Development of Artificial Intelligence algorithms from respiratory sounds recorded with the Pneumoscope in children and adolescents with wheezing disorders.
Descrizione riassuntiva dello studio
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)
Intervento studiato
• 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)
Malattie studiate
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)
Criteri di esclusione
• 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)
Luogo dello studio
Ginevra
(BASEC)
Sponsor
Prof. Alain Gervaix Hôpitaux Universitaires de Genève
(BASEC)
Contatto per ulteriori informazioni sullo studio
Persona di contatto in Svizzera
Isabelle Ruchonnet-Métrailler
+41795534169
isabelle.ruchonnet-metrailler@clutterhug.chHôpitaux Universitaires de Genève
(BASEC)
Informazioni scientifiche
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Nome del comitato etico approvante (per studi multicentrici solo il comitato principale)
Commissione d'etica Ginevra
(BASEC)
Data di approvazione del comitato etico
05.06.2025
(BASEC)
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x (BASEC)
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