Frequency of positive anti-PF4/polyanion antibody tests after COVID-19 vaccination with ChAdOx1 nCoV-19 and BNT162b2
Bibliographic record
Abstract
Vaccination using the adenoviral vector COVID-19 vaccine ChAdOx1 nCoV-19 (AstraZeneca) has been associated with rare vaccine-induced immune thrombotic thrombocytopenia (VITT). Affected patients test strongly positive in platelet factor 4 (PF4)/polyanion enzyme immunoassays (EIAs), and serum-induced platelet activation is maximal in the presence of PF4. We determined the frequency of anti-PF4/polyanion antibodies in healthy vaccinees and assessed whether PF4/polyanion EIA+ sera exhibit platelet-activating properties after vaccination with ChAdOx1 nCoV-19 (n = 138) or BNT162b2 (BioNTech/Pfizer; n = 143). In total, 19 of 281 participants tested positive for anti-PF4/polyanion antibodies postvaccination (All: 6.8% [95% confidence interval (CI), 4.4-10.3]; BNT162b2: 5.6% [95% CI, 2.9-10.7]; ChAdOx1 nCoV-19: 8.0% [95% CI, 4.5% to 13.7%]). Optical densities were mostly low (between 0.5 and 1.0 units; reference range, <0.50), and none of the PF4/polyanion EIA+ samples induced platelet activation in the presence of PF4. We conclude that positive PF4/polyanion EIAs can occur after severe acute respiratory syndrome coronavirus 2 vaccination with both messenger RNA- and adenoviral vector-based vaccines, but many of these antibodies likely have minor (if any) clinical relevance. Accordingly, low-titer positive PF4/polyanion EIA results should be interpreted with caution when screening asymptomatic individuals after vaccination against COVID-19. Pathogenic platelet-activating antibodies that cause VITT do not occur commonly following vaccination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".