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Record W6996971502

Treatment of Blunt Cerebrovascular Injury - A Systematic Review and Meta-Analysis, Multicenter Retrospective Review, and Protocol for a Feasibility Randomized Controlled Trial

2023· article· en· W6996971502 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2023
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialStroke (engine)BluntRetrospective cohort studyInjury Severity ScoreMajor bleedingClinical trialProtocol (science)Treatment and control groups
DOInot available

Abstract

fetched live from OpenAlex

Blunt cerebrovascular injury (BCVI) is an often-overlooked clinical problem that can result in stroke and cause devastating, potentially permanent, neurologic disabilities in young and otherwise healthy trauma patients. Early diagnosis and treatment of BCVI can reduce the risk of stroke and prevent disability, however, treatment also carries a risk of bleeding complications. More research is needed to understand the optimal management strategy to reduce the risk of stroke while minimizing bleeding complications.\nThe aim of this thesis is to review and critically appraise the literature to better understand the efficacy of various treatment strategies in preventing stroke following BCVI, evaluate current practice patterns and patient outcomes at Canadian Level I Trauma Centers, and create a feasibility randomized controlled trial protocol to assess practicability of a future randomized control trial determining the optimal dose of antiplatelet therapy in the treatment of BCVI.\nSystematic review and meta-analysis of existing literature revealed a slightly lower risk of stroke with the use of antiplatelets compared to anticoagulants (4.5% vs. 5.2%; OR 0.57; 95% CI 0.33 – 0.96, p = 0.04), although there was no difference in stroke rate when evaluating the use of specific agents, acetylsalicylic acid (ASA) vs. heparin (OR 0.43; 95% CI 0.15 – 1.20, p = 0.11). Bleeding complications were significantly higher with the use of anticoagulants and led to more severe bleeding requiring invasive intervention, suggesting better tolerance of antiplatelets in the trauma population. Retrospective review of trauma registries at two Canadian Level I Trauma Centers revealed that patients were more likely to develop stroke after BCVI if they were injured as a result of a motor vehicle collision (MVC), had a lower initial Glasgow Coma Scale (GCS) and higher Injury Severity Scale (ISS), did not meet Denver screening criteria, or had carotid artery injuries. Patients who suffered a stroke were more likely to require intensive care. Treatment interruptions or delays were not associated with increased risk of stroke, and the dose of therapy (81 mg ASA vs. 325 mg ASA) was not independently associated with an increase in stroke rate after adjustment for initial GCS, injury location, and grade of injury (OR 2.244; 95% CI 0.660-7.628).\nCurrent research suggests that early detection and treatment of BCVI can significantly reduce the risk of stroke. ASA has shown similar efficacy as heparin for stroke risk reduction but was associated with less bleeding complications. Currently, the optimal dose of ASA is still unknown. Data from retrospective reviews suggests that there is no difference in stroke rates when using low-dose (81 mg) vs. high-dose (325 mg) ASA but no experimental studies exist to evaluate this question. A randomized controlled trial is required to further assess different doses of ASA to determine the optimal dose that reduces the risk of stroke while minimizing bleeding complications.

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)0.045
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.060
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0180.023
Bibliometrics0.0050.006
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0040.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0310.003

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 head0.123
GPT teacher head0.390
Teacher spread0.267 · 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 designSystematic review
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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