Work-up and Management of Asymptomatic Extracranial Traumatic Vertebral Artery Injury
Bibliographic record
Abstract
BACKGROUND: Non-penetrating head and neck trauma is associated with extracranial traumatic vertebral artery injury (eTVAI) in approximately 1-2% of cases. Most patients are initially asymptomatic but have an increased risk for delayed stroke and mortality. Limited evidence is available to guide the management of asymptomatic eTVAI. As such, we sought to investigate national practice patterns regarding screening, treatment, and follow-up domains. METHODS: A cross-sectional, electronic survey was distributed to members of the Canadian Neurosurgical Society and Canadian Spine Society. We presented two cases of asymptomatic eTVAI, stratified by injury mechanism, fracture type, and angiographic findings. Screening questions were answered prior to presentation of angiographic findings. Survey responses were analyzed using descriptive statistics. RESULTS: One hundred-eight of 232 (46%) participants, representing 20 academic institutions, completed the survey. Case 1: 78% of respondents would screen for eTVAI with computed topography angiography (CTA) (97%), immediately (88%). The majority of respondents (97%) would treat with aspirin (89%) for 3-6 months (46%). Respondents would follow up clinically (89%) or radiographically (75%), every 1-3 months. Case 2: 73% of respondents would screen with CTA (96%), immediately (88%). Most respondents (94%) would treat with aspirin (50%) for 3-6 months (35%). Thirty-six percent of respondents would utilize endovascular therapy. Respondents would follow up clinically (97%) or radiographically (89%), every 1-3 months. CONCLUSION: This survey of Canadian practice patterns highlights consistency in the approach to screening, treatment, and follow-up of asymptomatic eTVAI. These findings are relevant to neurosurgeons, spinal surgeons, stroke neurologists, and neuro-interventionalists.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".