Minimal Change Disease After First Dose of Pfizer-BioNTech COVID-19 Vaccine: A Case Report and Review of Minimal Change Disease Related to COVID-19 Vaccine
Bibliographic record
Abstract
RATIONALE: While severe complications are generally uncommon with novel coronavirus disease 2019 (COVID-19) vaccine, there has been a steady increase in the number of patients presenting with nephrotic syndrome and acute kidney injury after the administration of COVID-19 vaccine. Physicians should be made aware of minimal change disease as a potential complication associated with COVID-19 vaccine. PRESENTING CONCERNS: A 60-year-old male without significant past medical history presented with new onset of nephrotic syndrome approximately 10 days after his first dose of Pfizer-BioNTech COVID-19 vaccine. Laboratory findings showed hypoalbuminemia (20 g/L), elevated urine albumin/creatinine ratio (668 mg/mmol), and elevated creatinine of 116 µmol/L from a baseline of 79 µmol/L. DIAGNOSIS: A diagnostic kidney biopsy was performed 6 weeks after the onset of the edema and approximately 8 weeks after his first dose of Pfizer-BioNTech COVID-19 vaccine. The kidney biopsy findings were consistent with minimal change disease with focal acute tubular injury. INTERVENTIONS: The patient was treated conservatively with ramipril 10 mg and furosemide 80 mg daily 5 weeks after the onset of swelling. Prednisone 1 mg/kg was initiated immediately when the kidney biopsy result became available (approximately 6 weeks after the onset of edema). OUTCOMES: The patient remitted with rapid weight loss starting 2 weeks post prednisone initiation. NOVEL FINDINGS: De novo minimal change disease with acute tubular injury is a kidney manifestation following the administration of Pfizer-BioNTech COVID-19 vaccine. Minimal change disease is potentially a rare complication of Pfizer-BioNTech COVID-19 vaccine.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| 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".