Detection of Coronary Artery Disease With Micro Electro-Mechanical Sensors
NCT ID: NCT04290091
Last Updated: 2025-07-14
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
930 participants
OBSERVATIONAL
2020-01-29
2023-12-31
Brief Summary
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Detailed Description
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A hallmark phenomenon in the development of CAD is the formation of arterial stenoses eventually limiting the arterial circulation. Myocardial ischemia caused by the stenoses may present symptoms considered typical, i.e, angina pectoris chest pain, but the symptoms may vary up to an asymptomatic state. Estimating the pre-test likelihood of angiographically significant CAD (≥50% diameter stenotic CAD) is a fundamental component in the initial evaluation of symptomatic patients presenting with suspected CAD. This determination directly influences subsequent decisions for noninvasive diagnostic testing and treatment. However, studies have shown a relatively low prevalence of either ischemia or obstructive CAD on noninvasive imaging and invasive angiography (IA) in this population. Therefore, additional methods are needed to improve patient selection for such testing.
Mechanocardiography (MCG) assesses the condition of the heart by measuring the mechanical activity (cardiac muscle motion) of the heart from the surface of thorax. MCG can be measured with accelerometer and gyroscope which react to recoil and vibration caused my cardiac contraction.
This study aims to validate how the gyroscope and accelerometer derived parameters can identify patients with hemodynamically significant CAD in combined contrast computed tomography (CT) coronary angiography and positron emission tomography (PET) perfusion imaging in combination of high-sensitive troponin testing. The performance of different MCG algorithms will be tested offline as a head-to-head comparison with medical history, cardiovascular events, high-sensitive troponin values, coronary computed tomography angiography (CCTA) and PET scan results.
Conditions
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Study Design
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COHORT
CROSS_SECTIONAL
Study Groups
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Patients with CAD
Patients who have hemodynamically significant CAD.
No interventions assigned to this group
Patients without CAD
Patients who don't have hemodynamically significant CAD.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* Patients visiting hospital for suspected CAD and undergoing CCTA
* Signed informed consent as an acceptance to participate to the trial
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Precordior Ltd
INDUSTRY
Responsible Party
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Principal Investigators
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Juhani Knuuti, MD, PhD
Role: PRINCIPAL_INVESTIGATOR
Turku University Hospital
Locations
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Turku University Hospital
Turku, , Finland
Countries
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References
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Haddad F, Saraste A, Santalahti KM, Pankaala M, Kaisti M, Kandolin R, Simonen P, Nammas W, Jafarian Dehkordi K, Koivisto T, Knuuti J, Mahaffey KW, Blomster JI. Smartphone-Based Recognition of Heart Failure by Means of Microelectromechanical Sensors. JACC Heart Fail. 2024 Jun;12(6):1030-1040. doi: 10.1016/j.jchf.2024.01.022. Epub 2024 Apr 3.
Other Identifiers
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DECADE
Identifier Type: -
Identifier Source: org_study_id
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