Continuous Glucose Monitoring in Critically Ill Patients With COVID-19: Results of an Emergent Pilot Study

Abstract

Background: Amidst the coronavirus disease 2019 (COVID-19) pandemic, continuous glucose monitoring (CGM) has emerged as an alternative for inpatient point-of-care blood glucose (POC-BG) monitoring. We performed a feasibility pilot study using CGM in critically ill patients with COVID-19 in the intensive care unit (ICU).

Methods: Single-center, retrospective study of glucose monitoring in critically ill patients with COVID-19 on insulin therapy using Medtronic Guardian Connect and Dexcom G6 CGM systems. Primary outcomes were feasibility and accuracy for trending POC-BG. Secondary outcomes included reliability and nurse acceptance. Sensor glucose (SG) was used for trends between POC-BG with nursing guidance to reduce POC-BG frequency from one to two hours to four hours when the SG was in the target range. Mean absolute relative difference (MARD), Clarke error grids analysis (EGA), and Bland-Altman (B&A) plots were calculated for accuracy of paired SG and POC-BG measurements.

Results: CGM devices were placed on 11 patients: Medtronic (n = 6) and Dexcom G6 (n = 5). Both systems were feasible and reliable with good nurse acceptance. To determine accuracy, 437 paired SG and POC-BG readings were analyzed. For Medtronic, the MARD was 13.1% with 100% of readings in zones A and B on Clarke EGA. For Dexcom, MARD was 11.1% with 98% of readings in zones A and B. B&A plots had a mean bias of -17.76 mg/dL (Medtronic) and -1.94 mg/dL (Dexcom), with wide 95% limits of agreement.

Conclusions: During the COVID-19 pandemic, CGM is feasible in critically ill patients and has acceptable accuracy to identify trends and guide intermittent blood glucose monitoring with insulin therapy.

Keywords: COVID-19; continuous glucose monitoring; critically ill; hospital; inpatient; intensive care unit.

Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.

Real-time sensor data displayed outside the patient room. Upper left: Dexcom G6 on an iPhone. Upper right: Medtronic Guardian Connect on iPad. Bottom: Medtronic display of blood glucose (red teardrops) superimposed on sensor glucose (blue line graph). Reproduced from Sadhu.

Figure 2.

Examples of a patient on each of the continuous glucose monitoring (CGM) systems with paired sensor glucose and blood glucose measurements graphed over time to demonstrate superimposed trending.

Figure 3.

Clarke error grid analysis—Medtronic.

Figure 4.

Clarke error grid—Dexcom.

Figure 5.

Bland-Altman plot—Medtronic.

Figure 6.

Bland-Altman plot—Dexcom.