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Record W3097504758 · doi:10.1177/1120672120963452

Late recurrence of idiopathic Brown’s syndrome successfully treated with oral corticosteroids

2020· article· en· W3097504758 on OpenAlexaff
Cody Lo, Jonathan A. Micieli

Bibliographic record

VenueEuropean Journal of Ophthalmology · 2020
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsUniversity of TorontoKensington HealthUniversity of British Columbia
Fundersnot available
KeywordsMedicineSubclinical infectionPrednisoneSurgeryPresentation (obstetrics)Connective tissue diseaseDermatologyDiseaseInternal medicineAutoimmune disease

Abstract

fetched live from OpenAlex

INTRODUCTION: Idiopathic Brown's syndrome is a restrictive strabismus of the superior oblique tendon that often presents in pediatric populations and rarely occurs in adults. CASE DESCRIPTION: We present here a case of a 41-year-old man with an idiopathic left Brown's syndrome that recurred after presenting with similar symptoms 14 years prior that was originally treated with oral corticosteroids. This patient had a negative work up for connective tissue disease and only exhibited subtle left trochlear thickening on orbital MRI with contrast. Since he had a good response to oral corticosteroids in the past, this repeat occurrence was treated with oral Prednisone and he promptly responded. His double vision resolved within 2 weeks and he continued to have a normal examination 6 months after presentation. CONCLUSION: We suspect this case was related to a subclinical inflammatory process resulting in the MRI findings and response to steroids. This case demonstrates that idiopathic Brown's syndrome can recur more than a decade later in adults and oral corticosteroids are an effective treatment option even in the absence of an underlying rheumatological condition.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.276
Teacher spread0.238 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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