Vaccine-Induced Immune Thrombotic Thrombocytopenia after Receiving the ChAdOx1 nCoV-19 Vaccine
Bibliographic record
Abstract
Vaccine-induced prothrombotic immune thrombocytopenia (VIPIT) is a rare complication noted after immunization against coronavirus disease with the ChAdOx1 nCoV-19 (AstraZeneca) vaccine. Here we report such a case in a 61-year-old gentleman who presented twenty days after receiving the vaccine and was diagnosed with massive bilateral pulmonary emboli with a saddle embolus. This is the third such case in Canada. This case serves to highlight that venous thromboembolism in an older, male patient presenting in a typical manner can still be VIPIT, despite reports of this occurring predominantly in young females with intracranial and splanchnic thromboses. It is important to make the diagnosis accurately and in a timely fashion because the management strategy differs from that of classic venous thromboembolism. Heparin anticoagulants should be avoided, and intravenous immunoglobulin is critical to consider as part of the treatment. RésuméLa thrombocytopénie thrombotique immunitaire induite par le vaccin (TTIV) est une complication rare, signalée après l’immunisation contre la maladie à coronavirus par le vaccin ChAdOx1 nCoV-19 (AstraZeneca). Cet article expose le cas d’un homme de 61 ans qui s’est présenté à l’hôpital 20 jours après avoir reçu le vaccin et a reçu un diagnostic d’embolie pulmonaire bilatérale massive avec une embolie en selle. Il s’agit du troisième cas du genre au Canada. Ce cas vient démontrer qu’un homme plus âgé qui présente les symptômes typiques d’une thromboembolie veineuse peut être atteint d’une TTIV, même si l’on rapporte qu’elle survient essentiellement chez les jeunes femmes atteintes de thromboses intracrâniennes et splanchniques. Il est important de poser le diagnostic rapidement et avec précision, car la stratégie de prise en charge de la TTIV diffère de celle de la thromboembolie veineuse classique. Les anticoagulants à base d’héparine doivent être évités, et il est essentiel de considérer l’administration d’immunoglobulines par voie intraveineuse dans le cadre du traitement.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| 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 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".