High Inflammatory Infiltrate Correlates With Poor Symptomatic Improvement After Surgical Treatment for Superior Limbic Keratoconjunctivitis
Bibliographic record
Abstract
PURPOSE: Superior limbic keratoconjunctivitis (SLK) is a chronic and recurrent condition of unknown etiology. It is often managed conservatively, but there is a high rate of success with surgical management for severe or recalcitrant cases. The purpose of this article is to describe and analyze clinicopathological features of patients with SLK who underwent surgical treatment and their association with the clinical outcome. METHODS: A total of 22 eyes from 18 patients who underwent surgical SLK management were retrospectively analyzed. Clinicopathological data were collected including details of follow-up and patient satisfaction (n = 15). Moreover, 12 cases had specimens available for review of histopathologic findings and COX-2 expression analysis by immunohistochemistry. RESULTS: From a clinical perspective, 66.7% of the SLK eyes had nonmechanical factors contributing to SLK, and 66.7% of eyes demonstrated significant symptomatic improvement after surgery. Histopathological analysis of all the lesions showed acanthosis and goblet cell loss. Unexpectedly, in 93% of the eyes, dilated lymphatic vessels were found. Furthermore, a high inflammatory infiltrate correlated with minimal symptomatic improvements (P = 0.013). Moreover, COX-2 expression was higher in patients with SLK than in a normal conjunctiva (P = 0.001). CONCLUSIONS: In this study, the most common systemic association with SLK was the patient's autoimmune status. Histopathological evaluation revealed that high inflammatory infiltration in the biopsy might be predictive of minimal symptomatic improvement with surgical management. Finally, the higher COX-2 expression in patients with SLK compared with that in individuals with a normal conjunctiva supports the use of anti-COX-2 drugs as a possible therapeutic target.
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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 | 0.000 | 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) | 0.001 | 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".