Efficacy of Antithrombotic Therapy and Risk of Hemorrhagic Complication in Blunt Cerebrovascular Injury Patients with Concomitant Injury: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The risk-benefit balance of antithrombotic therapy administration for blunt cerebrovascular injuries (BCVI) patients with concomitant injuries at high risk for bleeding is an ongoing therapeutic conundrum for trauma clinicians. We performed a systematic review to assess the reported efficacy and safety of treatment in this population with respect to prevention of ischemic stroke and risk of hemorrhagic complications. STUDY DESIGN: A systematic electronic literature search of MEDLINE, EMBASE, Cochrane Library, and Web of Science databases was performed from January 1, 1996 to December 31, 2021. Studies were included if they reported treatment-stratified clinical outcomes after antithrombotic therapy in BCVI patients with concomitant injuries at high risk of bleeding into a critical site. Data were extracted from selected studies by two independent reviewers, including the main outcomes of interest were BCVI-related ischemic stroke rates and rates of hemorrhagic complications. RESULTS: Of the 5,999 studies reviewed, 10 reported on the effects of treating BCVI patients with concurrent traumatic injuries and were included for review. In the pooled data, among patients with BCVI and concomitant injury who received any form of antithrombotic therapy, the BCVI-related stroke rate was 7.6%. The subgroup of patients who did not receive therapy had an overall BCVI-related stroke rate of 34%. The total rate of hemorrhagic complications in the treated population was 3.4%. CONCLUSIONS: In BCVI patients with concomitant injuries at high risk for bleeding, antithrombotic use reduces the risk of ischemic strokes with a low reported risk of serious hemorrhagic complications.
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| 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) | 0.002 | 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 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".