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Diabetes care
07, 2021;44 (7): 1641-1646.

Accuracy of Dexcom G6 Continuous Glucose Monitoring in Non-Critically Ill Hospitalized Patients With Diabetes.

Georgia M Davis, Elias K Spanakis, Alexandra L Migdal, Lakshmi G Singh, Bonnie Albury, Maria Agustina Urrutia, K Walkiria Zamudio-Coronado, William H Scott, Rebecca Doerfler, Sergio Lizama, Medha Satyarengga, Kashif Munir, Rodolfo J Galindo, Priyathama Vellanki, Saumeth Cardona, Francisco J Pasquel, Limin Peng, Guillermo E Umpierrez
Author Information
  1. Georgia M Davis: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  2. Elias K Spanakis: Division of Endocrinology, Baltimore Veterans Affairs Medical Center, Baltimore, MD. ORCID
  3. Alexandra L Migdal: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  4. Lakshmi G Singh: Division of Endocrinology, Baltimore Veterans Affairs Medical Center, Baltimore, MD.
  5. Bonnie Albury: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  6. Maria Agustina Urrutia: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  7. K Walkiria Zamudio-Coronado: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  8. William H Scott: Division of Endocrinology, Baltimore Veterans Affairs Medical Center, Baltimore, MD.
  9. Rebecca Doerfler: Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD.
  10. Sergio Lizama: Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD.
  11. Medha Satyarengga: Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD.
  12. Kashif Munir: Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD.
  13. Rodolfo J Galindo: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA. ORCID
  14. Priyathama Vellanki: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  15. Saumeth Cardona: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA.
  16. Francisco J Pasquel: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA. ORCID
  17. Limin Peng: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA.
  18. Guillermo E Umpierrez: Division of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA geumpie@emory.edu. ORCID
PMID: 34099515 DOI: 10.2337/dc20-2856

Abstract

OBJECTIVE: Advances in continuous glucose monitoring (CGM) have transformed ambulatory diabetes management. Until recently, inpatient use of CGM has remained investigational, with limited data on its accuracy in the hospital setting.
RESEARCH DESIGN AND METHODS: To analyze the accuracy of Dexcom G6, we compared retrospective matched-pair CGM and capillary point-of-care (POC) glucose data from three inpatient CGM studies (two interventional and one observational) in general medicine and surgery patients with diabetes treated with insulin. Analysis of accuracy metrics included mean absolute relative difference (MARD), median absolute relative difference (ARD), and proportion of CGM values within 15, 20, and 30% or 15, 20, and 30 mg/dL of POC reference values for blood glucose >100 mg/dL or ≤100 mg/dL, respectively (% 15/15, % 20/20, % 30/30). Clinical reliability was assessed with Clarke error grid (CEG) analyses.
RESULTS: A total of 218 patients were included (96% with type 2 diabetes) with a mean age of 60.6 ± 12 years. The overall MARD ( = 4,067 matched glucose pairs) was 12.8%, and median ARD was 10.1% (interquartile range 4.6, 17.6]. The proportions of readings meeting % 15/15, % 20/20, and % 30/30 criteria were 68.7, 81.7, and 93.8%, respectively. CEG analysis showed 98.7% of all values in zones A and B. MARD and median ARD were higher in the case of hypoglycemia (<70 mg/dL) and severe anemia (hemoglobin <7 g/dL).
CONCLUSIONS: Our results indicate that CGM technology is a reliable tool for hospital use and may help improve glucose monitoring in non-critically ill hospitalized patients with diabetes.

Associated Data

figshare | 10.2337/figshare.14454357

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Grants

  1. K23 GM128221/NIGMS NIH HHS
  2. P30 DK111024/NIDDK NIH HHS
  3. K23 DK113241/NIDDK NIH HHS
  4. I01 CX001825/CSRD VA
  5. K23 DK123384/NIDDK NIH HHS
  6. UL1 TR002378/NCATS NIH HHS
  7. K23 DK122199/NIDDK NIH HHS

MeSH Term

Aged
Blood Glucose
Blood Glucose Self-Monitoring
Diabetes Mellitus, Type 1
Diabetes Mellitus, Type 2
Humans
Middle Aged
Reproducibility of Results
Retrospective Studies

Chemicals

Blood Glucose
Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.
Article has an altmetric score of 7

Word Cloud

Created with Highcharts 10.0.0CGM%glucosediabetesmg/dLaccuracypatientsMARDmedianARDvaluesmonitoringinpatientusedatahospitalDexcomG6POCincludedmeanabsoluterelativedifference1520respectively15/1520/2030/30CEG61248%7OBJECTIVE:AdvancescontinuoustransformedambulatorymanagementrecentlyremainedinvestigationallimitedsettingRESEARCHDESIGNANDMETHODS:analyzecomparedretrospectivematched-paircapillarypoint-of-carethreestudiestwointerventionaloneobservationalgeneralmedicinesurgerytreatedinsulinAnalysismetricsproportionwithin30%30referenceblood>100≤100ClinicalreliabilityassessedClarkeerrorgridanalysesRESULTS:total21896%type2age60±yearsoverall=067matchedpairs101%interquartilerange176]proportionsreadingsmeetingcriteria688193analysisshowed987%zonesBhighercasehypoglycemia<70severeanemiahemoglobin<7g/dLCONCLUSIONS:resultsindicatetechnologyreliabletoolmayhelpimprovenon-criticallyillhospitalizedAccuracyContinuousGlucoseMonitoringNon-CriticallyIllHospitalizedPatientsDiabetes

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