Diabetes Mellitus, Type 2NCT04269655
Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)
A study testing Cloud-Based Continuous Glucose Monitoring in people with Diabetes Mellitus, Type 2, run by Scripps Whittier Diabetes Institute at 1 site in United States.
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. Read more about this study
- Who is it for?
- Ages 18 to 100 years
- Conditions the study is for
- Diabetes Mellitus, Type 2
- What is being tested?
- Cloud-Based Continuous Glucose Monitoring
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 6 participants
- Where
- 1 siteUnited States
- Study dates
- 25 Feb 2020to 17 Mar 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- ≥ 18 years of age
- English or Spanish speaker
- ≥ one of the following: diagnosis of type 2 diabetes documented in the EMR, or use of anti-hyperglycemic agent documented in the EMR, or serum or POC glucose > 200 mg/dL in the first 24 hours of admission
Who cannot join
- Anticipated LOS < 24 hours
- Current or anticipated ICU placement
- Does not speak English or Spanish
- Known adhesive allergy
- Current participation in medication or device study
- Pregnant
- Any other condition that the PI Dr. Philis-Tsimikas or the attending physician deem contraindicated
Trial locations and contacts
1 site in 1 country.
United States1 site
Scripps Whittier Diabetes Institute
La Jolla, California, 92037
About this study
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.
Read the detailed 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.
- Conditions
- Diabetes Mellitus, Type 2
- Being tested
- Cloud-Based Continuous Glucose Monitoring
- Keywords
- Diabetes, Continuous Glucose Monitor, Blood Glucose, Cost-Effectiveness, Hospital, Diabetes Management, Technology, Remote Monitoring, Digital Dashboard, Cloud-Based, Hypoglycemia, Hyperglycemia, Real-Time, Clinical Decision-Making, Wireless Transmission
- Medical subject headings
- Diabetes Mellitus, Type 2, Diabetes Mellitus, Hypoglycemia, Hyperglycemia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Cloud-Based Continuous Glucose MonitoringDevice
The CGM data will be transmitted via bluetooth to a smartphone. The smartphone will automatically transmit values to a secure cloud-based platform, which then populates to the: (1) web-based, CGM data management tool for evaluation purposes (both groups), and (2) Digital Dashboard for monitoring and intervention (intervention only).
| Study group | Role | What they receive |
|---|---|---|
| Intervention CB CGM | Experimental | On CB CGM patients, CGM data will also be transmitted from the bedside smartphone to the Digital Dashboard. The Digital Dashboard will integrate CGM data for CB CGM's participants for presentation via two views: (1) Real-Time Management and (2) Clinical Optimization. Telemetry technicians to conduct site-based monitoring, and the Diabetes APN will conduct remote management of patients at the site from a central, Scripps Diabetes Hub, per below. (Note, as CGMs are not FDA-approved for in-hospital glucose management, CB CGM participants will also have their glucose monitored via the hospital's standard POC testing protocol described for UC). Receives: Device: Cloud-Based Continuous Glucose Monitoring |
| Usual Care | No intervention | For UC, CGM data will be blinded to the care team and used for evaluation purposes only. Glucose will be monitored via the hospital's standard POC testing protocol (i.e., prior to meals and at bedtime for patients who are eating, and every 4-6 waking hours for patients who are not eating). Glucose management in UC is designed to minimize differences between groups, aside from CGM monitoring: UC (and intervention) participants' glucose levels will be managed using the glucose management protocol and the Diabetes APN will assess UC participants' POC data documented in the EMR from the previous 24-48 hours and make recommendations for changes to the basal/bolus regimen to improve glucose management. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Percentage time-in-range of interstitial glucose values
Percentage time-in-range (70-200 mg/dL) of interstitial glucose values
Measured: Through duration of index hospitalization, an average of 3 days
Percentage time in hypoglycemia of interstitial glucose values
Percentage time in hypoglycemia (<70 mg/dL) of interstitial glucose values
Measured: Through duration of index hospitalization, an average of 3 days
Percentage time in severe hyperglycemia of interstitial glucose values
Percentage time in severe hyperglycemia (>300 mg/dL) of interstitial glucose values
Measured: Through duration of index hospitalization, an average of 3 days
Secondary outcomes (4)
Infection rates
Infection rates in hospital
Measured: Through duration of index hospitalization, an average of 3 days
Length of stay (LOS)
Length of stay in hospital
Measured: Through duration of index hospitalization, an average of 3 days
Cost of hospitalization
Healthcare costs associated with stay in hospital
Measured: Through duration of index hospitalization, an average of 3 days
Hospital readmission rate
Readmission to hospital within 30-days post-discharge
Measured: 30 days from the discharge date of the index hospitalization
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Feb 2020
- Study start25 Feb 2020
- Primary completion17 Mar 2020
- Study completion17 Mar 2020
Why it stopped: COVID-19
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetes Mellitus, Type 2Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- This is a parallel groups, randomized controlled trial (RCT) utilizing a 4:1 (Intervention: UC) ratio. This design was selected to maximize the number of Scripps patients receiving the CB CGM intervention, while also ensuring an adequate and representative UC group for comparison purposes.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 6 participants (actual)
Sponsor and investigators
- Lead sponsor
- Scripps Whittier Diabetes Institute
- Sponsor type
- University, hospital or other
- Collaborators
- DexCom, Inc.
- Responsible party
- Principal investigator, Athena Philis-Tsimikas, Scripps Whittier Diabetes Institute
- Investigators
- Athena Philis-Tsimikas, MD, Principal investigator, Scripps Whittier Diabetes InstituteAddie Fortmann, PhD, Study director, Scripps Whittier Diabetes Institute
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04269655
- Sponsor's protocol ID
- 19-7468
- Status last verified
- May 2023
- First submitted
- 10 Feb 2020
- Last updated
- 17 May 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 May 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Scripps Digital Diabetes: Cloud-Based Continuous Glucose Monitoring (CB CGM)
- ClinicalTrials.gov ID
- NCT04269655
- Acronym / sponsor ID
- 19-7468
- Conditions
- Diabetes Mellitus, Type 2
- Keywords
- Diabetes, Continuous Glucose Monitor, Blood Glucose, Cost-Effectiveness, Hospital, Diabetes Management, Technology, Remote Monitoring
- Study type
- Interventional
- Recruitment status
- TerminatedReason stopped: COVID-19
- Enrolment
- 6 participants (actual)
- Lead sponsor
- Scripps Whittier Diabetes InstituteUniversity, hospital or other
- Collaborators
- DexCom, Inc.
- Study start
- 25 Feb 2020 (actual)
- Primary completion
- 17 Mar 2020 (actual)
- Study completion
- 17 Mar 2020 (actual)
- First posted
- 17 Feb 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- Model description
- This is a parallel groups, randomized controlled trial (RCT) utilizing a 4:1 (Intervention: UC) ratio. This design was selected to maximize the number of Scripps patients receiving the CB CGM intervention, while also ensuring an adequate and representative UC group for comparison purposes.
| Arm | Type | Receives |
|---|---|---|
| Intervention CB CGM | Experimental | Device: Cloud-Based Continuous Glucose MonitoringOn CB CGM patients, CGM data will also be transmitted from the bedside smartphone to the Digital Dashboard. The Digital Dashboard will integrate CGM data for CB CGM's participants for presentation via two views: (1) Real-Time Management and (2) Clinical Optimization. Telemetry technicians to conduct site-based monitoring, and the Diabetes APN will conduct remote management of patients at the site from a central, Scripps Diabetes Hub, per below. (Note, as CGMs are not FDA-approved for in-hospital glucose management, CB CGM participants will also have their glucose monitored via the hospital's standard POC testing protocol described for UC). |
| Usual Care | No intervention | –For UC, CGM data will be blinded to the care team and used for evaluation purposes only. Glucose will be monitored via the hospital's standard POC testing protocol (i.e., prior to meals and at bedtime for patients who are eating, and every 4-6 waking hours for patients who are not eating). Glucose management in UC is designed to minimize differences between groups, aside from CGM monitoring: UC (and intervention) participants' glucose levels will be managed using the glucose management protocol and the Diabetes APN will assess UC participants' POC data documented in the EMR from the previous 24-48 hours and make recommendations for changes to the basal/bolus regimen to improve glucose management. |
Who may qualify
- Ages
- 18 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- ≥ 18 years of age
- English or Spanish speaker
- ≥ one of the following: diagnosis of type 2 diabetes documented in the EMR, or use of anti-hyperglycemic agent documented in the EMR, or serum or POC glucose > 200 mg/dL in the first 24 hours of admission
Key exclusion criteria (7 listed)
- Anticipated LOS < 24 hours
- Current or anticipated ICU placement
- Does not speak English or Spanish
- Known adhesive allergy
- Current participation in medication or device study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Cloud-Based Continuous Glucose MonitoringThe CGM data will be transmitted via bluetooth to a smartphone. The smartphone will automatically transmit values to a secure cloud-based platform, which then populates to the: (1) web-based, CGM data management tool for evaluation purposes (both groups), and (2) Digital Dashboard for monitoring and intervention (intervention only). | Device | Intervention CB CGM |
Primary outcome
Percentage time-in-range of interstitial glucose values
Time frame: Through duration of index hospitalization, an average of 3 days
Percentage time-in-range (70-200 mg/dL) of interstitial glucose values
Percentage time in hypoglycemia of interstitial glucose values
Time frame: Through duration of index hospitalization, an average of 3 days
Percentage time in hypoglycemia (<70 mg/dL) of interstitial glucose values
Percentage time in severe hyperglycemia of interstitial glucose values
Time frame: Through duration of index hospitalization, an average of 3 days
Percentage time in severe hyperglycemia (>300 mg/dL) of interstitial glucose values
4 secondary outcomes
Infection rates
Time frame: Through duration of index hospitalization, an average of 3 days
Length of stay (LOS)
Time frame: Through duration of index hospitalization, an average of 3 days
Cost of hospitalization
Time frame: Through duration of index hospitalization, an average of 3 days
Hospital readmission rate
Time frame: 30 days from the discharge date of the index hospitalization
Results and safety
The study was stopped early (reason given: COVID-19). Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 May 2023.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Athena Philis-Tsimikas, MD principal investigator
Scripps Whittier Diabetes Institute
Addie Fortmann, PhD study director
Scripps Whittier Diabetes Institute
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Cloud-Based Continuous Glucose Monitoring in people with Diabetes Mellitus, Type 2, run by Scripps Whittier Diabetes Institute at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: stopped early, as of the sponsor's last update on 17 May 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study was stopped early (reason given: COVID-19). Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Percentage time-in-range of interstitial glucose values (time frame: Through duration of index hospitalization, an average of 3 days). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 May 2023.