Choroidal vascularity profile in diabetic eyes using wide field optical coherence tomography
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose To report the wide-field choroidal vascularity up to the mid-equator area in diabetic retinopathy (DR) subjects using wide-field optical coherence tomography (WF-OCT). Design Prospective, Cross-sectional study. Participants Forty-seven eyes of 25 DR subjects. Methods WF-OCT images (55 degrees) were obtained using Spectralis HRA + OCT (Heidelberg Engineering, Germany) in extremes of gazes in all quadrants and manual montages were created to obtain wide field images up to mid equator. A previously reported semi-automated algorithm was used to calculate choroidal vascularity profile (CVI). Regression analysis was performed to identify the factors influencing CVI. Results Forty-seven eyes from 25 patients were enrolled in the study. The mean age was 68.4 ± 10.6 years. The refractive error (spherical equivalent) ranged from −2.25 to +3.75 diopters. Most common DR grade among study subjects was moderate NPDR (29.41%) and 74.5% eyes had diabetic macular edema (DME). The mean CVI in the macular area (58.29 ± 3.63) was significantly lower than in any of the other fundus areas (all p ˂ 0.01). The maximum CVI was seen in the nasal region (66.60 ± 5.61), followed by temporal (65.69 ± 3.81), superior (65.01 ± 4.87), and inferior (63.80 ± 5.42). The vertical macular area had the least coefficient of variation (CV) of CVI (0.06) while the inferior quadrant had the highest CV (0.08). Conclusion The current study describes the CVI profile on WF-OCT in DR eyes up to mid-equator. The significant increase of the CVI compared to healthy subjects and its significant regional variations introduce this novel quantitative parameter as a reliable biomarker of the diabetes-induced choroidal microangiopathy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| 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) | 0.001 | 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 it