Serotonin‐release assay‐negative heparin‐induced thrombocytopenia
Bibliographic record
Abstract
Heparin-induced thrombocytopenia (HIT) is a prothrombotic drug reaction caused by platelet-activating anti-platelet factor 4 (PF4)/heparin antibodies. Pathogenic HIT antibodies can be detected by the serotonin-release assay (SRA), a platelet activation test. We have regarded the SRA performed in our medical community ("McMaster" SRA) as having high sensitivity and specificity. Recently, the concept of "SRA-negative HIT" has been proposed for enzyme-immunoassay (EIA)-positive/SRA-negative patients with a HIT-compatible clinical picture, who test positive in a PF4-enhanced platelet activation assay. After identifying an index case of SRA-negative HIT, we estimated the frequency of this condition by performing the "PF4-SRA" (modified SRA using high concentrations of added PF4 rather than heparin) in EIA-positive patients from a cohort study evaluating clinical and laboratory diagnosis of HIT. We defined SRA-negative HIT as patients meeting three criteria: clinical picture compatible with HIT (4Ts ≥ 4 points); EIA-positive (≥1.00 units); and PF4-SRA-positive. Among 430 patients, 35 were EIA-positive/SRA-positive and 27 were EIA-positive/SRA-negative. Among these 27 SRA-negative patients, three were found to have subthreshold levels of platelet-activating antibodies by PF4-SRA, of whom one met clinical criteria for SRA-negative HIT. Thus, based on identifying one patient with SRA-negative HIT within a cohort study that found 35 SRA-positive HIT patients, we estimate the sensitivity of the McMaster SRA for diagnosis of HIT to be 35/36 (97.2%; 95% CI, 85.8-99.9%). Although the McMaster SRA is highly sensitive for HIT, occasional SRA-negative but EIA-positive patients strongly suspected of having HIT can have this diagnosis supported by a PF4-enhanced activation assay such as the PF4-SRA.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".