Use of a Silicon Microneedle Chip-Based Device for the Extraction and Subsequent Analysis of Dermal Interstitial Fluid in Heart Failure Patients


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Date

2025-04-02

Publication Type

Journal Article

ETH Bibliography

yes

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Data

Abstract

Background/Objectives: Dermal interstitial fluid (dISF) is probably the most interesting biofluid for biomarker analysis as an alternative to blood, enabling higher patient comfort and closer or even continuous biomarker monitoring. The prerequisite for dISF-based analysis tools is having convenient access to dISF, as well as a better knowledge of the presence, concentration, and dynamics of biomarkers in dISF. Hollow microneedles represent one of the most promising platforms for access to pure dISF, enabling the mining of biomarker information. Methods and Results: Here, a microneedle-based method for dISF sampling is presented, where a combination of hollow microneedles and sub-pressure is used to optimize both penetration depth in skin and dermal interstitial fluid sampling volumes, and the design of an open, prospective, exploratory, and interventional study to examine the detectability of inflammatory and cardiocirculatory biomarkers in the dISF of heart failure patients, the relationship between dISF-derived and blood-derived biomarker levels, and their kinetics during a cardiopulmonary exercise test (CPET) is introduced. Conclusions: The dISF sampling method and study presented here will foster research on biomarkers in dISF in general and in heart failure patients in particular. The study is part of the European project DIGIPREDICT—Digital Edge AI-deployed DIGItal Twins for PREDICTing disease progression and the need for early intervention in infectious and cardiovascular diseases beyond COVID-19.

Publication status

published

Editor

Book title

Journal / series

Volume

15 (8)

Pages / Article No.

989

Publisher

MDPI

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

microneedle; dermal interstitial fluid; biomarkers; high-sensitivity CRP; NT-proBNP; lactate; biomarker kinetics; inflammation; heart failure; micro-electro-mechanical systems (MEMS)

Organisational unit

Notes

Funding

101017915 - Edge AI-deployed DIGItal Twins for PREDICTing disease progression and need for early intervention in infectious and cardiovascular diseases beyond COVID-19 (EC)

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