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Record W3009752056 · doi:10.1097/ta.0000000000002640

A systematic review and meta-analysis of traumatic intracranial hemorrhage in patients taking prehospital antiplatelet therapy: Is there a role for platelet transfusions?

2020· review· en· W3009752056 on OpenAlexaboutno aff
Jurgis Alvikas, Sara P. Myers, Charles B. Wessel, David O. Okonkwo, Bellal Joseph, Carlos A. Peláez, Cody Doberstein, Andrew R. Guillotte, Matthew R. Rosengart, Matthew D. Neal

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2020
Typereview
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineMeta-analysisPlatelet transfusionOdds ratioSubgroup analysisInternal medicineRandomized controlled trialConfidence intervalPlatelet

Abstract

fetched live from OpenAlex

BACKGROUND: Platelet transfusion has been utilized to reverse platelet dysfunction in patients on preinjury antiplatelets who have sustained a traumatic intracranial hemorrhage (tICH); however, there is little evidence to substantiate this practice. The objective of this study was to perform a systematic review on the impact of platelet transfusion on survival, hemorrhage progression and need for neurosurgical intervention in patients with tICH on prehospital antiplatelet medication. METHODS: Controlled, observational and randomized, prospective and retrospective studies describing tICH, preinjury antiplatelet use, and platelet transfusion reported in PubMed, Embase, Cochrane Reviews, Cochrane Trials and Cochrane DARE databases between January 1987 and March 2019 were included. Investigations of concomitant anticoagulant use were excluded. Risk of bias was assessed using the Newcastle-Ottawa scale. We calculated pooled estimates of relative effect of platelet transfusion on the risk of death, hemorrhage progression and need for neurosurgical intervention using the methods of Dersimonian-Laird random-effects meta-analysis. Sensitivity analysis established whether study size contributed to heterogeneity. Subgroup analyses determined whether antiplatelet type, additional blood products/reversal agents, or platelet function assays impacted effect size using meta-regression. RESULTS: Twelve of 18,609 screened references were applicable to our questions and were qualitatively and quantitatively analyzed. We found no association between platelet transfusion and the risk of death in patients with tICH taking prehospital antiplatelets (odds ratio [OR], 1.29; 95% confidence interval [CI], 0.76-2.18; p = 0.346; I = 32.5%). There was no significant reduction in hemorrhage progression (OR, 0.88; 95% CI, 0.34-2.28; p = 0.788; I = 78.1%). There was no significant reduction in the need for neurosurgical intervention (OR, 1.00; 95% CI, 0.53-1.90, p = 0.996; I = 59.1%; p = 0.032). CONCLUSION: Current evidence does not support the use of platelet transfusion in patients with tICH on prehospital antiplatelets, highlighting the need for a prospective evaluation of this practice. LEVEL OF EVIDENCE: Systematic Reviews and Meta-Analyses, Level III.

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)0.023
metaresearch head score (Gemma)0.055
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.055
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0270.047
Bibliometrics0.0110.011
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.357
Teacher spread0.308 · 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

Citations32
Published2020
Admission routes1
Has abstractyes

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