Optimization of Glycemic Control in the Hospital and Critical Care Setting

Diabetes Mellitus Clinical Trial

Official title:

Development of a Comprehensive Clinical Decision Support System and Educational Tool to Support Optimization of Glycemic Control in the Hospital and Critical Care Setting

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04015388
• Other study ID #: 2013H0285
• Status: Completed
• Start date: August 19, 2014
• Est. completion date: February 4, 2021

Study information

• Verified date: February 2021
• Source: Ohio State University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Continuous Glucose Monitoring collected using the iPro device, to complete a large dataset consisting of routine electronic health records, biological, neurophysiological, physiological, and glycemic data. This dataset will eventually contribute to the further development and optimization of a comprehensive simulation, training, and clinical decision support system designed to contribute the optimization of glycemic control in the hospital and critical care setting.

Description:

Although recent advances in technology such as electronic medical records and continuous glucose monitoring provide enhanced monitoring capabilities, optimal glycemic control in the hospital and critical care setting is still extremely difficult to obtain. These technologies provide little to no identification of trends in data, and clinical decision support.

The goal of this research study was to collect data to support further development and optimization of a comprehensive clinical decision support system with simulation, training, and clinical decision support functionality. The system will also be designed to provide real-time performance measurement and feedback to ensure glycemic control is maintained at an optimal level.

The continuous glucose monitor (CGM) device utilized in this investigation was the iPro Recorder® (Medtronic Diabetes, Northridge, CA), a FDA approved monitoring device which reports glucose values every five minutes.

Subjects with a history of hyperglycemia or current hyperglycemia were identified either in the intensive care unit or prior to surgery. Upon enrollment of eligible patients in the study, CGM device was placed on subject's abdomen or thigh. The times logged by the CGM device were synchronized to achieve valid data pairing according to time. Subjects were visited as needed or at least twice in a 24-hour period to ensure that the devices were still in place and comfortable for the patient. After 72 hours of data collection, the CGM device was removed and the area of attachment cleaned.

Research staff collected medical history and standard of care glucose point of care obtained during subject's participation into the study. Other data from the patient's standard of care monitor, such as oxygen saturation levels, blood pressure, respiratory and heart rate, were collected as part of the patient's safety assessment assurance.

Data analysis will be completed offsite by investigators at Aptima, Inc. and their wholly owned subsidiary, Analytic Diabetic Systems, LLC. All patient data collected in this investigation was appropriately de-identified.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 127
• Est. completion date: February 4, 2021
• Est. primary completion date: August 2, 2016
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. Male or Female, = 18 years of age.

2. Subject able to provide written informed consent to participate in the study.

3. Female subject with a negative urine or serum pregnancy test, or not of childbearing potential, defined as surgically sterile due to bilateral tubal ligation, bilateral oophorectomy or hysterectomy; or are postmenopausal for at least 1 year.

4. Have a blood sugar value of >140 mg/dL or an glycosylated hemoglobin A1C (HbA1C) values >6.5% upon admission to the surgical Intensive Care Unit (ICU), medical ICU, or cardiovascular ICU, and have or not have been diagnosed with type 1 or type 2 diabetes.

Exclusion Criteria:

1. Subjects younger than 18 years old.

2. Subjects who are prisoners.

3. Subjects with known hypersensitivity to latex or tape.

4. Females who are pregnant or breastfeeding.

5. Subjects unable to provided informed consent.

6. Subjects unable to participate in the study for any reason in the opinion of the Principal Investigator.

7. Subjects enrolled in other research studies.

Related Conditions & MeSH terms

• Diabetes Mellitus
• Hyperglycemia

Intervention

Device:
• iPro Continuous Glucose Monitoring
iPro device is a continuous glucose monitoring (CGM) FDA approved device. This CGM device consists of a small recorder which reports glucose values every five minutes. This recorder is connected directly to a glucose sensor. The glucose-oxidase based sensor measures extracellular fluid in the subcutaneous tissue. The tiny and flexible sensors are typically inserted just beneath the skin, usually in the abdominal area, but can also be placed in the buttock, or anterior or lateral thigh.

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Ohio State University

References & Publications (10)

Cox DJ, Gonder-Frederick LA, Kovatchev BP, Julian DM, Clarke WL. Progressive hypoglycemia's impact on driving simulation performance. Occurrence, awareness and correction. Diabetes Care. 2000 Feb;23(2):163-70. — View Citation

Engoren M, Schwann TA, Habib RH. Elevated hemoglobin A1c is associated with readmission but not complications. Asian Cardiovasc Thorac Ann. 2014 Sep;22(7):800-6. doi: 10.1177/0218492313515895. Epub 2013 Dec 6. — View Citation

Giugliano D, Marfella R, Coppola L, Verrazzo G, Acampora R, Giunta R, Nappo F, Lucarelli C, D'Onofrio F. Vascular effects of acute hyperglycemia in humans are reversed by L-arginine. Evidence for reduced availability of nitric oxide during hyperglycemia. Circulation. 1997 Apr 1;95(7):1783-90. — View Citation

Ingels C, Debaveye Y, Milants I, Buelens E, Peeraer A, Devriendt Y, Vanhoutte T, Van Damme A, Schetz M, Wouters PJ, Van den Berghe G. Strict blood glucose control with insulin during intensive care after cardiac surgery: impact on 4-years survival, dependency on medical care, and quality-of-life. Eur Heart J. 2006 Nov;27(22):2716-24. Epub 2006 Apr 11. — View Citation

Inzucchi SE, Siegel MD. Glucose control in the ICU--how tight is too tight? N Engl J Med. 2009 Mar 26;360(13):1346-9. doi: 10.1056/NEJMe0901507. Epub 2009 Mar 24. — View Citation

Kanji S, Buffie J, Hutton B, Bunting PS, Singh A, McDonald K, Fergusson D, McIntyre LA, Hebert PC. Reliability of point-of-care testing for glucose measurement in critically ill adults. Crit Care Med. 2005 Dec;33(12):2778-85. — View Citation

Pappada SM, Borst MJ, Cameron BD, Bourey RE, Lather JD, Shipp D, Chiricolo A, Papadimos TJ. Development of a neural network model for predicting glucose levels in a surgical critical care setting. Patient Saf Surg. 2010 Sep 9;4(1):15. doi: 10.1186/1754-9493-4-15. — View Citation

Pappada SM, Cameron BD, Tulman DB, Bourey RE, Borst MJ, Olorunto W, Bergese SD, Evans DC, Stawicki SP, Papadimos TJ. Evaluation of a model for glycemic prediction in critically ill surgical patients. PLoS One. 2013 Jul 19;8(7):e69475. doi: 10.1371/journal.pone.0069475. Print 2013. — View Citation

Sung J, Bochicchio GV, Joshi M, Bochicchio K, Tracy K, Scalea TM. Admission hyperglycemia is predictive of outcome in critically ill trauma patients. J Trauma. 2005 Jul;59(1):80-3. — View Citation

Van den Berghe G. How does blood glucose control with insulin save lives in intensive care? J Clin Invest. 2004 Nov;114(9):1187-95. Review. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Evaluate performance of glucose predictive models, clinical decision support algorithms, and performance measures in simulated real-time setting.	Glucose measurements collected (mg/dL) in the iPro device will be further analyzed to create an algorithm to predict glucose changes (hyperglycemia or hypoglycemia).	Glucose levels collected since placement of the iPro device (Hour 0) until removal of the ipro device (Hour 72)
Secondary	Ensure data collected has considerable quantity of hypoglycemia, normoglycemia, and hyperglycemia for algorithm model development and optimization.	Glucose measurements collected (mg/dL) in the iPro device will be reviewed to confirmed that sufficient hyperglycemia or hypoglycemia episodes, as well as normal glucose values, were recorded. Available data will be used to create the algorithm to predict glucose changes.	Glucose levels collected since placement of the iPro device (Hour 0) until removal of the ipro device (Hour 72)
Secondary	Further development of GlyCU system functionality (simulation, training, and clinical decision support capabilities) and identification of necessary steps for integration with the OSUWMC electronic health record database.	Correlate glucose measurements collected (mg/dL) in the iPro device with the glucose values collected as at standard of care for each study subject at the Ohio State University Wexner Medical Center (OSUWMC).	Glucose levels collected since placement of the iPro device (Hour 0) until removal of the ipro device (Hour 72)