Haemodialysis in patients treated with oral anticoagulant: should we heparinize?
Bibliographic record
Abstract
BACKGROUND: Anticoagulation for the haemodialysis circuit in patients treated with oral anticoagulation poses additional haemorrhagic risk. The few available data suggest that tapering or even stopping heparinization is feasible and the HeprAN membrane with grafted heparin was developed to decrease heparin dose. The objective of our study was to evaluate the need for additional anticoagulation in patients on long-term oral anticoagulation, according to the type of membrane used. METHODS: This is a prospective, randomized, crossover bifactorial trial in haemodialysed patients on oral anticoagulation. Each patient had four haemodialysis sessions with two different membranes [HeprAN or polysulphone (PS)] and with or without enoxaparin. Clinical coagulation was evaluated by the need for premature ending and by a visual score (Janssen scale). Coagulation activation markers were also measured: d-dimers, prothrombin fragments 1 + 2, thrombin-antithrombin complexes, tissue factor pathway inhibitor and platelet factor-4. RESULTS: Ten patients were included (M/F = 4/6, mean age 63 ± 15 years). None of the 40 sessions ended prematurely. The clotting scores were similar with or without enoxaparin (dialyser: 1.49 ± 0.19 versus 1.53 ± 0.17, P = 0.97; bubble trap: 0.75 ± 0.19 versus 0.78 ± 0.22, P = 0.62) and with the polysulphone or the HeprAN membrane (dialyser: 1.54 ± 0.20 versus 1.47 ± 0.16, P = 0.65; bubble trap: 0.74 ± 0.22 versus 0.79 ± 0.19, P = 0.58). There was no significant difference in coagulation activation markers between dialysis modalities; however, dialysis efficacy was significantly greater with the PS membrane (1.58 ± 0.07 versus 1.43 ± 0.06, P = 0.02). CONCLUSIONS: These results suggest that haemodialysis without additional anticoagulation is possible in patients with oral anticoagulation. The HeprAN membrane did not provide any additional benefit compared with a PS membrane.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".