P.117 Delayed contralateral presentation of a carotid cavernous fistula following trauma
Bibliographic record
Abstract
Background: We present a rare case of a left-sided carotid cavernous fistula (CCF) that presented 15 months post initial trauma with right-sided ophthalmic signs and symptoms. Highlighted is a contralateral endovascular approach to treating this traumatic CCF. Methods: Described is a case of a left-sided CCF caused by a self-inflicted gun shot wound to the head that was initially treated conservatively by neurosurgery and opthomology. The patient presented 15 months later with headache, acute right-sided periorbital swelling, severe right eye and facial pain. Results: Angiography confirmed the presence of a left-sided CCF with preferential drainage into the right cavernous sinus and right superior ophthalmic vein. The left internal carotid artery (ICA) was shown to be narrow and irregular. Multiple attempts to navigate the micro catheter through the vessel were unsuccessful. Instead, the fistula was embolized using a contralateral approach through the right internal carotid artery and across the anterior communicating artery. Imaging post-operatively confirmed successful occlusion of the CCF. Conclusions: This case is a rare example of a left-sided ICA occlusion secondary to trauma presenting 15 months after the initial injury with right-sided ophthalmic signs and symptoms. It is also one of only a few in the literature that describe successful treatment of traumatic CCF through a contralateral approach.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".