Multimodal imaging findings of multiple evanescent white dot syndrome in COVID-19 patients
Bibliographic record
Abstract
Purpose: To describe the multimodal imaging findings of a rare case of multiple evanescent white dot syndrome (MEWDS) associated with COVID-19. Methods: A case report was analyzed and described alongside COVID-19 associated MEWDS cases identified in the current literature. Results: A healthy 20-year-old man was evaluated after a three-day history of blurry vision occurring two months after COVID-19 infection. Multimodal imaging revealed signs of typical MEWDS, with optical coherence tomography angiography (OCT-A) demonstrating homogenous reflectivity. Six additional cases were reported in the literature, displaying clinical symptoms and imaging consistent with typical MEWDS but demonstrating higher rates of incomplete visual recovery and treatment use. Conclusions: COVID-19 associated MEWDS is a novel condition. This is the first known case of COVID-19 associated MEWDS with reported OCT-A findings in an otherwise healthy patient. Although posterior uveitis following COVID-19 infection is rare, clinicians should remain informed on the best practices for diagnosing and caring for patients with MEWDS.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".