A multicenter study to evaluate pain characteristics in osteogenesis imperfecta
Bibliographic record
Abstract
The objective was to describe pain characteristics and treatments used in individuals with varying severity of osteogenesis imperfecta (OI) and investigate pain-associated variables. This work was derived from a multicenter, longitudinal, observational, natural history study of OI conducted at 12 clinical sites of the NIH Rare Diseases Clinical Research Network's Brittle Bone Disorders Consortium. Children and adults with a clinical, biochemical, or molecular diagnosis of OI were enrolled in the study. We did a cross-sectional analysis of chronic pain prevalence, characteristics, and treatments used for pain relief and longitudinal analysis to find the predictors of chronic pain. We included 861 individuals with OI, in 41.8% chronic pain was present, with similar frequency across OI types. Back pain was the most frequent location. Nonsteroidal anti-inflammatory drugs followed by bisphosphonates were the most common treatment used. Participants with chronic pain missed more days from school or work/year and performed worse in all mobility metrics than participants without chronic pain. The variables more significantly associated with chronic pain were age, sex, positive history of rodding surgery, scoliosis, other medical problems, assistive devices, lower standardized height, and higher body mass index. The predictors of chronic pain for all OI types were age, use of a wheelchair, and the number of fractures/year. Chronic pain is prevalent in OI across all OI types, affects mobility, and interferes with participation. Multiple covariates were associated with chronic pain.
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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 | 0.005 | 0.002 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".