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Record W4280542127 · doi:10.1097/iop.0000000000002196

Predictive Modeling of New-Onset Postoperative Diplopia Following Orbital Decompression for Thyroid Eye Disease

2022· article· en· W4280542127 on OpenAlex
Archana Nair, Lilangi S. Ediriwickrema, Peter J. Dolman, Geoffrey Law, Andrew R. Harrison, Ali Mokhtarzadeh, Krista J. Stewart, Clara J. Men, Mark J. Lucarelli, Suzanne van Landingham, Maxwell Wingelaar, Rohan Verma, Allison Chen, Dinesh Selva, James Garrity, Laurence J. Eckel, Michael Kazim, Kyle J. Godfrey, Sally L. Baxter, Bobby S. Korn, Don O. Kikkawa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOphthalmic Plastic and Reconstructive Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Eye Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDiplopiaMedicineSurgeryGraves' ophthalmopathyDecompressionOrbit (dynamics)Extraocular musclesRetrospective cohort studyGraves' diseaseThyroidInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To identify risk factors for the development of new-onset, postoperative diplopia following orbital decompression surgery based on patient demographics, clinical exam characteristics, radiographic parameters, and surgical techniques. METHODS: We conducted a multi-center retrospective chart review of patients who underwent orbital decompression for thyroid eye disease (TED). Patient demographics, including age, gender, smoking history, preoperative exophthalmometry, clinical activity score (CAS), use of peribulbar and/or systemic steroids, and type of orbital decompression were reviewed. Postoperative diplopia was determined at a minimum of 3 months postoperatively and before any further surgeries. Cross-sectional area ratios of each extraocular muscle to orbit and total fat to orbit were calculated from coronal imaging in a standard fashion. All measurements were carried out using PACS imaging software. Multivariable logistic regression modeling was performed using Stata 14.2 (StataCorp, College Station, TX). RESULTS: A total of 331 patients without preoperative diplopia were identified. At 3 months postoperatively, 249 patients had no diplopia whereas 82 patients developed diplopia. The average postoperative follow-up was 22 months (range 3-156) months. Significant preoperative clinical risk factors for postoperative diplopia included older age at surgery, proptosis, use of peribulbar or systemic steroids, elevated clinical activity score, and presence of preoperative compressive optic neuropathy. Imaging findings of enlarged cross-sectional areas of each rectus muscle to the overall orbital area also conferred a significant risk of postoperative diplopia. Regarding surgical factors, postoperative diplopia was more common among those undergoing medial wall decompression, bilateral orbital surgery, and balanced decompression, whereas endoscopic medial wall decompression was found to be relatively protective. CONCLUSIONS: This study identifies risk factors associated with the development of diplopia following orbital decompression using multivariable data. This study demonstrates that several characteristics including age, clinical activity score, the cross-sectional muscle to orbit ratios, in addition to the type of orbital decompression surgery, are predictive factors for the development of new-onset postoperative diplopia.

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.

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 score0.289
Threshold uncertainty score0.905

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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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