Development of Artificial Intelligence algorithms from respiratory sounds recorded with the Pneumoscope in children and adolescents with wheezing disorders.
Résumé de l'étude
Wheezing disorders are the most common chronic illnesses in childhood, yet diagnosis and severity assessment often prove challenging for parents. Accurate diagnosis and risk evaluation of wheezing episodes are essential for optimal management and preventing adverse outcomes. Our team recently demonstrated that artificial intelligence (AI) can identify specific acoustic markers of wheezing disorders using lung sound analysis. We are now exploring AI's potential to accurately assess disease severity. Currently, doctors rely on a combination of tools to identify wheezing disorders and the pulse oximeter. The Pneumoscope is an all-in-one device that integrates a digital stethoscope, a pulse oximeter, and a thermometer, designed to harness artificial intelligence in real time for diagnosing respiratory diseases. This device would enable patients, parents, and non-medical healthcare providers (such as nurses and pharmacists) to detect wheezing episodes earlier and deliver timely, optimal care. Additionally, users could send recorded data and AI analysis to a remote specialist for further guidance, supporting telehealth services.
(BASEC)
Intervention étudiée
• Performance (sensitivity/specificity) of the Deep Breath algorithm for the diagnosis of wheezing disorders using the Pneumsocope,
• Safety assessment of the Pneumoscope: measurement of the possibility of adverse events (AE) / adverse device effect (ADE), such as contact allergy.
(BASEC)
Maladie en cours d'investigation
Wheezing disorders
(BASEC)
• Information and written consent from the patient or a legal representative. • Age > 1 year old, < 16 years old • Signs and symptoms suggestive of wheezing disorders (BASEC)
Critères d'exclusion
• Refusal of consent • Immune disorder, primary ciliary dyskinesia, history of neonatal bronchopulmonary dysplasia. • Hemodynamic impairment • Lack of understanding of the study protocol • Contraindications to the class of MD being studied, e.g. known hypersensitivity or allergy to the device material. • Participation in another study with an investigational drug or other MD within 30 days prior to and during the present study (BASEC)
Lieu de l’étude
Genève
(BASEC)
Sponsor
Prof. Alain Gervaix Hôpitaux Universitaires de Genève
(BASEC)
Contact pour plus d'informations sur l'étude
Personne de contact en Suisse
Isabelle Ruchonnet-Métrailler
+41795534169
isabelle.ruchonnet-metrailler@clutterhug.chHôpitaux Universitaires de Genève
(BASEC)
Informations scientifiques
non disponible
Nom du comité d'éthique approbateur (pour les études multicentriques, uniquement le comité principal)
Commission cantonale d'éthique de Genève
(BASEC)
Date d'approbation du comité d'éthique
05.06.2025
(BASEC)
Identifiant de l'essai ICTRP
non disponible
Titre officiel (approuvé par le comité d'éthique)
x (BASEC)
Titre académique
non disponible
Titre public
non disponible
Maladie en cours d'investigation
non disponible
Intervention étudiée
non disponible
Type d'essai
non disponible
Plan de l'étude
non disponible
Critères d'inclusion/exclusion
non disponible
non disponible
Critères d'évaluation principaux et secondaires
non disponible
non disponible
Date d'enregistrement
non disponible
Inclusion du premier participant
non disponible
Sponsors secondaires
non disponible
Contacts supplémentaires
non disponible
ID secondaires
non disponible
Résultats-Données individuelles des participants
non disponible
Informations complémentaires sur l'essai
non disponible
Résultats de l'essai
Résumé des résultats
non disponible
Lien vers les résultats dans le registre primaire
non disponible