Accuracy of the Dexcom G6 Continuous Glucose Monitoring System Following Cardiac Surgery

NCT ID: NCT04569240

Last Updated: 2025-11-10

Study Results

Results available

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Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

40 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-05-01

Study Completion Date

2024-07-01

Brief Summary

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This is a prospective longitudinal study to study the agreement between a novel continuous glucose monitoring system (CGMS) versus current blood glucose monitoring.

Subjects in this study will have their blood glucose measured regularly every 1-3 hours with current methods in the cardiovascular intensive care unit (CVICU), and by point of care glucose using the Accuchek Inform II on the regular floors, and the CGMS at the same time will be captured. Subjects will have measurements taken throughout their stay in the CVICU and on the regular floors.

Detailed Description

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Maintaining tight blood glucose control following surgery is imperative to reducing infections and neurologic dysfunction. This requires frequent blood sampling while in the intensive care unit, leading to increased waste of blood and utilizing time and resources to collect samples and wait for results. Additionally, when on the regular floors, frequent point of care fingersticks for glucose levels are needed for therapeutic intervention.

Continuous glucose monitoring systems (CGMS) are now available for ambulatory use in patients with diabetes. The potential of using such a system in the hospital, including during the postoperative critical care setting and upon transfer to the regular floor, may reduce personnel burden, produce rapid results, and decrease blood waste. However, these systems have not yet been validated for hospital use.

This is a prospective longitudinal study to study the agreement between a novel continuous glucose monitoring system (CGMS) versus current blood glucose monitoring.

Subjects in this study will have their blood glucose measured regularly every 1-3 hours with current methods in the CVICU, and by point of care glucose using the Accuchek Inform II on the regular floors, and the CGMS at the same time will be captured. Subjects will have measurements taken throughout their stay in the CVICU and on the regular floors. Agreement and correlation between systems will be calculated, and error will be classified using the Surveillance Error grid. The proportion of errors of at least moderate risk will be calculated.

Subject characteristics including demographics, comorbidities and baseline disease severity will be summarized using means and standard deviations for continuous measures and frequencies and percentages for categorical factors. To evaluate agreement between methods, concordance correlation coefficients will be calculated, using the method that adjusts for repeated measures as described by King and implemented in software by Carrasco. Analysis will be performed overall, and then stratifying by type of current measure, if the type of measurement varies across settings. Correlations will be calculated using the methods described by Bland and Altman and implemented by Bakdash and Marusich. Differences will also be evaluated for errors according to the Surveillance Error Grid. Rates of moderate or more severe errors will be calculated. For each measure above, 95% confidence intervals will be calculated, accounting for the clustering within subject.. Analyses will be performed using SAS software (version 9.4; Cary, NC) and R software (version 3.5; Vienna Austria).

Glucose readings obtained from the CGMS will be compared with

1. blood glucose from the arterial blood gas (ABG) or peripheral/central venous catheter if arterial catheter not in use (standard of care in CVICU) while patients are in the CVICU
2. fingerstick point of care (POC) glucose when patients are on the regular floors

Conditions

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Surgery--Complications

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

NONE

Study Groups

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Dexcom G6 continuous glucose monitor

All patients will have a Dexcom G6 continuous glucose monitor placed pre-operatively. The glucose readings will be collected for 10 days or upon discharge from the ICU and data will be compared with arterial blood glucose readings or venous Accu-Check Inform II glucose readings

Group Type OTHER

Dexcom G6 continuous glucose monitor

Intervention Type DEVICE

Dexcom G6 continuous glucose monitor will be applied to the upper outer arm before cardiovascular surgery. Data will be collected for 10 days or upon discharge from the ICU.

Interventions

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Dexcom G6 continuous glucose monitor

Dexcom G6 continuous glucose monitor will be applied to the upper outer arm before cardiovascular surgery. Data will be collected for 10 days or upon discharge from the ICU.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Age 18 years and above
* Planned cardiovascular surgery
* Planned admission to Cleveland Clinic Main Campus J5 or J6 or Q5 cardiovascular ICU (CVICU) post-operatively
* With or without known diabetes; if with known diagnosis of diabetes, diabetes can be type 1, type 2, or secondary

Exclusion Criteria

* Allergy to the material of the CGMS or the adhesive to be used
* Skin conditions precluding the use of the CGMS
* Pregnancy
* Other conditions that investigators deem inappropriate for the study
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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DexCom, Inc.

INDUSTRY

Sponsor Role collaborator

The Cleveland Clinic

OTHER

Sponsor Role lead

Responsible Party

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M. Cecilia Lansang, MD

Staff Physician, Director - Endocrinology Main Campus

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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M. Cecilia Lansang, MD, MPH

Role: PRINCIPAL_INVESTIGATOR

The Cleveland Clinic

Locations

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Cleveland Clinic

Cleveland, Ohio, United States

Site Status

Countries

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United States

References

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King TS, Chinchilli VM, Carrasco JL. A repeated measures concordance correlation coefficient. Stat Med. 2007 Jul 20;26(16):3095-113. doi: 10.1002/sim.2778.

Reference Type BACKGROUND
PMID: 17216594 (View on PubMed)

Carrasco JL, Phillips BR, Puig-Martinez J, King TS, Chinchilli VM. Estimation of the concordance correlation coefficient for repeated measures using SAS and R. Comput Methods Programs Biomed. 2013 Mar;109(3):293-304. doi: 10.1016/j.cmpb.2012.09.002. Epub 2012 Sep 29.

Reference Type BACKGROUND
PMID: 23031487 (View on PubMed)

Bland JM, Altman DG. Calculating correlation coefficients with repeated observations: Part 1--Correlation within subjects. BMJ. 1995 Feb 18;310(6977):446. doi: 10.1136/bmj.310.6977.446. No abstract available.

Reference Type BACKGROUND
PMID: 7873953 (View on PubMed)

Bakdash JZ, Marusich LR. Repeated Measures Correlation. Front Psychol. 2017 Apr 7;8:456. doi: 10.3389/fpsyg.2017.00456. eCollection 2017.

Reference Type BACKGROUND
PMID: 28439244 (View on PubMed)

Klonoff DC, Lias C, Vigersky R, Clarke W, Parkes JL, Sacks DB, Kirkman MS, Kovatchev B; Error Grid Panel. The surveillance error grid. J Diabetes Sci Technol. 2014 Jul;8(4):658-72. doi: 10.1177/1932296814539589. Epub 2014 Jun 13.

Reference Type BACKGROUND
PMID: 25562886 (View on PubMed)

Provided Documents

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Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

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20-698

Identifier Type: -

Identifier Source: org_study_id