DISCREPANCY BETWEEN FLUORESCEIN ANGIOGRAPHY AND OPTICAL COHERENCE TOMOGRAPHY IN DETECTION OF MACULAR DISEASE
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Bibliographic record
Abstract
In Brief Purpose: To compare high-resolution optical coherence tomography (OCT) and fluorescein angiography (FA) in detection of macular edema (ME) of various etiologies. Methods: In a retrospective study over a 12-month period at one retina center, data for consecutive eyes that had undergone simultaneous conventional FA (HRA; Heidelberg Engineering, Vista, CA) and StratusOCT (Carl Zeiss Meditec, Dublin, CA) to rule out ME were reviewed. A subset of patients underwent additional examination with extremely high-resolution (6-μm)/ultrahigh-speed spectral OCT/scanning laser ophthalmoscopy (OTI, Inc., Toronto, Ontario, Canada). Results: Of 1,272 eyes, 1,208 (94.97%) had the finding of ME or subretinal fluid confirmed by both techniques. There were 49 eyes (3.86%) for which FA showed dye leakage in the macular area and OCT showed normal foveal contour. Of 10 eyes in this group that underwent imaging with ultrahigh-speed spectral OCT/scanning laser ophthalmoscopy, 8 had subtle diffuse lucencies in the retina. For 15 eyes (1.17%), OCT showed intraretinal and subretinal fluid, which was missed by FA. Conclusions: Both FA and high-resolution OCT are highly sensitive techniques and correlate well in detection of ME. However, there is a small chance that when performed alone they might miss existing subtle ME. Both fluorescein angiography and high-resolution optical coherence tomography are highly sensitive techniques and correlate well in detection of macular edema. However, a small chance exists that when performed alone they might miss existing subtle macular edema.
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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) | 0.000 | 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 it