An environmental scan of limb loss rehabilitation centers across Canada
Bibliographic record
Abstract
BACKGROUND: The clinical landscape of limb loss rehabilitation across Canada is poorly delineated, lacks standard rehabilitation guidelines, and is without a shared clinical database. OBJECTIVE: To address these gaps, the objective of the present study was to undertake an environmental scan of the rehabilitation centers across Canada that provide inpatient and/or outpatient services to the limb loss community. STUDY DESIGN: An environmental scan was conducted to describe the rehabilitation service structure, program services, and outcome measures of sites across Canada. METHODS: A survey was sent to 36 rehabilitation centers providing care to people with amputations. RESULTS: Of the 36 centers, 31 completed the survey (11 = Ontario; 8 = Quebec; 6 = British Columbia; 2 = Saskatchewan; 2 = New Brunswick; 1 = Alberta; 1 = Manitoba). Twenty-five provided both inpatient and outpatient services, 1 provided inpatient care only, and 5 provided only outpatient services. Interprofessional services were provided to a wide range of upper extremity amputation and lower extremity amputation patient populations. Range of motion was the most commonly collected outcome for both patients with upper extremity amputation and lower extremity amputation. With regard to prosthetics and orthotics fabrication, 9 of the sites had these services on-site while 15 had off-site fabricators, 6 had both, and 1 provided no response. CONCLUSIONS: Our findings highlight that limb loss rehabilitation and prosthetic care delivery is variable across Canada with respect to clinical team members, locations of services, and complementary services such as mental health treatments and peer support groups.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".