Affiliation:
1. Department of Intensive Care Medicine, University Hospitals Leuven, Katholieke Universiteit Leuven, Leuven, Belgium
2. Department of Electrical Engineering (ESAT-SCD), iMINDS Medical Information Technologies, Katholieke Universiteit Leuven, Leuven (Heverlee), Belgium
Abstract
Abstract
BACKGROUND
Effective and safe glycemic control in critically ill patients requires accurate glucose sensors and adequate insulin dosage calculators. The LOGIC-Insulin calculator for glycemic control has recently been validated in the LOGIC-1 randomized controlled trial. In this study, we aimed to determine the allowable error for intermittent and continuous glucose sensors, on the basis of the LOGIC-Insulin calculator.
METHODS
A gaussian simulation model with a varying bias (0%–20%) and CV (−20% to +20%) simulated blood glucose values from the LOGIC-1 study (n = 149 patients) in 10 Monte Carlo steps. A clinical error grid system was developed to compare the simulated LOGIC-Insulin–directed intervention with the nominal intervention (0% bias, 0% CV). The severity of error measuring the clinical effect of the simulated LOGIC-Insulin intervention was graded as type B, C, and D errors. Type D errors were classified as acutely life-threatening (0% probability preferred).
RESULTS
The probability of all types of errors was lower for continuous sensors compared with intermittent sensors. The maximum total error (TE), defined as the first TE introducing a type B/C/D error, was similar for both sensor types. To avoid type D errors, TEs <15.7% for intermittent sensors and <17.8% for continuous sensors were required. Mean absolute relative difference thresholds for type C errors were 7.1% for intermittent and 11.0% for continuous sensors.
CONCLUSIONS
Continuous sensors had a lower probability for clinical errors than intermittent sensors at the same accuracy level. These simulations demonstrated the suitability of the LOGIC-Insulin control system for use with continuous, as well as intermittent, sensors.
Publisher
Oxford University Press (OUP)
Subject
Biochemistry (medical),Clinical Biochemistry
Cited by
22 articles.
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