Clinical and Serological Characteristics of Vaccine-Associated Immune Thrombocytopenia Following COVID-19 Vaccination
Bibliographic record
Abstract
Introduction: Vaccine-associated immune thrombocytopenia (VA-ITP) is a serious hematological complication that re-emerged during COVID-19 vaccination campaigns and continues to complicate vaccine safety. The mechanisms of VA-ITP are unknown, and the associated laboratory and patient outcomes have not been well characterized. In this study, we determined the association of VA-ITP with anti-platelet autoantibodies. Methods: We conducted a retrospective cohort study of adult patients with VA-ITP following COVID-19 vaccination identified from the McMaster ITP Registry between December 2020 and January 2024. VA-ITP was defined as new-onset thrombocytopenia (platelet count <100 x109/L) within 3 months of exposure to vaccination. We excluded patients with vaccine-induced immune thrombotic thrombocytopenia (VITT) and positive anti-PF4 antibodies. Platelet counts, vaccine type, and treatments were collected. Platelet antibody testing was performed using a direct monoclonal antibody immobilization of platelet antigens (MAIPA) assay to detect antibodies against platelet glycoprotein (GP) IIbIIIa and GPIbIX. Anti-PF4 antibodies were also measured in the enzyme-immunoassay (EIA) and in the PF4-enhanced serotonin release assay (PF4-SRA). The data were summarized using descriptive statistics. Results: We identified 6 VA-ITP patients after COVID-19 vaccination from the McMaster ITP Registry. Mean age was 52 years (range 28-70), 2 (33.3%) were female. Culprit vaccines were the ChAdOx1 nCoV-19 adenoviral vector (n=3, 50%; first vaccine only), and the BNT16B2b2 mRNA vaccine [n= 3, 50%; after first (n=1), third (n=1) or fourth vaccine (n=1)]. Median platelet count pre-vaccination was 248 x109/L (IQR 197 - 249 x109/L), and median presenting platelet count was 12 x109/L (IQR 9 - 82 x109/L) at 19.5 days (median; IQR 14 - 23 days) post vaccination. Median lowest platelet count was 7 x109/L (IQR 3 - 11 x109/L), occurring 65 days (median; IQR 57 - 384 days) post vaccination. No patients had thrombosis. Three (50%) of 6 patients had detectable platelet antibodies up to 156 days post-vaccination (range 70 - 247 days). Two patients had anti-GPIbIX only and 1 patient had both anti-GPIbIX and anti-GPIIbIIIa. Two patients had received the adenoviral vector vaccine, and one patient received the mRNA vaccine. Treatments for VA-ITP included corticosteroids (n=6), IVIg (n=5), thrombopoietin receptor agonists (n=3), rituximab (n=2), and splenectomy (n=1). Median number of treatments was 3 (IQR 3 - 4). One patient (16.7%) achieved a durable platelet count response, and 5 patients (83.3%) achieved an initial platelet count response and subsequently relapsed, requiring ongoing treatment at the end of follow up (median, 29.5 months; IQR 21.5 - 31). Among the 3 patients with anti-GPIbIX or anti-GPIIbIIIa antibodies, median number of treatments was 4 (range 3 - 5), median lowest platelet count was 6 x109/L (range 3 - 8 x109/L), and all had relapsed requiring ongoing treatment at the end of follow up. Among the 3 antibody-negative patients, the median number of treatments was 3 (range 2 - 3), median lowest platelet count was 11 x109/L (range 1 - 71 x109/L), and 2 (66.7%) required ongoing treatment at the end of follow up. All 6 patients received a median of 2.5 booster vaccines (IQR 1 - 4) during follow up; 2 patients (33.3%) experienced a decrease in platelet counts ≥20%, but none developed severe ITP. Conclusion: We found that 3 (50%) of 6 patients with VA-ITP after adenoviral vector and mRNA COVID-19 vaccines had detectable anti-platelet antibodies, including 2 patients with anti-GPIbIX and one patient with both anti-GPIbIX and anti-GPIIbIIIa. Antibody-positive VA-ITP tended to be more severe and require more treatment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".