Association of anti-heparin platelet factor 4 antibody levels and thrombosis in pediatric intensive care patients without thrombocytopenia
Bibliographic record
Abstract
Anti-heparin platelet factor 4 (anti-HPF4) antibodies have been demonstrated to play a pathogenetic role in the development of heparin-induced thrombocytopenia. In adults, the presence of anti-HPF4 antibodies without thrombocytopenia has been reported not to confer a thrombotic risk. To investigate whether this also holds true for children, we performed a case-control study in heparin-exposed patients from a pediatric intensive care unit. During the 30-month study period, 612 patients received heparin for at least 5 days. Of these, 10 patients developed thrombosis without thrombocytopenia and constituted the study group. These patients were compared with 19 matched control patients with neither thrombosis nor thrombocytopenia. Anti-HPF4 antibody levels were measured using an enzyme-linked immunosorbent assay (Asserachrom HPF4). All thrombosis patients and controls had lower anti-HPF4 antibody levels than the cut-off level recommended by the manufacturer for adults. However, median anti-HPF4 antibody levels were significantly higher in the thrombosis patients [51% of the manufacturer's cut-off; interquartile range (IQR), 47-53%] than in the control group (23%; IQR, 9-36%) (P = 0.004). At an anti-HPF4 cut-off level of 45%, the odds ratio for a thrombotic event amounted to 34 (95% confidence interval, 4.4-261.8), indicating an association between anti-HPF4 antibody levels and thrombosis despite the absence of thrombocytopenia. A role of anti-HPF4 antibodies in the development of catheter-related thrombosis is suggested.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".