Topical Insulin as a Novel Treatment for Persistent Epithelial Defects and Other Ocular Surface Disorders: A Systematic Review
Bibliographic record
Abstract
Abstract Purpose Through this systematic review, we evaluated the therapeutic potential of topical eye insulin in different concentrations to treat several surface ocular pathologies, including: persistent epithelial defects, diabetic keratopathy after a vitrectomy, neutrophic keratopathy and dry eye syndrome. We have consolidated through the data, what are the doses used, the methods of preparation for insulin, whether there are adverse effects and what would be the effectiveness of the eye drops with insulin. Methods We carried out an extensive search including Pubmed, Cochrane Library, Scopus and Web Of Science. We found 43 relevant studies, after which we excluded duplicates, animal studies, case reports, we ended up with 14 studies to include in the article. Through the Newcastle-Ottawa scale for observational studies and the Jadad scale for randomized controlled trials, we investigated the methodological quality of these articles. Results Within the review we included a significant number of 525 patients who used eye drops with insulin in concentrations from 0.5 to 2 U/ml, having an ocular benefit in corneal healing rates without adverse effects. The quality analysis of the included studies showed a NOS score of moderate-high quality, whereas the Jadad scale showed a high quality. Conclusions Our systematic review demonstrates that patients with persistent epithelial defects, diabetic keratopathy following vitrectomy, neurotrophic keratopathy, and dry eye syndrome showed significant improvements in corneal healing rates. To gain a clearer understanding of the effectiveness of insulin eye drops, future research should include direct comparisons with autologous serum eye drops and amniotic membrane eye drops. These studies will help establish comprehensive clinical guidelines.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".