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.
Cross-sectional diagnostic accuracy study.
16 diabetes centres were selected randomly from all eight administrative divisions of Bangladesh.
A total of 3200 adults aged 18 years and older were recruited using systematic random sampling between May and September 2022.
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.
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).
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.
The ‘Developing and evaluating an adapted behavioural activation intervention for depression and diabetes in South Asia (DiaDeM)’ trial investigates a psychological intervention, behavioural activation (BA), on people with both diabetes and depression in Bangladesh and Pakistan. This study aimed to aid the intervention and trial design.
This was a modelling study using microsimulation to assess the intervention’s cost-effectiveness. Diabetes was modelled using the UK Prospective Diabetes Study model based on Pakistani patients and depression was modelled using Patient Health Questionnaire-9 (PHQ-9) trajectories allowing for multiple depressive episodes. It was assumed that diabetes-related adverse events increased depression recurrence, while depression impacted haemoglobin A1c, increasing diabetes-related events. The model estimated (1) maximum cost of BA which would be cost-effective (headroom analysis) to inform intervention design, and (2) value of reducing uncertainty around different measures (value of information analysis) to prioritise data collection in the DiaDeM study.
Analysis was conducted from a Pakistani healthcare perspective over a lifetime with costs and outcomes discounted at 3%.
BA plus usual care was compared against usual care. BA involved six sessions by a trained (non-mental health) facilitator. The usual care comparator was the prevailing mix of pharmacological and non-pharmacological treatments used in Pakistan.
The primary outcome was disability-adjusted life-years (DALYs). Secondary outcomes included life years, healthcare costs and the rate of depression and diabetes-related events.
Over their lifetime, individuals receiving BA plus usual care avoid 3.2 (95% credible interval: 2.7 to 3.8) years of mild depression and experience fewer diabetes-related events. BA plus usual care resulted in an additional 0.27 (0.03 to 0.52) life years, 0.98 (0.45 to 1.86) DALYs averted and had incremental healthcare costs of –US$97 (–US$517 to US$142), excluding BA costs. The maximum cost per BA course at which was cost-effective is US$83 (US$9 to US$214). Value of information analysis found the most important measures to include in the trial are the impact of depression on diabetes and PHQ-9 over time.
This is the first model to jointly model depression and diabetes for South Asia and uses novel methods to reflect the diseases and inform intervention and trial design. This evidence has helped to inform the design of the DiaDeM intervention and the trial to evaluate it.
DiaDeM trial: ISRCTN40885204, DOI: ; pre-results, DOI: