Continuous Glucose Monitoring for High-Risk Type 2 Diabetes in the Hospital (Cyber GEMS)

Not Applicable

Recruiting

• Conditions: Type 2 Diabetes

• Registration Number: NCT05307237
• Lead Sponsor: Scripps Whittier Diabetes Institute

Brief Summary

Given the known serious consequences of uncontrolled blood sugars during hospitalization, this research plans to study an alternative seamlessly integrated continuous glucose monitoring (CGM) system in the hospital to test a dynamic and digitized, team-based approach to glucose management in an underserved and understudied, yet high-risk population. A digital dashboard will facilitate real-time, remote monitoring of a large volume of patients simultaneously; automatically identify and prioritize patients for intervention; and will detect any and all potentially dangerous hypoglycemic episodes in a hospital environment. The study will focus on clinical metrics of glucose control and infection that are in-line with patient priorities and US hospital quality initiatives.

Detailed Description

There is strong evidence that poor glycemic control in the hospital is common. Given the known consequences of uncontrolled blood sugars during a hospitalization (e.g., infection, serious neurological and cardiac complications, mortality, longer lengths of stay, readmissions, higher healthcare costs), health systems devote significant resources to developing protocols for improving glucometrics. Despite the widespread use and demonstrated effectiveness of continuous glucose monitoring (CGM) for ambulatory glucose management, CGMs is not routinely used in US hospitals. Therefore, the long-term goal to develop Cloud-Based Real-Time Glucose Evaluation and Management System (Cyber GEMS) is to provide an effective, real-time solution to augment existing processes, to provide a valuable test of real-world effectiveness, while capitalizing on standardized algorithms to facilitate sustainability and scalability to other systems and at-risk populations. The intervention will enable hospital care teams to take immediate steps based on the wireless transmission of glucose data from the Dexcom G6 device, sent to a digital dashboard, where integration with existing real-world hospital processes can provide immediate prioritization to prevent or correct impending hypoglycemia and severe hyperglycemic events. This study is a randomized controlled trial, defined as a Phase II/III definitive clinical trial that in turn establishes efficacy and effectiveness of this intervention. Aim 1 will establish the effectiveness of Cyber GEMS versus Usual Care (UC) in increasing the % time patients are in-range and decreasing % time in hypoglycemia and severe hyperglycemia during hospitalization. Aim 2 will evaluate the effectiveness of Cyber GEMS versus UC in decreasing hospital-acquired infection risk. A digital dashboard will facilitate real-time, wireless transmission of glucose data of a large volume of patients simultaneously; automatically identify and prioritize patients for intervention; and detect potentially dangerous hypoglycemic episodes - all at a reduced burden than current methods of stratification and review. The uninterrupted coverage, and efficient and remote diabetes specialist oversight in Cyber GEMS is a scalable, novel, team-based approach to maximize the use of continuously streaming CGM data for optimal glucose management.

Study Timeline

• Study First Submitted: 2021-11-11
• Study First Submitted QC: 2022-03-23
• Study First Posted: 2022-04-01
• Study Start: 2022-04-19
• Status Verified: 2025-06
• Last Update Submitted: 2025-06-02
• Last Update Posted: 2025-06-05
• Primary Completion: 2025-11-30
• Study Completion: 2025-11-30

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 554

Inclusion Criteria

• Documented previous or current Type 2 Diabetes (T2D) diagnosis as defined by either diagnosis in the chart or an HbA1c > or = to 6.5% in the last 90 days
• Either on subcutaneous (SQ) insulin orders, or greater than two serum or Point of Care (POC) glucose > or = 200 mg/dL in most recent 24 hours of admission

Exclusion Criteria

• Anticipated length of stay < 24 hours;
• Current or anticipated ICU placement;
• Does not speak English or Spanish;
• Known allergy to adhesives;
• Current participation in any medication or device research study;
• Pregnant;
• Any other condition that Multiple Principal Investigator (MPI) Philis-Tsimikas or the attending physician deems contraindicated

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Infection Rate	Immediately following intervention completion	Rates of hospital-acquired infection are defined as skin wound or surgical site, central line-associated bloodstream infection, urinary tract infection, bacteremia, clostridium difficile infection, or pneumonia not present at admission. Unadjusted incidence rates among study participants will be compared between intervention and control groups via Chi-Square test of two proportions.
Percent time in range	Immediately following intervention completion	Participants will have their percent time in range calculated following a minimum CGM data collection period of 12 hours and expressed as a percentage where: Percent Time in Range= 100 (Number readings in range (70-200mg/dL)/Total number of readings from CGM). Number of readings will be used in calculation, which scale directly with time.
Percent time spent in hypoglycemia and percent time in severe hyperglycemia	Immediately following intervention completion	Our second outcome will be assessed by the same methods as the first, but instead looking at Percent Time in Severe Hyperglycemic Range (\>300mg/dL) and Percent Time in Hypoglycemic Range (\<70mg/dL).

Secondary Outcome Measures

Name	Time	Method
Glucose Variability	Immediately following intervention completion	Using CGM data, glucose variability will be determined by first calculating the coefficient of variation for each participant, dividing the standard deviation of the glucose readings of that participant, by the mean of those readings and multiplying by 100 to get a percentage. Mean coefficients of variation will be compared between intervention and control groups by a students t test.
Electronic Medical Record (EMR) - Derived Outcomes: HbA1C	Immediately following intervention completion	Additional metrics of glycemic control will be captured for each study participant from the EMR including: HbA1C. Like primary outcome analyses, group mean differences of each variable will be assessed unadjusted with a students t-test utilized to detect between-group differences.
Electronic Medical Record (EMR) - Derived Outcome: fasting POC blood glucose	Immediately following intervention completion	Additional metrics of glycemic control will be captured for each study participant from the EMR including fasting point-of-care (POC) blood glucose measurements (mg/dL). Like primary outcome analyses, group mean differences of each variable will be assessed unadjusted with a students t-test utilized to detect between-group differences.

Trial Locations

Locations (1)

Scripps Mercy Hospital; 🇺🇸 Chula Vista, California, United States