Long-Term Proton Pump Inhibitor Use Is Not Associated With Changes in Bone Strength and Structure
Bibliographic record
Abstract
OBJECTIVES: Multiple studies have reported an association between proton pump inhibitor (PPI) use and fracture. However, the causality of this association is questionable, as there is not a well defined mechanism of action, nor is there evidence of an effect on PPIs on areal bone mineral density (aBMD) using dual photon X-ray absorptiometry (DXA). It is possible that PPIs may induce changes in bone structure which would predispose to fracture in the absence of changes in aBMD. We used three-dimensional quantitative computed tomography (3D-QCT) imaging to determine if long-term PPI use was associated with structural changes in bone independent of aBMD. METHODS: We enrolled a sample of long-term (≥5 years) PPI users matched to a similar cohort of persons with no PPI use in the previous 5 years. All subjects underwent assessment of aBMD using DXA, volumetric BMD using 3D-QCT, as well as markers of bone metabolism. Measures of bone strength, including buckling ratio and section modulus, were also compared between the two samples. RESULTS: 104 subjects were enrolled (52 PPI users and 52 PPI non-users). There were no differences detected in standard BMD, volumetric BMD, markers of bone metabolism or measures of bone strength between the two groups. CONCLUSIONS: Long-term PPI use is not associated with any changes in bone mineral density or bone strength that would predispose to an increased risk of fracture. These findings provide further evidence that the association between PPI use and fracture is not causal.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".