P.092 Eagles and Talons: A case of cervical artery dissection from Eagle syndrome and fibromuscular dysplasia
Bibliographic record
Abstract
Background: Eagle syndrome (also known as stylohyoid syndrome) and fibromuscular dysplasia (FMD) are rare conditions that have both been shown to be associated with cervical artery dissections (CAD). Direct mechanical injury from a neighboring bony fragement can produce arterial dissections and is the proposed mechanism in Eagle syndrome. The etiology of FMD remains unclear, however, similar shearing stresses have been proposed. We present a case in which both of these conditions were present. Methods: Case report Results: A previously healthy 52 year old male presented with an acute left MCA syndrome with computer tomography angiography followed by convensional angiography confirming a complete occlusion of the left ICA at the carotid bifurcation with evidence of a dissection of the proximal cervical carotid artery. Luminal irregularities proximal to the dissection and also of the right ICA were in keeping with fibromuscular dysplasia. A carotid stent was placed and a thrombectomy was performed for a proximal left M2 occlusion. On further review of the CT, the patient had markedly elongated styloid processes bilaterally, meeting criteria for Eagle syndrome. Conclusions: Previous literature has not described these two conditions coexisiting. We question whether chronic mechanical stress from an elongated styloid process could lead to arteries having an irregular or beading appearance resembling fibromuscular dysplasia.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".