Real-World Data from the First US Commercial Users of an Implantable Continuous Glucose Sensor.

Real-World Data from the First US Commercial Users of an Implantable Continuous Glucose Sensor.

Sanchez, Patricia;Ghosh-Dastidar, Samanwoy;Tweden, Katherine S;Kaufman, Francine;
diabetes technology & therapeutics 2019
264
sanchez2019realworlddiabetes

Abstract

The Eversense CGM System, with the first 90-day implantable sensor, received FDA approval June 2018. No real-world experience has been published.De-identified sensor glucose (SG) data from 01Aug18 to 11May19 in the Eversense Data Management System (DMS) were analyzed for the first 205 patients who reached a 90-day wear period on the Eversense CGM system. The mean SG, standard deviation (SD), median interquartile range (IQR), coefficient of variation (CV), glucose measurement index (GMI), and percent and time in minutes across glucose ranges were computed for the 24-hour time period and nighttime (0000 - 0600). Sensor accuracy, sensor reinsertion rate, transmitter wear time, and safety data were assessed.Of the 205 patients, 129 identified as type 1, 18 as type 2, and 58 were unreported. Fifty were CGM naïve, 112 had prior CGM experience, and 43 were unreported. The mean SG was 161.8 mg/dL, SD was 57.4 mg/dL, CV was 0.35 and GMI was 7.18%. Percent SG at <54 mg/dL was 1.2% (18 minutes), <70 mg/dL was 4.1% (59.7 minutes), Time in Range (≥70 to 180 mg/dL) was 62.3% (897.7 minutes), >180-250 mg/dL was 21.9% (315.8 minutes) and >250 mg/dL was 11.6% (166.7 minutes). Nighttime values were similar. The MARD (SD) using 27,708 calibration paired points against SMBG was 11.2% (11.3%). The sensor reinsertion rate was 78.5%. The median transmitter wear time was 83.6%. There were no related serious adverse events.The Eversense real-world data showed excellent glycemic results, sensor accuracy, and safety. These data suggest that the Eversense CGM system is a valuable tool for diabetes management.

Citation

ID: 12292
Ref Key: sanchez2019realworlddiabetes
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
12292
Unique Identifier:
10.1089/dia.2019.0234
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet