title: Can glycaemic variability, as calculated from blood glucose self-monitoring, predict the development of complications in type 1 diabetes over a decade?
abstract: OBJECTIVE
  Is glycaemic variability an independent risk factor for the development of microvascular complications in addition to average glycaemia, as assessed by glycated haemoglobin (HbA(1c))? In this study, an 11-year follow-up was carried out in patients with type 1 diabetes. The standard deviation of blood glucose (SDBG) concentration, an index of glycaemic variability, was calculated from self-monitored blood glucose data at baseline.
  
  
  METHODS
  A total of 100 patients were randomly selected from 442 consecutive type 1 diabetic patients attending our outpatients clinic. SDBG was calculated from 70 measurements taken over a period of four weeks. Onset and progression of micro- and macrovascular complications were recorded over the 11-year follow-up.
  
  
  RESULTS
  As expected, the prevalence of complications increased over time. Statistical analyses showed that HbA(1c) was an independent predictor of the incidence (P=0.004) and prevalence (P=0.01) of nephropathy. SDBG was found to be a predictor of the prevalence of peripheral neuropathy (P=0.03), and showed borderline significance in predicting the incidence of peripheral neuropathy (P=0.07). SDBG was also a highly significant predictor of hypoglycaemic unawareness (P=0.001).
  
  
  CONCLUSIONS
  We conclude that variability of blood glucose may be important in the development of peripheral neuropathy in patients with type 1 diabetes, and that the nervous system may be particularly vulnerable to glycaemic variability.
authors.affiliation: Department of Clinical Sciences, Danderyd Hospital, Division of Internal Medicine, Karolinska Institutet, 182 88 Stockholm, Sweden. joakim.bragd@ds.se
authors.forename: J
authors.initials: J
authors.lastname: Bragd
authors.forename: U
authors.initials: U
authors.lastname: Adamson
authors.forename: L B
authors.initials: LB
authors.lastname: Bäcklund
authors.forename: P E
authors.initials: PE
authors.lastname: Lins
authors.forename: E
authors.initials: E
authors.lastname: Moberg
authors.forename: P
authors.initials: P
authors.lastname: Oskarsson
mesh_terms: D000328:Adult; D001364:Awareness; D001786:Blood Glucose / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring / Q000379:methods*; D015992:Body Mass Index; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000150:complications* / Q000188:drug therapy; D003925:Diabetic Angiopathies / Q000097:blood / Q000453:epidemiology*; D003928:Diabetic Nephropathies / Q000097:blood / Q000453:epidemiology; D003929:Diabetic Neuropathies / Q000097:blood / Q000453:epidemiology; D003930:Diabetic Retinopathy / Q000097:blood / Q000453:epidemiology; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis*; D006801:Humans; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011237:Predictive Value of Tests; D015995:Prevalence
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin