Utility of citrate dialysate in management of acute kidney injury in children
Bibliographic record
Abstract
Dialysis concentrate acidified with citrate as opposed to acetate has been reported to prevent clotting in hemodialysis circuits, and improve dialysis efficiency in adults. There is no information on its use in children. The purpose of the study was to evaluate the utility of citrate dialysate for renal replacement therapy in a pediatric population with acute kidney injury. We performed a retrospective review of our experience using Citrasate(®) concentrate from December 2007 to August 2009. All treatments were provided using the Fresenius 2008 dialysis machine. Citrasate(®) was utilized in 7 children aged 60.3±51.0 months (mean±SD), range 13 months to 12 years. The number of treatments varied from 4 to 31 (mean 12±8 treatments) for a total of 89 treatments. Rare sporadic mild hypocalcemia was noted but could not be definitively linked with the use of Citrasate(®). Four children also required low-dose heparin (3.6-15 U/kg/h) due to clotting. Activated clotting times (when checked) were not affected by this low-dose heparin therapy. Some degree of clotting occurred in 21 of 89 (23.5%) treatments. Early termination of treatment due to thrombosis was required in 7 of 89 (7.8%) treatments. In summary, use of Citrasate(®) dialysis concentrate was well tolerated in critically ill children with acute kidney injury. Citrasate(®) reduced but did not completely eliminate the need for heparin in our population. Further study in a more diverse population would be helpful.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".