Developing clinical practice guidelines for physiotherapists working with people with inherited bleeding disorders
Bibliographic record
Abstract
INTRODUCTION: Several bleeding disorders are characterized by haemorrhage into joints and muscles. These conditions are best managed by interdisciplinary teams that include physiotherapists. In 1997, physiotherapists from haemophilia treatment centres in Canada formed the Canadian Physiotherapists in Hemophilia Care (CPHC). The guiding principles of the CPHC reflect a commitment to evidence-based practice, education and collaboration. AIM: To describe the process used by CPHC to develop evidence-based clinical practice guidelines to inform best practice, guide decision-making and help educate physiotherapists, students, and other team members about the physiotherapy management of people with bleeding disorders. METHODS: We followed the procedures outlined in the American Physical Therapy Association's Clinical Practice Guideline Process Manual (2018). Namely, we selected a working group, determined the scope of the guidelines, performed a literature search, selected and appraised the evidence, drafted the guidelines as practice statements, assigned a strength of recommendation to each practice statement and disseminated the guidelines. RESULTS: Thirty-nine practice statements were developed in nine practice areas. Strength of evidence was strong for two statements, moderate for one and weak for three. The remainder were graded as theoretical or best practice. CONCLUSION: To our knowledge, these are the first evidence-based clinical practice guidelines that cover all aspects of physiotherapy management of people with bleeding disorders. Some areas, such as exercise and manual therapy, have been well investigated. However, the overall low levels of evidence and low strengths of recommendations highlight the need for more rigorous research with this population.
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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 | 0.105 | 0.345 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.014 | 0.012 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".