The role of optical coherence tomography angiography in assessing diabetic choroidopathy: a systematic review
Bibliographic record
Abstract
BACKGROUND: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, affecting both retinal and choroidal vasculature. While advances in imaging technology, particularly optical coherence tomography angiography (OCTA), provide new opportunities to assess choroidal changes in diabetic patients, the role of OCTA in early diagnosis and monitoring of diabetic choroidopathy remains unclear. OBJECTIVE: This review aims to evaluate the potential role of OCTA in diagnosing and monitoring diabetic choroidopathy. METHODS: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Databases including PubMed, Embase, Cochrane Library, Google Scholar, ISI, and Scopus were searched for studies on diabetic choroidopathy assessed by OCTA. Studies included were peer-reviewed, published in English, and excluded case reports, conference proceedings, and studies on treated DR patients. Two independent reviewers screened articles for eligibility based on predefined criteria. RESULTS: OCTA allows for non-invasive, high-resolution visualization of retinal and choroidal microvasculature, providing both qualitative and quantitative data. The majority of studies indicate a significant decrease in choroidal perfusion parameters in diabetic patients without DR compared to healthy controls. Conflicting evidence exists regarding the correlation between choriocapillaris flow reduction and DR severity. OCTA may also predict changes in visual function related to choroidal perfusion, though it cannot fully replace clinical examinations. CONCLUSIONS: OCTA is a valuable tool for early detection and monitoring of diabetic choroidopathy. However, its role is limited by variability in findings and its inability to detect certain features of diabetic microangiopathy. Further studies are needed to clarify its clinical utility and standardize assessment methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".