The Association of Lacrimal Gland Inflammation with Alopecia Areata
Bibliographic record
Abstract
PURPOSE: To describe the association of lacrimal gland inflammation with alopecia areata. METHODS: We reviewed the medical records of 4 patients diagnosed with lacrimal gland inflammation who had an antecedent or subsequent episode of alopecia. Data was collected on the presentation age, gender, medical history, disease onset, symptoms and signs, imaging, histopathology, systemic evaluation, management and outcome. Pathology and imaging results were correlated with clinical findings. RESULTS: Three patients were Asian and one Caucasian. Two developed alopecia after presentation for lacrimal inflammation. The remaining two had a history of alopecia totalis (2 years and 10 years). Three of the 4 patients presented or developed other systemic disorders, including seizures, thrombocytopenia, optic neuritis, ulcerative colitis, allergic rhinitis, lymphadenopathy, vasculitic rash and positive p-ANCA values. All received oral corticosteroids, with the addition of methotrexate therapy in one for relapsing inflammation. CONCLUSIONS: Lacrimal gland inflammation and alopecia areata are autoimmune processes that can be seen in association with each other.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".