Pediatric Ocular Surface Inflammatory Diseases: Clinical Features and Practice Patterns
Bibliographic record
Abstract
PURPOSE: To characterize nationwide real-world practice patterns and complications of pediatric ocular surface inflammatory diseases (POSID) using a large US health insurance claims database. METHODS: This retrospective cohort study analyzed patients younger than 18 years diagnosed with POSID in the Optum Labs Data Warehouse between 2018 and 2019. Blepharokeratoconjunctivitis (BKC), herpes simplex keratoconjunctivitis (HSK), and vernal keratoconjunctivitis (VKC) were identified by ICD codes. Clinical data from 6 months before to 3 years after the index visit were assessed. Multivariate logistic regression identified risk factors for amblyopia. RESULTS: Among 6116 children (67.1% aged 5-15 years; 56.6% male), HSK showed the highest baseline rates of corneal scarring (7.5%) and ulceration (5.5%), compared with BKC (2.3%, 2.7%) and VKC (1.1%, 0.9%) (P < 0.001). High-potency topical corticosteroids were more frequently prescribed for BKC (17.8%) than HSK (15.0%) or VKC (14.2%) (P = 0.02), while topical immunomodulators were used in only 1.7% of cases despite recommendations. Amblyopia prevalence rose from 2.5% to 4.5% over 3 years, with stromal scarring at diagnosis (odds ratio 2.43, 95% confidence interval 1.40-4.24) and high-potency corticosteroid use (odds ratio 1.60, 95% confidence interval 1.17-2.18) as independent risk factors. CONCLUSIONS: POSID subtypes exhibit distinct clinical features, significant differences in management, and progressive complications over time. Nationwide patterns show over-reliance on corticosteroids, underuse of immunomodulators, and gaps between guideline recommendations and practice, underscoring the need for earlier recognition, steroid-sparing therapy, and sustained inflammation control.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".