Vogt-Koyanagi-Harada disease following influenza vaccination
Bibliographic record
Abstract
Purpose: To report a case of Vogt-Koyanagi-Harada (VKH) disease following influenza vaccination. Observations: A 30-year-old Filipino male developed bilateral pain, redness, photophobia, floaters, headache and tinnitus 2 days after receiving the annual influenza vaccine. He presented to the emergency department 5 days after symptom onset. His past medical and ocular history was unremarkable. His best-corrected distance visual acuity (BCVA) was 20/100 in the right eye (OD) and 20/150 in the left eye (OS). Slit-lamp examination revealed fine keratic precipitates and 1+ anterior chamber cells in both eyes (OU). Dilated fundus examination revealed 1+ vitreous cells with trace haze and multiple serous retinal detachments OU. Magnetic resonance imaging (MRI) of the brain and chest X-ray were unremarkable. Serologic testing was negative for infectious, inflammatory and neoplastic causes. The patient tested positive for HLA-DR4. A diagnosis of acute Vogt-Koyanagi-Harada disease was made and high-dose oral prednisone, intravitreal triamcinolone acetonide and mycophenolate mofetil were needed to achieve quiescence. At 6 months follow-up, our patient remains in remission with no active intraocular inflammation or subretinal fluid. His BCVA has improved to 20/50 OD and 20/30 OS. Conclusion and importance: The annual influenza vaccine may be a trigger for onset or recurrence of VKH in genetically susceptible individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".