Here is the design of a clinical trial:

Official Title: Community Based Intervention for Management of Diabetes in Nepal (COBIN-D): A Cluster Randomised Controlled Trial

Included conditions:
- Type 2 Diabetes Mellitus

Study Armgroups:
- {'label': 'FCHV visit-diabetes', 'type': 'EXPERIMENTAL', 'interventionNames': ['Behavioral: FCHV visit']}
- {'label': 'FCHV no visit-diabetes', 'type': 'NO_INTERVENTION'}

Interventions:
- {'type': 'BEHAVIORAL', 'name': 'FCHV visit', 'description': 'FCHVs will visit selected households 3 times a year for providing health promotion messages and measure the blood glucose', 'armGroupLabels': ['FCHV visit-diabetes']}

Primary Outcomes:
- {'measure': 'Mean fasting blood glucose level', 'description': 'Change in mean fasting blood glucose level in diabetes populations', 'timeFrame': '1 year'}

Please estimate the sample size based on the assumption: 
95% confidence interval, significance level of 0.05, standard deviation of 2.1, intracluster correlation of 0.01, design effect of 1.1, 80% power, and up to 20% loss to follow-up.
Sample size calculation
        The sample size for the baseline survey will be calculated with 95% confidence interval (zâ=â1.96), based on the following assumptions: margin of error (alpha),Â 5%; estimated prevalence of diabetes,Â 9.5% [31]; design effect,Â 2; and anticipated response rate,Â 80%. We will only include the â¥â25Â years age group, so we will have four age groups for each sex (total strataâ=â8); this will result in a sample sizeÂ ofÂ 2643. The sample size was calculated based on the method suggested by the WHO STEPWISE Approach [32]. According to the STEPS sample size calculator, a margin of error of 0.05 is suggested in a prevalence survey for an expected prevalence of 10% or greater. In addition, a smaller margin of error of 0.02 or 0.01 is considered appropriate when the expected prevalence is lower than 10%. The anticipated prevalence of type 2 diabetes was 9.5% in the earlier study [31], which is very close to 10%; this being an assumption, a margin of error of 0.05 was included. For the intervention study, we took a reference of a lifestyle intervention study for diabetes management conducted in a rural community-based setting, which showed a mean reduction in fasting blood glucose by 1.0Â mmol/L after intervention in the diabetic population [33]. Using the two-sided t test with a significance level of 0.05 and assuming a standard deviation of 2.1, considering an intracluster correlation of 0.01, and the design effect of 1.1 and 80% power, we will need seven clusters with 13 individuals per intervention arm. Allowing for up to 20% loss to follow-up, the sample size was adjusted to 16 in each cluster, i.e., 112 individuals per arm or a total of 224 diabetes patients.