Yucheng Zhang, Dalton Budhram, Priya Bapat, Sharon Dhaliwal, Ethan Parikh, Hoda Gad, Andrej Orszag, Wajeeha Cheema, Abdulmohsen Bakhsh, Natasha J Verhoeff, Alanna Weisman, Michael Fralick, Noah M Ivers, David Z I Cherney, George Tomlinson, Doug Mumford, Leif Erik Lovblom, Bruce A Perkins
Weekly well-day capillary ketone testing, using existing strips before they expire, may provide a practical approach to stratify baseline DKA risk while reducing testing burden.
OBJECTIVE: Independent of clinical risk factors, performing well-day capillary ketone monitoring over a month predicts near-term diabetic ketoacidosis (DKA) risk. We aimed to determine the minimum frequency of tests needed to maintain similar accuracy.
RESEARCH DESIGN AND METHODS: Using regression and machine-learning gradient-boosted tree (GBT) models on the Empagliflozin as Adjunctive to Insulin Therapy 2 (EASE 2) and EASE 3 trial repository (n = 1,410), we simulated the testing frequencies of capillary ketones over a 1-month interval for predicting DKA or severe ketosis in the next month.
RESULTS: Compared with the baseline twice-weekly ketone testing frequency, once-weekly well-day ketone testing was the lowest frequency that maintained prediction accuracy in maximum ketone models (area under the receiver operating characteristic curve 0.692 vs. 0.678; P = 0.19) and GBT models (0.719 vs. 0.711; P = 0.38).
CONCLUSIONS: Weekly well-day capillary ketone testing, using existing strips before they expire, may provide a practical approach to stratify baseline DKA risk while reducing testing burden.