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Record W3013422974 · doi:10.1177/1751143720914181

Anti-N-methyl- <scp>d</scp> -aspartate receptor encephalitis: A primer for acute care healthcare professionals

2020· article· en· W3013422974 on OpenAlexaff
Dustin Anderson, Nabeela Nathoo, Jennifer A. McCombe, Penelope Smyth, Peter G. Brindley

Bibliographic record

VenueJournal of the Intensive Care Society · 2020
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEncephalitisMedicineAutoimmune encephalitisIntensive care unitImmunologyInternal medicine

Abstract

fetched live from OpenAlex

This primer summarizes the diagnosis, treatment, complications, and prognosis of anti-N-methyl-d-aspartate receptor encephalitis for healthcare professionals, especially those in acute care specialities. Anti-N-methyl-d-aspartate receptor encephalitis is an immune-mediated encephalitis that is classically paraneoplastic and associated with ovarian teratomas in young women. Other less common neoplastic triggers include testicular cancers, Hodgkin lymphoma, lung and breast cancers. It may also be triggered by infection, occurring as a para-infectious phenomenon, seen most commonly after herpes simplex-1 encephalitis. Presentation varies but typically consists of behavioural and cognitive manifestations, seizures, dysautonomia, movement disorders, central hypoventilation, and coma, necessitating intensive care unit admission. Diagnosis of anti-N-methyl-d-aspartate receptor encephalitis requires high clinical suspicion plus ancillary testing, the most sensitive being cerebrospinal fluid analysis for anti-N-methyl-d-aspartate receptor antibodies. Imaging in search of an ovarian teratoma should be exhaustive and tumours need to be surgically treated. Treatment should be expeditious with pulsed steroids and either plasma exchange or intravenous immunoglobulin. Second-line treatments include intravenous rituximab, cyclophosphamide, azathioprine, and intrathecal methotrexate. Most patients recover to be functionally independent, but the in-hospital course can be months long followed by extensive rehabilitation. Given the lengthy course of illness, we explain why education and debriefing are important for staff, and where families can obtain additional help.

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 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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.551
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.028
GPT teacher head0.337
Teacher spread0.309 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations5
Published2020
Admission routes1
Has abstractyes

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