Remote Continuous Glucose Monitoring With a Computerized Insulin Infusion Protocol for Critically Ill Patients in a COVID-19 Medical ICU: Proof of Concept

Author:

Davis Georgia M.1,Faulds Eileen2ORCID,Walker Tara3,Vigliotti Debbie4,Rabinovich Marina4,Hester Joi5,Peng Limin6,McLean Barbara7,Hannon Patricia7,Poindexter Norma7,Saunders Petrena7,Perez-Guzman Citlalli1,Tekwani Seema S.8,Martin Greg S.8,Umpierrez Guillermo1ORCID,Agarwal Shivani9,Dungan Kathleen2ORCID,Pasquel Francisco J.1ORCID

Affiliation:

1. Division of Endocrinology, Metabolism, and Lipids, Emory University School of Medicine, Atlanta, GA

2. Division of Endocrinology, The Ohio State University, Columbus, OH

3. Information Technology, Grady Health System, Atlanta, GA

4. Department of Pharmacy, Grady Health System, Atlanta, GA

5. Department of Medicine, Morehouse School of Medicine, Atlanta, GA

6. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA

7. Division of Critical Care, Grady Health System, Atlanta, GA

8. Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Emory University School of Medicine, Atlanta, GA

9. Fleischer Institute for Diabetes and Metabolism, New York Regional Center for Diabetes Translational Research, Albert Einstein College of Medicine, Bronx, NY

Abstract

OBJECTIVE The use of remote real-time continuous glucose monitoring (CGM) in the hospital has rapidly emerged to preserve personal protective equipment and reduce potential exposures during coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS We linked a hybrid CGM and point-of-care (POC) glucose testing protocol to a computerized decision support system for continuous insulin infusion and integrated a validation system for sensor glucose values into the electronic health record. We report our proof-of-concept experience in a COVID-19 intensive care unit. RESULTS All nine patients required mechanical ventilation and corticosteroids. During the protocol, 75.7% of sensor values were within 20% of the reference POC glucose with an associated average reduction in POC of 63%. Mean time in range (70–180 mg/dL) was 71.4 ± 13.9%. Sensor accuracy was impacted by mechanical interferences in four patients. CONCLUSIONS A hybrid protocol integrating real-time CGM and POC is helpful for managing critically ill patients with COVID-19 requiring insulin infusion.

Funder

National Institute of Diabetes and Digestive and Kidney Diseases

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference16 articles.

1. Association between achieving inpatient glycemic control and clinical outcomes in hospitalized patients with COVID-19: a multicenter, retrospective hospital-based analysis;Klonoff;Diabetes Care

2. Glycemic characteristics and clinical outcomes of COVID-19 patients hospitalized in the United States;Bode;J Diabetes Sci Technol,2020

3. Outcomes in patients with hyperglycemia affected by COVID-19: can we do more on glycemic control;Sardu;Diabetes Care,2020

4. Individualizing inpatient diabetes management during the coronavirus disease 2019 pandemic;Pasquel;J Diabetes Sci Technol,2020

5. Implementation of continuous glucose monitoring in the hospital: emergent considerations for remote glucose monitoring during the COVID-19 pandemic;Galindo;J Diabetes Sci Technol,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3