The Double Layer Sign Is Highly Predictive of Progression to Exudation in Age-Related Macular Degeneration
Bibliographic record
Abstract
PURPOSE: The presences of a double layer sign (DLS) and a shallow irregular retinal pigment epithelium (RPE) elevation (SIRE) were investigated using spectral domain-OCT (SD-OCT) imaging to determine their ability to predict progression to exudative macular neovascularization (eMNV) in the unaffected fellow eyes (study eye) of participants with age-related macular degeneration (AMD) with newly diagnosed unilateral eMNV. DESIGN: Retrospective, reanalysis of SD-OCT scans of study eyes from the Early Detection of Neovascular AMD (EDNA) study with 3 years follow-up (FU). PARTICIPANTS: The EDNA study repository of SD-OCT scans was assessed for inclusion. Cases with incomplete data sets, low quality scans, or exhibiting other pathology were excluded, which resulted in 459 eligible cases. METHODS: Spectral domain-OCT volume scans of study eyes were graded for irregular elevation of the RPE (IE), with length, and height measurements made on the most affected B-scan. Eyes with heterogeneous reflectivity within the IE were classified as exhibiting the DLS. Eyes with DLS where the length of separation between RPE and Bruch's membrane was ≥ 1000 μm in length and < 100 μm in height were subclassified as SIRE. MAIN OUTCOME MEASURES: Hazard of progression to eMNV for DLS and SIRE. RESULTS: Of the 459 eyes, 268 had IE, of which 101 were DLS-like and 51 also fulfilled criteria for SIRE. Over the 3 years FU period, 104 (23%) eyes progressed to eMNV. After an FU of 18 months, a significantly higher proportion of study eyes (P < 0.001) with IE, DLS, and SIRE developed eMNV compared with those without these features (IE: 17% vs. no IE 6.3%; DLS: 23% vs. no DLS 9.9%; SIRE: 22% vs. no SIRE 11%). In the adjusted Cox regression models, a significantly greater hazard of progression (P < 0.001) was associated with the presence of IE (adjusted hazard ratio [HR], 3.01; 95% confidence interval [CI], 1.88-4.82), DLS (adjusted HR, 3.41; 95% CI, 2.26-5.14), or SIRE (adjusted HR, 2.83; 95% CI, 1.68-4.75). CONCLUSION: The DLS is a highly sensitive predictor of progression to eMNV, and the use of SIRE does not improve predictability. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".