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Record W4413836344 · doi:10.1177/22925503251371048

Acquired Brown Syndrome as a Postoperative Complication of Orbital Wall Fracture Repair with Metallic Mesh

2025· article· en· W4413836344 on OpenAlexaff
Justin J. Lee, Nikhil S. Patil, Trent Schimmel, Matthew D. Benson, Joshua J. DeSerres

Bibliographic record

VenuePlastic Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicFacial Trauma and Fracture Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineDiplopiaSurgeryOrbital FractureStrabismus surgeryReduction (mathematics)Internal fixationFixation (population genetics)Strabismus

Abstract

fetched live from OpenAlex

Background: Surgical repair of orbital fractures comes with risks. One rare risk is interference with the actions of the superior oblique tendon-muscle complex causing an acquired Brown syndrome. We present the case of a 45-year-old man who developed acquired Brown syndrome after undergoing repair of a large orbital floor and medial orbital wall fracture using a titanium mesh implant. A case report was prepared to discuss a rare surgical risk with open reduction internal fixation (ORIF) of an orbital wall fracture. Methods: A retrospective chart review was performed. Results: Post-operative ophthalmological assessment revealed persistent diplopia along with limitations of up-gaze particularly in the adducted position. Ultimately, the patient underwent surgical repositioning of the orbital implant, which seemingly released the superior oblique muscle-tendon complex, resolving most of the diplopia. No further treatment with prisms or strabismus surgery has been required. Conclusions: Acquired Brown syndrome is a potential risk of surgical repair of orbital fractures involving the medial orbital wall. Herein this case study, we describe a case of acquired Brown syndrome following ORIF of an orbital floor and medial wall fracture, which was alleviated with a revision surgery.

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)0.001
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 score0.292
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.254
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 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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