The relationship between joint surgery and quality of life in adults with arthrogryposis: An international study
Bibliographic record
Abstract
Individuals with Arthrogryposis Multiplex Congenita (AMC) are born with multiple joint contractures in multiple body areas, typically manifested as clubfeet, extended or flexed knees and/or elbows, and internal shoulder rotation, and clasped hands. They require multiple surgeries as children, but there is little data that reports their aging and future quality of life (QOL). This study describes the relationship between AMC-related surgically-managed joints in childhood and adulthood, and QOL as adults. Participants (n = 83) from 14 countries completed an online questionnaire followed by a telephone/Skype interview as adults. Data points collected regarding total number of surgeries, affected joints, country of origin, sex, age, and SF-36's Physical Capacity Score (PCS) for QOL were analyzed using a beta regression model to explore which factors may potentially influence adult QOL. The average number of surgeries per participant was 9.8, with at least 50% performed during childhood. 78, 45, and 31% of participants had foot, knee, and hip surgeries, respectively. The model demonstrated that knee and/or shoulder surgeries were more likely to have a negative correlation with PCS; elbow surgery, however, showed a positive correlation, as elbow function may impact independent function. However, future expansion of this data set to a longitudinal registry would provide better ongoing surgery-specific data.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".