CHORIOCAPILLARIS FLOW DEFICITS AS A RISK FACTOR FOR PROGRESSION OF AGE-RELATED MACULAR DEGENERATION
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 evaluate the association between choriocapillaris (CC) flow deficits and structural optical coherence tomography biomarkers and the progression of intermediate age-related macular degeneration (iAMD) to complete retinal pigment epithelial and outer retinal atrophy. METHODS: Retrospective analysis of consecutive patients with iAMD with a minimum follow-up of 12 months. Odds ratios of intraretinal hyperreflective foci, hyporeflective drusen cores, subretinal drusenoid deposits, the presence of drusen volume ≥0.03 mm3 within a central 3-mm circle, fellow eye with late stage of AMD, and CC flow deficits at baseline and months of follow-up were estimated from logistic regression. RESULTS: A total of 112 eyes with iAMD were included. Eyes that progressed were significantly more likely to show intraretinal hyperreflective foci, hyporeflective drusen cores, and drusen volume ≥0.03 mm3. The CC flow deficit was also significantly greater in eyes that developed complete retinal pigment epithelial and outer retinal atrophy. Intraretinal hyperreflective foci, hyporeflective drusen cores, drusen volume ≥0.03 mm3, and higher CC flow deficits were significantly and independently associated with the development of complete retinal pigment epithelial and outer retinal atrophy. CONCLUSION: The CC flow deficit was significantly greater in iAMD eyes that progressed to complete retinal pigment epithelial and outer retinal atrophy and remained an independent risk factor when structural optical coherence tomography biomarkers were considered. CC flow deficits may be useful for enhancing risk stratification and prognostication of patients with iAMD.
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) | 0.000 | 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