Abstract 19310: High Frequency QRS Analysis has Incremental Diagnostic Accuracy Over ST-Segment Analysis Alone for Ischemia Identification in Patients Referred for Exercise Myocardial Perfusion Imaging

Abstract

Introduction: Myocardial perfusion imaging (MPI) to identify ischemia is expensive, but existing electrocardiographic techniques have poor sensitivity. A novel method of high-frequency QRS analysis (HF-QRS) may improve ischemia detection. We sought to compare HF-QRS to standard ST-segment analysis for the identification of any and significant (≥10%) left ventricular (LV) ischemia by exercise SPECT MPI. Methods: We analyzed 292 consecutive patients. HF-QRS was determined within a bandwidth of 150 -250 Hz. A 50% relative reduction and ≥1 µV drop in the HF-QRS signal in ≥3 leads and ≥1mm ST-depression were the criteria for positivity for HF-QRS and ST-analysis, respectively. Quantitative, gated-SPECT MPI was performed according to standard protocols. Sensitivities and specificities and incremental diagnostic accuracy were assessed using chi-square and logistic regression analyses. Results: The mean cohort age was 59.6 years and 64.7 were male. Twenty nine percent had known coronary artery disease. LV ischemia was present in 54 patients (18.4%) and significant (≥10%) LV ischemia in 17 (5.8%). ST-analysis and HF-QRS analyses were positive in 42 (14.4%) and 70 (23.9%) respectively. As shown in the figure, ST-analysis had poor sensitivity for any ischemia that improved but remained low for ≥10% LV ischemia. HF-QRS had substantially higher sensitivities for both any and ≥10% LV ischemia. The 84.9% specificity of HF-QRS analysis for any ischemia was similar to the 86.6% specificity of ST-analysis. ST depression failed to add incremental diagnostic information to clinical risk factors (p=0.519), while HF-QRS increased the model Χ2 from 39.3 to 54.2 (p<0.001). Conclusions: High-frequency QRS analysis substantially improves the detection of any and significant ischemia over ST-segment analysis alone in patients undergoing exercise stress. This novel method has the potential to decrease the high rate of MPI for CAD risk stratification.