ArticleClinics (Sao Paulo, Brazil)2023
A clinical model to predict successful renal replacement therapy (RRT) discontinuation in patients with Acute Kidney Injury (AKI).
Article in Clinics (Sao Paulo, Brazil), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 4 citations in OpenAlex.
- Prediction model for successful liberation from continuous renal replacement therapy in patients with acute kidney injury: development and temporal validation.Frontiers in medicine · 2026Article
- 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
- Continuous Renal Replacement Therapy in Critically-Ill Term and Preterm Newborns: A Single-Center Study in Belgrade.Children (Basel, Switzerland) · 2025Article
- Article
- Risk prediction models for successful discontinuation in acute kidney injury undergoing continuous renal replacement therapy.iScience · 2024Article
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Authors and funding
9 authors at 1 institution in 1 country.
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Abstract
introductionIdeal timing of Renal Replacement Therapy (RRT) discontinuation in Acute Kidney Injury (AKI) is still unknown. We aimed to study the role of creatinine-related variables in predicting RRT successful discontinuation and to propose a clinical predictive score.
methodsIn this single-centre retrospective study, we evaluated all AKI patients in whom RRT was interrupted for at least 48 hours. Patients who were still RRT-independent 7 days after initial RRT cessation were included in the "Success" group and opposed to the "Failure" group. We evaluated baseline characteristics and variables collected at the time of RRT interruption, as well as the Kinetic estimated Glomerular Filtration Rate (KeGFR), the simple variation in serum Creatinine (ΔsCr), and the incremental creatinine ratio on the first three days after RRT interruption. Multivariable analysis was performed to evaluate prediction of success. Internal validation using a simple binomial generalized regression model with Lasso estimation and 5-fold cross validation method was performed.
resultsWe included 124 patients, 49 in the "Failure" group and 75 in the "Success" group. All creatinine-related variables predicted success in simple and multiple logistic regression models. The best model generated a clinical score based on the odds ratio obtained for each variable and included urine output, non-renal SOFA score, fluid balance, serum urea, serum potassium, blood pH, and the variation in sCr values after RRT discontinuation. The score presented an area under the ROC of 0.86 (95% CI 0.76‒1.00).
conclusionCreatinine variation between the first 2 consecutive days after RRT discontinuation might predict success in RRT discontinuation. The developed clinical score based on these variables might be a useful clinical decision tool to guide hemodialysis catheter safe removal.
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