Clinical Trial Details
— Status: Terminated
Administrative data
| NCT number |
NCT04269655 |
| Other study ID # |
19-7468 |
| Secondary ID |
|
| Status |
Terminated |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
February 25, 2020 |
| Est. completion date |
March 17, 2020 |
Study information
| Verified date |
May 2023 |
| Source |
Scripps Whittier Diabetes Institute |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Individuals with diabetes in the hospital often experience poor glycemic control, which
places them at greater risk for infection, neurological and cardiac complications, mortality,
longer lengths of stay, readmissions, and higher healthcare costs. There are few effective
interventions for monitoring hospital glucose management therefore the long-term goal of
developing Cloud-Based Real-Time Glucose Evaluation and Management System is to provide an
effective, real-time continuous glucose monitoring solution necessary for clinical
decision-making which can be easily managed for clinical risk 24 hrs/day. The innovative
intervention will enable hospital care teams to take immediate steps based on 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 randomized
controlled trial is defined as a Phase III/IV definitive clinical trial to establish efficacy
and effectiveness of this intervention. Aim 1 will assess mean differences of % time in range
between intervention and Usual Care groups to find occurrence of glucose levels that are in
range at 70-200mg/dL. Aim 2 will apply the same method, using % time above range of >300mg/dL
(severe hyperglycemia) and % time below range <70mg/dL (hypoglycemia). Poor glycemic control
in the hospital is common and given the known consequences of uncontrolled blood sugars
during a hospitalization, health systems devote significant resources to developing protocols
for improving glucometrics. The likely impact of this innovative research is to have an
efficient, and seamless alternative for continually monitoring glucose levels in the
hospital. The Digital Dashboard facilitates real-time, remote monitoring of a large volume of
patients simultaneously; automatically identifies and prioritizes patients for intervention;
and will detect any and all potentially dangerous hypoglycemic episodes. The work proposed
pushes the limits of these challenges by providing evidence, identified by a team-based
approach to glucose management in an underserved and understudied population supplementing
prior data designed to improve outcomes among high-risk patients with type 2 diabetes (T2D)
and related cardio metabolic conditions. The proposed intervention is flexible, sustainable,
and has high dissemination potential.
Description:
This research study is designed to address these gaps by directly comparing the values of
non-blinded, real-time and remotely monitored CGM data versus standard POC testing for
hospital-based glucose management. Specifically, the investigators will investigate
Cloud-Based Continuous Glucose Monitoring (CB CGM) versus standard POC testing (Usual Care;
UC) in increasing % time-in-range (70-200 mg/dL), and in decreasing % time in hypoglycemia
(<70 mg/dL) and severe hyperglycemia (>300 mg/dL) among N=300 adults with T2D. Patients will
be enrolled at Scripps Mercy Hospital San Diego, Definitive Observation Unit (DOU) located in
Hillcrest. This hospital serves predominantly low income, underinsured, ethnic/racial
minority population in San Diego, California (CA). Participants will be randomized either to
intervention or UC using a 4:1 ratio.
All participants will have a CGM inserted upon enrollment. For the UC group, CGM data will be
blinded and used for evaluation only; glucose will be monitored via the hospital's standard
point-of-care (POC) testing protocol. For the intervention group, CGM data will be
non-blinded and transmitted to a HIPAA-compliant Digital Dashboard, which filters and
prioritizes patients by clinical risk (algorithm-based) using real-time CGM data.
The Digital Dashboard will be monitored 24-hours/day by site-based telemetry teams for hyper-
and hypoglycemic episodes that need rapid management per protocol. A centrally-located,
Diabetes Advanced Practice Nurse (APN) will also remotely monitor glucose trends on the
Digital Dashboard and recommend daily insulin adjustments to optimize the therapeutic
regimen. Electronic medical records (EMR) will be used to identify eligible patients, and to
compare exploratory outcomes (infection rate, LOS, healthcare costs, readmissions) between
intervention and usual care.
Aim 1: To evaluate the effectiveness of CB CGM versus UC in increasing % time-in-range
(70-200 mg/dL).
Aim 2: To evaluate the effectiveness of CB CGM versus UC in decreasing % time in hypoglycemia
(<70 mg/dL) and severe hyperglycemia (>300 mg/dL).
Aim 3: To document the differences between CB CGM and UC in outcomes commonly affected by
glycemic control in the hospital (infection rates, LOS, cost, 30-day hospital readmissions).
Process Aim: To evaluate feasibility, acceptability, sustainability, and scaling potential of
CB CGM from patient, nursing, and physician perspectives.
