Differences in coagulation in clotting of vascular access in hemodialysis patients
Bibliographic record
Abstract
Arteriovenous graft (AVG) thrombosis is a frequent cause of graft failure. We evaluated coagulation protein concentrations, platelet function, and viscoelasticity factors in 20 hemodialysis (HD) patients with AVGs. The goal was to determine whether significant differences in protein concentrations, platelet function, and viscoelasticity factors exist among dialysis patients requiring frequent AVG declot procedures vs. those who do not. Twenty HD patients were enrolled: 10 frequent clotters (>3 declots in the previous year) and 10 were nonclotters. Patients on antiplatelets or chronic anticoagulation were excluded. Laboratories were drawn pretreatment and heparinase was added to counteract any potential heparin effect. Coagulation protein concentrations including tissue factor (TF), thrombin/antithrombin III complex (TAT), and prothrombin fragment 1 + 2 (F(1+2)) were assayed. The time to clot onset was measured by force onset time (FOT). Platelet contractile force (PCF) measured the force produced by platelets during clot retraction, whereas clot rigidity was measured as clot elastic modulus (CEM). FOT, CEM, and PCF were measured by Hemodyne. Both groups had upregulation of the TF pathway, as TF, TAT, and F(1+2) levels were similarly increased over baseline levels. Hemodialysis patients with frequent AVG clotting had higher levels of both PCF and CEM compared with nonclotters. Additionally, the frequent clotters had a lower FOT relative to nonclotters, although both were considered in the normal range. Our study suggests that HD patients with recurrent AVG thrombotic events form clots with higher tensile strength compared with HD patients without recurrent graft thrombosis.
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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 | 0.000 | 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".