Identifying patients at high risk for diabetic ketoacidosis (DKA) is crucial for informing efforts at preventive intervention. This study sought to develop and validate an electronic medical record (EMR)-based tool for predicting DKA risk in pediatric patients with type 1 diabetes. Based on analysis of data from 1,864 patients with type 1 diabetes, three factors emerged as significant predictors of DKA: most recent A1C, type of health insurance (public vs. private), and prior DKA. A prediction model was developed based on these factors and tested to identify and categorize patients at low, moderate, and high risk for experiencing DKA within the next year. This work demonstrates that risk for DKA can be predicted using a simple model that can be automatically derived from variables in the EMR.
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Spring 2022
Feature Articles|
April 15 2022
An Automated Risk Index for Diabetic Ketoacidosis in Pediatric Patients With Type 1 Diabetes: The RI-DKA
David D. Schwartz
;
1Section of Psychology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
Corresponding author: David D. Schwartz, ddschwar@bcm.edu
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Rosa Banuelos;
Rosa Banuelos
2Texas Children’s Hospital Quality Outcomes and Analytics, Houston, TX
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Serife Uysal;
Serife Uysal
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Mili Vakharia;
Mili Vakharia
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Kristen R. Hendrix;
Kristen R. Hendrix
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
4Piedmont Physicians Endocrinology, Columbus, GA
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Kelly Fegan-Bohm;
Kelly Fegan-Bohm
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Sarah K. Lyons;
Sarah K. Lyons
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Rona Sonabend;
Rona Sonabend
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Sheila K. Gunn;
Sheila K. Gunn
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Selorm Dei-Tutu
Selorm Dei-Tutu
3Section of Pediatric Diabetes and Endocrinology, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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Corresponding author: David D. Schwartz, ddschwar@bcm.edu
Clin Diabetes 2022;40(2):204–210
Citation
David D. Schwartz, Rosa Banuelos, Serife Uysal, Mili Vakharia, Kristen R. Hendrix, Kelly Fegan-Bohm, Sarah K. Lyons, Rona Sonabend, Sheila K. Gunn, Selorm Dei-Tutu; An Automated Risk Index for Diabetic Ketoacidosis in Pediatric Patients With Type 1 Diabetes: The RI-DKA. Clin Diabetes 1 April 2022; 40 (2): 204–210. https://doi.org/10.2337/cd21-0070
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