Coronary Arterial Disease (CAD), Arterial Stiffness, Aortic Valve Disease, Heart Failure
Conditions
Brief summary
This clinical investigation will evaluate a novel contactless technology for assessing arterial stiffness and pulse wave characteristics and explore its potential in assessment of coronary artery disease, aortic stenosis and heart failure, in a population-based sample aged 58-72 years. It will be the first in clinical setting, pilot stage, observational investigation to evaluate the clinical safety, performance and diagnostic accuracy of Cardio P4, a laser-doppler vibrometry (LDV) and microwave radar-based device.
Detailed description
Cardiovascular disease (CVD) is the leading cause of death globally, placing a large burden on the healthcare system. In asymptomatic individuals, there exists several risk scores to predict cardiovascular events (like SCORE2, SCORE2-OP and Framinham Risk Score). In patients with suspected symptoms of coronary artery disease, the European Society of Cardiology advice to estimate the pre-test probability by the risk factor-weighted clinical likelihood (RF-CL). Most of these scores include the key factors for CAD development including age, sex, LDL- (or non-HDL) cholesterol, diabetes, smoking history, blood pressure or hypertension. Coronary computed tomography angiography (CCTA) is one of the main recommended examinations at low-intermediary risk based on PTP. While the procedure is non-invasive and relatively safe in comparison to invasive alternatives, they still represent a risk to the patient by radiation exposure and incidental findings, and is associated with lack of availability. One key issue is that once a patient has a CCTA performed showing coronary atherosclerosis, that entails optimized prevention, with solid evidence. However, patients without symptoms of CAD are less studied regarding the degree of CAD. The present SCAPIS trial is the largest such trial on CCTA in 30 000 patients age 50 to 64 years, 25 182 individuals without known coronary heart disease were included. In these asymptomatic persons, CCTA-detected atherosclerosis was found in 42.1% and a significant stenosis (≥50%) in 5.2%. Arterial stiffness, commonly assessed as pulse wave velocity (PWV), is a marker of aging of the cardiovascular system, and is independently associated with coronary artery disease. Increased arterial stiffness is an early indicator of cardiovascular disease and may improve precision in risk stratification. Laser-Doppler and microwave radar are new promising methods for analysis of pulse waves in human blood vessels. The technology may be more suitable for screening through enabling lower operator dependence and faster assessment time in comparison to standard assessment methods, and may contribute to lower overall healthcare costs and improved precision in identification of CVD. Analysis of the pulse waveform characteristics such as time intervals and acceleration may in addition to PWV be useful as predictors of risk. We have shown that specific features from the early phase of the waveform (amplitude ratio) are most predictive when analysing similar pressure waveforms captured from the peripheral arteries (by photoplethysmography). Cardiac timings extracted from a pulse waveform such as left ventricular ejection time and pre-ejection period are independent predictors of diseases such as aortic valve stenosis and heart failure, and may provide an effective method for risk estimation. The most common methods today for diagnosis of cardiac disease (such as aortic stenosis, heart failure) include laboratory tests, assessment of symptoms and echocardiography. Echocardiography is non-invasive, but has high reliance on operator skill which may cause variability in image acquisition and interpretation. Machine-learning of many waveform features simultaneously, or feature-less analysis using neural networks and language-model driven analysis, may further improve the prediction. The main aim of the study is to evaluate the potential value of a novel laser-radar-based vibrometer technology that can measure among several features arterial stiffness, and its possible role to improve risk stratification of coronary artery disease. Secondary aims include to evaluate cardiac timings using laser doppler vibrometry for a possible role to improve risk stratification of patients with aortic stenosis and systolic or diastolic dysfunction.
Interventions
DIAGNOSTIC_TESTCoronary Computer Tomography (CCTA)
Use of standard equipment for usual care
OTHERLaser Doppler Vibrometry and single-lead ECG
Physiological data acquisition equipment
DEVICEEchocardiography
GE Vivid E95
DEVICEPulse Wave Velocity
Arteriograph, Tensiomed, Hungary
Sponsors
HJN Sverige AB/Neko Health
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
58 Years to 72 Years
Healthy volunteers
Yes
Inclusion criteria
* Subjects already included in the main / general SCAPIS 2 study at Danderyd Hospital in Stockholm, and of which has also participated in the echocardiography examination
Exclusion criteria
* Patients unable to provide an informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Area under receiver operating curve (ROC) to predict CAD-RADS ≥2 | Typically within 2 months of enrolment | Change in area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding Vibrometer-based SSN femoral PWV to the standard risk factors. Coronary artery disease reporting and data system (CAD-RADS) ≥2 refers to the classification of coronary artery disease with at least moderate stenosis as identified on coronary computer tomography angiography. The classification follows the CAD-RADS 2.0 definition. Stenosis is graded in severity from 0-5. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Area under receiver operating curve (ROC) to predict CAD-RADS ≥2 | Typically within 2 months of enrolment | Change in area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding Vibrometer-based amplitude-ratio from the early phase of the waveform to the standard risk factors. |
| Area under receiver operating curve (ROC) to predict CAD-RADS ≥2 stratified by sex | Typically within 2 months of enrolment | Prespecified subgroup analysis stratified by sex. Change in area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding Vibrometer-based SSN femoral PWV to the standard risk factors. |
| Area under receiver operating curve (ROC) to predict CAD-RADS ≥2 stratified by body mass index strata | Typically within 2 months of enrolment | Prespecified subgroup analysis stratified by body mass index strata. Change in area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding Vibrometer-based SSN femoral PWV to the standard risk factors. |
| Correlation between vibrometer-based PWA from the suprasternal notch and PWV by Arteriograph | Typically within 2 months of enrolment | Vibrometer-based PWA (e.g. LVET, PEP) derived from the SSN in relation to PWV acquired by Arteriograph (Tensiomed Inc). |
| Correlation between vibrometer-based PWA from the suprasternal notch and CAD-RADS score | Typically within 2 months of enrolment | Vibrometer-based PWA (e.g. LVET, PEP) derived from the SSN in relation to degree of coronary artery disease by CAD-RADS. |
| Correlation between pressure sensor (piezo) based PWV and CAD-RADS score | Typically within 2 months of enrolment | Peripheral pressure sensor (piezo) based PWA (such as shape and properties) from sensors on the hands and feet in relation to degree of coronary artery disease by CAD-RADS |
| Correlation between vibrometer-based LVET and degree of aortic valve calcification | Same day as enrolment | Vibrometer-based LVET in relation to degree of aortic valve calcification, where degree of calcification is assessed by X-ray computed tomography (CT) as a standardised score. |
| Correlation between vibrometer-based PEP/LVET and degree of aortic valve calcification | Same day as enrolment | Vibrometer-based PEP/LVET ratio in relation to degree of aortic valve calcification, where degree of calcification is assessed by X-ray CT as a standardised score. |
| Area under receiver operating curve (ROC) to predict CAD-RADS ≥3 | Typically within 2 months of enrolment | Change in area under receiver operating curve (ROC) to predict CAD-RADS ≥3 when adding Vibrometer-based SSN femoral PWV to the standard risk factors. |
| Machine learning analysis of Vibrometer signals | Typically within 2 months of enrolment | Change in area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding machine-learning interpretation of the Vibriometry-signal to models based on traditional risk factors for coronary artery disease. |
| Correlation between vibrometer-based PWV and left ventricular mass index | Same day as enrolment | Vibrometer-based SSN-femoral PWV in relation to left ventricular mass index (LVMI), as assessed by echocardiography. LVMI is the left ventricular mass indexed by the total body surface area, it has been associated with coronary artery disease events. |
| Correlation between vibrometer-based left ventricular ejection time and left ventricular ejection fraction | Same day as enrolment | Vibrometer-based left ventricular ejection time (LVET), derived by quantifying aortic valve opening and closure at the SSN, in relation to left ventricular ejection fraction (LVEF). |
| Correlation between vibrometer-based PEP/LVET ratio and LVEF | Same day as enrolment | Ratio of vibrometer-based pre-ejection period (PEP) and LVET in relation to LVEF. PEP is the time from depolarization to aortic opening, LVET is the timing from aortic opening to closure. The ratio is associated with cardiovascular outcomes, such as heart failure. |
| Correlation between vibrometer-based LVET and degree of aortic stenosis | Same day as enrolment | Vibrometer-derived LVET in relation to degree of aortic stenosis, where degree of stenosis is assessed by echocardiography as a score 0-4 (0 = no sign, 4 = severe). The alternative to use DVI ratio instead of this score will also be evaluated. |
| Correlation between vibrometer-based PEP/LVET ratio and degree of aortic stenosis | Same day as enrolment | Vibrometer-derived PEP/LVET ratio in relation to degree of aortic stenosis, where degree of stenosis is assessed by echocardiography as a score 0-4 (0 = no sign, 4 = severe). The alternative to use doppler velocity index (DVI) instead of this score will also be evaluated. DVI is a doppler echocardiographic index, it is in the context of aortic stenosis calculated as the ratio of maximum velocity across the left ventricular outflow tract (LVOT) and the maximum velocity across the aortic valve obtained by continuous-wave doppler. It is a dimensionless index. |
| Correlation between vibrometer-based LVET and markers of diastolic dysfunction | Same day as enrolment | Vibrometer-based LVET in relation to diastolic dysfunction, assessed by E/é, left ventricular mass index (LVMI) and left atrial volume (LAVi) from echocardiography. E/é is the ratio between early mitral inflow velocity and mitral annular early diastolic velocity. LVMI is the mass of the left ventricle indexed by the body surface area. LAVi is the left atrial volume indexed by the body surface area. All are dimensionless ratios which are associated with severity of diastolic dysfunction. |
| Correlation between vibrometer-based PEP/LVET markers of diastolic dysfunction | Same day as enrolment | Vibrometer-based PEP/LVET ratio in relation to diastolic dysfunction, assessed by E/é, LVMI and left atrial volume from echocardiography. |
| Correlation between vibrometer-based PWV and CAC score | Typically within 2 months of enrolment | Vibrometer-based SSN-femoral PWV in relation to coronary artery calcium (CAC) score. The CAC score is a measure of amount of calcified plaque in the coronary arteries, measured using CCTA. The CAC score is associated with increased coronary artery disease risk and future cardiovascular events. |
Countries
Sweden
Contacts
Primary ContactMattias Windå
Outcome results
None listed