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Record W4405051177 · doi:10.1182/blood-2024-211507

Longitudinal Laboratory and Clinical Outcomes in Vaccine-Induced Immune Thrombotic Thrombocytopenia after 3 Years

2024· article· en· W4405051177 on OpenAlexaffabout
Michael Hack, Rumi Clare, Hina Bhakta, Donald M. Arnold, Ishac Nazy

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineImmunologyImmune thrombocytopeniaImmune systemInternal medicinePlatelet

Abstract

fetched live from OpenAlex

Introduction: Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare yet severe complication that occurs 5 - 30 days after adenoviral vector-based vaccines against SARS-CoV-2. Patients with VITT present with thrombocytopenia and venous or arterial thrombosis, in unusual locations such as cerebral venous sinus thrombosis (CVST). The pathophysiology of VITT involves the generation of antibodies against platelet factor 4 (PF4, CXCL4), forming immune complexes that activate platelets, thereby leading to thrombosis. VITT is similar to the immune-mediated drug reaction known as heparin-induced thrombocytopenia (HIT), which presents as thrombocytopenia with an increased risk of thrombosis in patients with recent heparin administration. It has been shown that anti-PF4/heparin antibodies in HIT patients typically persist for 50 to 85 days. Initial reports have shown that some patients with VITT have persistent anti-PF4 antibodies without ongoing or new clinical symptoms; however, a description of VITT antibodies and clinical symptoms after prolonged follow-up is currently lacking. In this study, we report VITT anti-PF4 antibody levels, their ability to activate platelets, and clinical outcomes from VITT patients in Canada after nearly 3 years. Methods: VITT patient follow-up samples were studied (n = 30) after a median of 23.8 months (4.2 - 35.5 months) post-vaccination with an adenoviral vector-based vaccine against SARS-CoV-2. VITT follow-up samples were tested for the presence of anti-PF4 IgG/A/M antibodies using a commercially available enzyme immunoassay [EIA; positive optical density (OD) 405nm ≥ 0.4] and tested for their functional ability to activate platelets using the PF4-serotonin release assay (SRA; positive ≥ 20% 14C-serotonin release) with increasing concentrations of exogenous human PF4. Self-reported clinical outcomes from VITT patients were also collected. Results: In our cohort of VITT patients, anti-PF4 IgG/A/M antibodies were detected in 22 out of 30 (73.3%) individuals at their most recent follow-up. Of the 22 VITT patients who tested positive for anti-PF4 antibodies, 14 (63.6%) had platelet-activating anti-PF4 antibodies. Clinical follow-up data were available for 8 out of the 14 (57.1%) patients with persistent platelet-activating antibodies. Among these patients, 7 out of 8 (87.5%) continued to receive anticoagulant therapy (Apixaban or Rivaroxaban; n = 5) or anti-platelet therapy (Aspirin; n = 2). There were no reported cases of recurrent thrombosis. Conclusion: The persistence of anti-PF4 antibodies in VITT contrasts with the transient nature of HIT antibodies, which typically become undetectable after 2 to 3 months following heparin administration. None of the VITT patients experienced thrombotic events despite having persistent pathogenic anti-PF4 antibodies, possibly due to continued treatment. Therefore, ongoing surveillance of VITT patients is imperative to fully understand persistent serological and clinical outcomes such as the risk of recurrent thrombosis over time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.032
GPT teacher head0.337
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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