Trial Outcomes & Findings for Volatilome and Single-Lead Electrocardiogram Optimize Ischemic Heart Disease Diagnosis Using Machine Learning Models (NCT NCT06181799)
NCT ID: NCT06181799
Last Updated: 2025-08-15
Results Overview
Assessing the diagnostic accuracy of the stress electrocardiography test in ischemic heart disease
Recruitment status
COMPLETED
Target enrollment
80 participants
Primary outcome timeframe
The study was completed on 10.06.2024; the outcome measure was assessed during 6 months for the stress electrocardiography test
Results posted on
2025-08-15
Participant Flow
Participant milestones
| Measure |
Experimental Group
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
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|---|---|---|
|
Overall Study
STARTED
|
31
|
49
|
|
Overall Study
COMPLETED
|
31
|
49
|
|
Overall Study
NOT COMPLETED
|
0
|
0
|
Reasons for withdrawal
Withdrawal data not reported
Baseline Characteristics
Race and Ethnicity were not collected from any participant.
Baseline characteristics by cohort
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Total
n=80 Participants
Total of all reporting groups
|
|---|---|---|---|
|
Age, Continuous
|
59.93 years
STANDARD_DEVIATION 11.70 • n=31 Participants
|
53.96 years
STANDARD_DEVIATION 9.23 • n=49 Participants
|
56.28 years
STANDARD_DEVIATION 10.60 • n=80 Participants
|
|
Sex: Female, Male
Female
|
17 Participants
n=31 Participants
|
22 Participants
n=49 Participants
|
39 Participants
n=80 Participants
|
|
Sex: Female, Male
Male
|
14 Participants
n=31 Participants
|
27 Participants
n=49 Participants
|
41 Participants
n=80 Participants
|
|
Race and Ethnicity Not Collected
|
—
|
—
|
0 Participants
Race and Ethnicity were not collected from any participant.
|
|
Region of Enrollment
Russia
|
31 Participants
n=31 Participants
|
49 Participants
n=49 Participants
|
80 Participants
n=80 Participants
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 6 months for the stress electrocardiography testAssessing the diagnostic accuracy of the stress electrocardiography test in ischemic heart disease
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
|---|---|---|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of the Stress-ECG Test in Ischemic Heart Disease
AUC
|
0.507 Proportion probability
Interval 0.388 to 0.625
|
0.507 Proportion probability
Interval 0.388 to 0.625
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of the Stress-ECG Test in Ischemic Heart Disease
Sensitivity
|
0.484 Proportion probability
Interval 0.306 to 0.657
|
0.484 Proportion probability
Interval 0.306 to 0.657
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of the Stress-ECG Test in Ischemic Heart Disease
Specificity
|
0.531 Proportion probability
Interval 0.392 to 0.673
|
0.531 Proportion probability
Interval 0.392 to 0.673
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of the Stress-ECG Test in Ischemic Heart Disease
NPV NPV NPV NPV
|
0.619 Proportion probability
Interval 0.465 to 0.758
|
0.619 Proportion probability
Interval 0.465 to 0.758
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of the Stress-ECG Test in Ischemic Heart Disease
PPV
|
0.395 Proportion probability
Interval 0.238 to 0.553
|
0.395 Proportion probability
Interval 0.238 to 0.553
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 6 months for the obtained volatilome data.Analyze the volatile organic compounds of the exhaled breath in individuals with stress-induced myocardial perfusion defect on stress computed tomography myocardial perfusion imaging (CTP) with vasodilation test (adenosine triphosphate) and compare them with individuals without stress-induced myocardial perfusion defect after a physical stress test, and compare them with rest results as independent variables. Machine learning model was used to assess the diagnostic accuracy of the exhaled breath in the diagnosis of ischemic heart disease
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
|---|---|---|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Exhaled Breath Analysis for Ischemic Heart Disease
AUC
|
0.838 Proportion probability
Interval 0.736 to 0.914
|
0.838 Proportion probability
Interval 0.736 to 0.914
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Exhaled Breath Analysis for Ischemic Heart Disease
Sensitivity
|
0.839 Proportion probability
Interval 0.692 to 0.964
|
0.839 Proportion probability
Interval 0.692 to 0.964
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Exhaled Breath Analysis for Ischemic Heart Disease
Specificity
|
0.776 Proportion probability
Interval 0.666 to 0.889
|
0.776 Proportion probability
Interval 0.666 to 0.889
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Exhaled Breath Analysis for Ischemic Heart Disease
NPV
|
0.884 Proportion probability
Interval 0.771 to 0.975
|
0.884 Proportion probability
Interval 0.771 to 0.975
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Exhaled Breath Analysis for Ischemic Heart Disease
PPV
|
0.703 Proportion probability
Interval 0.559 to 0.849
|
0.703 Proportion probability
Interval 0.559 to 0.849
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 6 months for the single lead ECG parameters with pulse wave functionAnalyze the parameters of the single-lead electrocardiogram with pulse wave function in individuals with stress-induced myocardial perfusion defect on stress computed tomography myocardial perfusion imaging (CTP) with vasodilation test and compare them with individuals without stress-induced myocardial perfusion defect as an independent variable. Machine learning model was used to assess the diagnostic accuracy of the single-lead ECG with pulse wave function in the diagnosis of ischemic heart disease.
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
|---|---|---|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Single-Lead ECG With Pulse Wave Analysis in Ischemic Heart Disease
AUC
|
0.67 Proportion probability
Interval 0.53 to 0.801
|
0.67 Proportion probability
Interval 0.53 to 0.801
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Single-Lead ECG With Pulse Wave Analysis in Ischemic Heart Disease
Sensitivity
|
0.516 Proportion probability
Interval 0.333 to 0.695
|
0.516 Proportion probability
Interval 0.333 to 0.695
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Single-Lead ECG With Pulse Wave Analysis in Ischemic Heart Disease
Specificity
|
0.755 Proportion probability
Interval 0.628 to 0.88
|
0.755 Proportion probability
Interval 0.628 to 0.88
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Single-Lead ECG With Pulse Wave Analysis in Ischemic Heart Disease
NPV
|
0.712 Proportion probability
Interval 0.586 to 0.83
|
0.712 Proportion probability
Interval 0.586 to 0.83
|
|
Diagnostic Accuracy (AUC, Sensitivity, Specificity, NPV, PPV) of Single-Lead ECG With Pulse Wave Analysis in Ischemic Heart Disease
PPV
|
0.571 Proportion probability
Interval 0.387 to 0.758
|
0.571 Proportion probability
Interval 0.387 to 0.758
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 1 week for the total cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) data.Analyzing the taken blood samples for total cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) in individuals with stress-induced myocardial perfusion defect on stress computed tomography myocardial perfusion imaging (CTP) with vasodilation test and comparing them with individuals without stress-induced myocardial perfusion defect as independent variables.
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
|---|---|---|
|
Changes in the Concentration of Total Cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
Total cholesterol (mmol/L)
|
5.61 mmol/L
Standard Deviation 1.56
|
5.49 mmol/L
Standard Deviation 1.43
|
|
Changes in the Concentration of Total Cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
TG (mmol/L)
|
1.41 mmol/L
Standard Deviation 0.77
|
1.16 mmol/L
Standard Deviation 0.54
|
|
Changes in the Concentration of Total Cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
LDL (mmol/L)
|
3.46 mmol/L
Standard Deviation 1.08
|
3.27 mmol/L
Standard Deviation 0.96
|
|
Changes in the Concentration of Total Cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
HDL (mmol/L)
|
1.28 mmol/L
Standard Deviation 0.34
|
1.44 mmol/L
Standard Deviation 0.50
|
|
Changes in the Concentration of Total Cholesterol, TG (mmol/L), LDL (mmol/L), LDL (mmol/L), HDL (mmol/L), and VLDL (mmol/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
VLDL (mmol/L)
|
0.64 mmol/L
Standard Deviation 0.35
|
0.52 mmol/L
Standard Deviation 0.25
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 1 week for the Apolipoprotein В (g/L) data.Analyzing the taken blood samples for Apolipoprotein B (g/L) in individuals with stress-induced myocardial perfusion defect on stress computed tomography myocardial perfusion imaging (CTP) with vasodilation test and comparing them with individuals without stress-induced myocardial perfusion defect as independent variables.
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
|---|---|---|
|
Changes in the Concentration of Apolipoprotein B (g/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
|
1.19 g/L
Standard Deviation 0.35
|
1.08 g/L
Standard Deviation 0.27
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 1 week for the lipoprotein (а) (mg/L) and c-RP (mg/L) data.Analyzing the taken blood samples for lipoprotein (a) (mg/L) and C-RP (mg/L) in individuals with stress-induced myocardial perfusion defect on stress computed tomography myocardial perfusion imaging (CTP) with vasodilation test and comparing them with individuals without stress-induced myocardial perfusion defect as independent variables.
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
|---|---|---|
|
Changes in the Concentration of Lipoprotein (а) (mg/L) and c-RP (mg/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
lipoprotein (а) (mg/L)
|
213.22 mg/L
Standard Deviation 207.23
|
253.67 mg/L
Standard Deviation 252.70
|
|
Changes in the Concentration of Lipoprotein (а) (mg/L) and c-RP (mg/L) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
c-RP (mg/L)
|
3.81 mg/L
Standard Deviation 2.96
|
3.09 mg/L
Standard Deviation 3.33
|
PRIMARY outcome
Timeframe: The study was completed on 10.06.2024; the outcome measure was assessed during 1 week for the IL- 6 (pg/mL) data.Analyzing the taken blood samples for IL-6 (pg/mL) in individuals with stress-induced myocardial perfusion defect on stress computed tomography myocardial perfusion imaging (CTP) with vasodilation test and comparing them with individuals without stress-induced myocardial perfusion defect as independent variables.
Outcome measures
| Measure |
Experimental Group
n=31 Participants
The group is planned to include 31 people with myocardial perfusion defect on the stress computed tomography myocardial perfusion Imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
|
Control Group
n=49 Participants
The group is planned to include 49 people without myocardial perfusion defect on the stress computed tomography myocardial perfusion imaging (by using contrast enhanced multi-slice spiral computed tomography (CE-MSCT) using adenosine triphosphate (ATP)).
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.
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|---|---|---|
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Changes in the Concentration of IL- 6 (pg/mL) in Individuals With Stress-induced Myocardial Perfusion Defect vs. Without.
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0.88 pg/mL
Standard Deviation 0.91
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0.86 pg/mL
Standard Deviation 1.12
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Adverse Events
Experimental Group
Serious events: 0 serious events
Other events: 0 other events
Deaths: 0 deaths
Control Group
Serious events: 0 serious events
Other events: 0 other events
Deaths: 0 deaths
Serious adverse events
Adverse event data not reported
Other adverse events
Adverse event data not reported
Additional Information
Basheer Abdullah Marzoog
I.M. Sechenov First Moscow State Medical University (Sechenov University)
Phone: +7(996) 960 28 20
Email: [email protected]
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place