Article
Heart Rate Variability Parameters Derived from Exercise ECG in the Detection of Coronary Artery Disease
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Published: | February 8, 2007 |
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Question: Can the HRV methods using the exercise ECG measurement be exploited in the detection of coronary artery disease (CAD)?
Methods used: The study population consisted of 200 patients, 100 (78 male/22 female) with CAD verified by angiography (mean age 55+/-6, BMI 27.7+/-4.6, max load 150+/-41, max HR 133+/-12, 74 beta blocker users) and 100 (48/52) references (54+/-8, 26.1+/-4.1, 185+/-54, 164+/-12, none), who underwent a bicycle stress test with one minute workload increase. HRV parameters used were SDNN, Poincaré plot indices SD1 and SD2. Also the maximum ST-segment depression (STD) from the 12-lead ECG, excluding aVL, aVR and V1, was measured. Parameters were defined at rest, end of exercise (Expeak) and one minute recovery (Rec1). HRV parameters were determined in one minute segments in each phase and were also corrected by multiplying RR values by square of mean HR of the used segment, denoted cSDNN, cSD1 and cSD2. Overall diagnostic performance was evaluated by area under the ROC curve (AUC). Correlation with HR was evaluated with Pearson’s correlation coefficients.
Results: Table 1 [Tab. 1] presents AUCs for the parameters, correlation coefficients with HR and significance level. The AUCs for HR at rest, Expeak and Rec1 were 0.759, 0.907 and 0.907.
Conclusion: The overall diagnostic performances of HRV parameters in the detection of CAD seemed promising. This might partially be explained with difference in achieved HR and beta-blocker users in CAD group. Diagnostic value of HR corrected HRV parameters seemed to be limited to the resting ECG.