Clinical outcomes associated with serological subsets of heparin-induced thrombocytopenia
Bibliographic record
Abstract
Abstract Background: Heparin Induced Thrombocytopenia (HIT) is an immune-mediated drug reaction classically characterized by platelet activating anti-platelet factor 4(PF4)/heparin antibodies, leading to reduced platelet count and increased risk of thrombosis. The gold standard diagnostic test is the serotonin release assay (SRA), which is performed by mixing patient serum with pedigree donor platelets labelled with 14C-serotonin with or without heparin. A typical positive SRA result shows heparin-dependent platelet activation. A subset of patients with HIT also demonstrate platelet activation that is independent of heparin (known as an atypical, or autoimmune SRA pattern). Whether serological subsets of HIT are associated with different clinical outcomes is not known. Objective: To assess the clinical outcomes associated with different serological subsets of HIT patients based on the presence or absence of heparin-independent platelet activation in the SRA. Methods: Retrospective cohort study at McMaster University, which is a tertiary care referral center and the reference HIT testing center for Canada. All patients with a positive anti-PF4/heparin enzyme immunoassay and a positive SRA (14C-serotonin release ≥ 20% with therapeutic dose heparin) managed at our centre between January 2006 and May 2025 were included. The subset of patients with heparin-independent platelet activation was defined by 14C-serotonin release ≥ 20% in the absence of heparin. The first available SRA result and corresponding clinical encounter were analyzed for each patient. Baseline demographics, previous thrombosis, admission diagnosis, heparin exposure and baseline laboratory values were extracted from medical records. The primary outcome was a composite of any objectively confirmed and documented arterial or venous thrombosis within 90 days of the positive SRA result. Other outcomes included platelet count, fibrinogen level, and mortality. Data extraction was completed blinded to the results of the SRA. For each clinical outcome, univariate analyses were conducted to compare patients with with and without heparin-independent platelet activation. Logistic regression was used to examine the association between serological subsets and the occurrence of any thrombosis adjusting for patient sex and age, nadir platelet count, nadir fibrinogen, and surgery during admission. Results: Of 194 patients with HIT, 100 (52%) demonstrated heparin-independent platelet activation. Patients with the heparin-independent serology were similar to patients with the heparin-dependent serology with respect to age (69.0±14.0 and 69.3±11.6), sex (53% and 52.1% female), surgical admission (70% and 68.1%), previous thrombosis (55% and 56.4%) and baseline platelet count (248±89 and 259±89 x10^9/L). Patients with heparin-independent serology had higher 4T scores (6.13±1.18 vs 5.33±1.55, p<0.001) and higher optical density of the anti-PF4/heparin enzyme immunoassay (2.53±0.76 vs 2.25±0.68, p=0.005). The heparin-independent serology was associated with worse clinical outcomes including a lower nadir platelet count (54±29 vs 70±47 x10^9/L, p=0.003), thrombosis (60% vs 46.8%, p=0.033), myocardial infarction (6% vs 0%, p=0.008) and cerebral sinus venous thrombosis (3% vs 0%, p=0.042). There was no difference between groups in nadir fibrinogen level, timing of thrombosis following HIT diagnosis, or mortality. After adjusting for patient demographics and clinical characteristics, the heparin-independent serology was associated with a higher risk of thrombosis (OR=2.04,95%CI 1.05-3.98, p=0.036). Conclusion: The subset of HIT patients with heparin-independent platelet activation had a higher risk of thrombosis and lower platelet count nadir compared with HIT patients who had a heparin-dependent serology. Reporting subsets of SRA results may improve HIT outcomes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".