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Comparative Study
. 2019 Mar 1;4(3):256-264.
doi: 10.1001/jamacardio.2019.0035.

Prognostic Value of Vasodilator Stress Cardiac Magnetic Resonance Imaging: A Multicenter Study With 48 000 Patient-Years of Follow-up

John F Heitner  1 , Raymond J Kim  2 , Han W Kim  2 , Igor Klem  2 , Dipan J Shah  3 , Dany Debs  3 , Afshin Farzaneh-Far  4 , Venkateshwar Polsani  5 , Jiwon Kim  6 , Jonathan Weinsaft  6 , Chetan Shenoy  7 , Andrew Hughes  7 , Preston Cargile  8 , Jean Ho  1 , Robert O Bonow  9   10 , Elizabeth Jenista  2 , Michele Parker  2 , Robert M Judd  2
Affiliations
Comparative Study

Prognostic Value of Vasodilator Stress Cardiac Magnetic Resonance Imaging: A Multicenter Study With 48 000 Patient-Years of Follow-up

John F Heitner et al. JAMA Cardiol. .

Erratum in

  • Error in Conflict of Interest Disclosure.
    [No authors listed] [No authors listed] JAMA Cardiol. 2019 May 1;4(5):497. doi: 10.1001/jamacardio.2019.0951. JAMA Cardiol. 2019. PMID: 30969317 Free PMC article. No abstract available.

Abstract

Importance: Stress cardiac magnetic resonance imaging (CMR) is not widely used in current clinical practice, and its ability to predict patient mortality is unknown.

Objective: To determine whether stress CMR is associated with patient mortality.

Design, setting, and participants: Real-world evidence from consecutive clinically ordered CMR examinations. Multicenter study of patients undergoing clinical evaluation of myocardial ischemia. Patients with known or suspected coronary artery disease (CAD) underwent clinical vasodilator stress CMR at 7 different hospitals. An automated process collected data from the finalized clinical reports, deidentified and aggregated the data, and assessed mortality using the US Social Security Death Index.

Main outcomes and measures: All-cause patient mortality.

Results: Of the 9151 patients, the median (interquartile range) patient age was 63 (51-70) years, 55% were men, and the median (interquartile range) body mass index was 29 (25-33) (calculated as weight in kilograms divided by height in meters squared). The multicenter automated process yielded 9151 consecutive patients undergoing stress CMR, with 48 615 patient-years of follow-up. Of these patients, 4408 had a normal stress CMR examination, 4743 had an abnormal examination, and 1517 died during a median follow-up time of 5.0 years. Using multivariable analysis, addition of stress CMR improved prediction of mortality in 2 different risk models (model 1 hazard ratio [HR], 1.83; 95% CI, 1.63-2.06; P < .001; model 2: HR, 1.80; 95% CI, 1.60-2.03; P < .001) and also improved risk reclassification (net improvement: 11.4%; 95% CI, 7.3-13.6; P < .001). After adjustment for patient age, sex, and cardiac risk factors, Kaplan-Meier survival analysis showed a strong association between an abnormal stress CMR and mortality in all patients (HR, 1.883; 95% CI, 1.680-2.112; P < .001), patients with (HR, 1.955; 95% CI, 1.712-2.233; P < .001) and without (HR, 1.578; 95% CI, 1.235-2.2018; P < .001) a history of CAD, and patients with normal (HR, 1.385; 95% CI, 1.194-1.606; P < .001) and abnormal left ventricular ejection fraction (HR, 1.836; 95% CI, 1.299-2.594; P < .001).

Conclusions and relevance: Clinical vasodilator stress CMR is associated with patient mortality in a large, diverse population of patients with known or suspected CAD as well as in multiple subpopulations defined by history of CAD and left ventricular ejection fraction. These findings provide a foundational motivation to study the comparative effectiveness of stress CMR against other modalities.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr R. Kim reported grants from the National Heart, Lung, and Blood Institute during the conduct of the study and equity interest in Heart Imaging Technologies. Dr Weinsaft reported personal fees from Adverum Pharmaceuticals outside the submitted work and direction of a cardiac magnetic resonance imaging core lab for analysis of imaging data acquired as part of an industry sponsored study focused on Friedreich Ataxia. Dr Cargile reported grants and other support from National Institutes of Health during the conduct of the study and support from Heart Imaging Technologies outside the submitted work. Dr Jenista reported grants from Siemens during the conduct of the study and personal fees from HeartIT outside the submitted work. Dr Judd reported grants from National Institutes of Health during the conduct of the study and equity interest in Heart Imaging Technologies. All other authors have no conflicts of interest.

Figures

Figure 1.
Figure 1.. Automated Process of Data Collection
Each of the 7 hospitals used the same software for routine clinical cardiac magnetic resonance image interpretation (CMR) and reporting. The clinical data were then automatically deidentified and sent to the cloud database. EHR indicates electronic health record; HL7, health level 7 communication standard; SSDI, Social Security Death Index.
Figure 2.
Figure 2.. Kaplan-Meier Survival Curves for All Patients After Adjustment for Age, Sex, and Cardiac Risk Factors
The thinner lines indicate 95% confidence intervals. Numbers at bottom indicate patients at risk.
Figure 3.
Figure 3.. Kaplan-Meier Survival Curves for All Patients (N = 9151) in 8 Subpopulations After Adjustment for Patient Age, Sex, and Cardiac Risk Factors
CAD indicates coronary artery disease; LVEF, left ventricular ejection fraction.
See this image and copyright information in PMC

References

    1. Amsterdam EA, Wenger NK, Brindis RG, et al. . 2014 AHA/ACC Guideline for the management of patients with non–ST-elevation acute coronary syndromes. J Am Coll Cardiol. 2014;64(24):e139-e228. doi:10.1016/j.jacc.2014.09.017 - DOI - PubMed
    1. Yancy CW, Jessup M, Bozkurt B, et al. ; American College of Cardiology Foundation; American Heart Association Task Force on Practice Guidelines . 2013 ACCF/AHA Guideline for the management of heart failure. J Am Coll Cardiol. 2013;62(16):e147-e239. doi:10.1016/j.jacc.2013.05.019 - DOI - PubMed
    1. Nandalur KR, Dwamena BA, Choudhri AF, Nandalur MR, Carlos RC. Diagnostic performance of stress cardiac magnetic resonance imaging in the detection of coronary artery disease: a meta-analysis. J Am Coll Cardiol. 2007;50(14):1343-1353. doi:10.1016/j.jacc.2007.06.030 - DOI - PubMed
    1. Hamon M, Fau G, Née G, Ehtisham J, Morello R, Hamon M. Meta-analysis of the diagnostic performance of stress perfusion cardiovascular magnetic resonance for detection of coronary artery disease. J Cardiovasc Magn Reson. 2010;12:29. doi:10.1186/1532-429X-12-29 - DOI - PMC - PubMed
    1. Greenwood JP, Maredia N, Younger JF, et al. . Cardiovascular magnetic resonance and single-photon emission computed tomography for diagnosis of coronary heart disease (CE-MARC): a prospective trial. Lancet. 2012;379(9814):453-460. doi:10.1016/S0140-6736(11)61335-4 - DOI - PMC - PubMed

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