Acquired Hemophilia A Developed Post COVID-19 Vaccine: An Extremely Rare Complication
Bibliographic record
Abstract
Acquired hemophilia A (AHA) is a rare autoimmune bleeding disorder caused by circulating autoantibodies (inhibitor) directed against coagulation factor VIII (FVIII). We report a 39-year-old single female who presented to emergency department with sudden onset gross hematuria 10 days following her first dose of Pfizer-BioNTech severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA (coronavirus disease 2019 (COVID-19)) vaccine. Coagulation profile revealed isolated prolongation of the activated partial thromboplastin time due to FVIII deficiency with normal von Willebrand factor and activity. Mixing study revealed time-dependent inhibitor pattern that was successively identified as directed against FVIII using the Nijmegen-modified Bethesda assay. FVIII inhibitor in a titer of 17.2 Bethesda Units/mL was detected. While thrombosis is a frequent complication of severe COVID-19 infection, on the other hand, bleeding is rare in the setting of COVID-19 infection/vaccination with no anticoagulants. Till date, a couple of cases of acquired hemophilia developed after receiving mRNA derived COVID-19 vaccines (Pfizer-BioNTech SARS-CoV-2 mRNA vaccine and Moderna mRNA vaccines) had been reported. It is important to raise the awareness about this rare side effect that might be directly induced by the mRNA COVID-19 vaccine or that the vaccine could have triggered it in a genetically predisposed individual. We recommend considering screening for an inhibitor (by mixing study) in cases with otherwise unexplained onset hemorrhagic disorder and/or isolated activated partial thromboplastin time prolongation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".