Heparin‐free renal replacement therapy for chronic hemodialyzed patients at high risk for bleeding: a comparison of on‐line predilution hemodiafiltration with conventional hemodialysis
Bibliographic record
Abstract
BACKGROUND: In chronic hemodialysis patients with high risk of bleeding, optimal anticoagulation of the extracorporeal circuit is challenging. Heparin-free hemodialysis (HD) with heparin-coated AN69ST dialyzer is now considered as a good option and recommended by experts. Predilutional hemodiafiltration (HDF) may represent also a feasible alternative but has been poorly investigated. In this study, our aim was to evaluate the performance of on-line automated predilution heparin-free HDF as compared to conventional heparin-free HD with a heparin-coated membrane. METHODS: We prospectively studied chronic hemodialysis patients at high risk of bleeding consecutively admitted to hospital who underwent heparin-free renal replacement therapy (RRT) in our nephrology department. During 1 year, we routinely used heparin-free HD and on-line HDF in these settings. By using a propensity score, we compared HDF to HD regarding to session failure and efficiency. RESULTS: One hundred and seventy-nine patients were included in the study. Clotting phenomena necessitating premature termination of RRT sessions were encountered in 19% of them. After propensity score matching, the comparison of 77 HD and 77 HDF sessions showed no significant differences in duration of the sessions and in dialyzer clotting. By multivariate analysis, a blood flow less than 250 mL/min and recent surgery were the only parameters associated with extracorporeal circuit thrombosis. CONCLUSION: Heparin-free on-line predilutional HDF is a safe and effective technique for chronic hemodialysis patients with increased bleeding risk. The use of an automatic substitution volume that avoids filters hemoconcentration and of a blood flow above 250 mL/min strongly contribute to the observed performance. Further studies are, however, intended to confirm these results.
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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) | 0.001 | 0.001 |
| 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".