Septic Thrombosis of the Cavernous Sinus: Two Different Mechanisms
Bibliographic record
Abstract
PURPOSE: Septic thrombosis of the cavernous sinus is a rare condition that may lead to significant morbidity and mortality if not diagnosed and treated urgently. We present two recent cases of bilateral septic cavernous sinus thrombosis with differing etiologies, the first of dental origin and the second a complication of sphenoid sinusitis. METHODS: Case report. RESULTS: A diagnosis of cavernous sinus thrombosis was made based on clinical findings and confirmed by imaging in both patients. The etiology in the first patient was related to poor dental hygiene, with resultant spread of infection to the cavernous sinuses. The second had bilateral sphenoid sinusitis, with intravascular gas noted in both orbits and cavernous sinuses. This is the first reported occurrence of such an event associated with septic cavernous sinus thrombosis. Bilateral sphenoidotomies with evacuation of the sinuses were performed, and Haemophilus influenzae was cultured from the sphenoidotomy fluid and blood. Broad spectrum intravenous antibiotics were given in both patients, and complete recovery achieved within weeks. CONCLUSION: In septic thrombosis of the cavernous sinus, early recognition and prompt management with broad spectrum intravenous antibiotics is crucial for full recovery. The primary source of sepsis may be a distant focus with septicemia preceding thrombosis of the cavernous sinus. Alternatively, infection may spread from facial regions via the facial venous plexus or from the sphenoid sinus directly to the adjacent cavernous sinus.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".