Can We Equate All Proton Pump Inhibitors with One Another?
Bibliographic record
Abstract
The article of Hinson and colleagues1 is important in that they show that long-term use of proton pump inhibitors can affect parathyroid hormone (PTH) levels independent of bisphosphonate use, which may be an important risk factor for fractures in elderly adults. However, there are some points that should be addressed. First, the greater risk of osteoporosis and fracture with PPIs such as esomeprazole, omeprazole, pantoprazole, and rabeprazole has been shown in many studies,2, 3 although this effect may not be generalized to all PPIs. Moreover, the type of each PPI molecule may affect PTH levels differently. PTH levels may not be attributable to a group effect of PPIs. It would be better if the authors could provide information about the individual effects of each PPI type on PTH levels. Second, the authors mention that the inclusion criteria included measurement of calcium, vitamin D, and PTH levels, but seeing as it is a retrospective study, there is no information about levels of these parameters before starting a PPI or bisphosphonates prescription. Therefore, the possibility cannot be excluded that the calcium levels of subjects in the PPI group were lower before the use of the medication. Conflict of Interest: The authors state that they have no conflicts of interest. Author Contributions: Sumer, Aycicek, Arik, Kara, Canbaz: preparation of manuscript. Ulger: review of concept. Sponsor's Role: No sponsor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.026 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".