Sex-related differences in wear patterns in primary elbow osteoarthritis
Bibliographic record
Abstract
Background We have observed differences in patterns of arthritic wear between male and female patients undergoing arthroscopic management of elbow osteoarthritis. The objective of the study was to examine sex-related radiographic differences in symptomatic primary elbow osteoarthritis through a matched cohort study. Methods Fifty patients with primary elbow osteoarthritis that required surgery were identified and divided into two cohorts matched by sex and age from an institutional database. Basic patient demographics were recorded. The minimum joint space width (JSW) of the radiocapitellar and ulnohumeral compartments were measured on coronal and sagittal CT images, by two reviewers. Results The mean age of the 50 patients was 56 ± 6 years. The mean size adjusted ulnohumeral JSW for males was 1.5 ± 0.4 mm and females was 1.0 ± 0.5 mm, p = 0.003. The mean size adjusted radiocapitellar JSW for males was 1.1 ± 0.6 mm and females was 1.3 ± 0.7 mm, p = 0.37. Comparing radiocapitellar and ulnohumeral JSW within each sex, radiocapitellar JSW was significantly narrower in males ( p = 0.008) but the radiocapitellar and ulnohumeral JSW was similar in females ( p = 0.11). Conclusion In our study, we found that male patients with primary elbow osteoarthritis had cartilage loss predominantly in the radiocapitellar articulation. Female patients had similar radiocapitellar and ulnohumeral JSW suggesting more symmetric cartilage wear.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".