Intracranial Caseating Granulomas with No Infectious Organism Detected
Bibliographic record
Abstract
BACKGROUND: Caseating granuloma is a classic histopathological feature of mycobacterial infections. Occasionally, no infectious organism is demonstrated despite extensive examination of intracranial caseating granulomas. The pathogenesis and optimal management strategy for patients with such intracranial caseating granulomas with no detectable infectious organism (ICGNs) remain unclear. METHODS: The study was a retrospective case-series design in a referral hospital setting. Patients with intracranial caseating granulomas in whom no infectious etiology was identified after appropriate investigations were reviewed. RESULTS: Eight patients with ICGN (four females and four males) were identified in an eight-year-period. Average age on presentation was 46 years (range 21-69 years). Cerebrospinal fluid showed lymphocytic pleocytosis, elevated protein and decreased glucose. Neuroimaging showed multiple or single intraparenchymal and meningeal enhancements. Intracranial ICGN were demonstrated on biopsy. Immunomodulation was tried and resulted in improvement in five out of eight patients. In four patients, anti-mycobacterial treatment resulted in no improvement or worsening of clinical or radiological features. CONCLUSIONS: The response to therapy of intracranial caseating granulomas where no organism is identified after thorough investigations hints to non-infectious causes, and suggests current dogma regarding the significance of necrosis in granulomatous diseases should be re-evaluated. Our retrospective series suggests that patients may benefit from an early trial of immunomodulation therapy, a hypothesis to be tested in a randomized trial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".