Intermittent Intraperitoneal Administration of Magnesium Sulphate in an Elderly Patient Undergoing Dialysis
Bibliographic record
Abstract
Hypomagnesemia is not a typical concern in patients with stage 5 chronic kidney disease. Magnesium (Mg) is cleared renally, so Mg concentration is usually normal or even elevated in patients with chronic kidney disease. Up to 95% of renally filtered Mg can be reabsorbed in the nephron. Certain medications, such as diuretics (loop, thiazide, and osmotic), cisplatin, gentamicin, and s-lactam antibiotics, increase Mg excretion. The gastrointestinal absorption of Mg is dose-dependent and occurs by paracellular uptake at high Mg concentrations and by active transport at low Mg concentrations. Depending on the salt form, 30%–50% of ingested Mg is absorbed. Certain gastrointestinal disorders cause malabsorption, and certain medications, such as proton-pump inhibitors, reduce absorption, either of which can lead to hypomagnesemia. Renal dysfunction can lead to hypermagnesemia, yet gastrointestinal malabsorption can lead to hypomagnesemia; when these 2 conditions occur concurrently the change in serum magnesium is unpredictable. The clinical signs of hypomagnesemia range from fatigue, anemia, and hypokalemia to neuromuscular instability characterized by ataxia, vertigo, and hyperreflexia. Mild hypomagnesemia can be corrected by oral supplementation, with or without coadministration of vitamin D or a vitamin D analogue. In more severe cases, parenteral administration of magnesium sulphate is often required, most commonly by IV administration; however, in some cases, intraperitoneal (IP) administration of Mg has been successful in correcting hypomagnesemia. This report describes a patient with stage 5 chronic kidney disease whose hypomagnesemia was corrected by IP administration of magnesium sulphate.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 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".