P.006 Keeping neurosarcoidosis on the differential
Bibliographic record
Abstract
Background: Sarcoidosis is a multiorgan autoimmune disease characterized by the presence of non-caseating granulomas. The diagnosis can be difficult, particularly with central nervous system (CNS) involvement, and pathology outside of the CNS has to be carefully evaluated. Early and correct diagnosis is crucial for appropriate management particularly in children where sarcoidosis and neurosarcoidosis are rare. Methods: We describe a 16 year old previously healthy boy who presented with progressive pyramidal neurological signs and symptoms localizable primarily to the brain stem. Results: Initial imaging revealed striking brainstem, as well as cerebral, cerebellar and spinal cord perivascular enhancement. Lung involvement was subclinical with a miliary pattern on chest imaging and needle biopsy revealed an interstitial lymphocytic infiltration. Extensive serum and CSF rheumatological, autoimmune and infectious investigations were noncontributory. Serum ACE levels were at first within normal limits. Steroid treatment stabilized symptoms and perhaps coincidentally, separate rituximab treatments were followed within days by vertigo (with a new pontine lesion) or a respiratory decompensation. A wedge lung biopsy revealed granulomatosis. Current treatment consists of mycophenolate, methotrexate with a prednisone wean. Conclusions: This case report reinforces the varied manifestations and mimics of sarcoidosis (including CLIPPERS) and highlights the need for a high index of suspicion despite apparently negative investigations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".