SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY AND OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY FINDINGS IN WAARDENBURG SYNDROME
Bibliographic record
Abstract
PURPOSE: Waardenburg syndrome (WS) is a rare condition characterized by six main features. It has been previously observed that WS is also associated with hypopigmentation of the choroid through multimodal imaging. To our knowledge, this is the first report of using swept-source optical coherence tomography angiography (OCTA) on a patient with known WS. METHODS: Report of a single case. The swept-source OCT images were captured using Topcon DRI OCT Triton (Topcon, Inc, Tokyo, Japan), whereas swept-source OCTA images were captured by Optovue AngioVue (Optovue, Inc, Fremont, CA) using DualTrack Motion Correction Technology. RESULTS: In this case, OCTA demonstrated evidence of normal vasculature of all layers (superficial, deep, and choricocapillaris), a normal foveal avascular zone measuring 0.267 mm2 in the right eye and 0.307 mm2 in the left eye, and a normal capillary density measuring 49.8% in the right eye and 52.6% in the left eye. CONCLUSION: There are many conditions that may mimic the hypopigmentation of the choroid associated with WS; it has been documented that these similar conditions such as choroidal nevus, choroidal melanoma, and Vogt-Koyanagi-Harada syndrome all demonstrated abnormal OCTA findings. Unlike these conditions, our patient with WS had unremarkable OCTA findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".