Evidence mapPaperPMID 41039947Full record

ArticleDiabetes, obesity & metabolism2025

Contributions of intermittently scanned continuous glucose monitoring frequency and bolus insulin dosing on time in range: Analysis of data from CGM and connected insulin pens.

Pratik Choudhary, Kalvin Kao, Farhan Quadri, Elemer Balogh, Jody Foster

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Article in Diabetes, obesity & metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Technology in Diabetes: A Year in Review.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2026
    Review
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4 · The record

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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

5 authors.

Pratik ChoudharyDiabetes Research Centre, University of Leicester, Leicester, UK.
Kalvin KaoAbbott Diabetes Care, Alameda, California, USA.
Farhan QuadriAbbott Diabetes Care, Alameda, California, USA.
Elemer BaloghAbbott Diabetes Care, Maidenhead, UK.
Jody FosterAbbott Diabetes Care, Maidenhead, UK.

Funding

Abbott Diabetes Care
6 · The paper itself

Abstract

BACKGROUND AND

aimsIntegration of data from continuous glucose monitoring (CGM) and connected insulin pens allows us to investigate their use to optimise glucose control. This study examines how insulin bolus frequency reported by connected pens and frequency of glucose scans by an intermittently-scanned continuous glucose monitoring (isCGM) system relate to glycaemic control in a population of real-world European users.

methodsData from glucose sensors and connected insulin pens were aggregated for LibreView users who integrated their connected pen by January 1, 2024. The most recent 90-day window with ≥30 days' glucose data and ≥15 days of insulin bolus doses following their integration date was analysed. We stratified users by categories of average isCGM scan frequency: low (<6.1 scans/day), medium (6.1-14.0 scans/day) or high (>14.0 scans/day), and average bolus frequency: low (<3.1 boluses/day), medium (3.1-6.7 boluses/day) or high (>6.7 boluses/day).

resultsData from 10,993 users was available over 80.6 days/user. Median scans/day were 9.3 [6.1-14.0] and median bolus/day was 4.5 [3.1-6.7]. Increased daily scans were associated with greater time in range (TIR) 70-180 mg/dL (3.9-10.0 mmol/L) within each of the low, medium, and high bolus frequency groups. Increased bolus frequency was associated with increased TIR in the lowest scanning frequency group. Similar outcomes were observed for time above range (TAR) and glycaemic variability.

conclusionsWhile glucose monitoring frequency and insulin bolus dosing are both indicators of engagement with diabetes self-management, higher TIR has a closer association with increased rates of user engagement with isCGM than with increased rates of bolus dosing.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Glycemic ControlHypoglycemic AgentsInsulinInsulin Infusion SystemsAdultAgedContinuous Glucose MonitoringFemaleHumansMaleMiddle AgedBlood GlucoseHypoglycemic AgentsInsulinCGMconnected insulin penglycaemic variability. Interconnected devicestime above rangetime in range

Identifiers

PMID41039947
PMCPMC12587231

What Socratic holds

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LicenceCC BY
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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.