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Oophorectomy in NMDA receptor encephalitis and negative pelvic imaging

2020· article· en· W3092251305 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePractical Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicineOophorectomyRituximabOvarian TeratomaTeratomaImmunosuppressionSurgeryGynecologyHysterectomyPathologyInternal medicineLymphoma

Abstract

fetched live from OpenAlex

-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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.303
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it