title: Glycemic variability is higher in type 1 diabetes patients with microvascular complications irrespective of glycemic control.
abstract: BACKGROUND
  Increased glycemic variability (GV) may be associated with diabetes complications. Our study assessed the relationship between microvascular complications (MVCs) and GV calculated from continuous glucose monitoring (CGM) data in type 1 diabetes patients.
  
  
  METHODS
  Thirty-two patients with type 1 diabetes (16 with and 16 without MVC) participated in this cross-sectional study. Vibration perception threshold (VPT), microalbuminuria, and fundoscopy were used to detect MVC. CGM data were recorded for 2 weeks and analyzed using proprietary software. Total SD (SDT), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE) were compared.
  
  
  RESULTS
  Patients with any MVC had significantly higher GV, calculated from CGM, than patients without MVC (SDT, 4.1 ± 0.6 vs. 3.4 ± 0.8 mmol/L [P = 0.010]; CV, 0.43 ± 0.06 vs. 0.38 ± 0.08 [P = 0.032]; MAGE, 6.9 ± 1.2 vs. 5.9 ± 1.2 mmol/L [P = 0.014]) but comparable glycated hemoglobin (HbA1c) (70 ± 9 vs. 69 ± 10 mmol/mol [8.6 ± 0.8% vs. 8.5 ± 0.9%], difference not significant). No significant difference in GV was found between the two groups when using only self-monitored blood glucose (SMBG) data. A positive association was found between VPT and SDT in all patients (r = 0.51, P = 0.0026).
  
  
  CONCLUSIONS
  Patients with type 1 diabetes and any MVC had significantly higher GV calculated from CGM, but not from SMBG, than patients with comparable glycemic control but without complications. This supports the hypothesis that increased GV might be associated with MVC in type 1 diabetes and that HbA1c may not describe diabetes control completely.
authors.affiliation: 3rd Department of Internal Medicine, First Faculty of Medicine, Charles University , Prague, Czech Republic .
authors.forename: Jan
authors.initials: J
authors.lastname: Šoupal
authors.forename: Jan
authors.initials: J
authors.lastname: Škrha
authors.forename: Martin
authors.initials: M
authors.lastname: Fajmon
authors.forename: Eva
authors.initials: E
authors.lastname: Horová
authors.forename: Miloš
authors.initials: M
authors.lastname: Mráz
authors.forename: Jan
authors.initials: J
authors.lastname: Škrha
authors.forename: Martin
authors.initials: M
authors.lastname: Prázný
mesh_terms: D000328:Adult; D000419:Albuminuria; D000704:Analysis of Variance; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring; D003430:Cross-Sectional Studies; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000150:complications / Q000503:physiopathology; D003925:Diabetic Angiopathies / Q000097:blood / Q000209:etiology / Q000503:physiopathology; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000379:methods*; D016017:Odds Ratio; D011237:Predictive Value of Tests; D018570:Risk Assessment; D014732:Vibration
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human