Volatilome and Single-Lead Electrocardiogram Optimize Ischemic Heart Disease Diagnosis Using Machine Learning Models
NCT06181799 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 80
Last updated 2025-08-15
Summary
This is a prospective, case-control, single-center, observational, non-randomized study. It is designed to evaluate the diagnostic accuracy of functional tests involving physical exertion monitored via a 12-lead ECG, combined with analysis of exhaled breath volatile organic compounds (VOCs) and single-lead ECG parameters.
Conditions
- Coronary Artery Disease
- Ischemic Heart Disease
- Chronic Coronary Disease
- Angina Pectoris
- Stable Coronary Artery Disease CAD
Interventions
- DIAGNOSTIC_TEST
-
Mass spectrometry using the PTR TOF-1000 (IONICON PTR-TOF-MS - Trace VOC Analyzer, Eduard-Bodem-Gasse 3, 6020 Innsbruck, Austria (Europe).
Once enrolled in the study, all participants are scheduled to undergo the following tests: Analysis of the exhaled breath volatile organic compounds using real-time analytical methods (PTR-TOF-MS-1000; real-time mass spectrometer with ionization by the proton transfer method) before and after the physical exertion test, during 1 minute. Machine learning models will be employed to analyze the patterns identified in the exhaled air volatilome data. Before and immediately after the physical exertion test, all participants are scheduled to record a single-lead ECG and pulse wave for 3 minutes, using a portable single-lead recorder (Cardio-Qvark) (Russia, Moscow). Single-lead ECG and pulse wave parameters will be analyzed using machine learning models.
Sponsors & Collaborators
-
I.M. Sechenov First Moscow State Medical University
lead OTHER
Principal Investigators
-
Philipp Kopylov, Professor · I.M. Sechenov First Moscow State Medical University (Sechenov University)
Eligibility
- Min Age
- 40 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2023-11-01
- Primary Completion
- 2024-06-10
- Completion
- 2024-06-10
Countries
- Russia
Study Locations
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