Effectiveness of a Preservative-Free Eye Drop, Cyclosporine 0.05% Emulsion, and Omega-3 Supplementation as a Fixed Combination in Dry Eye Disease – a Pilot Study
Bibliographic record
Abstract
Purpose: We aim to evaluate the impact of combining a preservative-free drop, cyclosporine 0.05% emulsion, and omega-3 oral supplementation on the signs and symptoms of dry eye in a typical ophthalmic practice.Design: A retrospective case series conducted on patients with dry eye disease.Methods: Patients diagnosed with dry eye in a typical ophthalmology practice were initiated on a fixed combination regimen which included a preservative-free eye drop (I-DROP ® PUR GEL, I-MED pharma), cyclosporine 0.05% ophthalmic emulsion, and oral omega-3 supplement(Dry Eye Omega Benefits®, PRN)for 3 monthsconsecutively. The primary outcome measured was a symptom score using the Canadian Dry Eye Assessment Tool (CDEA). Secondary outcome measure was Non-invasive Keratograph Break-up Time (NIKBUT). Primary and secondary outcomes measured at baseline and 3 months following intervention were compared.Results: Thirty-six patients were included with a female male ratio of 2.6:1 and average age of 64.Patient symptoms improved significantly following the intervention as demonstrated by a lower CDEA score during the second visit compared to the first visit (16.11 vs. 19.50, respectively) (p< .05). NIKBUT scores were also significantly improved as demonstrated by a higher score during the second visit compared to the first in both the right (13.18 vs. 11.44) (p< .05) and left (14.62 vs. 12.78) (p< .01) eyes, respectively.Conclusion: A fixed combination of preservative-free eye drops, cyclosporine 0.05% and omega-3 supplementation may be an effective first line treatment option in alleviating symptoms and improving signs of patients suffering from dry eye.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".