Regional Citrate vs. Systemic Unfractionated Heparin Anticoagulation for Continuous Renal Replacement Therapy in Paediatric Patients: Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
The efficacy and safety of unfractionated heparin (UFH) and regional citrate anticoagulation (RCA) in continuous renal replacement therapy (CRRT) are subjects of controversy across paediatric patients. We conducted a search of the PubMed, Embase and Cochrane Library databases from inception to 2024. The Newcastle-Ottawa Scale was used to assess the quality of the included studies. Sensitivity analysis confirmed the stability of results; publication bias was investigated by Egger test. We conducted a search of the PubMed, Embase and Cochrane Library databases from inception to 2024, and 12 studies were included. Compared with UFH, RCA significantly prolonged circuit survival time (WMD 12.09, 95% CI: [4.48, 19.71], p = 0.002), reduced the risk of filter clotting (RR = 0.60, 95% CI: [0.42-0.85], p = 0.004) and bleeding (RR = 0.42, 95% CI: [0.23-0.79], p = 0.007). Although citrate anticoagulation was more likely to cause metabolic alkalosis (RR = 3.22, 95% CI: [1.34-7.75], p = 0.009) and hypocalcemia (RR = 2.92, 95% CI: [1.93-4.41], p < 0.001), metabolic complications were manageable and mild. Further subgroup analysis of paediatrics showed that, compared with children with an average weight > 10 kg, citrate anticoagulation significantly extended the circuit survival time of children with an average weight ≤ 10 kg (p < 0.001). Sensitivity analysis confirmed that the results were generally robust. RCA could be the first choice for anticoagulation in paediatrics, especially for infants weighing ≤ 10 kg.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".