Development of Walking indicators to advance the quality of spinal cord injury rehabilitation: SCI-High Project
Bibliographic record
Abstract
Objective: To describe the development of structure, process and outcome indicators that will advance the quality of walking rehabilitation for Canadians with spinal cord injury or disease (SCI/D) by 2020.Method: A framework for the evaluation of the quality of walking rehabilitation was developed by experts in walking after SCI/D. A systematic literature review identified factors influencing walking outcomes and potential walking indicators. A Driver diagram analysis summarized the factors affecting walking outcomes and subsequently informed the selection of structure and process indicators. Psychometric properties and clinical utility of potential walking indicators were considered during the selection of outcome indicators.Results: The structure indicator is the number of physical therapists using evidence-based walking interventions per number of ambulatory individuals with SCI/D. The process indicator is the number of received hours of walking interventions during inpatient rehabilitation per number of ambulatory individuals with SCI/D. The intermediary outcome indicator, which is collected at discharge from inpatient rehabilitation, is either the modified Timed Up and Go or the 10-Meter Walk Test, the choice of measure is dictated by the stage of walking recovery, as defined by the Standing and Walking Assessment Tool. The final outcome indicator, collected at 18 months post-discharge, is the Spinal Cord Independence Measure III-Mobility subscale.Conclusion: The selected indicators align with current clinical practice in Canada. The indicators will direct the timing and enhance the volume of walking therapy delivered, to ultimately increase the proportion of patients who achieve their walking potential by 18 months post-rehabilitation.
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 | 0.091 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 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".