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Heart Failure Diagnostic Performance of an Expirogram Analysis Algorithm Evaluating 4 Biomarkers

NCT06014593 · Status: TERMINATED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 60

Last updated 2025-02-04

No results posted yet for this study

Summary

Telemonitoring is a key clinical issue in heart failure (HF). Bedside measurement systems using handheld devices provide "digital biomarkers" useful for remote monitoring. A recent systematic review and meta-analysis showed that teleconsultations and telemonitoring at home improved the prognosis of HF patients compared with usual care. Biomarkers contained in exhaled air could constitute "digital biomarkers" in HF, as measurement is non-invasive, and 4 different species have shown their potential interest: NO, CO, acetone and isoprene. The assessment of these species in the exhaled air to remains an issue in the perspective of non-invasive biomarkers in HF. Indeed, it requires selective sensors with low limit of detection. In addition, these sensors should be miniaturizable. Quartz-enhanced photoacoustic spectroscopy (QEPAS) are sensors that are suitable in this context. Last, the measured concentration should be informative and directly related to the HF. However, the concentration each of these biomarkers is not homogeneous during the expiration as it reflects the different lung compartments. While the end-expiratory concentration constitutes a sample of the alveolar concentration (AC) that reflects the blood concentration (BC) of one specie, the relationship between alveolar and blood concentrations is complex as exchanges that take place within these different compartments. Thus, measuring the concentration of a specie in exhaled air during a complete exhalation (or "expirogram") depends not only on the BC of the specie, but also on changes in lung function. Because both BC and changes in lung function depend on the severity of the HF, obtaining a full expirogram each specie should provide valid diagnosis information in HF. The mathematical modelization of real-time QEPAS sensors based expirograms together with lung function parameters (volume, flow) and lung compartment identification (capnography i.e. exhaled CO2 concentration) could provide valid algorithms with a an acceptable diagnosis performance in HF.

Conditions

Interventions

DEVICE

expirogram

Recovery of heart failure data (left ventricular ejection fraction LVEF on cardiac echography (in mL), VO²max during, maximal cardio-pulmonary exercise test, plethysmographic spirometry, carbon monoxide transfer, NT-ProBNP assay,), clinical examination and finally expirogram with the device measuring the 4 exhaled biomarkers (CO/NO/Acetone/Isoprene).

Sponsors & Collaborators

  • Université Montpellier

    collaborator OTHER

  • University Hospital, Montpellier

    lead OTHER

Principal Investigators

  • Fares GOUZI, MD · CHU de Montpellier

Study Design

Allocation
NON_RANDOMIZED
Purpose
OTHER
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
25 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-04-26
Primary Completion
2024-10-31
Completion
2024-10-31

Countries

  • France

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06014593 on ClinicalTrials.gov