title: Random blood glucose may be used to assess long-term glycaemic control among patients with type 2 diabetes mellitus in a rural African clinical setting.
abstract: OBJECTIVE
  To investigate the diagnostic accuracy of random blood glucose (RBG) on good glycaemic control among patients with diabetes mellitus (DM) in a rural African setting.
  
  
  METHODS
  Cross-sectional study at St. Francis' Hospital in eastern Zambia. RBG and HbA1c were measured during one clinical review only. Other information obtained was age, sex, body mass index, waist circumference, blood pressure, urine albumin-creatinine ratio, duration since diagnosis and medication.
  
  
  RESULTS
  One hundred and one patients with DM (type 1 DM = 23, type 2 DM = 78) were included. Spearman's rank correlation coefficient revealed a significant correlation between RBG and HbA1c among the patients with type 2 DM (r = 0.73, P < 0.001) but not patients with type 1 DM (r = 0.17, P = 0.44). Furthermore, in a multivariate linear regression model (R(2) = 0.71) RBG (per mmol/l increment) (B = 0.28, 95% CI:0.24-0.32, P < 0.001) was significantly associated with HbA1c among the patients with type 2 DM. Based on ROC analysis (AUC = 0.80, SE = 0.05), RBG ≤7.5 mmol/l was determined as the optimal cut-off value for good glycaemic control (HbA1c <7.0% [53 mmol/mol]) among patients with type 2 DM (sensitivity = 76.7%; specificity = 70.8%; positive predictive value = 62.2%; negative predictive value = 82.9%).
  
  
  CONCLUSIONS
  Random blood glucose could possibly be used to assess glycaemic control among patients with type 2 DM in rural settings of sub-Saharan Africa.
authors.affiliation: Department of International Health, Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark; Department of Internal Medicine, Endocrinology Unit, Copenhagen University Hospital, Herlev, Denmark.
authors.forename: Jon B
authors.initials: JB
authors.lastname: Rasmussen
authors.forename: Lovisa S
authors.initials: LS
authors.lastname: Nordin
authors.forename: Niclas S
authors.initials: NS
authors.lastname: Rasmussen
authors.forename: Jakúp A
authors.initials: JA
authors.lastname: Thomsen
authors.forename: Laura A
authors.initials: LA
authors.lastname: Street
authors.forename: Ib C
authors.initials: IC
authors.lastname: Bygbjerg
authors.forename: Dirk L
authors.initials: DL
authors.lastname: Christensen
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism*; D003430:Cross-Sectional Studies; D003922:Diabetes Mellitus, Type 1 / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood*; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism*; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D012372:ROC Curve; D012016:Reference Values; D015203:Reproducibility of Results; D012424:Rural Population; D018709:Statistics, Nonparametric; D055815:Young Adult; D015024:Zambia
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin
keywords: Afrique subsaharienne; HbA1c; ROC curve; control glucémico; contrôle de la glycémie; courbe ROC; curva ROC; diabetes mellitus; diabète sucré; glucosa en sangre aleatoria; glycaemic control; glycémie aléatoire; random blood glucose; rural; sub-Saharan Africa; África sub-Sahariana