Diabetes Mellitus Is a Possible Risk Factor for the Development of Trochanteric Bursitis—A Large-Scale Population-Based Study
Bibliographic record
Abstract
Background: Trochanteric Bursitis (TB) is a common reason to seek primary care, previously shown to be associated with female gender and obesity. Diabetes mellitus (DM) has several musculoskeletal manifestations, but was never found to be associated with TB. Purpose: To explore the association between DM and TB, based on a large database. The secondary aim was to explore the influence of gender and insulin usage on the occurrence of TB. Study design: cross-sectional study. Methods: A population-based cohort consisting of 60,610 patients (55,428 without DM and 5182 with DM), of whom 5418 were diagnosed with TB. A logistic regression model was applied to estimate propensity scores. Results: The odds of individuals with DM being diagnosed with TB were 55.8% higher compared to the odds of patients without DM (OR: 1.558, 95% CI: [1.429, 1.70], p < 0.0001). We found that insulin users had a lower risk of TB than patients not using insulin (log-rank p < 0.0001). Females are 3.3 times more likely to have TB than males (RR: 3.337, 95% CI: [3.115, 3.584], p < 0.0001). Conclusions: DM is a risk factor for developing TB. Insulin had a protective effect against TB, suggesting that better glycemic control might prevent this painful infliction.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".