Abstract:
: Background: Continuous glucose monitoring (CGM) is a method of estimating blood glucose values from those recorded in the interstitial fluid. Because increasingly longer CGM measurements are possible, errors and data loss become more and more likely and potentially more damaging to accurate calculations of glycemic variability (GV) indices. Our research investigates the resistance of the CGM recording to data loss. Methods: We collected 71 CGM recordings (duration of min: 2, max: 265, median: 42 days) from patients with type 1 diabetes and used three algorithms to introduce missing data. We calculated mean and standard deviation (SD) of absolute percentage error of 12 variability indices and correlated those with the percentage of missing data and duration of the measurements. Results: Mean absolute percentage error of variability indices increased linearly with the percentage of missing data along with SD of absolute percentage error. Except for mean amplitude of glycemic excursions and time spent in hypoglycemia, all absolute errors never exceeded 25%, while mean absolute errors stayed below 5%. The gradient removal algorithm introduced errors larger than the single datapoint and block removal algorithms. The absolute percentage error of variability indices correlated negatively with the duration of the CGM measurements. Conclusions: Standard GV measurements in long-term glucose monitoring are robustly resistant to data loss.
journal_name
Diabetes Technol Therjournal_title
Diabetes technology & therapeuticsauthors
Kucharski P,Pagacz K,Szadkowska A,Młynarski W,Romanowski A,Fendler Wdoi
10.1089/dia.2018.0247subject
Has Abstractpub_date
2018-12-01 00:00:00pages
833-842issue
12eissn
1520-9156issn
1557-8593journal_volume
20pub_type
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