Influence of Treating Ocular Surface Disease on Intraocular Pressure in Glaucoma Patients Intolerant to Their Topical Treatments: A Report of 10 Cases
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate the effect of treating ocular surface disease (OSD) in patients with medically uncontrolled primary open-angle glaucoma (POAG) associated with OSD. METHODS: We compiled a retrospective observational case series of 10 patients with POAG that remained uncontrolled with topical treatments and who were referred for filtering glaucoma surgery. All patients underwent a complete assessment of their glaucoma and ocular surface for both eyes. The main treatments were change of topical antiglaucoma medications to preservative-free equivalents, removal of allergenic treatments or those identified as causing side effects, switch to another therapeutic class with the same efficacy but with a better safety profile and treatment of OSD. RESULTS: After a minimum follow-up of 6 months, we observed improved ocular surface in all patients, associated with an intraocular pressure (IOP) decrease or stabilization even if some antiglaucoma medications were removed. The mean IOP significantly decreased from 23.75±9.98 mm Hg to 15.15±4.75 mm Hg (-36.2%; P=0.0001). The mean number of IOP-lowering medications was 3.7±1.06 at presentation and 2.8±0.63 after treatment (P=0.01). The Oxford score also decreased from a mean 1.7±0.67 to 0.4±0.51 (-76.5%; P<0.001). For 2 patients, IOP was not sufficiently reduced after treatment and they finally underwent filtering surgery. CONCLUSIONS: The prevalence of OSD in POAG patients is very high, particularly in patients with uncontrolled glaucoma with multiple topical medications. Careful management of the ocular surface associated with a reduction of the toxicity of eyedrops may result in improvement of ocular surface health and better IOP control.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".