Antimelanoma Differentiation-Associated Gene 5 Antibody–Positive Interstitial Lung Disease After Vaccination With COVID-19 mRNA Vaccines
Bibliographic record
Abstract
Objective Melanoma differentiation-associated gene 5 (MDA5) is a viral RNA sensor induced by SARS-CoV-2. Similarities have been reported between the clinical presentations of coronavirus disease 2019 (COVID-19) pneumonia and anti-MDA5 antibody–positive interstitial lung disease (anti-MDA5-ILD). However, it is unknown whether COVID-19 mRNA vaccines are associated with anti-MDA5-ILD. Methods We retrospectively reviewed consecutive patients with anti-MDA5-ILD admitted to our hospital between April 2017 and March 2022. In addition, we investigated the clinical presentations of patients who developed anti-MDA5-ILD after vaccination with COVID-19 mRNA vaccines. We also examined the annual number of anti-MDA5-ILD cases before and after the COVID-19 vaccination campaign. Results Nine patients with anti-MDA5-ILD were seen during the study period, of whom 4 developed anti-MDA5-ILD between August and October 2021, approximately 6 to 12 weeks after vaccination with a COVID-19 mRNA vaccine and a few months after the rapid mRNA COVID-19 vaccination campaign in Japan. None of the 4 patients had evidence of SARS-CoV-2 infection. The difference in the annual number of anti-MDA5-ILD cases before vs after the COVID-19 vaccination campaign (1.25 ± 0.96 cases/yr vs 4.0 cases/yr) was not statistically significant ( P = 0.08). Conclusion We encountered 4 cases of anti-MDA5-ILD after COVID-19 vaccination. Further large population studies are needed to clarify the relationship between anti-MDA5-ILD and vaccination with COVID-19 mRNA vaccines.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".