Literature DB >> 26305390

Randomized Evaluation of Glycemic Control in the Medical Intensive Care Unit Using Real-Time Continuous Glucose Monitoring (REGIMEN Trial).

Christophe E M De Block1, Jens Gios2, Nina Verheyen1, Begoña Manuel-y-Keenoy3, Peter Rogiers4, Philippe G Jorens5, Cosimo Scuffi6, Luc F Van Gaal1.   

Abstract

BACKGROUND AND
OBJECTIVE: Hyperglycemia occurs commonly in patients admitted to medical intensive care units (MICUs). Whether real-time (RT) continuous glucose monitoring (CGM) improves glycemic control and variability and reduces hypoglycemia in severely ill MICU patients with an Acute Physiology and Chronic Health Evaluation II (APACHE-II) score of ≥20 has not been studied. SUBJECTS AND METHODS: Thirty-five patients (66 ± 10 years of age; APACHE-II score, 28 ± 6) were randomly assigned to RT-CGM (n = 16) using the GlucoDay(®)S (A. Menarini Diagnostics, Florence, Italy) device or to blinded CGM. Insulin was infused using a modified Yale protocol targeting a blood glucose level between 80 and 120 mg/dL. Outcome measures were percentage of time in normoglycemia (80-110 mg/dL) and in hypoglycemia (<60 mg/dL), glycemic variability (SD, coefficient of variation, mean amplitude of glucose excursions, and mean of daily differences), and CGM accuracy (error grid analyses, Bland-Altman bias plot, and mean absolute relative deviation).
RESULTS: During 96 h of monitoring, glycemia reached target (80-110 mg/dL) in 37 ± 15%, was between 70 and 180 mg/dL in 91 ± 10%, and <60 mg/dL in 2 ± 2% of the time. In the RT-CGM group glycemia averaged 119 ± 17 mg/dL versus 122 ± 11 mg/dL in the control group. Parameters of glucose variability and percentages of time at target glycemia and in hypoglycemia were similar between groups. GlucoDayS values and arterial glycemia correlated well, with 98.6% of data falling in Zones A and B of the error grid analysis. Mean absolute relative devation was 11.2%.
CONCLUSIONS: RT-CGM did not ameliorate glucose control or variability; neither did it reduce the number of hypoglycemic events, but our insulin infusion protocol led to overall good glucose control without a significant hypoglycemia risk, making further improvement difficult.

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Year:  2015        PMID: 26305390     DOI: 10.1089/dia.2015.0151

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  20 in total

1.  Safety of using real-time sensor glucose values for treatment decisions in adolescents with poorly controlled type 1 diabetes mellitus: a pilot study.

Authors:  Larry A Fox; Emilie Balkman; Kim Englert; Jobayer Hossain; Nelly Mauras
Journal:  Pediatr Diabetes       Date:  2016-07-20       Impact factor: 4.866

Review 2.  Diabetes Technology in the Inpatient Setting for Management of Hyperglycemia.

Authors:  Georgia M Davis; Rodolfo J Galindo; Alexandra L Migdal; Guillermo E Umpierrez
Journal:  Endocrinol Metab Clin North Am       Date:  2020-03       Impact factor: 4.741

Review 3.  Toward a Framework for Outcome-Based Analytical Performance Specifications: A Methodology Review of Indirect Methods for Evaluating the Impact of Measurement Uncertainty on Clinical Outcomes.

Authors:  Alison F Smith; Bethany Shinkins; Peter S Hall; Claire T Hulme; Mike P Messenger
Journal:  Clin Chem       Date:  2019-08-23       Impact factor: 8.327

Review 4.  Designing the Glucose Telemetry for Hospital Management: From Bedside to the Nursing Station.

Authors:  Medha Satyarengga; Tariq Siddiqui; Elias K Spanakis
Journal:  Curr Diab Rep       Date:  2018-08-29       Impact factor: 4.810

5.  Malglycemia is associated with poor outcomes in pediatric and adolescent hematopoietic stem cell transplant patients.

Authors:  Jenna Sopfe; Laura Pyle; Amy K Keating; Kristen Campbell; Arthur K Liu; R Paul Wadwa; Michael R Verneris; Roger H Giller; Gregory P Forlenza
Journal:  Blood Adv       Date:  2019-02-12

6.  Continuous Glucose Monitoring in Critically Ill Patients With COVID-19: Results of an Emergent Pilot Study.

Authors:  Archana R Sadhu; Ivan Alexander Serrano; Jiaqiong Xu; Tariq Nisar; Jessica Lucier; Anjani R Pandya; Bhargavi Patham
Journal:  J Diabetes Sci Technol       Date:  2020-10-16

7.  Continuous Glucose Monitor Use and Accuracy in Hospitalized Patients.

Authors:  Vikash Dadlani; Yogish C Kudva
Journal:  Diabetes Technol Ther       Date:  2016-08-08       Impact factor: 6.118

Review 8.  Inpatient Continuous Glucose Monitoring and Glycemic Outcomes.

Authors:  David L Levitt; Kristi D Silver; Elias K Spanakis
Journal:  J Diabetes Sci Technol       Date:  2017-03-14

9.  Accuracy and reliability of a subcutaneous continuous glucose monitoring device in critically ill patients.

Authors:  S Rijkenberg; S C van Steen; J H DeVries; P H J van der Voort
Journal:  J Clin Monit Comput       Date:  2017-12-07       Impact factor: 2.502

10.  Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline.

Authors:  Rodolfo J Galindo; Guillermo E Umpierrez; Robert J Rushakoff; Ananda Basu; Suzanne Lohnes; James H Nichols; Elias K Spanakis; Juan Espinoza; Nadine E Palermo; Dessa Garnett Awadjie; Leigh Bak; Bruce Buckingham; Curtiss B Cook; Guido Freckmann; Lutz Heinemann; Roman Hovorka; Nestoras Mathioudakis; Tonya Newman; David N O'Neal; Michaela Rickert; David B Sacks; Jane Jeffrie Seley; Amisha Wallia; Trisha Shang; Jennifer Y Zhang; Julia Han; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2020-09-28
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