Arterial Stiffness for Improved Prediction of Coronary Artery Disease by Coronary CT Angiography

Pulse Wave Velocity and Machine Learning for Prediction of Coronary Artery Disease by Coronary CT Angiography - The Heart Waves Study

This study will evaluate the ability of device-estimated pulse wave velocity and machine learning methods to improve the prediction of potential symptomatic coronary artery disease

Study Overview

• Status: Terminated
• Conditions: Coronary Artery Disease; Chest Pain; Dyspnea; Arterial Stiffness
• Intervention / Treatment: Diagnostic test: Coronary computer tomography angiography (CCTA); Other: Photoplethysmography (PPG) and single-lead ECG; Device: Brachial single cuff-based arterial stiffness

Detailed Description

In stable patients with suspected symptomatic coronary artery disease, an estimation of pre-test probability (PTP) and a clinical assessment are used to decide who should be investigated further. PTP has historically been based on age, sex, the nature of chest pain or dyspnea as angina equivalent. It is recommended to continue investigation of all with PTP ≥15%, but also to consider investigation at PTP 5-15% (low-intermediate risk) which is the majority of patients. Despite updates to PTP estimations in the 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes, it has been shown that they overestimate the risk of coronary artery disease.

In 2024, the ESC Guidelines were updated to recommend an updated clinical assessment method, the risk factor-weighted clinical likelihood (RF-CL), which is based on symtoms and number of risk factors. It has been shown to have better predictive ability compared to PTP alone, but is still largely based on epidemiological data, which may not be valid for all individuals.

Coronary computer tomography angiography (CCTA) is the method becoming increasingly established at low-intermediate risk. An initial, non-invasive strategy with CCTA compared to invasive or more advanced examinations is safe and simple. At the same time, CCTA is resource-intensive, with limited availability, and the examination involves both contrast, radiation and incidental findings. Thus, there is a need to improve the risk estimation.

Arterial stiffness assessed by pulse wave velocity is an independent marker for cardiovascular events and has been shown to be independently associated with the degree of coronary artery disease. Arterial stiffness is, however, rarely measured in the clinic as it traditionally has required cumbersome procedures. Newer methods include the brachial single cuff-based Arteriograph and the optical technique photoplethysmography (PPG), widely available in healthcare pulse oximeters, but increasingly also in different consumer devices, often complemented by single-lead ECG.

The main aim of this study is to evaluate arterial stiffness and its possible role to improve risk stratification of patients undergoing CCTA for potential coronary artery disease.

• Study Type: Observational
• Enrollment (Actual): 156

Contacts and Locations

Study Locations

• Sweden
  • Stockholm, Sweden
    • Danderyd University Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients undergoing coronary CTA to investigate potential symptomatic coronary artery disease

Description

Inclusion Criteria:

• Patients undergoing coronary computer tomography angiography to investigate stable suspected symptomatic coronary artery disease.
• Age 30 to <70 years of age.

Exclusion Criteria:

• Known coronary artery disease (prior myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft or any angiographic evidence of coronary artery disease ≥50% lesion in a major epicardial vessel).
• Known significant cardiac (> moderate valvular disease, heart failure with reduced ejection fraction, hypertrophic cardiomyopathy, or congenital heart disease), or pulmonary condition which could explain symptoms.
• Known ongoing atrial fibrillation/flutter.
• No Swedish social security number.
• Unable to provide written informed consent.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥3	Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥3 when adding photoplethysmography (PPG) estimated arterial stiffness to the standard model (including age, sex, symtom score [0-3] and number of risk factors [0-5]). Coronary artery disease reporting and data system (CAD-RADS) ≥3 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.	Typically within 1 month of enrollment

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥2	Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding photoplethysmography (PPG) estimated arterial stiffness to models with traditional risk factors for coronary artery disease. Coronary artery disease reporting and data system (CAD-RADS) ≥2 refers to the classification of coronary artery disease with at least mild 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.	Typically within 1 month of enrollment
Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥3 by Arterigraph	Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥3 when adding Arteriograph-estimated arterial stiffness to the standard model (including age, sex, symtom score [0-3] and number of risk factors [0-5]). Coronary artery disease reporting and data system (CAD-RADS) ≥3 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.	Typically within 1 month of enrollment
Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥2 by Arterigraph	Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding Arteriograph-estimated arterial stiffness to models with traditional risk factors for coronary artery disease. Coronary artery disease reporting and data system (CAD-RADS) ≥2 refers to the classification of coronary artery disease with at least mild 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.	Typically within 1 month of enrollment
Improved area under receiver operating curve (ROC) to predict Coronary artery calcium score	Improved area under receiver operating curve (ROC) to predict coronary artery calcium (CAC) score when adding photoplethysmography (PPG) or Arteriograph estimated arterial stiffness to models with traditional risk factors for coronary artery disease. PPG-ECG signals used in machine learning and advanced modelling may further improve the prediction. The coronary artery calcium (CAC) score is a measure of the amount of calcified plaque in the coronary arteries, as identified on coronary computer tomography angiography. Higher CAC scores are associated with increased risk of coronary artery disease and future cardiovascular events.	Typically within 1 month of enrollment
Number of patients diagnosed with acute or chronic coronary artery disease	As safety outcome; proportion of those who our model estimated as low risk and then diagnosed with acute or chronic coronary artery disease in the year following inclusion in the study.	1 year after enrollment
Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥3 by adding ECG	Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding estimated arterial stiffness and machine-learning interpretation of ECG to the standard model (including age, sex, symtom score [0-3] and number of risk factors [0-5]).	Typically within 1 month of enrollment
Machine learning analysis of photoplethysmography to predict CAD-RADS ≥2	Improved area under receiver operating curve (ROC) to predict CAD-RADS ≥2 when adding machine-learning interpretation of the photoplethysmography (PPG) signal to models based on traditional risk factors for coronary artery disease.	Typically within 1 month of enrollment
Machine learning analysis of photoplethysmography to predict aortic stenosis	Machine learning analysis of photoplethysmography (PPG) to predict the presense of aortic stenosis (mild-moderate-severe) on cardiac ultrasound.	Typically within 1 month of enrollment
Machine learning analysis of photoplethysmography to predict cardiac function	Machine learning analysis of photoplethysmography (PPG) to predict systolic and diastolic cardiac function assessed by cardiac ultrasound.	Typically within 1 month of enrollment

Collaborators and Investigators

• Sponsor: Danderyd Hospital
• Collaborators: KTH Royal Institute of Technology
• Investigators: Principal Investigator: Jonas Spaak, MD, PhD, Karolinska Institutet, Department of Clinical Sciences, Danderyd Hospital, Division of Cardiovascular Medicine, Stockholm, Sweden

Study record dates

Study Major Dates

• Study Start (Actual): October 24, 2023
• Primary Completion (Actual): July 1, 2025
• Study Completion (Actual): July 1, 2025

Study Registration Dates

• First Submitted: April 3, 2024
• First Submitted That Met QC Criteria: December 12, 2024
• First Posted (Actual): December 16, 2024

Study Record Updates

• Last Update Posted (Actual): April 17, 2026
• Last Update Submitted That Met QC Criteria: April 14, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Arterial Stiffness; Pulse Wave Velocity; Machine Learning; PPG; CAD-RADS; CACS
• Additional Relevant MeSH Terms: Pain; Neurologic Manifestations; Vascular Diseases; Cardiovascular Diseases; Heart Diseases; Respiratory Tract Diseases; Respiration Disorders; Signs and Symptoms, Respiratory; Arteriosclerosis; Arterial Occlusive Diseases; Coronary Disease; Myocardial Ischemia; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Coronary Artery Disease; Dyspnea; Chest Pain; serglycin
• Other Study ID Numbers: HW2

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No