Hereditary thrombotic thrombocytopenic purpura and COVID‐19: Impacts of vaccination and infection inrare disease
Bibliographic record
Abstract
Introduction: Severe COVID-19 is associated with an important increase of von Willebrand factor and mild lowering of ADAMTS13 activity that may, in the presence of a strong inflammatory reaction, increase the risk of acute thrombotic thrombocytopenic purpura (TTP). Although acute episodes of immune-mediated TTP associated with COVID-19 or SARS-CoV-2 vaccination have been reported, data about clinical evolution of hereditary TTP (hTTP) during the pandemic are scarce. Method: We conducted a survey among adult patients of the International Hereditary TTP Registry about SARS-CoV-2 vaccination, COVID-19, and occurrence of acute hTTP episodes. Results: Of 122 adult hTTP patients invited to participate, 86 (70.5%) responded. Sixty-five had been vaccinated (75.6%), of which 14 had received in addition a booster, resulting in 139 individual vaccine shots. Although vaccinations in patients on plasma prophylaxis were done within 1 week of the last plasma infusion, all 23 patients treated with plasma on demand were vaccinated without prior plasma infusions. One patient on uninterrupted weekly plasma infusions presented within 3 days from his second vaccination with neurological symptoms and computed tomography scan 9 days later showed subacute ischemic/hemorrhagic frontal lobe infarction. A second male patient developed acute myocarditis after his second dose of mRNA-1273 vaccine. Twelve (14%) patients had COVID-19, associated with an acute hTTP episode in three of them: one patient had a transient ischemic attack, one a stroke, and a pregnant woman was hospitalized to intensify plasma treatment. Discussion: The risk of an acute episode triggered by COVID-19 seems higher than following vaccination in hTTP patients, who can be safely vaccinated against SARS-CoV-2.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".