Back to Search Start Over

System Accuracy Assessment of a Combined Invasive and Noninvasive Glucometer.

Authors :
Pfützner A
Demircik F
Pfützner J
Kessler K
Strobl S
Spatz J
Pfützner AH
Lier A
Source :
Journal of diabetes science and technology [J Diabetes Sci Technol] 2020 May; Vol. 14 (3), pp. 575-581. Date of Electronic Publication: 2019 Oct 22.
Publication Year :
2020

Abstract

Background: The pain associated with pricking the fingertip for blood glucose self-testing is considered to be a major burden in diabetes treatment. This study was performed to evaluate the system accuracy of the invasive TensorTip Combo Glucometer (CoG) device component in accordance with ISO15197:2015 requirements and to explore the accuracy of the noninvasive tissue glucose prediction component.<br />Methods: One hundred samples were obtained from people with type 1 and type 2 diabetes and healthy volunteers (43 females, 57 males; age: 53 ± 16 years), with glucose distribution as requested by the ISO standard. Three strip lots were tested twice by healthcare professionals in comparison to YSI 2300 Stat Plus reference method followed by a noninvasive tissue glucose reading (NI-CoG). Mean Absolute (Relative) Difference (MARD) was calculated and a consensus error grid (CEG) analysis was performed.<br />Results: The ISO system accuracy criteria were met with the invasive strip technology by 586/600 of the data points (97.1%) and for each strip lot separately. All invasive results (100%) were within CEG-zone A and total MARD was calculated to be 7.1%. With the noninvasive reading, 99% of raw data points were in A + B (91.1% and 7.8%), and the total MARD was calculated to be 18.1%.<br />Discussion: The invasive component of the CoG device was shown to be in full compliance with the current ISO15197 criteria. Good results were also obtained with the NI-CoG tissue glucose prediction. This noninvasive technology would potentially be suitable for frequent pain-free glucose monitoring in many people with diabetes.

Details

Language :
English
ISSN :
1932-2968
Volume :
14
Issue :
3
Database :
MEDLINE
Journal :
Journal of diabetes science and technology
Publication Type :
Academic Journal
Accession number :
31640424
Full Text :
https://doi.org/10.1177/1932296819883306