Role of Cardioflux in Predicting Coronary Artery Disease (CAD) Outcomes

NCT ID: NCT03968809

Last Updated: 2023-02-23

Study Results

Results pending

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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Recruitment Status

COMPLETED

Total Enrollment

101 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-09-05

Study Completion Date

2020-06-20

Brief Summary

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This single-center clinical trial is designed to evaluate the CardioFlux magnetocardiograph diagnostic imaging system to predict major adverse cardiac events (MACE) in patients referred for evaluation for coronary artery disease.

Detailed Description

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This is a single-center, prospective, observational cohort trial to form a registry data set. Patients presenting for cardiac stress testing utilizing Single Photon Emission Computed Tomography (SPECT), cardiac CT angiography (CCTA), or cardiac catheterization will be offered to enroll in the registry and provide informed consent to undergo imaging with a CardioFlux magnetocardiography (MCG) prior to their procedure.

Multiple studies have shown that MCG accuracy is quite high in identifying patients with symptomatic coronary artery disease. This difference is dramatic enough to prove superiority over standard ECGs in diagnosis of vital ischemic and infarction parameters. Genetesis presents a novel MCG analysis system called CardioFlux (CF). This modality takes less than five minutes to complete, is radiation-free, and is an easy to operate system. This clinical trial will enroll patients of all cardiac risk levels presenting for various modalities of cardiac diagnostic testing to have CardioFlux scanning in addition to standard of care. Results will be interpreted and compared to the immediate results of nuclear (SPECT) stress testing, cardiac CT angiography, or cardiac catheterization.

Participants will be followed up at 30 days and 1 year via phone call or chart review. 30 day and 1 year MACE will be recorded and correlated with initial CardioFlux MCG results. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy will be calculated of CardioFlux relative to the incidence of MACE, and in comparison to the above diagnostic modalities.

Conditions

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Coronary Artery Disease

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Standard Coronary Artery Disease Screening

All patients presenting for standard coronary artery disease screening will undergo additional imaging with CardioFlux MCG. These patients will be followed longitudinally for short and long term MACE.

CardioFlux Magnetocardiography

Intervention Type DIAGNOSTIC_TEST

All patients enrolled and receiving standard screening tests for CAD will undergo a 2 minute scan with MCG. It will be determined if MCG scanning can provide equal or superior accuracy to predict MACE than standard testing.

Interventions

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CardioFlux Magnetocardiography

All patients enrolled and receiving standard screening tests for CAD will undergo a 2 minute scan with MCG. It will be determined if MCG scanning can provide equal or superior accuracy to predict MACE than standard testing.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* ≥ 18 years of age at the time of enrollment.
* Patient presenting for cardiac stress testing, cardiac CT angiography (CCTA), or cardiac catheterization.
* Consents to having an magnetocardiogram-CardioFlux study scan.

Exclusion Criteria

* \< 18 years of age
* Patients unable to fit into device
* Non-ambulatory patients
* Patients with implanted cardiac pacemakers/defibrillators
* Positive response on provided Metallic/Ferromagnetic Device Screening Form
* Atrial fibrillation with rapid ventricular response
* Patients with other sustained or incessant arrhythmias
* Patients with claustrophobia or unable to lie supine for 2 minutes
* Patients require supplemental oxygen at home
* Presence or reasonable clinical suspicion of any acute coronary syndrome for which delayed intervention could increase the risk or magnitude of damaged myocardium
* Patients scheduled for cardiac catheterization with indication of valvular disease
* Poor candidate for follow-up (e.g. no access to phone)
* Prisoners
* Repeat participants
* Patients participate in other research studies
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Genetesis Inc.

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Partho P Sengupta, M.D.

Role: PRINCIPAL_INVESTIGATOR

WVU Heart and Vascular Institute, J.W. Ruby Memorial Hospital

Locations

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J.W. Ruby Memorial Hospital

Morgantown, West Virginia, United States

Site Status

Countries

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United States

References

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Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, de Ferranti SD, Floyd J, Fornage M, Gillespie C, Isasi CR, Jimenez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu S, Longenecker CT, Mackey RH, Matsushita K, Mozaffarian D, Mussolino ME, Nasir K, Neumar RW, Palaniappan L, Pandey DK, Thiagarajan RR, Reeves MJ, Ritchey M, Rodriguez CJ, Roth GA, Rosamond WD, Sasson C, Towfighi A, Tsao CW, Turner MB, Virani SS, Voeks JH, Willey JZ, Wilkins JT, Wu JH, Alger HM, Wong SS, Muntner P; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart Disease and Stroke Statistics-2017 Update: A Report From the American Heart Association. Circulation. 2017 Mar 7;135(10):e146-e603. doi: 10.1161/CIR.0000000000000485. Epub 2017 Jan 25. No abstract available.

Reference Type BACKGROUND
PMID: 28122885 (View on PubMed)

Chaikovsky I, Hailer B, Sosnytskyy V, Lutay M, Mjasnikov G, Kazmirchuk A, Bydnyk M, Lomakovskyy A, Sosnytskaja T. Predictive value of the complex magnetocardiographic index in patients with intermediate pretest probability of chronic coronary artery disease: results of a two-center study. Coron Artery Dis. 2014 Sep;25(6):474-84. doi: 10.1097/MCA.0000000000000107.

Reference Type BACKGROUND
PMID: 24667125 (View on PubMed)

Goernig M, Liehr M, Tute C, Schlosser M, Haueisen J, Figulla HR, Leder U. Magnetocardiography based spatiotemporal correlation analysis is superior to conventional ECG analysis for identifying myocardial injury. Ann Biomed Eng. 2009 Jan;37(1):107-11. doi: 10.1007/s10439-008-9598-5. Epub 2008 Nov 18.

Reference Type BACKGROUND
PMID: 19015988 (View on PubMed)

Kwong JS, Leithauser B, Park JW, Yu CM. Diagnostic value of magnetocardiography in coronary artery disease and cardiac arrhythmias: a review of clinical data. Int J Cardiol. 2013 Sep 1;167(5):1835-42. doi: 10.1016/j.ijcard.2012.12.056. Epub 2013 Jan 19.

Reference Type BACKGROUND
PMID: 23336954 (View on PubMed)

Li Y, Che Z, Quan W, Yuan R, Shen Y, Liu Z, Wang W, Jin H, Lu G. Diagnostic outcomes of magnetocardiography in patients with coronary artery disease. Int J Clin Exp Med. 2015 Feb 15;8(2):2441-6. eCollection 2015.

Reference Type BACKGROUND
PMID: 25932186 (View on PubMed)

Lim HK, Kwon H, Chung N, Ko YG, Kim JM, Kim IS, Park YK. Usefulness of magnetocardiogram to detect unstable angina pectoris and non-ST elevation myocardial infarction. Am J Cardiol. 2009 Feb 15;103(4):448-54. doi: 10.1016/j.amjcard.2008.10.013. Epub 2008 Dec 25.

Reference Type BACKGROUND
PMID: 19195500 (View on PubMed)

Her AY, Park JW. Repolarization Heterogeneity of Magnetocardiography Predicts Long-Term Prognosis in Patients with Acute Myocardial Infarction. Yonsei Med J. 2016 Nov;57(6):1305-6. doi: 10.3349/ymj.2016.57.6.1305. No abstract available.

Reference Type BACKGROUND
PMID: 27593855 (View on PubMed)

Bang WD, Kim K, Lee YH, Kwon H, Park Y, Pak HN, Ko YG, Lee M, Joung B. Repolarization Heterogeneity of Magnetocardiography Predicts Long-Term Prognosis in Patients with Acute Myocardial Infarction. Yonsei Med J. 2016 Nov;57(6):1339-46. doi: 10.3349/ymj.2016.57.6.1339.

Reference Type BACKGROUND
PMID: 27593860 (View on PubMed)

Motwani M, Dey D, Berman DS, Germano G, Achenbach S, Al-Mallah MH, Andreini D, Budoff MJ, Cademartiri F, Callister TQ, Chang HJ, Chinnaiyan K, Chow BJ, Cury RC, Delago A, Gomez M, Gransar H, Hadamitzky M, Hausleiter J, Hindoyan N, Feuchtner G, Kaufmann PA, Kim YJ, Leipsic J, Lin FY, Maffei E, Marques H, Pontone G, Raff G, Rubinshtein R, Shaw LJ, Stehli J, Villines TC, Dunning A, Min JK, Slomka PJ. Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis. Eur Heart J. 2017 Feb 14;38(7):500-507. doi: 10.1093/eurheartj/ehw188.

Reference Type BACKGROUND
PMID: 27252451 (View on PubMed)

Other Identifiers

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1902469303

Identifier Type: -

Identifier Source: org_study_id

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