cPSTA System CADLAD Study

Coronary Artery Disease Clinical Trial

— CADLAD  

Official title:

Cardiac Phase Space Tomography Analysis (cPSTA) System: Coronary Artery Disease Learning and Development Study

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02784197
• Other study ID #: BSA-CD-001
• Status: Completed
• Phase: N/A
• Start date: May 2016
• Est. completion date: May 2018

Study information

• Verified date: June 2019
• Source: Analytics For Life
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This study is primarily designed to collect resting phase signals from eligible subjects using the Phase Signal Recorder (PSR) prior to coronary angiography to machine learn and test an algorithm for detecting the presence of significant coronary artery disease in symptomatic adult patient.

Description:

This clinical protocol is primarily designed to collect resting phase signals from eligible subjects using the Phase Signal Recorder (PSR) prior to coronary angiography to machine learn and test an algorithm for detecting the presence of significant coronary artery disease in symptomatic adult patient. In addition to this primary objective, machine-learned algorithms will be developed and tested to report the left ventricular ejection fraction and to identify the location of significant coronary artery disease. The performance of the machine-learned algorithm will be evaluated using a comparative paired trial design. In this study, the physician will not be provided the results of analysis performed and, accordingly, the results of the analyses will not be used to guide treatment decisions for the patient.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 2622
• Est. completion date: May 2018
• Est. primary completion date: December 2017
• Accepts healthy volunteers: No
• Gender: All
• Age group: 21 Years and older

Eligibility

Inclusion Criteria:

1. Age =21 years of age at the time of screening

2. Meets criteria for coronary angiography

3. Scheduled to undergo cardiac catheterization with coronary angiography

4. Ability to understand the requirements of the study and to provide written informed consent

Exclusion Criteria:

1. Prior documented myocardial infarction (MI)

2. Prior coronary artery bypass grafting (CABG) or previous coronary interventions (PCI)

3. Indication for invasive coronary angiography other than to assess for obstructive CAD (e.g., arrhythmia, cardiomyopathy, valvular abnormality)

4. Previous heart valve replacement

5. Previous sustained or paroxysmal atrial or ventricular arrhythmia

6. Infiltrative myocardial disease (Amyloid, Sarcoid, Right ventricular dysplasia)

7. Presence of cardiac implantable electronic device (CIED), including implantable cardioverter defibrillator (ICD), pacemaker (PM), implantable loop recorders and other monitors

8. Implantable Neuro-stimulators

9. Congenital Heart Disease

10. Pregnancy (breast feeding)

11. Currently taking any Type IA, IC or III antiarrhythmic

12. Any history of Amiodarone therapy

13. Clinically significant chest deformity (e.g., pectus excavatum or pectus carnitatum)

14. Breast implants

15. Neuromuscular Disease if the condition results in tremor or muscle fasciculations

Related Conditions & MeSH terms

• Coronary Artery Disease
• Coronary Disease
• Myocardial Ischemia

Intervention

Device:
• Phase Signal Recorder
The cPSTA System is a medical device system that uses passive tomography to analyze a patient's phase space data to identify the presence of significant coronary artery disease. The cPSTA System consists of several components that work together to obtain, transmit, analyze the data, and display the results, including the Phase Signal Acquisition System (PSAQ System), which is the Phase Signal Recorder (PSR) and the Phase Signal Data Repository (PSDR); analytical software; and secure web portal. For this study only the PSAQ System is used by the clinical site for the purposes of acquiring and transmitting the signal.

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Analytics For Life

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Machine-learned algorithm	Develop and test a machine-learned algorithm which maximizes the area under the receiver-operating characteristic (AUC-ROC) curve to 0.70 (expected) and clinically significant sensitivity and specificity to detect CAD when compared to clinical diagnosis of significant coronary artery disease (i.e., presence of =70% stenosis by angiography or reduced fraction flow of <=0.80) in at least one of the major coronary arteries (LMA, LAD, RCA, or LCX) or their distributions.	7 day