Key Points
Predicting the risk of mortality in patients with CRRT is important for appropriate management but challenging.
We developed equations for predicting the mortality risk of patients with CRRT, using clinical data of the patients.
The newly developed equations showed superior performance to SOFA and APACHE II scores.
Abstract
Background:Predicting the risk of death in patients admitted to the critical care unit facilitates appropriate management. In particular, among critically ill patients, patients with continuous renal replacement therapy (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 VENUS (VolumE maNagement Under body composition monitoring in critically ill patientS on CRRT) trial and 1,515 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 days, 14 days, 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 0.745, 0.743, and 0.726 for predicting 7-day, 14-day, 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.
- Received February 2, 2022.
- Revision received May 2, 2022.
- Accepted May 2, 2022.
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