A novel heart rate variability algorithm for the detection of myocardial ischemia: pilot data from a prospective clinical trial.

BACKGROUND Heart rate variability (HRV) analysis has been shown to be a predictor of sudden cardiac death and all-cause mortality in patients with cardiac disease. OBJECTIVES To examine whether newer HRV analysis algorithms, as used by the HeartTrends device, are superior to exercise stress testing (EST) for the detection of myocardial ischemia in patients without known coronary artery disease (CAD). METHODS We present pilot data of the first 100 subjects enrolled in a clinical trial designed to evaluate the yield of short-term (1 hour) HRV testing for the detection of myocardial ischemia. The study population comprised subjects without known CAD referred to a tertiary medical center for EST with single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). All patients underwent a 1 hour electrocardiographic acquisition for HRV analysis with a HeartTrends device prior to ESTwith MPI. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively) were calculated for EST and HRV analysis, using MPI as the gold standard for the non-invasive detection of myocardial ischemia. RESULTS In this cohort 15% had a pathologic MPI result. HRV analysis showed superior sensitivity (85%), PPV (50%) and NPV (97%) as compared to standard EST (53%, 42%, 90%, respectively), while the specificity of the two tests was similar (86% and 85%, respectively). The close agreement between HRV and MPI was even more pronounced among patients > 65 years of age. CONCLUSIONS Our pilot data suggest that the diagnostic yield of the novel HeartTrends HRV algorithm is superior to conventional EST for the non-invasive detection of myocardial ischemia.