Examining the Relationship Between Alcohol Use Disorder and Glaucoma: Protocol for a Scoping Review
Bibliographic record
Abstract
Background: Alcohol use disorder (AUD) is a condition characterized by uncontrollable alcohol use despite negative social, occupational, or health consequences. AUD affects major organ systems in the body, including the eyes, in different ways. Alcohol seems to have dose-dependent effects on intraocular pressure (IOP), with some quantities lowering IOP and promoting blood flow to the optic nerve head, whereas higher quantities are linked to cardiovascular disorders and systemic physiological changes affecting glaucoma development. Current research shows mixed findings on the correlation between alcohol consumption and glaucoma, and little has been investigated in the AUD population. This paper outlines a protocol for a scoping review that aims to characterize the literature on the connection between AUD and its related conditions, such as alcohol dependence and alcohol misuse, and glaucoma and its associated symptoms, including increased IOP, optic nerve damage, and vision loss. Objective: The overarching goal of this scoping review is to synthesize an extensive overview of the current literature surrounding AUD or alcohol consumption and glaucoma. We aim to (1) map the existing literature on alcohol and glaucoma; (2) identify how alcohol consumption is associated with glaucoma; and (3) synthesize evidence concerning the association between AUD or alcohol consumption, including drinking frequency, quantity, and type, and glaucoma. Methods: A biomedical librarian will conduct a systematic search of PubMed and MEDLINE, Embase, Web of Science, and CENTRAL. A 2-step process will be used to screen the results, using Covidence as the screening software. All unique records retrieved from the databases and those identified through supplemental searches will be screened by 2 reviewers independently using the eligibility criteria. This will be followed by data charting. This evidence synthesis will summarize findings in narrative and tabular formats. Results: This scoping review was started in Covidence in November 2024 and is currently funded by the National Institutes of Health Intramural Research Program. The projected end date for data collection and submission is between November 2025 and January 2026. Conclusions: This scoping review aims to clarify the mixed findings on the association between AUD or alcohol consumption and glaucoma. The findings will guide future research in this area.
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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 | 0.062 | 0.089 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.076 | 0.011 |
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".