Rehabilitation of proximal humerus fractures: An environmental scan of Canadian physiotherapy practice patterns
Bibliographic record
Abstract
Background: Proximal humerus fractures (PHFs) are common injuries particularly in older adults. Evidence-based protocols for PHF rehabilitation are lacking and physiotherapists use a variety of interventions. Purpose: To determine practice patterns and perceptions of physiotherapists who treat adults with PHF in Ontario, Canada. Method: A paper and pencil survey asking about respondent demographics and management of Neer Group 1 (minimally/nondisplaced) and complex (displaced 3- and 4-part) PHF was mailed to 875 randomly selected physiotherapists who were registered with the College of Physiotherapists of Ontario in 2013/2014 and working in practice areas likely to be accessed by adults with PHF. Results: The response rate was low (10%); 83 physiotherapists completed the survey - 80% had experience managing PHF. Respondents treated 1-5 individuals with PHF annually; more treated Neer Group 1 PHF (89%) than complex PHF (68%). Most individuals with PHF were older than 60 years (64%), female (76%) and accessed physiotherapy through a doctor’s referral (91%) more than 1 month post injury (33%). Main findings: Physiotherapists manage PHF using multi-component interventions and a minimum of 76% include the following elements: education and progression of passive, active assisted, active range of motion exercises and muscle retraining to build coordination and strength. Use of other elements was variable. The main factors influencing the treatment plan were the ability of the individual with PHF to comply, bone quality, and fracture type. Most respondents were unsure that there is sufficient PHF rehabilitation literature to guide treatment. Conclusions:This environmental scan is the first North American study to document practice patterns and attitudes of physiotherapists providing PHF rehabilitation. Elements used by physiotherapists in Ontario treating small numbers of individuals with Neer Group 1 or complex PHFs each year align well with the limited PHF rehabilitation literature available. Potential implications:Multi-disciplinary collaborations to design and conduct large, high quality, multi-centre prognostic studies and RCTs that evaluate the effectiveness of key aspects of non-surgical PHF rehabilitation in various patient groups are needed. Meanwhile, consensus guidelines should be developed in the context of region-specific physiotherapy service models to inform best practice in PHF rehabilitation management.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".