Peptic Ulcer Disease and Risk of Hip Fracture: A General Population-based Cohort Study
Bibliographic record
Abstract
AIMS: Previous studies reported proton pump inhibitor (PPI) use may increase the risk of fracture; however, the findings may be susceptible to indication bias because peptic ulcer disease (PUD), 1 major indication for PPIs, may affect skeletal health. Determining whether PUD would increase hip fracture risk may help identify high-risk populations and explore risk factors. METHODS: We conducted a cohort study using data from The Health Improvement Network (THIN) in the United Kingdom. THIN contains patient information such as disease diagnosis and medicine prescriptions. Up to 5 non-PUD individuals (n = 138 265) were matched to each case of incident PUD (n = 27 653) by age, sex, and body mass index. We examined the association between PUD and hip fracture by a multivariable Cox proportional hazard model. We repeated the same analysis among individuals with incident PUD and gastroesophageal reflux disease (GERD) (n = 27 160), another disease with similar indication for PPIs, as a positive control exposure. RESULTS: Over a mean of 5.6 years of follow-up, hip fracture occurred in 589 individuals with PUD and 2015 individuals without PUD (3.8 vs 2.6/1000 person-years), with a multivariable-adjusted hazard ratio (HR) being 1.44 (95% confidence interval [CI], 1.31-1.58). The association persisted among subgroups stratified by sex and age. In positive control exposure analysis, the hip fracture risk was also higher in PUD than GERD (3.8 vs 2.4/1000 person-years; multivariable-adjusted HR = 1.65; 95% CI, 1.45-1.7). CONCLUSIONS: This general population-based cohort study suggests, after controlling for acid-lowering medication and other potential risk factors, PUD is independently associated with an increased risk of hip fracture.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".