Exploring the contribution of carotid artery disease to the onset of non-arteritic ischemic optic neuropathies: A systematic review
Bibliographic record
Abstract
PURPOSE: The role of carotid artery disease (CAD) in the development of various types of ocular arterial occlusive disorders has often been reported. This systematic review aims to evaluate and review the current evidence regarding the role of CAD and the subsequent carotid artery hemodynamic alterations in the development of non-arteritic anterior (NA-AION) and posterior (NA-PION) ischemic optic neuropathy. METHODS: We systematically reviewed studies following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We systematically searched PubMed, Embase, and Scopus databases for relevant studies that clearly assessed the role of CAD and the subsequent carotid artery hemodynamic alterations in the development of NA-AION and NA-PION. All studies that examined the associations between CAD and the development of NA-AION and NA-PION in adults aged 18 years or older were synthesized. Quality assessment using the Newcastle-Ottawa Scale (NOS), and Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Case Reports and Case-Series were also conducted. RESULTS: Our search identified 1933 manuscripts published in the English language. The number of participants with non-arteritic ischemic optic neuropathy (NA-ION) ranged from 1 to 191, with a total of 478 patients experiencing either NA-AION (410 out of 478), NA-PION (13 out of 478), or a combination of thereof (1 out of 478). The number of participants with NA-ION due to atherosclerosis ranged from 1 to 191, with a total of 376 patients. CONCLUSIONS: Although carotid artery disease may rarely contribute to the development of NA-ION, it should be considered as a possible cause of NA-ION.
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.008 | 0.009 |
| 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) | 0.003 | 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".