Ovarian Teratoma and N-Methyl-D-Aspartate Receptor Autoimmune Encephalitis: Insights Into Imaging Diagnosis of Teratoma and Timing of Surgery
Bibliographic record
Abstract
Mature ovarian teratoma is the most common type of germ cell tumor and mostly detected incidentally in women in second or third decade. Recent researches have provided strong evidence between mature ovarian teratoma and encephalitis, which is caused due to the presence of anti-N-methyl-D-aspartate (NMDA) antibodies. We would like to report four patients who had typical neuropsychiatric manifestations, such as abnormal behavior, speech disorder, seizures, movement disorders, loss of consciousness, and autonomic dysfunction. All the patients had prolonged course of disease before the diagnosis of NMDA encephalitis had been made. The importance of timely evaluation of symptomatic young women with serum and cerebrospinal fluid (CSF) NMDA receptor (NMDAR) antibodies is emphasized. Imaging ranging from transvaginal ultrasound to positron emission tomography-computed tomography (PET-CT) will help in arriving at a probable diagnosis. Surgical treatment is the cornerstone of management, and patients responded well post surgery with almost full recovery, with addition of immunotherapy, physiotherapy, rehabilitation providing a vital role. There is significant variation in clinical presentation of encephalitis and thus in time to diagnosis for those with non-specific symptoms, particularly psychiatric ones. The index of suspicion of anti-NMDA encephalitis should be high in young females and involvement of a gynecology team needs to be done. Surgical removal of the teratoma is the key and the gynecology team should not be deterred by the acute symptoms and debilitating nature of the symptoms J Clin Gynecol Obstet. 2021;10(1):22-27 doi: https://doi.org/10.14740/jcgo715
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".