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BEYOND MONITORING: VALIDATION OF THE STATSTRIP GLUCOSE METER AS A DIAGNOSTIC TOOL FOR DIABETES MELLITUS

Background and aim: Despite their many potential advantages, point-of- care (POC) glucose meters for diabetes screening and diagnosis had been generally compromised due to insufficient accuracy. The aim of this study was to validate the performance of the POC glucose analyser (StatStrip, Nova Biomedical, USA) within the diagnostic procedure for diabetes. Methods: Fasting blood samples were taken from consenting patients reffered to our clinic with a working diagnosis of dysglycaemia. Venous and capillary blood sampling for reference laboratory procedure (hexokinase, Olympus AU400, Beckman Coulter, USA) and StatStrip glucose measurement, respectively, was carried out within five minutes. A 75-g oral glucose tolerance test was then performed and respective blood samples taken two hours after glucose load. WHO criteria for venous and capillary plasma glucose were used to classify patients into diagnostic categories. Results: A total of 180 patients (M/F: 80/100 ; age range 18-89, median 56 years) were included in this study. Bland-Altman analysis revealed no apparent bias between laboratory and StatStrip glucose results in the fasting samples [mean:-0.14, range(±1.96SD):-1.15-0.88 mmol/L], whereas mean bias in the post-load samples was -0.46 mmol/L [range(±1.96SD):-1.95-1.04 mmol/L]. Hematocrit had no influence on the bias between two methods in either fasting or post-load samples (P=0.483 and P=0.859, respectively). Inter-rater agreement analysis showed very good agreement (weighted kappa=0.821) between the methods when classifying subjects into the diagnostic categories of normoglycaemia, intermediate hyperglycaemia and diabetes by sample type-related classification criteria. Conclusion: StatStrip POC glucose meter might serve as a powerful tool for screening and diagnosis of diabetes and intermediate hyperglycaemia.

Diabetes; diagnosis; StatStrip; POCT

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