Random capillary blood glucose in the diagnosis of diabetes: a cross-sectional study in Bangladesh - Hajera Mahtab; Md Faruque Pathan; Md Robed Amin; Tasnima Siddiquee; Bishwajit Bhowmik; Sanjida Binte Munir; Shaila Parvin; Tareen Ahmed; Faria Afsana; Nazmul Kabir Qureshi; Ahmed Salam Mir; Rubayat Islam; et al. (BMJ Open)
Objective To assess the effectiveness of random capillary blood glucose as a diagnostic tool for type 2 diabetes and determine optimal cut-off values for adults in Bangladesh.Design Cross-sectional diagnostic accuracy study.Setting 16 diabetes centres were selected randomly from all eight administrative divisions of Bangladesh.Participants A total of 3200 adults aged 18 years and older were recruited using systematic random sampling between May and September 2022.Primary and secondary outcome measures The primary outcome was the diagnostic accuracy of random capillary blood glucose compared to fasting plasma glucose, 2-hour plasma glucose after a 75-gram glucose load and glycated haemoglobin. Secondary outcomes included sensitivity, specificity, area under the curve and agreement with the other diagnostic tests.Results Random capillary blood glucose showed a strong positive correlation and high concordance with fasting plasma glucose, 2-hour plasma glucose and glycated haemoglobin. A cut-off value of ≥8.7 mmol/L demonstrated improved diagnostic performance compared with the currently used cut-off of ≥11.1 mmol/L. This new threshold yielded higher sensitivity, specificity, area under the curve and agreement with other standard diagnostic tests. Notably, hyperglycaemic symptoms were not required for diagnosis. The number needed to screen to identify one case of type 2 diabetes using the ≥8.7 mmol/L cut-off was 2.74, lower than that for fasting plasma glucose (2.86) and random capillary blood glucose ≥11.1 mmol/L (4.68).Conclusions Random capillary blood glucose may be an effective and affordable diagnostic tool for type 2 diabetes in resource-limited settings. The proposed cut-off of ≥8.7 mmol/L offers improved diagnostic accuracy and reflects the population’s glucose distribution pattern.