TRIAL-INFORMED DKA MITIGATION EDUCATIONAL TOOL: THE TORONTO-MICHIGAN PATIENT-PROVIDER COLLABORATIVE

We have designed a three-step project to identify the critical components of a diabetic ketoacidosis (DKA) mitigation strategy that will be intended for use in clinical practice and research. DKA is a serious complication of diabetes that occurs when high blood sugar and acidic substances called ketones build to dangerous levels in the body and can poison the body. Recently, a new group of oral drugs used for treating diabetes by lowering blood glucose levels called Sodium Glucose Linked Transporter (SGLT) inhibitors have been introduced. They may help people with T1D treat their diabetes in conjunction with insulin, but they may also increase the risk of DKA. Our mitigation strategy will be used to effectively mitigate risk of DKA in the general type 1 diabetes (T1D) population, in the T1D population using Sodium Glucose Linked Transporter (SGLT) inhibition, and in large-scale trials of efficacy and safety of SGLT inhibition.

The study design includes three separate objectives: the first two call for new statistical analyses of existing clinical trials and observational studies, and the third calls for the development of a mitigation tool by a multidisciplinary team of patients, caregivers, and healthcare providers. The first two objectives are meant to inform the third, and one of those first two objectives applies to this data request to Boehringer Ingelheim through Vivli.org.

Our objective for this request is to define the optimal diagnostic thresholds for beta-hydroxybutyrate (BHB) levels to be used in mitigation strategies for patients using and not using SGLT inhibition therapy. BHB is a chemical that is used for energy by some cells in the body when sugar levels are low, and it can be checked using standard ketone tests as a marker of DKA. These optimal thresholds for BHB will therefore be helpful in predicting future DKA incidence in patients with T1D. We intend to analyze the data on the 1707 participants who were followed for 6-12 months in the EASE-2 and EASE-3 phase three clinical trials. Using “diagnostic study methods”, we will determine if there is a threshold level of BHB or ketones (obtained by the finger-stick method for obtaining a capillary blood sample from the finger) that identifies people at high risk of subsequent DKA events. The implication of this research is that the mitigation strategy can incorporate well-defined and validated thresholds to monitor for times when individual patients will be at elevated risk of DKA.

Based on our previous strong findings from objectives 1 and 2, we have interest in examining feature engineering and other advanced machine learning methods for the prediction of diabetic ketoacidosis in type 1 diabetes.

We have therefore added a new secondary objective and we hope to identify if lower frequency capillary ketone testing (e.g., once per week or less) could yield a prediction performance for future DKA that is equivalent to the higher testing frequency specified in the EASE trial protocol.