The prognostic significance of HR variability has been extensively studied in patients who have survived an AMI. Table summarizes the results of main studies assessing the prognostic significance of HR variability measurements from 24-h recordings. As early as Wolf et al. (1978
) showed that patients with a low magnitude of short-term HR variability (no sinus arrhythmia on 30 consecutive R–R intervals on admitting ECG) had a poor prognosis after AMI. In the late 1980s, the multicenter post-infarction project (MPIP) confirmed the predictive value of reduced HRV by measuring 24-h SD of N–N intervals (SDNN) over 24
h following AMI (Kleiger et al., 1987
). Adjustment for covariates did not explain this association. Other studies (including a reanalysis of MPIP) have shown that spectral measures of HR variability, mainly the very-low and low frequency spectral components, are reduced in survivors of AMI and that decreased values are associated with an increased risk of all-cause mortality (Bigger et al., 1992
Summary of main studies assessing the prognostic significance of heart rate variability after acute myocardial infarction.
Because accurate Holter scanning is relatively labor intensive, the group at St. George’s hospital in London experimented with global, geometric indices of HR variability (HR variability index) that were derived from the histogram of N–N intervals (Malik et al., 1989
). Decreased values for these measures were also found to be associated with higher risk of mortality (Fei et al., 1996
). In addition, this group suggested that markedly reduced SDNN for a single, stable 5-min period could pre-select patients in whom 24-h Holter recordings using geometric methods would provide significant risk stratification.
The autonomic tone and reflexes after myocardial infarction (ATRAMI) trial was a multicenter observational study performed about 10
years after MPIP. The ATRAMI investigators confirmed that reduced 24-h SDNN (<70
ms in this case) is associated with an increased mortality during 21
months of follow up (La Rovere et al., 1998
). Furthermore, the combination of low SDNN and left ventricular ejection fraction <35% carried a high risk of mortality.
Early studies focused on measurement of HR variability relatively early after AMI. Measures of HR variability appeared to be more depressed at the early phase of AMI with substantial improvement during recovery (Jokinen et al., 2003
). Despite this autonomic recovery, measurement of HR variability has been shown to yield similar prognostic information when the 24-h HRV measurements were performed late after AMI (Bigger et al., 1993
; Jokinen et al., 2003
The post-MI studies performed in the 1980s and 1990s used 24-h time and frequency domain as well as geometric measures of HR variability for risk stratification of patients after AMI. Although all statistical, geometrical, and spectral measures of HR variability differ in their manner of computation and analysis, these methods are fundamentally based on moment statistics and describe the magnitude of HR variability or of its underlying components. It is therefore not surprising that most of these measures that have been shown to have prognostic value have relatively close mutual correlation, and that there are only minor differences in prognostic power between them. It must be kept in mind though that measures of beat-to-beat HR variability which are supposed to reflect respiratory related vagal control of HR (HF power, pNN50, rMSSD) have rarely shown a strong association with outcome. This is likely because of the high prevalence of erratic rhythm in these populations resulting in higher measures for these parameters that do not reflect better parasympathetic function. One study showed that when erratic short-term R–R intervals was excluded from the analysis, HR variability related to respiratory cycles predicted sudden cardiac death even better than the standard HR variability indexes (Peltola et al., 2008
More recent studies have applied methods based on HR turbulence, non-linear dynamic, and maximum deceleration capacity of R–R intervals, which provide very different and perhaps complementary information on HR dynamics compared to traditional statistical methods (Mäkikallio et al., 2002
; Bauer et al., 2006
). Methods based on non-linear dynamics and HR turbulence have provided somewhat better prognostic information than that obtained by traditional methods (Bauer et al., 2006
; Perkiömäki et al., 2008
). In particular, decreased short-term fractal scaling exponent by the DFA method (called DFA1 or α1), a measure of greater randomness in HR patterns, has turned out to be a powerful non-linear index in risk stratification, a more powerful prognostic tool than other HR variability indexes in post-AMI populations (Huikuri et al., 2000
; Mäkikallio et al., 2002
). In the DIAMOND-MI trial, reduced short-term fractal scaling exponent identified post-AMI patients at a relative high risk of mortality and was more strongly related to outcome than traditional time and frequency domain measures (Huikuri et al., 2000
). Moreover, reduced scaling exponent was related to both arrhythmic and non-arrhythmic mortality (Huikuri et al., 2000
). In another study of consecutive patients with acute MI, both reduced short-term fractal scaling exponent and power–law slope were independently associated with recurrent non-fatal coronary events (Perkiömäki et al., 2008
). Another measure of increased randomness of HR patterns, such as the ratio of the axes of a Poincare plot fitted to the plot of each N–N interval vs. the next, also predicted mortality in the CAST trial (Stein et al., 2005
). Patients in the CAST were at variable times post-MI but were selected for having significant ventricular arrhythmias.
One study in the era of modern therapy showed a very-low incidence of severely depressed HR variability (SDNN <50
ms; Erdogan et al., 2008
). All patients in the study were treated with direct percutaneous coronary angioplasty within 12
h of their event. Although the 4-year survival was significantly higher in the low SDNN group, the positive predictive value was low, suggesting that the predictive power of HR variability may not be as high as earlier in patients receiving optimal medical and revascularization therapy. However, results were based on traditional time-domain HR variability measures and there was no report of results for non-linear measures or HR turbulence in this population.