Heart rate variability derived from exercise ECG in the detection of coronary artery disease

Abstract

The diagnostic performance of heart rate variability (HRV) analysis from exercise ECG in the detection of coronary artery disease (CAD) is unknown. Bicycle exercise ECG recordings from The Finnish Cardiovascular Study (FINCAVAS) of angiography-proofed CAD patients (n = 112) and a patient group with a low likelihood of CAD (n = 114) were analyzed. HRV parameters (SDNN, RMSSD, Poincaré SD1 and SD2) were calculated from 1 min segments before exercise, during exercise and after exercise. All the parameters were in addition calculated from heart rate (HR)-corrected RR-interval segments. The ST-segment depressions in each stage were also determined. The diagnostic performance of the parameters was evaluated with the area under the receiver operating characteristic (ROC) curve method. The uncorrected HRV parameters showed the best diagnostic performance in the recovery segments but the correlation with HR was also high (SDNN: 0.758/-0.64, RMSSD: 0.747/-0.60; area under the ROC/correlation coefficient). The HR correction decreased the correlation and the diagnostic performance in recovery segments (SDNN: 0.515/-0.12, RMSSD: 0.609/0.20). The diagnostic performance of ST-level at its best was higher than any of HRV parameters (ST-level: 0.795/0.36). According to the results, the HR correction decreased the diagnostic performance of the recovery phase. The HRV parameters calculated from 1 min segments of exercise test ECG were not as capable as traditional ST-segment analysis. In conclusion, the HRV analysis from exercise or recovery phase seems to be inadequate in the detection of CAD.

Effect of heart rate correction on pre- and post-exercise heart rate variability to predict risk of mortality—an experimental study on the FINCAVAS cohort

“…Nieminen et al (2007) justified that the non-linear inverse relationship between RR interval and HR could be the cause for misinterpretation when comparing subjects with different HR levels and this has been concurred by other researchers (Chiu et al, 2003; Sacha and Pluta, 2005; Sacha et al, 2005; Virtanen et al, 2007; Bailón et al, 2011). Possible physiological mechanisms involved have also been probed (Perini and Veicteinas, 2003; Goldberger et al, 2006).…”

“…The HRV indices computed from RR-interval measurements correlated with HR as a result of the non-linear relationship between the RR-interval and instantaneous HR (Chiu et al, 2003; Sacha and Pluta, 2005; Sacha et al, 2005; Nieminen et al, 2007; Virtanen et al, 2007; Bailón et al, 2011). Higher variability during rest and lower variability during recovery were associated with better prognosis, and this corresponds to observations made by Dewey et al (2007).…”

In vitroModel for Assessing Arrhythmogenic Properties of Drugs Based on High-resolution Impedance Measurements

“…As Poincaré plot is useful to illustrate short and longterm variability in beating signals and internal dynamics of beatings, some previous studies discussed the perturbations of parasympathetic and sinoatrial node affects by the Poincaré plot [35,36]. The variation observed in the distribution of the data points of Poincaré plot would be the consequence of high parasympathetic disturbance.…”

Can Reactivity of Heart Rate Variability Be a Potential Biomarker and Monitoring Tool to Promote Healthy Aging? A Systematic Review With Meta-Analyses

“…In contrast, two studies showed no between-group differences in vagally-mediated HRV [i.e., HFnu (Wood et al, (Kaltsatou et al, 2020). Higher intensities of exercise and higher heart rate were related to larger reductions of mRR (Virtanen et al, 2007), HF (Mayumi et al, 2008;Archiza et al, 2013), LFnu (Perini et al, 2000), LF/HF (Perini et al, 2000), and DFA-α1 (Karavirta et al, 2009) as well as larger increases in HFnu (Perini et al, 2000) during exercise. The addition of gait synchronization elevated DFA-α during walking (Wittstein et al, 2019).…”

“…The reported study interventions consisted of cognitive exercises (k = 21) (Cacioppo et al, 2000;Steptoe et al, 2002Wood et al, 2002;Kunz-Ebrecht et al, 2003;Marmot, 2005, 2006;Hamer and Steptoe, 2007;Capuana et al, 2012;Christensen Stephanie and Wright Heather, 2014;Collste et al, 2014;Lin et al, 2014Lin et al, , 2017aCrowley Olga et al, 2016;Norcliffe-Kaufmann et al, 2016;Wawrzyniak Andrew et al, 2016;Beer Noa et al, 2017;Betz Linda et al, 2017;Kuraoka et al, 2019;Perpetuini et al, 2019), cardiorespiratory exercises (k = 18) (Perini et al, 2000;Bartels Matthew et al, 2003;Takahashi et al, 2003;Davrath Linda et al, 2006;Virtanen et al, 2007;Mayumi et al, 2008;Karavirta et al, 2009;Dourado et al, 2010;Alves Naiane Ferraz et al, 2011;Sales et al, 2011;Wang Norman et al, 2011;Corrêa et al, 2013;Ahmadian and Dabidi Roshan, 2015;Junior Adalberto et al, 2019;Rodrigues Jhennyfer et al, 2019;Wittstein et al, 2019;Kaltsatou et al, 2020), resistance exercises (k = 6) (Piepoli et al, 1996;Petrofsky et al, 2009;Millar et al, 2011;<...>…”