy, task-specific therapy, and discharge planning. Within international stroke rehabilitation systems, differences in these processes have resulted in significant differences in outcomes. This allows for "real-world" comparisons of how differing processes affect patient outcomes. Those systems whose structures and processes of care best reflect current best evidence appear to achieve better outcomes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".