Epidemiology, aetiology, interventions and genomics in children with arthrogryposis multiplex congenita: protocol for a multisite registry
Bibliographic record
Abstract
INTRODUCTION: Arthrogryposis multiplex congenita (AMC) is an umbrella term including hundreds of conditions with the common clinical manifestation of multiple congenital contractures. AMC affects 1 in 3000 live births and is caused by lack of movement in utero. To understand the long-term needs of individuals diagnosed with a rare condition, it is essential to know the prevalence, aetiology and functional outcomes in a large sample. The development and implementation of a multicentre registry is critical to gather this data. This registry aims to improve health through genetic and outcomes research, and ultimately identify new therapeutic targets and diagnostics for treating children with AMC. METHODS AND ANALYSIS: Participants for the AMC registry will be recruited from seven orthopaedic hospitals in North America. Enrollment occurs in two phases; Part 1 focuses on epidemiology, aetiology and interventions. For this part, retrospective and cross-sectional data will be collected using a combination of patient-reported outcomes and clinical measures. Part 2 focuses on core subset of the study team, including a geneticist and bioinformatician, identifying causative genes and linking the phenotype to genotype via whole genome sequencing to identify genetic variants and correlating these findings with pedigree, photographs and clinical information. Descriptive analyses on the sample of 400 participants and logistic regression models to evaluate relationships between outcomes will be conducted. ETHICS AND DISSEMINATION: Ethical approval has been granted from corresponding governing bodies in North America. Dissemination of findings will occur via traditional platforms (conferences, manuscripts) for the scientific community. Other modalities will be employed to ensure that all stakeholders, including youth, families and patient support groups, may be provided with findings derived from the registry. Ensuring the findings are circulated to a maximum amount of interested parties will ensure that the registry can continue to serve as a platform for hypothesis-driven research and further advancement for AMC.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.001 | 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 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".