MétaCan
Menu
Back to cohort
Record W4409286071 · doi:10.1186/s13023-025-03671-x

Consensus-based recommendations for the rehabilitation of children with arthrogryposis multiplex congenita: an integrated knowledge translation approach

2025· article· en· W4409286071 on OpenAlexafffund
Noémi Dahan‐Oliel, Sarah Cachecho, Clarice Ribeiro Soares Araújo, Alicja Fąfara, Francis Lacombe, Ani Samargian, Maureen Donohoe, Ann Flanagan, Bart Kowalczyk, Courtney Krakie, Lisa V. Wagner, Carolina Navalón, Verity Pacey, Unni Steen, Trudy Wong, André Bussières

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité de MontréalCentre de réadaptation Lethbridge-Layton-MackayMcGill UniversityShriners Hospitals for Children - Canada
FundersFonds de Recherche du Québec - SantéNatera
KeywordsRehabilitationArthrogryposis multiplex congenitaMedicineKnowledge translationPhysical therapyOccupational therapyDelphi methodInternational Classification of Functioning, Disability and HealthOrthoticsArthrogryposisPhysical medicine and rehabilitationPsychologyKnowledge management

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.443
metaresearch head score (Gemma)0.611
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.443
Threshold uncertainty score0.687

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4430.611
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0070.013
Bibliometrics0.0320.019
Science and technology studies0.0050.006
Scholarly communication0.0170.018
Open science0.0160.023
Research integrity0.0150.016
Insufficient payload (model declined to judge)0.0080.003

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.

Opus teacher head0.039
GPT teacher head0.335
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueOrphanet Journal of Rare DiseasesSame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207