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Related Concept Videos

Instrumentation Amplifier01:25

Instrumentation Amplifier

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An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
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A Modified CGM Algorithm Enhances Data Availability While Retaining iCGM Performance.

Rebecca A Harvey Towers1, Xiaohe Zhang1, Rasoul Yousefi1

  • 1Dexcom, Inc., San Diego, CA, USA.

Journal of Diabetes Science and Technology
|April 15, 2021
PubMed
Summary

The Dexcom G6 continuous glucose monitoring (CGM) system algorithm was updated to reduce sensor errors. This enhancement improved data availability without compromising accuracy, benefiting patient experience and insulin delivery systems.

Keywords:
accuracyalgorithmcontinuous glucose monitoringdata availabilityperformance

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Area of Science:

  • Biomedical Engineering
  • Medical Device Technology
  • Diabetes Technology

Background:

  • Continuous glucose monitoring (CGM) is crucial for diabetes management.
  • Sensor errors in CGM systems can disrupt data collection and impact patient care.
  • The Dexcom G6 CGM System previously experienced sensor errors that affected data availability.

Purpose of the Study:

  • To evaluate an enhanced algorithm for the Dexcom G6 CGM System.
  • To assess the impact of the algorithm modification on sensor error frequency and duration.
  • To determine if accuracy was maintained after the algorithm update.

Main Methods:

  • Post-processing of raw signals from Dexcom G6 pivotal trials (NCT02880267).
  • Assessment of data availability changes after a limited real-world launch.
  • Comparison of accuracy metrics (e.g., %20/20, MARD) before and after algorithm modification.

Main Results:

  • Overall accuracy (%20/20) remained comparable (91.7% vs. 91.8%), and MARD was unchanged.
  • Mean data gap due to sensor error was nearly halved.
  • Total time spent in sensor error decreased by 59% in pivotal trials and 43% in a real-world launch.

Conclusions:

  • The enhanced Dexcom G6 algorithm successfully reduced sensor error frequency and duration.
  • Improved data availability from the CGM system can enhance patient experience.
  • Increased data availability facilitates better integration with automated insulin delivery systems.