Factors affecting ocular trauma in Iran: A systematic review study
Bibliographic record
Abstract
Background and Aims: Ocular trauma (OT) is a a major cause of ocular morbidity and blindness. This study was systematically conducted to determine the factors contributing to OT in Iran. Methods: In this study, a systematic review of all published articles in Persian and English languages from 2000 to 2023 was conducted to investigate the factors affecting OT in Iran. The included studies encompassed cross-sectional, cohort, and case-control designs. Articles were selected from internationally recognized databases, including PubMed, Web of Science, Scopus, and Google Scholar, as well as Persian databases such as SID and Magiran. The search strategy involved using keywords aligned with the (MeSH) terms, such as "oculars," "trauma," and "Iran." Initially, 403 articles were identified, and ultimately, 14 articles met the inclusion criteria. To ensure the prevention of bias and assess the quality of the selected articles, the Newcastle-Ottawa Scale was utilized. Result: In the present study, the majority of individuals in the reviewed articles were categorized as having mild eye injuries (13.8%). A higher percentage of injuries was observed in males compared to females, and a higher prevalence of injuries was also observed in the age group of over 30 years compared to other age groups. Among the mechanical causes, sharp trauma had the highest prevalence rate (72.5%), while falls had the lowest prevalence rate (14%), followed by sport-related injuries (29%). Non-mechanical injuries were mentioned in only one article and had a prevalence rate of 1.5. Conclusion: The results of the current research have shown that among the mechanical injuries, accidents involving motorcycles and sharp objects are the leading causes of OT in Iranians. Therefore, the use of protective equipment such as goggles and adherence to traffic laws play a particularly important role, especially in men higher the age of 30. These findings highlight the necessity for targeted educational and preventive measures to reduce OT in Iran.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".