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Response to Commentary on “Heart Rate Variability and Risk of All-Cause Death and Cardiovascular Events in Patients With Cardiovascular Disease: A Meta-Analysis of Cohort Studies”

The commentary reported methodological flaws and inaccuracies in reporting original research in our meta-analysis published in Volume 22 of Biological Research for Nursing (Fang et al., 2020). We welcome these comments and appreciate their value in stimulating further research. We want to take this opportunity to respond to the commentary. We appreciate that the commenters pointed out a misclassification of the outcomes. We misclassified the estimate for risk of sudden death associated with high frequency (HF) heart rate variability (HRV) extracted from the study by Anastasiou-Nana et al. (2005) as an estimate for all-cause death. We reanalyzed the data for risk of cardiovascular events and risk of all-cause death based on the revised classification of outcomes. The results remain largely unchanged and continue to support the notion that lower HRV was associated with a significantly higher risk of all-cause death and cardiovascular events. The pooled hazard ratio (HR) for all-cause death was 2.27 and that for cardiovascular events was 1.41 according to the current analysis. We have published an erratum to correct this mistake and are forever in debt to the commenter for this valuable comment. In this meta-analysis, we used random-effects modeling to meta-analyze the data. The summary estimates from the included studies included HRs, relative risks (RRs), and odds ratios (ORs), as the commentary pointed out. All of the studies that we included employed Cox models to examine the risk of cardiovascular events and mortality; thus, for the present analyses we assumed RR to be a valid approximation of HR. In a previously published meta-analysis study that examined the risk of cardiovascular events and mortality associated with walking, the authors also considered RR to be a valid approximation of HR (Hamer & Chida, 2008). Additionally, in a rare outcome, ORs are close to RR estimates (Stare & MaucortBoulch, 2016). Therefore, we used HR as a summary estimate to evaluate the risk of cardiovascular events and mortality associated with HRV in our meta-analysis. The commenters seem to have a misunderstanding regarding the estimates in a forest plot, as evidenced by their comment that our reported estimates in Figure 2 were different from those reported by the original papers. In our study, the HR estimates were from the outputs of the results with randomeffects models weighted by the inverse variance method using Comprehensive Meta-Analysis software, version 2.0. They also seemed to misunderstand another aspect of our presentation of the results in Figure 2, as demonstrated by their comment that “the authors calculate subtotals across diverse measures of HRV.” We conducted the subgroup analyses for the same HRV parameters and pooled the result when there were at least three studies reporting the same HRV parameter. The diamond-shaped symbols in Figure 2 represent pooled estimates for the total sample and subgroups. In the all-cause death outcome, we conducted subgroup analyses for the standard deviation of all normal to normal intervals (SDNN), HF, and LF parameters only. In the cardiovascular events outcome, we conducted subgroup analyses only for the SDNN, LF, and LF/HF parameters. The measures of HRV parameters varied among the included studies. For each HRV parameter, the risk estimate was calculated for the lowest value group against the highest one (reference group), according to the percentiles (median, tertiles, quartiles, and quintiles) of the HRV distribution of the study samples, reported cut off value, or author-defined cut off (e.g., receiver operating characteristic). Thus, the units or measures of HRV parameters were unlikely to have influenced the results.