Acute management of acquired brain injury part II: An evidence-based review of pharmacological interventions
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To review the research literature on pharmacological interventions used in the acute phase of acquired brain injury (ABI) to manage ICP and improve neural recovery. MAIN OUTCOMES: A literature search of multiple databases (CINAHL, EMBASE, MEDLINE and PSYCHINFO) and hand searched articles covering the years 1980-2008 was performed. Peer reviewed articles were assessed for methodological quality using the PEDro scoring system for randomized controlled trials (RCTs) and the Downs and Black tool for RCTs and non-randomized trials. Levels of evidence were assigned and recommendations were made. RESULTS: In total, 11 pharmacological interventions used in the acute management of ABI were evaluated. These included propofol, barbiturates, opioids, midazolam, mannitol, hypertonic saline, corticosteroids, progesterone, bradykinin antagonists, dimethyl sulphoxide and cannabinoids. Of these interventions, corticosteroids were found to be contraindicated and cannabinoids were reported as ineffective. The other nine interventions demonstrated some benefit for treatment of acute ABI. However, rarely did these benefits result in improved long-term patient outcomes. CONCLUSIONS: Substantial research has been devoted to evaluating the use of pharmacological interventions in the acute management of ABI. However, much of this research has focused on the application of individual interventions in small single-site trials. Future research will need to establish larger patient samples to evaluate the benefits of combined interventions within specific patient populations.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.010 | 0.011 |
| 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) | 0.006 | 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".