Antibodies to the Platelet Factor 4-Heparin Complex and Mortality in Chronic Hemodialysis Patients.
Bibliographic record
Abstract
Abstract Background: Heparin-induced thrombocytopenia is a serious complication of heparin therapy that can lead to thromboembolism, cardiovascular events or death. Patients with this disorder develop antibodies to the platelet factor 4-heparin (PF4-H) complex. Hemodialysis patients are repeatedly exposed to heparin and are at risk for developing PF4-H antibodies. The clinical impact of asymptomatic PF4-H antibodies in patients on chronic hemodialysis is not known. Objective: To determine the association between asymptomatic PF4-H antibodies and mortality in a cohort of chronic hemodialysis patients repeatedly exposed to heparin. Methods: Pre-dialysis blood samples were drawn from 419 asymptomatic patients. All patients received unfractionated heparin (Baxter) while on dialysis. All samples were screened for PF4-H antibodies using an ELISA assay (GTI PF4 Enhanced, GTI Diagnostics). All positive and indeterminate samples were then tested using an IgG-specific PF4-H ELISA assay and a platelet serotonin-release assay. Participants were then followed up prospectively for thromboembolic events, cardiovascular events, or death. Results: During a median follow-up of 2.5 years there were 129 deaths. After controlling for important potential confounding variables, the relative risk of death was 2.92 (95% CI: 1.18-7.25; P= 0.02) in patients with IgG-specific PF4-H antibodies and 4.08 (95% CI: 1.26–13.2; P= 0.02) in patients with IgG-specific antibodies and an indeterminate serotonin-release assay. Conclusions: PF4-H antibody formation is associated with increased all-cause mortality in patients on chronic hemodialysis. Further investigation is needed to determine if anticoagulation with alternative agents would improve survival in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".