Effects of magnesium on atrial fibrillation after cardiac surgery: a meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To assess the efficacy of the administration of magnesium as a method for the prevention of postoperative atrial fibrillation (AF) and to evaluate its influence on hospital length of stay (LOS) and mortality. METHODS: Literature search and meta-analysis of the randomised control studies published since 1966. RESULTS: 20 randomised trials were identified, enrolling a total of 2490 patients. Study sample size varied between 20 and 400 patients. Magnesium administration decreased the proportion of patients developing postoperative AF from 28% in the control group to 18% in the treatment group (odds ratio 0.54, 95% confidence interval (CI) 0.38 to 0.75). Data on LOS were available from seven trials (1227 patients). Magnesium did not significantly affect LOS (weighted mean difference -0.07 days of stay, 95% CI -0.66 to 0.53). The overall mortality was low (0.7%) and was not affected by magnesium administration (odds ratio 1.22, 95% CI 0.39 to 3.77). CONCLUSION: Magnesium administration is an effective prophylactic measure for the prevention of postoperative AF. It does not significantly alter LOS or in-hospital mortality.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.022 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".