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10.1177/1932296820964264

http://scihub22266oqcxt.onion/10.1177/1932296820964264
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33063556!7645121!33063556
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suck abstract from ncbi


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pmid33063556      J+Diabetes+Sci+Technol 2020 ; 14 (6): 1065-1073
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  • Continuous Glucose Monitoring in Critically Ill Patients With COVID-19: Results of an Emergent Pilot Study #MMPMID33063556
  • Sadhu AR; Serrano IA; Xu J; Nisar T; Lucier J; Pandya AR; Patham B
  • J Diabetes Sci Technol 2020[Nov]; 14 (6): 1065-1073 PMID33063556show ga
  • BACKGROUND: Amidst the coronavirus disease 2019 (COVID-19) pandemic, continuous glucose monitoring (CGM) has emerged as an alternative for inpatient point-of-care blood glucose (POC-BG) monitoring. We performed a feasibility pilot study using CGM in critically ill patients with COVID-19 in the intensive care unit (ICU). METHODS: Single-center, retrospective study of glucose monitoring in critically ill patients with COVID-19 on insulin therapy using Medtronic Guardian Connect and Dexcom G6 CGM systems. Primary outcomes were feasibility and accuracy for trending POC-BG. Secondary outcomes included reliability and nurse acceptance. Sensor glucose (SG) was used for trends between POC-BG with nursing guidance to reduce POC-BG frequency from one to two hours to four hours when the SG was in the target range. Mean absolute relative difference (MARD), Clarke error grids analysis (EGA), and Bland-Altman (B&A) plots were calculated for accuracy of paired SG and POC-BG measurements. RESULTS: CGM devices were placed on 11 patients: Medtronic (n = 6) and Dexcom G6 (n = 5). Both systems were feasible and reliable with good nurse acceptance. To determine accuracy, 437 paired SG and POC-BG readings were analyzed. For Medtronic, the MARD was 13.1% with 100% of readings in zones A and B on Clarke EGA. For Dexcom, MARD was 11.1% with 98% of readings in zones A and B. B&A plots had a mean bias of -17.76 mg/dL (Medtronic) and -1.94 mg/dL (Dexcom), with wide 95% limits of agreement. CONCLUSIONS: During the COVID-19 pandemic, CGM is feasible in critically ill patients and has acceptable accuracy to identify trends and guide intermittent blood glucose monitoring with insulin therapy.
  • |Adult[MESH]
  • |Aged[MESH]
  • |Betacoronavirus/physiology[MESH]
  • |Blood Glucose Self-Monitoring/instrumentation/methods[MESH]
  • |Blood Glucose/*analysis/metabolism[MESH]
  • |COVID-19[MESH]
  • |Coronavirus Infections/*blood/epidemiology/mortality/*therapy[MESH]
  • |Critical Illness/epidemiology/mortality/*therapy[MESH]
  • |Diabetes Mellitus/blood/diagnosis/mortality/therapy[MESH]
  • |Feasibility Studies[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Hyperglycemia/blood/diagnosis/mortality/therapy[MESH]
  • |Insulin Infusion Systems[MESH]
  • |Insulin/administration & dosage[MESH]
  • |Intensive Care Units[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Monitoring, Physiologic/*instrumentation/methods[MESH]
  • |Pandemics[MESH]
  • |Pilot Projects[MESH]
  • |Pneumonia, Viral/*blood/epidemiology/mortality/*therapy[MESH]
  • |Point-of-Care Systems[MESH]
  • |Prognosis[MESH]
  • |Reproducibility of Results[MESH]
  • |Retrospective Studies[MESH]


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