Trial reportJournal of diabetes science and technology2018
Evaluation of a New Noninvasive Glucose Monitoring Device by Means of Standardized Meal Experiments.
Trial report in Journal of diabetes science and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review.Annals of medicine and surgery (2012) · 2024Review
- Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.Diabetes care · 2023Review
- Noninvasive Glucose Sensing In Vivo.Sensors (Basel, Switzerland) · 2023Review
- Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus.Clinical chemistry · 2023Article
- Patent analysis of digital sensors for continuous glucose monitoring.Frontiers in public health · 2023Review
- Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies.Journal of diabetes science and technology · 2022Review
- Is Raman the best strategy towards the development of non-invasive continuous glucose monitoring devices for diabetes management?Frontiers in chemistry · 2022Review
- A Review of Non-Invasive Optical Systems for Continuous Blood Glucose Monitoring.Sensors (Basel, Switzerland) · 2021Review
- Dual-Retarder Mueller Polarimetry System for Extraction of Optical Properties of Serum Albumin Protein Media.Sensors (Basel, Switzerland) · 2021Article
- System Accuracy Assessment of a Combined Invasive and Noninvasive Glucometer.Journal of diabetes science and technology · 2020Article
- Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone.Sensors (Basel, Switzerland) · 2020Review
- New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms.Journal of diabetes science and technology · 2019Article
- The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors.Sensors (Basel, Switzerland) · 2019Review
- Improving patient self-care using diabetes technologies.Therapeutic advances in endocrinology and metabolism · 2019Review
- Noninvasive Monitoring of Blood Glucose Using Color-Coded Photoplethysmographic Images of the Illuminated Fingertip Within the Visible and Near-Infrared Range: Opportunities and Questions.Journal of diabetes science and technology · 2018Article
- Device and Method for Noninvasive Glucose Assessment.Journal of diabetes science and technology · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFrequent blood glucose readings are the most cumbersome aspect of diabetes treatment for many patients. The noninvasive TensorTip Combo Glucometer (CoG) component employs dedicated mathematical algorithms to analyze the collected signal and to predict tissue glucose at the fingertip. This study presents the performance of the CoG (the invasive and the noninvasive components) during a standardized meal experiment.
methodsEach of the 36 participants (18 females and males each, age: 49 ± 18 years, 14 healthy subjects, 6 type 1 and 16 type 2 patients) received a device for conducting calibration at home. Thereafter, they ingested a standardized meal. Blood glucose was assessed from capillary blood samples by means of the (non)invasive device, YSI Stat 2300 plus, Contour Next at time points -30, 0, 15, 30, 45, 60, 75, 90, 120, 150, and 180 minutes. Statistical analysis was performed by consensus error grid (CEG) and calculation of mean absolute relative difference (MARD) in comparison to YSI.
resultsFor the noninvasive (NI) CoG technology, 100% of the data pairs were found in CEG zones A (96.6%) and B (3.4%); 100% were seen in zone A for the invasive component and Contour Next. MARD was calculated to be 4.2% for Contour Next, 9.2% for the invasive component, and 14.4% for the NI component.
conclusionsAfter appropriate individual calibration of the NI technology, both the NI and the invasive CoG components reliably tracked tissue and blood glucose values, respectively. This may enable patients with diabetes to monitor their glucose levels frequently, reliably, and most of all pain-free.
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