Regional Citrate Anticoagulation with Duocart-biofiltration (DCB) versus Conventional Bicarbonate Hemodialysis (BHD) with Low Molecular Weight Heparin (LMWH)
Bibliographic record
Abstract
Background: LMWH ensures circuit permeability in hemodialysis but can lead to systemic bleeding for patients with hemorrhagic risk. Other anticoagulation alternatives are laborious and cumbersome with BHD. Regional citrate anticoagulation can be simplified with DCB, a new hemodialysis method using a dialysate containing only sodium chloride and bicarbonate. The optimal amount of ionic complement (Ca++, Mg++, K+) is automatically perfused into venous line according to the value of ionic dialysance measured every 15 minutes by the Integra dialysis monitor (Hospal, Italy). Methods: Thirty DCB-citrate sessions were performed in 10 patients at increased risk of bleeding. After resolution of bleeding risk, the same number of BHD sessions was performed in patients. The aim of this study is to compare pressure time of the arterio-venous access (PT), index thrombosis circuit (ITC 0:clean to 5:total thrombosis), Kt/V and biochemical data at the end of sessions (mean ± SD). DCB-citrate (n = 21) BHD-LMWH (n = 21) p PT (min) 4 ± 1.1 9 ± 4.6 < 0,01 ITC 1.75 ± 0.34 2.4 ± 0.6 < 0,01 Kt/V 1.21 ± 0.25 1.21 ± 0.27 NS Ca++(mmol/l) 2.8 ± 0.25 2.8 ± 0.2 NS HCO3-(mmol/l) 26 ± 2.7 29 ± 3 0,01 No bleeding, and no metabolic or citrate adverse-event were observed during DCB-citrate sessions. No change in perfusion rate of ionic complement was required. Conclusion: Regional citrate anticoagulation during DCB is safe, effective and good alternative of HBPM for patients with hemorrhagic risks.
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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 | 0.001 |
| 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 | 0.000 |
| 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".