Development of New Equations Predicting the Mortality Risk of Patients on Continuous RRT. Issue 9 (29th September 2022)

• Record Type: Journal Article
• Authors: Kang, Min Woo; Tangri, Navdeep; Kwon, Soie; Li, Lilin; Lee, Hyeseung; Han, Seung Seok; An, Jung Nam; Lee, Jeonghwan; Kim, Dong Ki; Lim, Chun Soo; Kim, Yon Su; Kim, Sejoong; Lee, Jung Pyo
• Is Part Of: Kidney360. Volume 3:Issue 9(2022)
• Page Start: 1494
• Page End: 1501
• Publication Date: 2022-09-29
• Subjects: acute kidney injury and ICU nephrology -- CRRT -- mortality -- prediction; 616.61
• DOI: 10.34067/KID.0000862022
• Languages: English
• ISSNs: 2641-7650

Abstract

Visual Abstract: Abstract : Key Points: Predicting the risk of mortality in patients with CRRT is important for appropriate management, but is challenging. We developed equations for predicting the mortality risk of patients with CRRT, using patients' clinical data. The newly developed equations showed superior performance to SOFA and APACHE II scores. Background: Predicting the risk of death in patients admitted to the critical care unit facilitates appropriate management. In particular, among patients who are critically ill, patients with continuous RRT (CRRT) have high mortality, and predicting the mortality risk of these patients is difficult. The purpose of this study was to develop models for predicting the mortality risk of patients on CRRT and to validate the models externally. Methods: A total of 699 adult patients with CRRT who participated in the VolumE maNagement Under body composition monitoring in critically ill patientS on CRRT (VENUS) trial and 1515 adult patients with CRRT in Seoul National University Hospital were selected as the development and validation cohorts, respectively. Using 11 predictor variables selected by the Cox proportional hazards model and clinical importance, equations predicting mortality within 7, 14, and 28 days were developed with development cohort data. Results: The equation using 11 variables had area under the time-dependent receiver operating characteristic curve (AUROC) values of 0.75, 0.74, and 0.73 for predicting 7-, 14-, and 28-day mortality, respectively. All equations had significantly higher AUROCs than the Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores. The 11-variable equation was superior to the SOFA and APACHE II scores in the integrated discrimination index and net reclassification improvement analyses. Conclusions: The newly developed equations for predicting CRRT patient mortality showed superior performance to the previous scoring systems, and they can help physicians manage patients.