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

Trial details

Who runs it

University Hospital, Montpellier

Trial code

NCT06014593

Record updated

4 February 2025

Original description

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.Read full original descriptionShow less

Evaluation of the Diagnostic Performance of an Algorithm for Analyzing Expirograms of 4 Biomarkers in Exhaled Air in Patients With Heart Failure

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.

Inclusion: Age from 25 to 85,; Stable or worsening heart failure, diagnosed by a cardiologist,; Patients requiring respiratory function tests and cardiac explorations as part of a work-up at Montpellier University Hospital (pre-cardiac transplant, pre-rehabilitation, pre-surgery, etc....).

Exclusion: Volunteers with no previous cardiorespiratory history or treatment; Age from 25 to 85,; Subject in a period of relative exclusion in relation to another protocol, or for whom the maximum annual indemnity of €6000 has been reached; Adult protected by law (guardianship, curatorship or safeguard of justice); Subject participating in another interventional research protocol; Subject not affiliated to a social security scheme or not benefiting from such a scheme; Pregnant or breast-feeding woman, patient unable to give consent, protected adult, vulnerable persons (art.L. 1121-6, L. 1121-7, L. 1211-8, L. 1211-9 of the french legislation); Subject deprived of liberty by judicial or administrative decision; Subject having refused to give consent; Healthy Volunteers :.

ClinicalTrials.gov NCT06014593