The following is a summary of “Risk Modeling to Reduce Monitoring of an Autoantibody-Positive Population to Prevent DKA at Type 1 Diabetes Diagnosis,” published in the March 2023 issue of Endocrinology & Metabolism by Rourke et al.

For a study, researchers sought to investigate whether reducing the frequency of metabolic monitoring visits while limiting the undiagnosed time for type 1 diabetes (T1D) patients could reduce the incidence of diabetic ketoacidosis (DKA) at diagnosis.

Data from TrialNet’s Pathway to Prevention (PTP), a cross-sectional longitudinal research identifying and monitoring at-risk families of persons with T1D, were analyzed. PTP was a population-based study that recruited participants from several nations. From March 2004 to April 2019, 6,193 individuals with autoantibody (AAB) positivity participated in PTP. For pediatric and adult populations with one or more AABs, they created models of clinical diagnostic progression and used estimated hazard rates to summarise the findings. In addition, an ideal monitoring visit schedule was established for each model to attain a minimum average undiagnosed time for each group.

The study found that halving the number of monitoring visits typically conducted in research studies would significantly reduce the incidence of DKA at T1D diagnosis in the population.

Reducing the frequency of metabolic monitoring visits while limiting undiagnosed time could reduce the incidence of DKA at T1D diagnosis, thus reducing the clinical burden for at-risk individuals. The finding could have significant clinical implications and provide a path for transitioning monitoring beyond the research setting.

Reference: https://academic.oup.com/jcem/article-abstract/108/3/688/6759855?redirectedFrom=fulltext