A178 DIAGNOSIS OF A MYCOTIC AORTIC ANEURYSM USING ENDOSCOPIC ULTRASOUND: A CASE REPORT
Bibliographic record
Abstract
Abstract Background The role of endoscopic ultrasound (EUS) has expanded over the last decade. It is a well-established imaging modality in the diagnosis of gastrointestinal and pancreatic lesions as well as in mediastinal lesions. To date, EUS has not been reported in the literature for the diagnosis of mycotic aortic aneurysm after intravesical bacille Calmette-Guérin (BCG) therapy. Aims This case report describes the presentation and diagnosis of a mycotic aneurysm in the context of disseminated Mycobacterium bovis infection. Methods An 86-year-old man with previous intravesical BCG immunotherapy for the treatment of bladder carcinoma presented with weight loss and deconditioning at admission. Based on the patient’s past medical history and age, malignancy was suspected. An endoscopic ultrasound (EUS) revealed a mass at the lymph node station 9 masquerading as a lymphadenopathy. Multiple investigations were completed. Following the second EUS, the diagnosis of mycotic aneurysm was raised. The smear collected with EUS guided fine needle aspiration (FNA) was positive after Ziehl-Neelsen staining. The diagnosis of mycotic aneurysm to Mycobacterium bovis was confirmed. Results Treatment was initiated with rifampin, isoniazid and ethambutol. Despite optimal medical management, the patient presented with new onset fever, and a clinical deterioration with positive mycobacterial blood cultures. Within two months of admission, the treatment was discontinued and the patient died in palliative care. Conclusions Recognition of mycotic aneurysms is critical for institution of appropriate therapy and averting more severe complications, as they are associated with significant morbidity. This case aims to raise awareness to this rare disease after BCG treatment. It also highlights the novel role of EUSin the challenging diagnosis of mycotic aneurysm. Funding Agencies None
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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) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".