AUTHOR=Ma Chifa , Zhang Weinan , Xie Rongrong , Wan Gang , Yang Guangran , Zhang Xuelian , Fu Hanjing , Zhu Liangxiang , Lv Yujie , Zhang Jiandong , Li Yuling , Ji Yu , Gao Dayong , Cui Xueli , Wang Ziming , Chen Yingjun , Yuan Shenyuan , Yuan Mingxia 

TITLE=Effect of Hemoglobin A1c Trajectories on Future Outcomes in a 10-Year Cohort With Type 2 Diabetes Mellitus

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.846823

DOI=10.3389/fendo.2022.846823

ISSN=1664-2392

ABSTRACT=Background: Hemoglobin A1c (HbA1c) variability may be a predictor of diabetic complications, but the predictive values of HbA1c trajectories remain unclear. We aimed to classify long-term HbA1c trajectories and to explore their effects on future clinical outcomes in a ten- year cohort with type 2 diabetes (T2DM).
Methods: 2161 participants with T2DM from the Beijing Community Diabetes Study were included. The ten-year follow-up was divided into two stages for the present data analysis. Stage I (from 2008 to 2014) was used to identify the HbA1c trajectories and to calculate the adjusted standard derivation of HbA1c (HbA1c-adjSD), or the coefficient of variation of HbA1c (HbA1c-CV). Stage II (from 2014 to 2018) was used to collect the records of the new occurrence of diabetes-related clinical outcomes. Latent growth mixture models were used to identify HbA1c trajectories. Cox proportional hazards models were used to explore the relationship between HbA1c trajectories, HbA1c-adjSD, or HbA1c-CV and the future outcomes. 
Results: Three HbA1c trajectories were identified, including low stable (88.34%), gradual decreasing (5.83%), and pre-stable and post-increase (5.83%). Either the risk of death or the chronic complications were significantly higher in the latter two groups compared to the low stable group after adjustment for average HbA1c and other traditional risk factors, the adjusted hazard ratios (HRs) for renal events, composite endpoint and all-cause death for the pre-stable and post-increase group were 2.83[95% confidence interval (CI): 1.25-6.41, P=0.013], 1.85(95%CI: 1.10-3.10, P=0.020) and 3.01(95%CI: 1.13-8.07, P=0.028), respectively, and the adjusted HR for renal events for gradual decreasing group was 2.37 (95%CI: 1.08-5.21, P=0.032). In addition, both univariate and multivariate Cox HR models indicated that participants in the fourth and third quartile of HbA1c-CV or HbA1c-adjSD were at higher risk of renal events compared participants in the first quartile.
Conclusions: HbA1c trajectories, HbA1c-CV and HbA1c-adjSD could all predict diabetes-related clinical outcomes. HbA1c trajectories could reflect long-term blood glucose fluctuation more intuitively, and non-stable HbA1c trajectories may predict increased risk of renal events, all-cause death and composite endpoint events, independent of average HbA1c.