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Record W2080115399 · doi:10.4021//jmc.v4i3.986

Anti-NMDA Receptor Paraneoplastic Encephalitis: An Important Differential Diagnosis in Subacute Psychosis

2012· article· en· W2080115399 on OpenAlexvenueno aff
André Gomes, Elika Pinho, Ana Teixeira‐Vaz, Pedro Castro, João Santos Antunes, Eduarda Pereira, Celeste Dias, Fernando Friões, Jorge Almeida

Bibliographic record

VenueJournal of Medical Cases · 2012
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEncephalitisAnti-NMDA receptor encephalitisOvarian TeratomaPsychosisNMDA receptorTeratomaDifferential diagnosisAutoimmune encephalitisPediatricsRespiratory systemPlasmapheresisAnesthesiaInternal medicineAntibodyImmunologyPathologyReceptorPsychiatry

Abstract

fetched live from OpenAlex

Anti NMDA (N-methyl D-aspartate) receptor encephalitis has been recently described in young women with ovarian teratoma. Memory and psychiatric disturbances are frequent followed by respiratory and autonomic failure warranting long intensive care admissions. We report on a female patient with paraneoplastic encephalitis manifested by behavioural changes and neurological impairment, followed by respiratory and hemodynamic instability. Anti-NMDA receptor antibodies were found in blood and spinal fluid in association with an imamature grade 2 ovarian teratoma. She made a full recovery after complete oophorectomy and institution of intravenous immunoglobulin and corticosteroids. Anti-NMDA encephalitis should be considered in any female patient presenting with de novo psychiatric symptoms. As in other paraneoplastic syndrome, its therapy is based in resection of the underlying tumor associated with immunomodulators. Timely initiation of therapy may significantly improve outcome as in this case. doi: http://dx.doi.org/10.4021/jmc986w

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.033
GPT teacher head0.328
Teacher spread0.295 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2012
Admission routes1
Has abstractyes

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