ArticleJournal of diabetes science and technology2015
Time Delay of CGM Sensors: Relevance, Causes, and Countermeasures.
Article in Journal of diabetes science and technology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
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The trial behind it
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Who cites it
71 citing papers in PubMed, 146 citations in OpenAlex.
- Trial
- A Randomized, Placebo-Controlled Double-Blind Trial of a Closed-Loop Glucagon System for Postbariatric Hypoglycemia.The Journal of clinical endocrinology and metabolism · 2020Trial
- Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes.Diabetes technology & therapeutics · 2019Trial
- Microneedle-Based Continuous Levodopa Monitoring in Patients with Parkinson's Disease.ACS sensors · 2026Article
- The dawn phenomenon in diabetes: pathophysiology from periphery to central nervous system and circadian rhythm-based therapeutic strategies.Acta diabetologica · 2026Review
- A pilot study testing a continuous glucose monitoring sensor in lean growing pigs fed contrasting diets, to document nocturnal and diurnal glycemic excursions as well as their relationships.Veterinary and animal science · 2026Review
- Accuracy of Dexcom G6 Pro and G7 Continuous Glucose Monitors in Patients Treated with Maintenance Dialysis.Diabetes technology & therapeutics · 2026Article
- Continuous glucose monitoring (CGM) systems in Poland, Europe, and beyond in 2025: principles, available technologies, and future perspectives.Archives of medical science : AMS · 2026Article
- Dermal Glucose Sensing has a Shorter Time Lag Relative to Blood Glucose: Implications for Hypoglycemia Detection and Time in Range.Journal of diabetes science and technology · 2025Article
- Characterizing glucose in labor: Continuous glucose monitoring in parturients without diabetes.Pregnancy (Hoboken, N.J.) · 2025Article
- Differential Absorbance and PPG-Based Non-Invasive Blood Glucose Measurement Using Spatiotemporal Multimodal Fused LSTM Model.Sensors (Basel, Switzerland) · 2025Article
- Diabetes Mellitus in Pregnancy: Implications for Obstetric Anesthesia.Anesthesiology · 2025Review
- Article
- A low-power approach to optical glucose sensing via polarisation switching.Scientific reports · 2025Article
- Calibration and performance of a Raman-based device for non-invasive glucose monitoring in type 2 diabetes.Scientific reports · 2025Article
- Assessing Dynamic Cognitive Function in the Daily Lives of Youths With and Without Type 1 Diabetes: Usability Study.JMIR formative research · 2025Article
- Subcutaneous depth-selective spectral imaging with mμSORS enables noninvasive glucose monitoring.Nature metabolism · 2025Article
- Clinical performance evaluation of the SiJoy GS1 continuous glucose monitor during oral glucose tolerance testing in healthy adults.Frontiers in endocrinology · 2025Article
- Breaking through lag: enhancing intradermal electro-osmotic flow and the future of delay-free continuous glucose monitoring.Frontiers in bioengineering and biotechnology · 2025Article
- Expanding the horizon of continuous glucose monitoring into the future of pediatric medicine.Pediatric research · 2024Review
11 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundContinuous 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.
methodsCGM 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.
resultsOverall 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.
conclusionsPrediction 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.