Evidence map›Paper›PMID 41361848›Full record

ArticleJournal of diabetes science and technology2025

Dermal Glucose Sensing has a Shorter Time Lag Relative to Blood Glucose: Implications for Hypoglycemia Detection and Time in Range.

Khadije Ahmad, Peter Rule, Brianna Bañez, Daniel Hale, Bill Van Antwerp

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Article in Journal of diabetes science and technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Khadije AhmadLaxmi Therapeutic Devices, Goleta, CA, USA.ORCID 0009-0001-4664-4456
Peter RuleLaxmi Therapeutic Devices, Goleta, CA, USA.
Brianna BañezLaxmi Therapeutic Devices, Goleta, CA, USA.
Daniel HaleLaxmi Therapeutic Devices, Goleta, CA, USA.
Bill Van AntwerpLaxmi Therapeutic Devices, Goleta, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCurrent continuous glucose monitors (CGM) sensing glucose in the subcutaneous tissue have a significant time lag (τ). This delay could result in severe hypo/hyperglycemia and lower time in range (TIR). Dermal sensing can greatly reduce time lag.

methodsIn a clinical study conducted at two US-based clinical centers, subjects with type 1 diabetes mellitus (DM) wore a novel dermal CGM + Abbott-Libre 3 or Dexcom-G7. All were compared to a YSI-glucose analyzer. Time lag kinetics for all sensors were modeled using the two-compartment model and compared to published data. Time lag data and its potential effect on TIR were also analyzed.

resultsData from 55 subjects showed fast kinetics for the dermal CGM. In total, 93% of the Laxmi sensors had a τ of 0-2 minutes, whereas commercial CGMs had a varying distribution of τ (-10 to 10+ minutes). This reduction in τ by 10 minutes has profound effects on errors in insulin administration in both open-loop and in a proportional-integral-derivative (PID) model of automated insulin delivery (AID). To evaluate the effect of tau on TIR, we used an in silico PID controller in a well-accepted model (UVA type 1 diabetes simulator) over a variety of conditions. We observed that tau greatly affects TIR and the distribution of the time out of range parameters.

conclusionDermal sensing has a time lag close to 0. Individuals with DM can have lower glucose targets with a system that eliminates fear of hypoglycemia, resulting in higher TIR and better control of DM.

Indexed as

continuous glucose monitoringdermal glucose sensingiCGMtime in rangetime lag

Identifiers

PMID41361848
PMCPMC12689353

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