Machine learning based study of longitudinal HbA1c trends and their association with all-cause mortality: Analyses from a National Diabetes Registry.

Objective The association of long-term HbA1c variability with mortality has been previously suggested. However, the significance of HbA1c variability and trends in different age and HbA1c categories is unclear. Research design and methods Data on patients with diabetes listed in the Israeli National Diabetes Registry during years 2012-2016 (observation period) were collected. Patients with >4 HbA1c measurements, type 1 diabetes, eGFR 7%) at end of observation period. Models were adjusted for demographic, clinical and laboratory measurements including HbA1c, standard deviation (SD) of HbA1c and HbA1c trend. Results This historical cohort study included 293,314 patients. Increased HbA1c variability (high SD) during the observation period was an independent predictor of mortality in patients aged >55 years (p 7% at the end of the observation period (p=0.02 in age 35-54; p 55). Patients with an increasing vs. stable HbA1c trend had a greater mortality risk only in the elderly group (>70), yet in both HbA1c categories (p Conclusions HbA1c variability and trend are important determinants of mortality risk and should be considered when adjusting glycemic targets. This article is protected by copyright. All rights reserved.