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Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
Negative predictive value of stress myocardial perfusion imaging and coronary computed tomography angiography: A
Roberta Green1, Valeria Cantoni1, Mario Petretta2
1Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy.
Background:
Comparing the prognostic value of a negative finding by stress single-photon emission computed tomography myocardial perfusion imaging (MPI) and coronary computed tomography angiography (CCTA) may be useful to evaluate how better identify low-risk patients. We performed a meta-analysis to compare the long-term negative predictive value (NPV) of normal stress MPI and normal CCTA in subjects with suspected coronary artery disease (CAD).
Methods And Results:
Studies published between January 2000 and November 2016 were identified by database search. We included MPI and CCTA studies that followed-up ≥100 subjects for ≥5 years and providing data on clinical outcome for patients with negative tests. Summary risk estimates for normal perfusion at MPI or <50% coronary stenosis at CCTA were derived in random effect regression analysis, and causes of heterogeneity were determined in meta-regression analysis. We identified 12 eligible articles (6 MPI and 6 CCTA) including 33,129 patients (26,757 in MPI and 6372 in CCTA studies) with suspected CAD. The pooled annualized event rate (AER) for occurrence of hard events (death and nonfatal myocardial infarction) was 1.06 (95% confidence interval, CI 0.49-1.64) in MPI and 0.61 (95% CI 0.35-0.86) in CCTA studies. The pooled NPV was 91% (95% CI 86-96) in MPI and 96 (95% CI 95-98) in CCTA studies. The summary rates between MPI and CCTA were not statistically different. At meta-regression analysis, no significant association between AER and clinical and demographical variables considered was found for overall studies.
Conclusions:
Stress MPI and CCTA have a similar ability to identify low-risk patients with suspected CAD.
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