Role of platelet factor 4–heparin complex antibody (HIT antibody) in the pathogenesis of thrombotic episodes in patients on hemodialysis
Bibliographic record
Abstract
Heparin-induced thrombocytopenia (HIT) is a severe complication in patients on hemodialysis (HD). It has been reported that platelet factor-4 (PF-4)-heparin complex antibody (HIT antibody) plays an important role in the pathogenesis of this serious complication. In the present study, we investigated the role of HIT antibody in the pathogenesis of thrombotic complications including shunt failure, cerebrovascular disease (CVD) and atherosclerosis in patients on dialysis. Plasma concentration of HIT antibody in patients on HD was 0.143+/-0.008 (n=105). This was significantly higher in patients on continuous ambulatory peritoneal dialysis (CAPD: 0.087+/-0.006, p=0.0008, n=22) and in non-dialysis patients (0.113+/-0.011, p=0.0011, n=12). There was a significant negative correlation between HIT antibody and the duration of dialysis. However, no significant correlation was found between HIT antibody and other factors including age, dose of heparin, platelet count and hemoglobin. There was a significant correlation between the number of failed arteriovenous fistula and HIT antibody levels. In addition, in patients with a history of CVD, plasma concentrations of HIT antibody were significantly higher compared with patients without CVD (CVD(+): 0.200+/-0.029 vs. (-): 0.127+/-0.005, p<0.0001). It is possible that genetic factors may also play a role in the expression of HIT antibody. From these data, it appears possible that HIT antibody plays an important role in the pathogenesis of thrombosis in patients on HD. Further studies are needed to clarify the role of HIT antibody in the pathogenesis of thrombotic episodes in these patients.
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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 | 0.000 |
| 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".