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Record W4412816283 · doi:10.1097/wno.0000000000002382

The Diagnostic Yield of Antiacetylcholine Receptor Antibodies Versus Antimuscle Kinase Antibodies in Ocular Myasthenia Gravis: A Meta-Analysis

2025· article· en· W4412816283 on OpenAlexaff
Edward Tran, Gautham Nair, Lulu Bursztyn, Clare L. Fraser, Edsel Ing

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2025
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsUniversity of TorontoUniversity of AlbertaWestern University
Fundersnot available
KeywordsMedicineOcular myastheniaMeta-analysisMyasthenia gravisInternal medicineAutoantibodyAntibodySerologyConfidence intervalGastroenterologyImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Ocular myasthenia gravis (OMG) is an autoimmune disease characterized by autoantibodies targeting postsynaptic proteins at the neuromuscular junction, leading to weakness and fatigability of the levator palpebrae superioris, orbicularis oculi and extraocular muscles. Although OMG is primarily a clinical diagnosis, serological antibody testing, predominantly acetylcholine receptor (AChR) antibodies, is usually performed. The clinical utility of muscle-specific kinase (MuSK) antibodies is less well established in OMG. This meta-analysis evaluates the use of anti-AChR and anti-MuSK in patients with OMG and the relative costs of simultaneous vs sequential testing. METHODS: Studies were extracted from Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase (Ovid), Medline (Ovid), and additional gray literature. A systematic review was conducted using Covidence with 2 independent reviewers for study selection and data extraction. The meta-analysis was conducted with R version 4.4.1 on RStudio, and the meta package. Depending on the level of heterogeneity, either a fixed-effects or random-effects model was used to pool the data. Funnel plots were used to assess publication bias. RESULTS: The pooled analysis of 44 studies (n = 4,937 patients with OMG) revealed 59% (95% confidence interval [CI]: 52%-66%) positivity for anti-AChR, whereas the pooled analysis of 34 studies with (n = 3,380) showed 5% (95% CI: 2%-9%) positivity for anti-MuSK. From 62 studies (n = 5,180), 4 patients (0.1%) were doubly seropositive for anti-AChR and anti-MuSK. In patients with OMG positive for AChR antibodies, 5 studies (n = 527) reported a thymoma prevalence of 35% (95% CI: 3%-90%), underscoring the clinical value of anti-AChR testing. Four studies (n= 259) showed that anti-AChR positive patients had a 1.82 (95% CI: 1.15-2.88) times greater risk of progressing from OMG to generalized myasthenia gravis. CONCLUSIONS: Almost two-thirds (59%) of the patients with OMG tested positive for AChR antibodies, but MuSK antibodies were only detected in 5% of patients. Positivity for anti-AChR in OMG was associated with a worse prognosis, including a higher prevalence of thymomas and an increased risk of disease generalization. Given the relatively low prevalence of anti-MuSK and the higher cost of anti-MuSK testing, clinicians could consider a stepwise approach to the serological diagnosis of OMG, where anti-MuSK is ordered only if the initial anti-AChR returns negative.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.094
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
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 head0.062
GPT teacher head0.344
Teacher spread0.282 · 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 designObservational
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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