Optimization of Glycemic Control in the Hospital and Critical Care Setting

NCT ID: NCT04015388

Last Updated: 2021-02-11

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

127 participants

Study Classification

OBSERVATIONAL

Study Start Date

2014-08-19

Study Completion Date

2021-02-04

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Hyperglycemia Diabetes Mellitus

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Diabetes Mellitus / Hyperglycemia

iPro Continuous Glucose Monitoring on subjects with blood sugar value \>140 mg/dL upon admission to the intensive care unit or who have been diagnosed with type 1 or type 2 diabetes or have glycosylated hemoglobin A1C (HbA1C) values \> 6.5% prior to admission.

iPro Continuous Glucose Monitoring

Intervention Type DEVICE

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.

Interventions

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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.

Intervention Type DEVICE

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Ohio State University

OTHER

Sponsor Role lead

Responsible Party

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Ravi Tripathi

Principal Investigator, Clinical Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Ravi Tripathi, MD

Role: PRINCIPAL_INVESTIGATOR

Ohio State University

References

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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. doi: 10.2337/diacare.23.2.163.

Reference Type BACKGROUND
PMID: 10868825 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 24887924 (View on PubMed)

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. doi: 10.1161/01.cir.95.7.1783.

Reference Type BACKGROUND
PMID: 9107164 (View on PubMed)

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. doi: 10.1093/eurheartj/ehi855. Epub 2006 Apr 11.

Reference Type BACKGROUND
PMID: 16608860 (View on PubMed)

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. No abstract available.

Reference Type BACKGROUND
PMID: 19318385 (View on PubMed)

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. doi: 10.1097/01.ccm.0000189939.10881.60.

Reference Type BACKGROUND
PMID: 16352960 (View on PubMed)

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. doi: 10.1097/01.ta.0000171452.96585.84.

Reference Type BACKGROUND
PMID: 16096543 (View on PubMed)

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. doi: 10.1172/JCI23506.

Reference Type BACKGROUND
PMID: 15520847 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 20828400 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23894489 (View on PubMed)

Other Identifiers

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2013H0285

Identifier Type: -

Identifier Source: org_study_id

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