Chia-Lin Lee1, Wayne Huey-Herng Sheu2, I-Te Lee3, Shih-Yi Lin4, Wen-Miin Liang5, Jun-Sing Wang6, Yu-Fen Li7. 1. Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650, Sec. 4, Taiwan Boulevard, Taichung 407, Taiwan; Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan; Department of Public Health, College of Public Health, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan. 2. Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650, Sec. 4, Taiwan Boulevard, Taichung 407, Taiwan; Department of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan; Institute of Medical Technology, College of Life Science, National Chung-Hsing University, Taichung, Taiwan; School of Medicine, National Defence Medical Centre, Taipei, Taiwan. 3. Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650, Sec. 4, Taiwan Boulevard, Taichung 407, Taiwan; Department of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan; Department of Medicine, School of Medicine, Chung Shan Medical University, Taichung, Taiwan. 4. Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650, Sec. 4, Taiwan Boulevard, Taichung 407, Taiwan; Department of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan. 5. Department of Public Health, College of Public Health, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan. 6. Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, No. 1650, Sec. 4, Taiwan Boulevard, Taichung 407, Taiwan; Department of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan. Electronic address: jswang@vghtc.gov.tw. 7. Department of Public Health, College of Public Health, China Medical University, No. 91, Hsueh-Shih Road, Taichung 404, Taiwan. Electronic address: yufenli@mail.cmu.edu.tw.
Abstract
AIM: To investigate the effect of changes in fasting plasma glucose (FPG) variability, as assessed by 2-year trajectories of FPG variability, on mortality risk in patients with type 2 diabetes (T2D). METHODS: From 2009 to 2012, outpatients with T2D, aged>18 years, were enrolled from a medical centre. FPG was measured every 3 months for 2 years in 3569 people. For each of the eight 3-month intervals, FPG variability and means were calculated, with variability defined as the coefficient of variation of FPG. Also, trajectories of FPG variability and means were determined separately, using group-based trajectory analysis with latent class growth models. These models were fitted using the SAS Proc Traj procedure. The primary outcome was all-cause mortality, which was followed-up to the end of 2014. RESULTS: Five distinct trajectories of FPG variability (low, increasing, fluctuating, decreasing and high) and means (well controlled, stable control, worsening control, improving control and poor control) were established. The five trajectories of mean FPG were all associated with the same mortality risk. In contrast, in comparison to the low FPG variability trajectory, the fluctuating, decreasing and high variability trajectories all had significantly higher risks of mortality, with respective hazards ratios of 2.63 (95% CI: 1.40-4.93; P=0.003), 2.78 (95% CI: 1.33-5.80; P=0.007) and 4.44 (95% CI: 1.78-11.06; P=0.001) after multivariable adjustment. CONCLUSION: Changes in FPG variability were independently associated with increased mortality risk in patients with T2D.
AIM: To investigate the effect of changes in fasting plasma glucose (FPG) variability, as assessed by 2-year trajectories of FPG variability, on mortality risk in patients with type 2 diabetes (T2D). METHODS: From 2009 to 2012, outpatients with T2D, aged>18 years, were enrolled from a medical centre. FPG was measured every 3 months for 2 years in 3569 people. For each of the eight 3-month intervals, FPG variability and means were calculated, with variability defined as the coefficient of variation of FPG. Also, trajectories of FPG variability and means were determined separately, using group-based trajectory analysis with latent class growth models. These models were fitted using the SAS Proc Traj procedure. The primary outcome was all-cause mortality, which was followed-up to the end of 2014. RESULTS: Five distinct trajectories of FPG variability (low, increasing, fluctuating, decreasing and high) and means (well controlled, stable control, worsening control, improving control and poor control) were established. The five trajectories of mean FPG were all associated with the same mortality risk. In contrast, in comparison to the low FPG variability trajectory, the fluctuating, decreasing and high variability trajectories all had significantly higher risks of mortality, with respective hazards ratios of 2.63 (95% CI: 1.40-4.93; P=0.003), 2.78 (95% CI: 1.33-5.80; P=0.007) and 4.44 (95% CI: 1.78-11.06; P=0.001) after multivariable adjustment. CONCLUSION: Changes in FPG variability were independently associated with increased mortality risk in patients with T2D.
Authors: Jun Jie Benjamin Seng; Amelia Yuting Monteiro; Yu Heng Kwan; Sueziani Binte Zainudin; Chuen Seng Tan; Julian Thumboo; Lian Leng Low Journal: BMC Med Res Methodol Date: 2021-03-11 Impact factor: 4.615