Early Magnesium Treatment After Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) is an important cause of poor outcome after aneurysmal subarachnoid hemorrhage (SAH). Trials of magnesium treatment starting <4 days after symptom onset found no effect on poor outcome or DCI in SAH. Earlier installment of treatment might be more effective, but individual trials had not enough power for such a subanalysis. We performed an individual patient data meta-analysis to study whether magnesium is effective when given within different time frames within 24 hours after the SAH. METHODS: Patients were divided into categories according to the delay between symptom onset and start of the study medication: <6, 6 to 12, 12 to 24, and >24 hours. We calculated adjusted risk ratios with corresponding 95% confidence intervals for magnesium versus placebo treatment for poor outcome and DCI. RESULTS: We included 5 trials totaling 1981 patients; 83 patients started treatment<6 hours. For poor outcome, the adjusted risk ratios of magnesium treatment for start <6 hours were 1.44 (95% confidence interval, 0.83-2.51); for 6 to 12 hours 1.03 (0.65-1.63), for 12 to 24 hours 0.84 (0.65-1.09), and for >24 hours 1.06 (0.87-1.31), and for DCI, <6 hours 1.76 (0.68-4.58), for 6 to 12 hours 2.09 (0.99-4.39), for 12 to 24 hours 0.80 (0.56-1.16), and for >24 hours 1.08 (0.88-1.32). CONCLUSIONS: This meta-analysis suggests no beneficial effect of magnesium treatment on poor outcome or DCI when started early after SAH onset. Although the number of patients was small and a beneficial effect cannot be definitively excluded, we found no justification for a new trial with early magnesium treatment after SAH.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".