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Record W4323808780 · doi:10.1136/tsaco-2022-001051

Beta blockers in traumatic brain injury: a systematic review and meta-analysis

2023· review· en· W4323808780 on OpenAlexaff
Shannon Hart, Melissa Lannon, Andrew T. Chen, Amanda Martyniuk, Sunjay Sharma, Paul T. Engels

Bibliographic record

VenueTrauma Surgery & Acute Care Open · 2023
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsMeta-analysisTraumatic brain injuryBETA (programming language)MedicineSystematic reviewInternal medicinePsychologyMEDLINEComputer sciencePsychiatryBiology

Abstract

fetched live from OpenAlex

Background Traumatic brain injury (TBI) is a major cause of death and disability worldwide. Beta blockers have shown promise in improving mortality and functional outcomes after TBI. The aim of this article is to synthesize the available clinical data on the use of beta blockers in acute TBI. Methods A systematic search was conducted through MEDLINE, Embase, and Cochrane Central Register of Controlled Trials for studies including one or more outcomes of interest associated with use of beta blockers in TBI. Independent reviewers evaluated the quality of the studies and extracted data on all patients receiving beta blockers during their hospital stay compared with placebo or non-intervention. Pooled estimates, CIs, and risk ratios (RRs) or ORs were calculated for all outcomes. Results 13 244 patients from 17 studies were eligible for analysis. Pooled analysis demonstrated a significant mortality benefit of overall use of beta blocker (RR 0.8, 95% CI 0.68 to 0.94, I 2=75%). Subgroup analysis of patients with no preinjury use of beta blocker compared with patients on preinjury beta blockers showed no mortality difference (RR 0.99, 95% CI 0.7 to 1.39, I 2=84%). There was no difference in rate of good functional outcome at hospital discharge (OR 0.94, 95% CI 0.56 to 1.58, I 2=65%); however, there was a functional benefit at longer-term follow-up (OR 1.75, 95% CI 1.09 to 2.8, I 2=0%). Cardiopulmonary and infectious complications were more likely in patients who received beta blockers (RR 1.94, 95% CI 1.69 to 2.24, I 2=0%; RR 2.36, 95% CI 1.42 to 3.91, I 2=88%). Overall quality of the evidence was very low. Conclusions Use of beta blockers is associated with decreased mortality at acute care discharge as well as improved functional outcome at long-term follow-up. Lack of high-quality evidence limits definitive recommendations for use of beta blockers in TBI; therefore, high-quality randomized trials are needed to further elucidate the utility of beta blockers in TBI. PROSPERO registration number CRD42021279700.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.032
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.191
GPT teacher head0.407
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations19
Published2023
Admission routes1
Has abstractyes

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