Consensus-based recommendations for the rehabilitation of children with arthrogryposis multiplex congenita: an integrated knowledge translation approach
Bibliographic record
Abstract
BACKGROUND: Arthrogryposis multiplex congenita (AMC) is a group of rare disorders characterized by multiple joint contractures present at birth. Early rehabilitation is essential to minimize joint contractures and maximize autonomy and participation among individuals with AMC. However, there is little robust scientific evidence to inform best practice. This project aimed to develop consensus-based recommendations for the rehabilitation management of children with AMC in the following priority areas: early intervention and motor development, muscle and joint function, orthotics, mobility, participation in areas of life, pain, psychosocial wellbeing, and perioperative rehabilitation. RESULTS: This multi-phase project used an integrated knowledge translation approach. Based on the results from scoping reviews on the priority areas identified for the rehabilitation of children with AMC, and a clinician survey describing current practices in AMC rehabilitation, three panels of expert clinicians in occupational therapy, physical therapy, orthopedics, physiatry, and social work, as well as people with lived experience and researchers from 10 countries developed consensus-based recommendations for rehabilitation, in concordance with the Grading of Recommendations, Assessment, Development and Evaluations framework (GRADE) criteria. A modified Delphi process was completed with a wider group of international AMC experts to revise and validate the recommendations (Round 1 = 41 and Round 2 = 37 experts). A five-member external review panel appraised the recommendations using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. The final 16 recommendations reached a mean agreement rate of 96.6% after two Delphi rounds. The overall quality was rated at 96.6% on the AGREE II tool. Interviews with clinicians and managers identified facilitators and barriers to implementation of the recommendations in practice using the Theoretical Domain Framework. CONCLUSION: Consensus-based, expert validated recommendations for the rehabilitation of children with AMC were developed by a wide range of stakeholders, healthcare users and providers. The proposed recommendations are expected to contribute to improving child- and family-centered practice and health outcomes. Future work includes a knowledge translation strategy to promote sharing and implementation of the recommendations in practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".