Internal carotid artery aneurysm in skull base osteomyelitis: does the pattern of cranial nerve involvement matter?
Bibliographic record
Abstract
OBJECTIVE: Carotid artery aneurysm is a potentially fatal complication of skull base osteomyelitis. It is important to know the warning signs for this complication, as early diagnosis is of great importance. This report aimed to determine whether the pattern of cranial nerve involvement may predict the occurrence of aneurysm involving the internal carotid artery in skull base osteomyelitis. METHODS: Two diabetic patients with skull base osteomyelitis were incidentally diagnosed with pseudo-aneurysm of the petrous internal carotid artery on follow-up magnetic resonance imaging. They presented with lower cranial nerve palsy; however, facial nerve function was almost preserved in both cases. Computed tomography angiography confirmed aneurysms at the junction of the horizontal and vertical segments of the petrous carotid artery. RESULTS: Internal carotid artery trapping was conducted using coil embolisation. Post-coiling magnetic resonance imaging demonstrated no procedure-related complications. Regular follow up has demonstrated that patients' symptoms are improving. CONCLUSION: One should be mindful of this potentially fatal complication in skull base osteomyelitis patients with lower cranial nerve palsies, with or without facial nerve involvement, especially in the presence of intracranial thromboembolic events or Horner's syndrome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".