ArticleKidney research and clinical practice2024
Validation of prediction model for successful discontinuation of continuous renal replacement therapy: a multicenter cohort study.
Article in Kidney research and clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Prediction model for successful liberation from continuous renal replacement therapy in patients with acute kidney injury: development and temporal validation.Frontiers in medicine · 2026Article
- Development and validation of an interpretable predictive machine learning model for successful weaning of continuous renal replacement therapy.Scientific reports · 2025Observational
- Liberation from continuous renal replacement therapy due to renal recovery in adults and children: a literature review and Delphi consensus on clinical practice.Critical care (London, England) · 2025Review
- The 5th Asia Pacific AKI CRRT 2023: Best Movement to Critical Care, Save Lives.Kidney research and clinical practice · 2024Article
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Authors and funding
14 authors.
Funding
Abstract
backgroundContinuous renal replacement therapy (CRRT) has become the standard modality of renal replacement therapy (RRT) in critically ill patients. However, consensus is lacking regarding the criteria for discontinuing CRRT. Here we validated the usefulness of the prediction model for successful discontinuation of CRRT in a multicenter retrospective cohort.
methodsOne temporal cohort and four external cohorts included 1,517 patients with acute kidney injury who underwent CRRT for >2 days from 2018 to 2020. The model was composed of four variables: urine output, blood urea nitrogen, serum potassium, and mean arterial pressure. Successful discontinuation of CRRT was defined as the absence of an RRT requirement for 7 days thereafter.
resultsThe area under the receiver operating characteristic curve (AUROC) was 0.74 (95% confidence interval, 0.71-0.76). The probabilities of successful discontinuation were approximately 17%, 35%, and 70% in the low-score, intermediate-score, and highscore groups, respectively. The model performance was good in four cohorts (AUROC, 0.73-0.75) but poor in one cohort (AUROC, 0.56). In one cohort with poor performance, attending physicians primarily controlled CRRT prescription and discontinuation, while in the other four cohorts, nephrologists determined all important steps in CRRT operation, including screening for CRRT discontinuation.
conclusionThe overall performance of our prediction model using four simple variables for successful discontinuation of CRRT was good, except for one cohort where nephrologists did not actively engage in CRRT operation. These results suggest the need for active engagement of nephrologists and protocolized management for CRRT discontinuation.
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