Functional hypoparathyroidism secondary to magnesium deficiency in long-term users of proton pump inhibitor
Bibliographic record
Abstract
Gastroesophageal reflux disease (GERD) is a gastrointestinal motility disorder that results from the reflux of stomach contents into the esophagus resulting in symptoms or complications. GERD is now widely prevalent around the world, with clear evidence of increasing prevalence in many developing countries. Treatment for most people with GERD includes lifestyle changes and medication. Proton pump inhibitors (PPIs) are a mainstay therapy for all gastric acid-related diseases. Long-term use of PPIs is associated with hypomagnesaemia, hypokalemia, hypocalcaemia, osteoporosis and bone fractures, chronic renal disease, acute renal disease, and other. Clinical concerns arise from a small but growing number of case reports presenting PPI-induced hypomagnesaemia. In 2011 the U.S. Food and Drug Administration is informing the public that prescription PPI may cause low serum magnesium levels if taken for prolonged periods of time. In this article, we present the case of a 56-year-old patient with muscle cramps, violation of cardiac rhythm, lethargy and other caused by hypomagnesaemia, hypocalcaemia and hypokalemia with a low parathyroid hormone level while using a PPI. After magnesium repletion abnormalities resolved. A causal relation with PPI use was supported by the recurrence of hypomagnesaemia after re-challenge.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".