Real-world Accuracy of CGM in Inpatient Critical and Noncritical Care Settings at a Safety-Net Hospital.

Erin Finn, Lindsay Schlichting, Laura Grau, Ivor S Douglas, Rocio I Pereira
Author Information
  1. Erin Finn: Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Colorado, Aurora, CO.
  2. Lindsay Schlichting: Medicine Service, Denver Health and Hospital Authority, Denver, CO.
  3. Laura Grau: Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado, Aurora, CO.
  4. Ivor S Douglas: Medicine Service, Denver Health and Hospital Authority, Denver, CO.
  5. Rocio I Pereira: Division of Endocrinology, Metabolism, and Diabetes, Department of Medicine, University of Colorado, Aurora, CO. ORCID

Abstract

OBJECTIVE: We sought to determine real-world accuracy of inpatient continuous glucose monitoring (CGM) at multiple levels of acuity in a large safety-net hospital.
RESEARCH DESIGN AND METHODS: We analyzed records from hospitalized patients on Dexcom G6 CGM, including clinical, point of care (POC), and laboratory (Lab) glucose, and CGM data. POC/Lab values were matched to the closest timed CGM value. Encounters were divided into not critically ill (NCI) versus critically ill (CI). CGM accuracy was evaluated.
RESULTS: Paired readings (2,744 POC-CGM; 3,705 Lab-CGM) were analyzed for 233 patients with 239 encounters (83 NCI, 156 CI). POC-CGM aggregated and average mean absolute relative differences (MARD) were 15.1% and 17.1%. Lab-CGM aggregated and average MARDs were 11.4% and 12.2%. Accuracy for POC-CGM and Lab-CGM was 96.5% and 99.1% in Clarke Error Grid zones A/B.
CONCLUSIONS: Real-world accuracy of inpatient CGM is acceptable for NCI and CI patients. Further exploration of conditions associated with lower CGM accuracy in real-world settings is warranted.

References

  1. Diabetes Care. 2021 Mar;44(3):847-849 [PMID: 33361145]
  2. Diabetes Care. 2009 Jun;32(6):1119-31 [PMID: 19429873]
  3. Diabetes Care. 2021 Jul;44(7):1641-1646 [PMID: 34099515]
  4. Diabetes Care. 2023 Apr 1;46(4):864-867 [PMID: 36809308]
  5. Endocr Pract. 2023 Mar;29(3):155-161 [PMID: 36566985]
  6. Diabetes Technol Ther. 2005 Oct;7(5):776-9 [PMID: 16241881]
  7. J Clin Endocrinol Metab. 2022 Jul 14;107(8):2101-2128 [PMID: 35690958]
  8. J Clin Monit Comput. 2018 Oct;32(5):953-964 [PMID: 29218549]
  9. Curr Opin Endocrinol Diabetes Obes. 2022 Feb 1;29(1):1-9 [PMID: 34845159]
  10. Diabetes Care. 2022 Oct 1;45(10):2369-2375 [PMID: 35984478]
  11. J Clin Endocrinol Metab. 2022 Jul 14;107(8):2139-2147 [PMID: 35690929]
  12. J Clin Endocrinol Metab. 2021 Sep 27;106(10):e4007-e4016 [PMID: 34100545]
  13. Diabetes Care. 2022 Jan 1;45(Suppl 1):S244-S253 [PMID: 34964884]
  14. J Diabetes Sci Technol. 2022 Sep;16(5):1136-1143 [PMID: 33971753]
  15. Psychol Methods. 2020 Jun;25(3):292-320 [PMID: 32191105]
  16. Diabetes Care. 2020 Nov;43(11):2736-2743 [PMID: 32759361]
  17. Diabetes Care. 2020 Nov;43(11):2873-2877 [PMID: 32855160]
  18. J Diabetes Sci Technol. 2020 Nov;14(6):1065-1073 [PMID: 33063556]

Grants

  1. R01 DK130351/NIDDK NIH HHS

MeSH Term

Humans
Blood Glucose Self-Monitoring
Blood Glucose
Inpatients
Safety-net Providers
Reproducibility of Results
Critical Illness

Chemicals

Blood Glucose

Word Cloud

Created with Highcharts 10.0.0CGMaccuracypatientsNCICIPOC-CGMLab-CGM1%real-worldinpatientglucoseanalyzedcriticallyillaggregatedaverageAccuracyReal-worldOBJECTIVE:soughtdeterminecontinuousmonitoringmultiplelevelsacuitylargesafety-nethospitalRESEARCHDESIGNANDMETHODS:recordshospitalizedDexcomG6includingclinicalpointcarePOClaboratoryLabdataPOC/LabvaluesmatchedclosesttimedvalueEncountersdividedversusevaluatedRESULTS:Pairedreadings27443705233239encounters83156meanabsoluterelativedifferencesMARD1517MARDs114%122%965%99ClarkeErrorGridzonesA/BCONCLUSIONS:acceptableexplorationconditionsassociatedlowersettingswarrantedInpatientCriticalNoncriticalCareSettingsSafety-NetHospital

Similar Articles

Cited By