Anticoagulation, delivered dose and outcomes in <scp>CRRT</scp>: The program to improve care in acute renal disease (<scp>PICARD</scp>)
Bibliographic record
Abstract
Delivered dialysis dose by continuous renal replacement therapies (CRRT) depends on circuit efficacy, which is influenced in part by the anticoagulation strategy. We evaluated the association of anticoagulation strategy used on solute clearance efficacy, circuit longevity, bleeding complications, and mortality. We analyzed data from 1740 sessions 24 h in length among 244 critically ill patients, with at least 48 h on CRRT. Regional citrate, heparin, or saline flushes was variably used to prevent or attenuate filter clotting. We calculated delivered dose using the standardized Kt/Vurea . We monitored filter efficacy by calculating effluent urea nitrogen/blood urea nitrogen ratios. Filter longevity was significantly higher with citrate (median 48, interquartile range [IQR] 20.3-75.0 hours) than with heparin (5.9, IQR 8.5-27.0 hours) or no anticoagulation (17.5, IQR 9.5-32 hours, P < 0.0001). Delivered dose was highest in treatments where citrate was employed. Bleeding complications were similar across the three groups (P = 0.25). Compared with no anticoagulation, odds of death was higher with the heparin use (odds ratio [OR] 1.82, 95% confidence interval [CI] 1.02-3.32; P = 0.033), but not with citrate (OR 1.02 95% CI 0.54-1.96; P = 0.53). Relative to heparin or no anticoagulation, the use of regional citrate for anticoagulation in CRRT was associated with significantly prolonged filter life and increased filter efficacy with respect to delivered dialysis dose. Rates of bleeding complications, transfusions, and mortality were similar across the three groups. While these and other data suggest that citrate anticoagulation may offer superior technical performance than heparin or no anticoagulation, adequately powered clinical trials comparing alternative anticoagulation strategies should be performed to evaluate overall safety and efficacy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".