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Sclerosing Orbital Inflammation and Systemic Disease

2012· article· en· W954613141 on OpenAlexaff
Bryan J. Winn, Jack Rootman

Bibliographic record

VenueOphthalmic Plastic and Reconstructive Surgery · 2012
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSystemic diseaseMedicineSystemic inflammationDiseaseInflammationInternal medicinePathologyGastroenterology

Abstract

fetched live from OpenAlex

PURPOSE: To determine the clinical differences between sclerosing orbital inflammation (SOI) isolated to the orbit and SOI manifesting as part of systemic inflammatory disease. METHODS: For the case series, the authors identified patients with SOI from their patient database and tabulated their clinical data. For the literature review, a search for case reports of SOI in the English literature was performed. The clinical data of each were tabulated and analyzed. RESULTS: For the case series, 13 cases of SOI were identified, 2 with multifocal fibrosclerosis (MFF) and 4 with other systemic inflammatory diseases. Of the 5 bilateral cases, 4 (80%) had some form of systemic inflammatory disease including 2 with MFF. Only 2 (25%) of the 8 unilateral cases had systemic inflammatory disease. The average ESR was 7 mm/hour for those without systemic disease and 41 mm/hour with evidence of systemic disease (p = 0.038). For the literature review, the authors identified 68 case reports of SOI not previously reported in large case series, 34 associated with MFF, 5 associated with other systemic disease, and 29 not associated with any systemic disease. Sixty-nine percent of cases with systemic disease had bilateral orbital involvement, whereas only 3.6% of those without systemic disease were bilateral (p = 1.15 × 10(-8)). Twenty of the cases with MFF noted ESR (83 mm/hour, mean), 95% of which were above normal. ESR was noted in only one non-MFF, nonsystemic disease case and was normal. CONCLUSIONS: SOI in the setting of MFF or other systemic inflammatory disease is often bilateral and associated with an elevated ESR.

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)0.000
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 score0.007
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.226
Teacher spread0.209 · 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
Published2012
Admission routes1
Has abstractyes

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