Citrate vs. acetate dialysate on intradialytic heparin dose: A double blind randomized crossover study
Bibliographic record
Abstract
Introduction Citrate containing dialysate has a calcium-binding anticoagulant effect compared to standard acetic acid containing dialysate. We performed a randomized, double-blind, crossover trial in maintenance HD patients to determine if citrate dialysate ("citrate") safely allows for a lower cumulative heparin dose ("heparin dose"). Methods Intradialytic heparin was adjusted to the minimum during a 2-week run-in phase. Patients remaining on heparin at the end of the run-in phase were then randomized to two weeks of HD with acetate dialysate ("acetate") followed by two weeks of citrate (sequence 1) or two weeks of citrate followed by two weeks of acetate (sequence 2). We estimated a minimum of 14 patients are required to show a 30% reduction in heparin dose per HD session with citrate compared with acetate. Twenty-five patients entered the run-in phase, 20 were randomized, and 19 completed the study. Findings The mean heparin dose was reduced by 19% (656 units, 95% CI -174 to -1139 units, P = 0.011) in the acetate group, and 30% (1046 units 95% CI -498 to 1594 units, P < 0.001) in the citrate group. There was no difference in the mean heparin dose reduction between the two dialysates (P > 0.05). The intradialytic ionized calcium in the citrate group was lowered by 0.10 mmol/L (95% CI 0.07 to 0.14 mmol/L, P < 0.001), and remained unchanged in the acetate group. Discussion Although citrate is a safe alternative to acetate, it does not result in additional heparin dose reduction.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".