Oophorectomy in NMDA receptor encephalitis and negative pelvic imaging
Bibliographic record
Abstract
-methyl-D-aspartate receptor (NMDAR) encephalitis. When a teratoma is detected on imaging, its removal is first-line therapy. Even with multiple imaging modalities, occasionally, the teratoma is found only on subsequent imaging, long after initial presentation. Very rarely, patients have undergone oophorectomy despite negative imaging, with pathology demonstrating teratoma, and resulting clinical improvement. We present a patient in whom removal of a teratoma, not visible on conventional imaging, resulted in marked clinical improvement. Such cases present a major clinical challenge, needing to consider the risks of oophorectomy, including sterilisation and early menopause, versus the possibility of death in the absence of response to first-line (eg, corticosteroids, plasma exchange, intravenous immunoglobulin), second-line (eg, rituximab) and third-line (eg, bortezomib) immunosuppression. This decision is made more difficult as patients are usually females of childbearing age who at the time lack capacity to make medical decisions. This case also highlights the lack of consensus and guidelines for imaging modalities used to detect teratoma and when to pursue oophorectomy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".