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Am Heart J. 2016 Apr;174:138-46. doi: 10.1016/j.ahj.2016.01.012. Epub 2016 Jan 23.

Cardiovascular outcomes after pharmacologic stress myocardial perfusion imaging.

Author information

1
Robert J. Burns Nuclear Cardiology Laboratory, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging and Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, Canada; Institute for Clinical Evaluative Sciences, University of Toronto, Toronto, Canada. Electronic address: dlee@ices.on.ca.
2
Robert J. Burns Nuclear Cardiology Laboratory, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging and Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, Canada; Ted Rogers Centre for Heart Research, University of Toronto, Toronto, Canada.
3
Institute for Clinical Evaluative Sciences, University of Toronto, Toronto, Canada.
4
Robert J. Burns Nuclear Cardiology Laboratory, University of Toronto, Toronto, Canada; Joint Department of Medical Imaging and Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, Canada.

Abstract

BACKGROUND:

While pharmacologic stress single photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) is used for noninvasive evaluation of patients who are unable to perform treadmill exercise, its impact on net reclassification improvement (NRI) of prognosis is unknown.

METHODS:

We evaluated the prognostic value of pharmacologic stress MPI for prediction of cardiovascular death or non-fatal myocardial infarction (MI) within 1 year at a single-center, university-based laboratory. We examined continuous and categorical NRI of pharmacologic SPECT-MPI for prediction of outcomes beyond clinical factors alone.

RESULTS:

Six thousand two hundred forty patients (median age 66 years [IQR 56-74], 3466 men) were studied and followed for 5963 person-years. SPECT-MPI variables associated with increased risk of cardiovascular death or non-fatal MI included summed stress score, stress ST-shift, and post-stress resting left ventricular ejection fraction ≤50%. Compared to a clinical model which included age, sex, cardiovascular disease, risk factors, and medications, model χ(2) (210.5 vs. 281.9, P < .001) and c-statistic (0.74 vs. 0.78, P < .001) were significantly increased by addition of SPECT-MPI predictors (summed stress score, stress ST-shift and stress resting left ventricular ejection fraction). SPECT-MPI predictors increased continuous NRI by 49.4% (P < .001), reclassifying 66.5% of patients as lower risk and 32.8% as higher risk of cardiovascular death or non-fatal MI. Addition of MPI predictors to clinical factors using risk categories, defined as <1%, 1% to 3%, and >3% annualized risk of cardiovascular death or non-fatal MI, yielded a 15.0% improvement in NRI (95% CI 7.6%-27.6%, P < .001).

CONCLUSIONS:

Pharmacologic stress MPI substantially improved net reclassification of cardiovascular death or MI risk beyond that afforded by clinical factors.

PMID:
26995380
DOI:
10.1016/j.ahj.2016.01.012
[Indexed for MEDLINE]

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