Human platelet antigens polymorphisms and susceptibility of thrombosis in hemodialysis patients
Bibliographic record
Abstract
To investigate the association between the polymorphisms of human platelet antigen (HPA)-1,2,3,4,5 and susceptibility to develop thrombosis accident in arteriovenous fistula (AVF), genomic DNA of 112 hemodialysis (HD) patients and 100 healthy blood donors were genotyped by PCR-SSP. The patients were classified into 2 groups: G1 included 54 HD patients presented at least one thrombotic episode on the level of the AVF, and G2 included 58 HD patients without any episode of thrombosis. The allelic frequencies of HPA-1, 2, 3, and 5 among patients and controls did not reveal significant differences. However, the HPA-4b allele was significantly more frequent in G1 than in controls or in G2 patients (23.1% vs. 11.5% and 0.9%, respectively), p<0.01 and p<0.001. The genotype distribution of HPA-4 polymorphism reveals that the HPA-4a4b genotype was more frequent in G1 patients (23/54: 42.6%) than in all HD patients (25/112: 22.3%) or in G2 patients (1/58: 1.72%) (p<0.001, odds ratio: 45.6). Among 24 HD patients with HPA-4a4b genotype, 23 (96%) developed at least 1 or more thrombotic episode on the level of their AVF. However, 30 patients (34.5%) among 87 HD patients with HPA-4a4a genotype presented thrombotic episode (p<0.001). These results reveal a significant association between HPA-4a4b and thrombosis, and it is likely that HPA polymorphisms could be useful markers for potential risk of thrombosis in hemodialysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".