Literature DB >> 33471639

Real-World Improvements in Hypoglycemia in an Insulin-Dependent Cohort With Diabetes Mellitus Pre/Post Tandem Basal-Iq Technology Remote Software Update.

Jordan E Pinsker1, Scott Leas2, Lars Müller3, Steph Habif4.   

Abstract

OBJECTIVE: Software updatable insulin pumps, such as the t:slim X2 pump from Tandem Diabetes Care, enable access to new technology as soon as it is commercialized. The remote software update process allows for minimal interruption in therapy compared to purchasing a new pump; however, little quantitative data exist on the software update process or on pre/post therapeutic outcomes. We examined real-world usage and impact of a remote software updatable predictive low-glucose suspend (PLGS) technology designed to reduce hypoglycemic events in people with insulin-dependent diabetes.
METHODS: Approximately 15,000 U.S. Tandem pump users remotely updated their t:slim X2 software to Basal-IQ PLGS technology since its commercial release. We performed a retrospective analysis of users who uploaded at least 21 days of pre/post PLGS update usage data to the Tandem t:connect web application between August 28, 2018, and October 21, 2019 (N = 6,170). Insulin delivery and sensor-glucose values were analyzed per recent international consensus and American Diabetes Association guidelines. Software update performance was also assessed.
RESULTS: Median software update time was 5.36 minutes. Overall glycemic outcomes for pre and post software update showed a decrease in sensor time <70 mg/dL from 2.14 to 1.18% (-1.01; 95% confidence interval &lsqb;CI], -0.97, -1.05; P<.001), with overall sensor time 70 to 180 mg/dL increasing from 57.8 to 58.5% (0.64; 95% CI, 0.04, 1.24; P<.001). These improvements were sustained at 3, 6, and 9 months after the update.
CONCLUSION: Introduction of a software updatable PLGS algorithm for the Tandem t:slim X2 insulin pump resulted in sustained reductions of hypoglycemia. ABBREVIATIONS: ADA = American Diabetes Association; CGM = continuous glucose monitoring; CI = confidence interval; PLGS = predictive low-glucose suspend; SG = sensor glucose; T1D = type 1 diabetes; T2D = type 2 diabetes; TIR = time-in-range.
© 2020 American Association of Clinical Endocrinologists. Published by Elsevier, Inc. All rights reserved.

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Year:  2020        PMID: 33471639     DOI: 10.4158/EP-2019-0554

Source DB:  PubMed          Journal:  Endocr Pract        ISSN: 1530-891X            Impact factor:   3.443


  3 in total

1.  Predictive Low-Glucose Suspend Necessitates Less Carbohydrate Supplementation to Rescue Hypoglycemia: Need to Revisit Current Hypoglycemia Treatment Guidelines.

Authors:  Jordan E Pinsker; Amy Bartee; Michelle Katz; Amy Lalonde; Richard Jones; Eyal Dassau; Howard Wolpert
Journal:  Diabetes Technol Ther       Date:  2021-02-18       Impact factor: 6.118

2.  Sensor-Augmented Insulin Pump with Predictive Low-Glucose Suspend (PLGS): Determining Optimal Settings of Pump and Sensor in a Multicenter Cohort of Patients with Type 1 Diabetes.

Authors:  Michael Joubert; Anaïs R Briant; Laurence Kessler; Fatéma Fall-Mostaine; Severine Dubois; Bruno Guerci; Laurène Schoumacker-Ley; Yves Reznik; Jean-Jacques Parienti
Journal:  Diabetes Ther       Date:  2022-08-01       Impact factor: 3.595

3.  Real-World Patient Reported Outcomes and Glycemic Results with Initiation of Control-IQ Technology.

Authors:  Jordan E Pinsker; Lars Müller; Alexandra Constantin; Scott Leas; Michelle Manning; Molly McElwee Malloy; Harsimran Singh; Steph Habif
Journal:  Diabetes Technol Ther       Date:  2020-08-26       Impact factor: 6.118

  3 in total

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