Literature DB >> 31477942

Accuracy of Glucose Meter among Adults in a Semi-urban Area in Kathmandu, Nepal.

Asmita Pokhrel1, Vinutha Silvanus2, Buddhi Raj Pokhrel3, Binaya Baral1, Madhav Khanal1, Prajwal Gyawali4, Laxman Pokhrel1, Deepak Regmi5.   

Abstract

INTRODUCTION: Glucose meters are gaining popularity in monitoring of blood glucose at household levels and in health care set-ups due to their portability, affordability and convenience of use over the laboratory based reference methods. Still they are not free of limitations. Operator's technique, extreme temperatures, humidity, patients' medication, hematocrit values can affect the reliability of glucose meter results. Hence, the accuracy of glucose meter has been the topic of concern since years. Therefore, present study aims to evaluate the analytical and clinical accuracy of glucose meter using International Organization for Standardization 15197 guideline.
METHODS: A community based descriptive cross-sectional study was conducted in Kapan, Kathmandu, Nepal in April 2018. Glucose levels were measured using glucose meter and reference laboratory method simultaneously among 203 adults ≥20 years, after an overnight fasting and two hours of ingestion of 75 grams glucose. Modified Bland-Altman plots were created by incorporating ISO 15197 guidelines to check the analytical accuracy and Park error grid was used to evaluate the clinical accuracy of the device.
RESULTS: Modified Bland-Altman plots showed>95% of the test results were beyond the acceptable analytical criteria of ISO 15197:2003 and 2013. Park Error Grid-Analysis showed 99% of the data within zones A and B of the consensus error grid.
CONCLUSIONS: Glucose meter readings were within clinically acceptable parameters despite discrepancies on analytical merit. Possible sources of interferences must be avoided during the measurement to minimize the disparities and the values should be interpreted with caution.

Entities:  

Keywords:  accuracy; analytical; Bland-Altman plots; clinical; glucose meter; Park error grid.

Mesh:

Substances:

Year:  2019        PMID: 31477942      PMCID: PMC8827580     

Source DB:  PubMed          Journal:  JNMA J Nepal Med Assoc        ISSN: 0028-2715            Impact factor:   0.406


  23 in total

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Authors:  Lutz Heinemann; Volker Lodwig; Guido Freckmann
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4.  System accuracy evaluation of 43 blood glucose monitoring systems for self-monitoring of blood glucose according to DIN EN ISO 15197.

Authors:  Guido Freckmann; Christina Schmid; Annette Baumstark; Stefan Pleus; Manuela Link; Cornelia Haug
Journal:  J Diabetes Sci Technol       Date:  2012-09-01

5.  Executive summary: guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus.

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Journal:  Clin Chem       Date:  2011-05-26       Impact factor: 8.327

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Journal:  Clin Chem       Date:  1989-02       Impact factor: 8.327

7.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

8.  How Should Blood Glucose Meter System Analytical Performance Be Assessed?

Authors:  David A Simmons
Journal:  J Diabetes Sci Technol       Date:  2015-08-31

9.  Investigation of the Accuracy of 18 Marketed Blood Glucose Monitors.

Authors:  David C Klonoff; Joan Lee Parkes; Boris P Kovatchev; David Kerr; Wendy C Bevier; Ronald L Brazg; Mark Christiansen; Timothy S Bailey; James H Nichols; Michael A Kohn
Journal:  Diabetes Care       Date:  2018-06-13       Impact factor: 19.112

10.  Assessment of analytical performance of glucose meter in pediatric age group at tertiary care referral hospital.

Authors:  Mohit Vijay Rojekar; Vandana Kumawat; Jayesh Panot; Surekha Khedkar; Arati Adhe-Rojekar
Journal:  J Diabetes Metab Disord       Date:  2017-09-13
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