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Feasibility of Real-Time Continuous Glucose Monitoring of Critical Care Patients with Diabetes
Learning outcome: Learn about the process of implementing a hybrid protocol for continuous glucose monitoring in the inpatient setting with the Dexcom CGM ecosystem. Discussion to include implementation plan, efficacy, benefits, and challenges.
Purpose: This study aims to evaluate the feasibility of CGM in patients with hyperglycemia or diabetes mellitus in the critical care setting. We investigate the efficacy [NS1] of CGM technology in the management of glucose levels and explore whether CGM can be used in a hybrid protocol with point-of-care testing and as an accurate and safe alternative to current practice.
Background: Evidence shows there are adverse outcomes for hospitalized patients with poorly controlled diabetes, such as increased risk of infection, 90-day mortality, and other complications. To reduce potential harm to patients, glucose levels should be maintained between 140-180 mg/dl in the critical care setting. Continuous glucose monitoring (CGM) is an alternative to point-of-care testing (POCT) with finger sticks. Fingersticks are painful for the patient and expose nurses to blood-borne pathogens and other infectious diseases. Studies demonstrate a 33% reduction in POCT when CGM technology was used to guide monitoring, reduction of hypoglycemic events with predictive alerts, and improved patient outcomes. However, more research is needed in the critical care environment.
Methods: Over a one-year period ending April 1, 2024, eligible patients were enrolled to receive CGM alongside standard POCT during their stay in a 22-bed combined critical care unit within a 455-bed tertiary care hospital in New York. Clinical care will not be determined by the CGM data. Data will be abstracted and analyzed from the enrolled patients to evaluate the efficacy of the values based on mean absolute relative difference (MARD). POCT glucose will be used as the standard reference. In addition to POCT and CGM data, we will collect data on demographics, diabetes type, comorbidities, body mass index, medication use, and medical history. Univariate associations between variables will be measured using Wilcoxon rank-sum and Spearman rank correlation. A 2-sided significance level of 0.05 will be used for all the statistical tests.
Results: This is an ongoing study. Data analysis will begin at the closure of enrollment.
Implications for clinical practice: There are benefits and challenges to the implementation of CGM in the critical care environment. Similar studies have confirmed accuracy in critically ill patients. Essential components of a standardized workflow for implementation have been identified, and the nursing staff and providers have supported this technology as an alternative to point-of-care testing. Automatic integration into electronic medical records and financial cost analysis would be beneficial towards a more comprehensive argument for feasibility.
Learning Objective
After completing this learning activity, the participant will be able to assess innovations being used by other professionals in the specialty and evaluate the potential of implementing the improvements into practice.
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