Recruiting
Oscillometry and Machine Learning Approaches
Unicentric retrospective study designed to analyses the performance of various machine learning approaches to predict patterns of chronic respiratory diseases such as asthma, based mainly on clinical information and respiratory spirometry/oscillometry.
ClinicalTrials.gov IDNCT07447596
PhaseNot Applicable
Enrollment50
SponsorFundació Institut de Recerca de l'Hospital de la Santa Creu i Sant Pau
Age18 Years
SexALL
Conditions studied
Asthma COPD
About this study
Unicentric retrospective study designed to analyses the performance of various machine learning approaches to predict patterns of chronic respiratory diseases such as asthma, based mainly on clinical information and respiratory spirometry/oscillometry.
Interventions
- Other: 1 — Compare oscillometry results with spirometryClick to apply
Primary outcomes
- Oscillometric breathing pattern (1 year)
Eligibility information
Inclusion Criteria:
* 18 - 90 years
* Spirometry available
* Confirmed clinical diagnosis of COPD, asthma, interstitial lung disease according to national or international guidelines
Exclusion Criteria:
* Acute respiratory infection
Study locations
- Hospital de la Santa Creu i Sant Pau, Barcelona, 08041 Spain
Before you participate: Varda Clinical is an independent discovery tool, not the study sponsor or a medical provider. Eligibility can only be determined by the official study team. Discuss potential risks and benefits with a qualified healthcare professional.
Source: ClinicalTrials.gov. Record last refreshed by Varda Clinical: 2026-09-27.