Hypomagnesaemia, an independent risk factor for the development of post‐transplant diabetes mellitus in liver and renal transplant recipients? A systematic review
Bibliographic record
Abstract
BACKGROUND: Post-transplantation diabetes mellitus (PTDM) is common after solid organ transplantation. In the past decade, there has been increasing interest in the association between hypomagnesaemia and the development of PTDM. This systematic review aimed to investigate the current knowledge regarding the association between hypomagnesaemia and PTDM in adult liver and renal transplant recipients. METHODS: A literature search of five databases, Medline, Embase, ProQuest, Scopus and Google Scholar, as well as article reference lists, was performed. Eligible studies that focused on adult liver and renal transplant recipients without pretransplantation hyperglycaemia or diabetes were included. Other eligibility criteria included quantitative studies which reported magnesium concentrations, studies with at least 6 months of follow-up, and studies published in English. The Newcastle-Ottawa Assessment Tool was used for the quality assessment. RESULTS: In total, 12 studies were included in the final analysis. Eleven focused on renal transplantation and one on liver transplantation. All studies were medium to high quality with eight out of 12 achieving the highest rating of nine. Eight studies found a negative association between either pretransplant or early post-transplant serum magnesium concentration and the risk of PTDM, three studies found no association between these two variables, and one study found a positive association between the magnesium concentration at 8 weeks after transplantation and glycosylated haemoglobin A1C. CONCLUSIONS: Further large-scale prospective studies with at least 6 months of follow-up are needed to confirm these findings, particularly in liver transplantation, to further clarify and explore the relationship between hypomagnesaemia and PTDM.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".