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Record W4384951922 · doi:10.1097/wno.0000000000001950

Maculopathies Referred to Neuro-Ophthalmology Clinic as Optic Neuropathies: A Case Series

2023· article· en· W4384951922 on OpenAlexaff
Amir R. Vosoughi, Laura Donaldson, Jonathan A. Micieli, Edward Margolin

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2023
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsUniversity of ManitobaToronto Western HospitalMcMaster UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsOphthalmologyNeuro-ophthalmologyOptometrySeries (stratigraphy)MedicineGlaucomaGeology

Abstract

fetched live from OpenAlex

BACKGROUND: The clinical features of maculopathies and optic neuropathies often overlap: Both present with decreased visual acuity and variable loss of color vision; thus, maculopathy can be misdiagnosed as optic neuropathy, leading to patient harm. We aimed to determine what findings and/or tests were most helpful in differentiating between optic neuropathy and maculopathy. METHODS: A retrospective chart review of consecutive patients over 4.5 years who were referred to neuro-ophthalmology clinics with the diagnosis of optic neuropathy but whose final diagnosis was maculopathy. Patient demographics, mode of presentation, clinical profile, complete ophthalmological examination, results of all ancillary testing, and final diagnosis were recorded. RESULTS: A total of 47 patients (27 women) were included. The median age was 55 years (range, 18-85). Most referrals were by ophthalmologists (72.3%) and optometrists (12.8%). The diagnosis of maculopathy was made in 51.1% of patients at the time of first neuro-ophthalmic consultation. Only 6.4% patients (3) had relative afferent pupillary defect. Benign disc anomalies (tilted, myopic, small, or anomalous discs) were present in 34.0%, and 21.3% had pathologic disc changes unrelated or secondary to maculopathy. Macular ocular coherence tomography (OCT) was abnormal in 84.4% (with outer retinal pathology in 42.2% and inner retina pathology in 17.8%). Retinal nerve fiber layer (RNFL) thickness was normal in 82.6% of patients. CONCLUSIONS: Macular OCT is a high-yield test in differentiating between optic neuropathy and maculopathy and should be obtained in patients with suspected optic neuropathies who have normal RNFL thickness. Macular dystrophies, particularly cone dystrophies, unspecified retinal disorders, and macular degeneration were the most common mimics of optic neuropathy. The diagnosis was often present on OCT of the macula. The presence of coexistent benign and pathological disc anomalies may lead to maculopathy being misdiagnosed as optic neuropathy.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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)0.0010.001

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 head0.061
GPT teacher head0.353
Teacher spread0.291 · 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.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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