Ocular sarcoidosis: A clinicopathological study
Bibliographic record
Abstract
Abstract Purpose: This study aims to deliver an in-depth analysis and detailed account of 15 patients diagnosed with ocular and periocular sarcoidosis, each case substantiated by biopsy and histopathological examination. Furthermore, our series emphasizes the critical role of computed tomography (CT) scans in assessing the lacrimal gland, particularly when clinical symptoms, paraclinical findings, and radiological evidence suggest the presence of sarcoidosis. Methodology: We conducted a retrospective analysis of biopsy-diagnosed sarcoidosis cases at the MUHC-McGill University Ocular Pathology and Translational Research Laboratory spanning from 1995 to 2023. Pathological descriptions were thoroughly assessed, and clinical information was obtained from medical records for each patient. Results: A total of 15 cases were analyzed, 8 females and 7 males, with ages ranging from 16 to 89. All biopsies revealed granulomatous inflammation characterized by discrete, noncaseating granulomas. The most common site for biopsy was the lacrimal gland, followed by conjunctiva. Patients who underwent lacrimal gland biopsy exhibited bilateral, symmetrical enlargement of the gland, as confirmed by a CT scan. Conclusion: Diagnosing sarcoidosis presents significant challenges. Conducting blind biopsies is inadvisable and should be avoided. Targeted biopsies of abnormal lesions in the conjunctiva and eyelid have been proven to be diagnostic. In cases of suspected sarcoidosis, a CT scan of the orbit serves as an invaluable tool for determining the optimal biopsy site, thereby enhancing diagnostic accuracy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".