Double-Positive Anti–Glomerular Basement Membrane Antibody and Myeloperoxidase Antineutrophil Cytoplasmic Autoantibody–Associated Glomerulonephritis Post COVID-19 mRNA vaccine: A Case Series of 4 Patients
Bibliographic record
Abstract
Rationale: Vaccines remain central to the management of COVID-19 pandemic, including the need for repeat doses of vaccines to boost immunity. There has been an accumulating case count of glomerulopathies temporally associated with COVID-19 vaccination. This case series presents 4 patients who developed double-positive anti-glomerular basement membrane antibody (anti-GBM) and myeloperoxidase (MPO) antineutrophil cytoplasmic autoantibody (ANCA)-associated glomerulonephritis after COVID-19 mRNA vaccination. This report contributes to our collective knowledge about the pathophysiology and clinical outcomes associated with this rare complication. Presenting Concerns of the Patient: Four patients developed nephritic syndrome within 1 to 6 weeks after receiving a COVID-19 mRNA vaccine (3 post Pfizer-BioNTech and 1 post Moderna vaccination). Three of the 4 patients also had hemoptysis. Diagnosis: Three of the 4 patients had double-positive serology, whereas the fourth patient had renal biopsy findings consistent with double-positive disease, although anti-GBM serology was negative. All patients had renal biopsy findings consistent with double-positive anti-GBM and ANCA-associated glomerulonephritis. Interventions: All 4 patients were treated with pulse steroids, cyclophosphamide, and plasmapheresis. Outcomes: Of the 4 patients, 1 demonstrated complete remission, 2 remained dialysis-dependent, and the fourth is deceased. Of the 2 patients who received repeat vaccination with COVID-19 mRNA vaccine, 1 patient had second serologic flare of anti-GBM in response to the vaccine. Novel Findings: This case series reinforces growing evidence that COVID-19 mRNA vaccine-induced glomerulonephritis is a rare but real phenomenon. Dual ANCA and anti-GBM nephritis can present after the first dose of COVID-19 mRNA vaccine or after several administrations of the vaccine. We are the first to report cases of double-positive MPO ANCA and anti-GBM nephritis after Pfizer-BioNTech vaccination. To our knowledge, we are also the first to report outcomes of repeat COVID-19 vaccination in patients with de novo flare of ANCA and anti-GBM nephritis temporally associated with COVID-19 vaccination.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".