Bibliographic record
Abstract
BACKGROUND: Acute traumatic brain injury is a leading cause of death and disability in young adults. Magnesium had been considered as a potential therapeutic tool because of its activity on NMDA-receptors, calcium channels and neuron membranes. Animals studies have indicated a beneficial effect of magnesium on outcome after brain injury, but its efficacy in humans is unknown. OBJECTIVES: To quantify the effect of magnesium administration on mortality and morbidity in patients with acute traumatic brain injury. SEARCH STRATEGY: We searched the Cochrane Injuries Group's specialised register, Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, National Research Register, Current Controlled Trials, SIGLE, LILACS, Zetoc. The searches were conducted in July 2005. SELECTION CRITERIA: We included all randomized controlled trials comparing any magnesium salt with no magnesium or with placebo, in patients following acute traumatic brain injury. DATA COLLECTION AND ANALYSIS: Two authors independently screened search results and assessed the full texts of potentially relevant studies for inclusion. Data were extracted and methodological quality was examined. MAIN RESULTS: Three studies met the inclusion criteria, one of which is an ongoing study. Two studies were included in the analysis. No data on mortality were available. For Glasgow Outcome Score at six months the pooled WMD = 0.55 (95% CI -0.15 to 1.26), P = 0.12. AUTHORS' CONCLUSIONS: There is currently no evidence to support the use of magnesium salts in patients with acute traumatic brain injury.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".