The potential role of vitamin D supplementation in the treatment of Dry Eye Disease (DED): a systematic review
Bibliographic record
Abstract
Background: Dry Eye Disease (DED) is a prevalent condition that involves instability, increased osmolarity, and inflammation of the tear film and ocular surface. Vitamin D is known for its anti-inflammatory properties. Association between vitamin D deficiency and increased incidence of DED has been suggested. However, no study currently exists that systematically reviews the potential role of vitamin D as a treatment for DED. Methods: The literature search was performed on December 2021 through PubMed, Scopus, ProQuest, EBSCOhost, ScienceDirect, dan Cochrane Library using the relevant keywords. The risk of bias was assessed using the Cochrane Risk of Bias tool, ROBINS-I tools, and the Newcastle-Ottawa Scale. Results: A total of 700 articles were found, 6 of which were considered relevant based on PRISMA protocol. The included articles consist of 2 case controls, a randomized interventional study, and 3 observational studies. Vitamin D supplementation improved tear stability, symptoms of dry eye disease, and serum vitamin D level affected the efficacy of topical therapy for DED. Conclusion: Despite this beneficial finding, serum vitamin D level does not significantly correlate with DED symptoms which the multifactorial nature of the disease might cause.
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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 | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 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".