Literature DB >> 28604064

Bolus Insulin Dose Error Distributions Based on Results From Two Clinical Trials Comparing Blood Glucose Monitoring Systems.

Scott Pardo1, Nancy Dunne1, David A Simmons1.   

Abstract

BACKGROUND: In 2 previous clinical trials, fingertip capillary blood samples were evaluated using prespecified blood glucose monitoring systems (BGMSs) and a reference YSI glucose analyzer. In post hoc analyses, hypothetical insulin doses were calculated using these blood glucose measurements; dosing errors were compared for each trial.
METHOD: For each blood glucose measurement, premeal bolus insulin dosing was determined for a hypothetical person, assuming a 60-g carbohydrate meal and 100-mg/dL target blood glucose level (adjusting 1/25 insulin sensitivity and 1/15 insulin:carbohydrate ratio inputs to account for BGMS measurement error). Dosing error was the difference between doses calculated using the BGMS and YSI results.
RESULTS: In Clinical Trial 1, 95% dose error ranges (in units of insulin) were: CONTOUR®NEXT EZ BGMS (EZ), -0.9 to 0.5; Accu-Chek® Aviva BGMS (ACA), -0.5 to 1.8; FreeStyle Freedom Lite® BGMS (FFL), -3.2 to -0.3; OneTouch® Ultra®2 BGMS (OTU2), -4.1 to 0.3; and Truetrack® BGMS (TT), -3.9 to 2.2. In Clinical Trial 2, these ranges were: CONTOUR®NEXT BGMS (CN), -0.7 to 1.7; Accu-Chek® Aviva Nano BGMS (ACAN), -1.3 to 1.8; FreeStyle Lite® BGMS (FSL), -5.1 to 0.2; OTU2, -1.9 to 1.2; OneTouch® Verio® Pro BGMS (OTVP), -1.0 to 1.9; and TT, -5.1 to 1.7. Within each trial, EZ and CN had statistically significantly smaller insulin dose error ranges than other BGMSs ( P <0.0001).
CONCLUSIONS: The ranges of insulin dose errors were statistically significantly smaller with EZ and CN than with all other BGMSs in this post hoc analysis. Differences in BGMS accuracy could result in clinically important differences in insulin dosing.

Entities:  

Keywords:  blood glucose monitoring; diabetes management; dosing errors; insulin; self-monitoring of blood glucose

Mesh:

Substances:

Year:  2017        PMID: 28604064      PMCID: PMC5950998          DOI: 10.1177/1932296817713025

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  13 in total

1.  Impact of blood glucose self-monitoring errors on glucose variability, risk for hypoglycemia, and average glucose control in type 1 diabetes: an in silico study.

Authors:  Marc D Breton; Boris P Kovatchev
Journal:  J Diabetes Sci Technol       Date:  2010-05-01

2.  Predicted blood glucose from insulin administration based on values from miscoded glucose meters.

Authors:  Charles H Raine; Scott Pardo; Joan Lee Parkes
Journal:  J Diabetes Sci Technol       Date:  2008-07

3.  Accuracy evaluation of five blood glucose monitoring systems: the North American comparator trial.

Authors:  Solveig Halldorsdottir; Mary Ellen Warchal-Windham; Jane F Wallace; Scott Pardo; Joan Lee Parkes; David A Simmons
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

4.  Accuracy evaluation of contour next compared with five blood glucose monitoring systems across a wide range of blood glucose concentrations occurring in a clinical research setting.

Authors:  Leslie J Klaff; Ronald Brazg; Kristen Hughes; Ann M Tideman; Holly C Schachner; Patricia Stenger; Scott Pardo; Nancy Dunne; Joan Lee Parkes
Journal:  Diabetes Technol Ther       Date:  2015-01       Impact factor: 6.118

5.  Importance of blood glucose meter and carbohydrate estimation accuracy.

Authors:  Naunihal S Virdi; John J Mahoney
Journal:  J Diabetes Sci Technol       Date:  2012-07-01

6.  Self-monitoring of blood glucose: practical aspects.

Authors:  Julienne K Kirk; Jane Stegner
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

7.  The impact of non-model-related variability on blood glucose prediction.

Authors:  Jonas Kildegaard; Jette Randløv; Jens Ulrik Poulsen; Ole K Hejlesen
Journal:  Diabetes Technol Ther       Date:  2007-08       Impact factor: 6.118

8.  Clinical implications and economic impact of accuracy differences among commercially available blood glucose monitoring systems.

Authors:  Erwin S Budiman; Navendu Samant; Ansgar Resch
Journal:  J Diabetes Sci Technol       Date:  2013-03-01

9.  Testing versus guessing blood glucose values: impact on self-care behaviors in type 2 diabetes.

Authors:  Jeremy Pettus; Patricia Stenger; Holly C Schachner; Nancy Dunne; Joan Lee Parkes; Scott Pardo; Steven V Edelman
Journal:  Curr Med Res Opin       Date:  2014-06-30       Impact factor: 2.580

Review 10.  Interferences and Limitations in Blood Glucose Self-Testing: An Overview of the Current Knowledge.

Authors:  Michael Erbach; Guido Freckmann; Rolf Hinzmann; Bernhard Kulzer; Ralph Ziegler; Lutz Heinemann; Oliver Schnell
Journal:  J Diabetes Sci Technol       Date:  2016-08-22
View more
  2 in total

1.  Laboratory Evaluation of Linearity, Repeatability, and Hematocrit Interference With an Internet-Enabled Blood Glucose Meter.

Authors:  Filiz Demircik; Valeria Kirsch; Sanja Ramljak; Mario Vogg; Anke H Pfützner; Andreas Pfützner
Journal:  J Diabetes Sci Technol       Date:  2019-04-11

2.  User Performance Evaluation of Four Blood Glucose Monitoring Systems Applying ISO 15197:2013 Accuracy Criteria and Calculation of Insulin Dosing Errors.

Authors:  Guido Freckmann; Nina Jendrike; Annette Baumstark; Stefan Pleus; Christina Liebing; Cornelia Haug
Journal:  Diabetes Ther       Date:  2018-03-03       Impact factor: 2.945

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.