TY - JOUR
T1 - Time delay of CGM sensors
T2 - Relevance, causes, and countermeasures
AU - Schmelzeisen-Redeker, Günther
AU - Schoemaker, Michael
AU - Kirchsteiger, Harald
AU - Freckmann, Guido
AU - Heinemann, Lutz
AU - Del Re, Luigi
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was (partially) funded by Roche Diagnostics.
Publisher Copyright:
© 2015 Diabetes Technology Society.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2015/9
Y1 - 2015/9
N2 - Background: Continuous glucose monitoring (CGM) is a powerful tool to support the optimization of glucose control of patients with diabetes. However, CGM systems measure glucose in interstitial fluid but not in blood. Rapid changes in one compartment are not accompanied by similar changes in the other, but follow with some delay. Such time delays hamper detection of, for example, hypoglycemic events. Our aim is to discuss the causes and extent of time delays and approaches to compensate for these. Methods: CGM data were obtained in a clinical study with 37 patients with a prototype glucose sensor. The study was divided into 5 phases over 2 years. In all, 8 patients participated in 2 phases separated by 8 months. A total number of 108 CGM data sets including raw signals were used for data analysis and were processed by statistical methods to obtain estimates of the time delay. Results: Overall mean (SD) time delay of the raw signals with respect to blood glucose was 9.5 (3.7) min, median was 9 min (interquartile range 4 min). Analysis of time delays observed in the same patients separated by 8 months suggests a patient dependent delay. No significant correlation was observed between delay and anamnestic or anthropometric data. The use of a prediction algorithm reduced the delay by 4 minutes on average. Conclusions: Prediction algorithms should be used to provide real-time CGM readings more consistent with simultaneous measurements by SMBG. Patient specificity may play an important role in improving prediction quality.
AB - Background: Continuous glucose monitoring (CGM) is a powerful tool to support the optimization of glucose control of patients with diabetes. However, CGM systems measure glucose in interstitial fluid but not in blood. Rapid changes in one compartment are not accompanied by similar changes in the other, but follow with some delay. Such time delays hamper detection of, for example, hypoglycemic events. Our aim is to discuss the causes and extent of time delays and approaches to compensate for these. Methods: CGM data were obtained in a clinical study with 37 patients with a prototype glucose sensor. The study was divided into 5 phases over 2 years. In all, 8 patients participated in 2 phases separated by 8 months. A total number of 108 CGM data sets including raw signals were used for data analysis and were processed by statistical methods to obtain estimates of the time delay. Results: Overall mean (SD) time delay of the raw signals with respect to blood glucose was 9.5 (3.7) min, median was 9 min (interquartile range 4 min). Analysis of time delays observed in the same patients separated by 8 months suggests a patient dependent delay. No significant correlation was observed between delay and anamnestic or anthropometric data. The use of a prediction algorithm reduced the delay by 4 minutes on average. Conclusions: Prediction algorithms should be used to provide real-time CGM readings more consistent with simultaneous measurements by SMBG. Patient specificity may play an important role in improving prediction quality.
KW - Accuracy
KW - CGM
KW - Continuous glucose monitoring
KW - MARD
KW - Performance comparison
KW - Performance evaluation
KW - Precision
KW - Time delay
KW - Blood Glucose Self-Monitoring/instrumentation
KW - Biosensing Techniques/instrumentation
KW - Humans
KW - Middle Aged
KW - Male
KW - Diabetes Mellitus, Type 1/blood
KW - Young Adult
KW - Blood Glucose/analysis
KW - Algorithms
KW - Time Factors
KW - Adult
KW - Female
KW - Hypoglycemic Agents/therapeutic use
KW - Insulin Infusion Systems
UR - http://www.scopus.com/inward/record.url?scp=84977745154&partnerID=8YFLogxK
U2 - 10.1177/1932296815590154
DO - 10.1177/1932296815590154
M3 - Article
C2 - 26243773
AN - SCOPUS:84977745154
SN - 1932-2968
VL - 9
SP - 1006
EP - 1015
JO - Journal of diabetes science and technology
JF - Journal of diabetes science and technology
IS - 5
ER -