Age-Related Macular Degeneration Prevalence and its Risk Factors in Iran: A Systematic Review and Meta-Analysis Study
Bibliographic record
Abstract
Purpose: To estimate the prevalence of age-related macular degeneration (AMD) and determine its risk factors in Iran. Methods: A comprehensive electronic search was conducted in PubMed, Scopus, Web of Science, and Google Scholar, with no restrictions on time or language of publication. Eleven studies meeting the eligibility criteria were included. Six studies with a total sample size of 9930 were included in the meta-analysis to calculate the overall prevalence of AMD in Iran. Meta-analysis was performed using Stata/MP version 15.0. Risk of bias assessment was carried out based on the Newcastle-Ottawa Scale. Results: All participants in the studies were over 40 years old. The pooled prevalence of AMD was estimated to be 9.9% (95% confidence interval [CI]: 6.3%-13.5%). After accounting for publication bias, this estimated decreased to 6.4% (95% CI: 4%-10.2%). Smoking (odds ratio [OR]: 1.781; 95% CI: 1.152-2.756), hypertension (HTN) (OR: 1.512; 95% CI: 1.119-2.044), diabetes mellitus (DM) (OR: 1.545; 95% CI: 1.088-2.194), and hyperlipidemia (OR: 1.512; 95% CI: 1.055-2.165) were identified as AMD risk factors. Conclusion: Based on the results of the present review, the prevalence of AMD in the Iranian population over 40 years of age is estimated to be 6.4%, and having a history of smoking, HTN, DM, and hyperlipidemia are identified as risk factors of AMD in Iran. Further original studies are needed to draw more accurate conclusions.
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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 | 0.013 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".