Beta-blockers and Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: To determine if beta-(β)-blockers improve outcomes after acute traumatic brain injury (TBI). BACKGROUND: There have been no new inpatient pharmacologic therapies to improve TBI outcomes in a half-century. Treatment of TBI patients with β-blockers offers a potentially beneficial approach. METHODS: Using MEDLINE, EMBASE, and CENTRAL databases, eligible articles for our systematic review and meta-analysis (PROSPERO CRD42016048547) included adult (age ≥ 16 years) blunt trauma patients admitted with TBI. The exposure of interest was β-blocker administration initiated during the hospitalization. Outcomes were mortality, functional measures, quality of life, cardiopulmonary morbidity (e.g., hypotension, bradycardia, bronchospasm, and/or congestive heart failure). Data were analyzed using a random-effects model, and represented by pooled odds ratio (OR) with 95% confidence intervals (CI) and statistical heterogeneity (I). RESULTS: Data were extracted from 9 included studies encompassing 2005 unique TBI patients with β-blocker treatment and 6240 unique controls. Exposure to β-blockers after TBI was associated with a reduction of in-hospital mortality (pooled OR 0.39, 95% CI: 0.27-0.56; I = 65%, P < 0.00001). None of the included studies examined functional outcome or quality of life measures, and cardiopulmonary adverse events were rarely reported. No clear evidence of reporting bias was identified. CONCLUSIONS: In adults with acute TBI, observational studies reveal a significant mortality advantage with β-blockers; however, quality of evidence is very low. We conditionally recommend the use of in-hospital β-blockers. However, we recommend further high-quality trials to answer questions about the mechanisms of action, effectiveness on subgroups, dose-response, length of therapy, functional outcome, and quality of life after β-blocker use for TBI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".