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Abstract

Aim

Our aims were (1) to design and standardize a statistical approach for data reduction in continuous glucose monitoring, allowing comparison of circadian glycemic patterns in therapeutic subcohorts of patients with type 1 diabetes, and (2) to investigate the applicability of this approach for CGMS^® assessment in clinical study of basal insulin replacement quality with various timings of basal injections (pre-breakfast, dinner, bedtime) of a new insulin analog.

Methods

Prospective randomized three-arm parallel study with switch over after 6 months for another 3 months of free choice injection time point (options pre-breakfast, pre-dinner and bedtime) of the new insulin analog in 16 type 1 diabetic subjects on functional insulin treatment (FIT: basal, prandial and correctional dosages). CGMS^® was used at the end of each follow up period of a clinical study. Representative daily profiles were off-line computed as “circadian sensor modal days” for each insulin regimen consisting of consecutive means of hourly glucose values.

Results

Although the overall quality of glycemic control (HbA_IC) for different regimens did not reach statistical differences, CGMS^® displayed slightly divergent maximal swings in the course of glycemia (p=0.04–0.08) and allowed – with delineated data reduction procedure – a reliable between treatment comparison.

Conclusion

Off-line computation of “hourly circadian sensor modal days” for data reduction can be effectively used with CGMS^® for description of circadian glycemic patterns in type 1 diabetes. (Int J Artif Organs 2003; 26: 728–34)

Keywords

Continuous subcutaneous glucose monitoring Hourly circadian sensor modal day Type 1 diabetes mellitus Long-acting insulin analog Randomized open clinical trial

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Computerized Generation of Circadian Sensor Modal Days with Continuous Glucose Monitoring for Comparison of Various Insulin Regimens Based on Insulin Glargine in Type 1 Diabetes

Abstract

Aim

Methods

Results

Conclusion

Keywords

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References