Evidence mapPaperPMID 38323362Full record

ArticleJournal of diabetes science and technology2024

Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology.

Viral N Shah, Halis K Akturk, Alex Trahan, Nicole Piquette, Alex Wheatcroft, Elain Schertz, Karen Carmello, Lars Mueller, Kirstin White, Larry Fu and 5 more

Registry-linked trialAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05204134 (Adaptation of Insulin Delivery Settings to Improve Clinical Outcomes With AID Use), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05204134 nacompletednot on this map

Adaptation of Insulin Delivery Settings to Improve Clinical Outcomes With AID Use

TypeinterventionalSponsorTandem Diabetes Care, Inc.Ran2022 to 2022Enrolled33ConditionsType 1 DiabetesArmsAutomated Insulin Delivery Settings Initialization and Adaptation Algorithm
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Viral N ShahBarbara Davis Center for Diabetes, University of Colorado, Aurora, CO, USA.ORCID 0000-0002-3827-7107
Halis K AkturkBarbara Davis Center for Diabetes, University of Colorado, Aurora, CO, USA.ORCID 0000-0003-4518-5179
Alex TrahanTandem Diabetes Care, San Diego, CA, USA.
Nicole PiquetteTandem Diabetes Care, San Diego, CA, USA.
Alex WheatcroftTandem Diabetes Care, San Diego, CA, USA.
Elain SchertzTandem Diabetes Care, San Diego, CA, USA.
Karen CarmelloTandem Diabetes Care, San Diego, CA, USA.
Lars MuellerTandem Diabetes Care, San Diego, CA, USA.
Kirstin WhiteTandem Diabetes Care, San Diego, CA, USA.
Larry FuTandem Diabetes Care, San Diego, CA, USA.
Ravid Sassan-KatchalskiTandem Diabetes Care, San Diego, CA, USA.
Laurel H MesserTandem Diabetes Care, San Diego, CA, USA.ORCID 0000-0001-7493-0989
Steph HabifTandem Diabetes Care, San Diego, CA, USA.
Alex ConstantinTandem Diabetes Care, San Diego, CA, USA.
Jordan E PinskerTandem Diabetes Care, San Diego, CA, USA.ORCID 0000-0003-4080-9034

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D).

methodsAfter a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns.

resultsTime in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9,

conclusionsComputerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 1Feasibility StudiesHypoglycemic AgentsInsulinInsulin Infusion SystemsAdultAlgorithmsFemaleGlycated HemoglobinHumansMaleMiddle AgedBlood GlucoseGlycated HemoglobinHypoglycemic AgentsInsulinadaptationautomated insulin deliveryControl-IQinitializationt:slim X2

Identifiers

PMID38323362
PMCPMC11535304

What Socratic holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.