ArticleClinical diabetes : a publication of the American Diabetes Association2022
An Automated Risk Index for Diabetic Ketoacidosis in Pediatric Patients With Type 1 Diabetes: The RI-DKA.
Article in Clinical diabetes : a publication of the American Diabetes Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- The Development and Validation of Multivariable Electronic Health Record-Based Models to Predict Diabetic Ketoacidosis-Related Hospitalizations for Adults with Type 1 Diabetes.Diabetes technology & therapeutics · 2026Article
- Prediction of acute metabolic complications in hospitalized elderly patients with type 2 diabetes using admission HbA1c and hypertension: a retrospective cohort study.American journal of translational research · 2026Article
- Reducing Diabetic Ketoacidosis Incidence in Children With Type 1 Diabetes Through Wraparound Services at Texas Children's Hospital: The REACH Program.Clinical diabetes : a publication of the American Diabetes Association · 2025Article
- Predicting and Ranking Diabetic Ketoacidosis Risk Among Youth with Type 1 Diabetes with a Clinic-to-Clinic Transferrable Machine Learning Model.Diabetes technology & therapeutics · 2025Article
- Characterizing the relationship between social determinants of health and risk of albuminuria among children with type 1 diabetes.Journal of diabetes and its complications · 2024Article
- A Machine Learning Model for Risk Stratification of Postdiagnosis Diabetic Ketoacidosis Hospitalization in Pediatric Type 1 Diabetes: Retrospective Study.JMIR diabetes · 2024Article
- A Comprehensive System for Identifying Patients With Type 1 Diabetes at Increased Risk for Diabetic Ketoacidosis at Texas Children's Hospital.Clinical diabetes : a publication of the American Diabetes Association · 2022Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.