Nonlinear Heart Rate Variability Analysis May Predict Atrial Fibrillation After Coronary Artery Bypass Grafting

Heart Rate Variability and Its Role in Predicting Atrial Fibrillation in Patients Undergoing Coronary Artery Bypass Graft

Background

An association between heart rate variability (HRV) and cardiac events in certain diseases has been demonstrated. However, the association with new-onset atrial fibrillation (AF) after coronary artery bypass grafting (CABG) is still controversial. This study aimed to investigate the association between HRV and new-onset AF in patients undergoing CABG during a 6-month follow-up.

Methods

This prospective study included 119 consecutive patients who underwent off-pump CABG. All patients were assessed using 24-hour Holter recordings 2 days before CABG and 1 week, 3 months, and 6 months postoperatively. HRV was analyzed, and AF was detected from its recordings.

Main results

In patients undergoing CABG, NYHA III increased the AF rate 7 days postoperatively, and advanced age and diabetes were associated with AF 6 months postoperatively. A reduction in time-domain measurements before surgery was significantly associated with a higher risk of developing AF seven days postoperatively; no association between preoperative HRV and AF was found at six months. Reduced preoperative HRV (SDNN (standard deviation of all normal-to-normal intervals [) < 50 ms) was an independent predictor of AF at 3 (AUC = 0.65) and 6 months (AUC = 0.62) following surgery.

Conclusion

A reduction in the time domain measurements before CABG was associated with a higher risk of new-onset AF at 7 days postoperatively but not at 6 months. An SDNN <50 ms was a weak independent predictor of a higher incidence of AF at 3 and 6 months post-surgery.

Predicting atrial fibrillation after cardiac surgery: a scoping review of associated factors and systematic review of existing prediction models

INTRODUCTION

Postoperative atrial fibrillation (POAF) is common after cardiac surgery and associated with increased hospital length of stay, patient morbidity and mortality. We aimed to identify factors associated with POAF and evaluate the accuracy of available POAF prediction models.

METHODS

We screened articles from Ovid MEDLINE® and PubMed Central® (PMC) and included studies that evaluated risk factors associated with POAF or studies that designed or validated POAF prediction models. We only included studies in cardiac surgical patients with sample size n ⩾ 50 and a POAF outcome group ⩾20. We summarised factors that were associated with POAF and assessed prediction model performance by reviewing reported calibration and discriminative ability.

RESULTS

We reviewed 232 studies. Of these, 142 fulfilled the inclusion criteria. Age was frequently found to be associated with POAF, while most other variables showed contradictory findings, or were assessed in few studies. Overall, 15 studies specifically developed and/or validated 12 prediction models. Of these, all showed poor discrimination or absent calibration in predicting POAF in externally validated cohorts.

CONCLUSIONS

Except for age, reporting of factors associated with POAF is inconsistent and often contradictory. Prediction models have low discrimination, missing calibration statistics, are at risk of bias and show limited clinical applicability. This suggests the need for studies that prospectively collect AF relevant data in large cohorts and then proceed to validate findings in external data sets.

Preoperative heart rate variability as a predictor of perioperative outcomes: a systematic review without meta-analysis

Heart rate variability (HRV) is a predictor of mortality and morbidity after non-lethal cardiac ischemia, but the relation between preoperatively measured HRV and intra- and postoperative complications is sparsely studied and most recently reviewed in 2007. We, therefore, reviewed the literature regarding HRV as a predictor for intra- and postoperative complications and outcomes. We carried out a systematic review without meta-analysis. A PICO model was set up, and we searched PubMed, EMBASE, and CENTRAL. The screening was done by one author, but all authors performed detailed review of the included studies. We present data from studies on intraoperative and postoperative complications, which were too heterogeneous to warrant formal meta-analysis, and we provide a pragmatic review of HRV indices to facilitate understanding our findings. The review was registered in PROSPERO (CRD42021230641). We screened 2337 records for eligibility. 131 records went on to full-text assessment, 63 were included. In frequency analysis of HRV, low frequency to high frequency ratio could be a predictor for intraoperative hypotension in spinal anesthesia and lower total power could possibly predict intraoperative hypotension under general anesthesia. Detrended fluctuation analysis of HRV is a promising candidate for predicting postoperative atrial fibrillation. This updated review of the relation between preoperative HRV and surgical outcome suggests a clinically relevant role of HRV but calls for high quality studies due to methodological heterogeneity in the current literature. Areas for future research are suggested.

Comparative study of short-term cardiovascular autonomic control in cardiac surgery patients who underwent coronary artery bypass grafting or correction of valvular heart disease

Introduction: Our aim was to perform a comparative study of short-term cardiovascular autonomic control in cardiac surgery patients who underwent coronary artery bypass grafting (CABG) or surgical correction of valvular heart disease (SCVHD ). Methods: The synchronous 15 minutes records of heart rate variability (HRV) and finger's photoplethysmographic waveform variability (PPGV) were performed in 42 cardiac surgery patients (12 women) aged 61.8 ± 8.6 years (mean ± standard deviation), who underwent CABG, and 36 patients (16 women) aged 54.2 ± 14.9 years, who underwent SCVHD , before surgery and in 5-7 days after surgery. Conventional time and frequency domain measures of HRV and index S of synchronization between the slow oscillations in PPGV and HRV were analyzed. We also calculated personal dynamics of these indices after surgery. Results: We found no differences (Р > 0.05) in all studied autonomic indices (preoperative and post-surgery) between studied patients' groups, except for the preoperative heart rate, which was higher in patients who underwent SCVHD (P = 0.013). We have shown a pronounced preoperative and post-surgery variability (magnitude of inter-quartile ranges) of all autonomic indices in studied patients. In the cluster analysis based on cardiovascular autonomic indices (preoperative and post-surgery), we divided all patients into two clusters (38 and 40 subjects) which did not differ in all clinical characteristics (except for the preoperative hematocrit, P = 0.038), index S, and all post-surgery HRV indices. First cluster (38 patients) had higher preoperative values of the HR, TP, HF, and HF%, and lower preoperative values of the LF% and LF/HF. Conclusion: The variability of cardiovascular autonomic indices in on-pump cardiac surgery patients (two characteristic clusters were identified based on preoperative indices) was not associated with their clinical characteristics and features of surgical procedure (including cardioplegia).

Baroreflex sensitivity and outcomes following coronary surgery

Postoperative atrial fibrillation, acute kidney dysfunction and low cardiac output following coronary surgery are associated with morbidity and mortality. The purpose of this study is to determine if the preoperative autonomic control is a determinant of these postoperative complications. This is a prospective cohort study on 150 adult patients undergoing surgical coronary revascularization with cardiopulmonary bypass. The patients received an autonomic control assessment after the induction of anesthesia. Baroreflex sensitivity was computed by spectral analysis and expressed as BRSαHF and BRSαLF for measure respectively in the high and low frequency domains. Atrial fibrillation was adjudicated at any postoperative time during the hospital stay. Acute kidney dysfunction was defined as any increase of serum creatinine levels from preoperative values within the first 48 hours after surgery, and acute kidney injury was adjudicated at a 50% increase. Low cardiac ouput syndrome was defined as the need for inotropic support > 48 hours. Thirty-eight (26.4%) patients experienced postoperative atrial fibrillation; 32 (22.2%) had acute kidney dysfunction and 5 (3.5%) acute kidney injury; 14(10%) had a low cardiac output state. No indices of baroreflex sensitivity were associated with atrial fibrillation or acute kidney injury. A low value of BRSαLF was associated with acute kidney dysfunction and low cardiac output state. A BRSαLF < 3 msec/mmHg was an independent risk factor for acute kidney dysfunction (odds ratio 3.0, 95% confidence interval 1.02–8.8, P = 0.045) and of low cardiac output state (odds ratio 17.0, 95% confidence interval 2.9–99, P = 0.002). Preoperative baroreflex sensitivity is linked to postoperative complications through a number of possible mechanisms, including an autonomic nervous system-mediated vasoconstriction, a poor response to hypotension, and an increased inflammatory reaction.

Preoperative heart rate variability predicts atrial fibrillation after coronary bypass grafting

BACKGROUND

The purpose of the present study was to investigate the association between preoperative heart rate variability and atrial fibrillation after off-pump coronary artery bypass graft surgery.

METHODS

Of 524 consecutive patients undergoing isolated coronary artery bypass surgery, 390 were retrospectively analyzed after excluding the following 134 cases: on-pump surgery (n = 6), emergency (n = 106), chronic atrial fibrillation (n = 17), and pacemaker rhythm (n = 5). The following time-domain factors of heart rate variability were calculated: standard deviation of all normal-to-normal QRS (SDNN) and square root of mean of sum of squares of differences between adjacent normal-to-normal QRS (RMSSD).

RESULTS

Atrial fibrillation occurred in 98 patients (25%) after surgery. Patients not having atrial fibrillation had significantly lower heart rate variability than did patients having atrial fibrillation, with median values of 91 versus 121 for SDNN and 19 versus 25 for RMSSD. Reduced heart rate variability was significantly associated with a lower risk of postoperative atrial fibrillation: the adjusted hazard ratio (95% confidence interval) was 0.29 (0.17 to 0.49) for SDNN 99 ms or less and 0.47 (0.30 to 0.74) for RMSSD 20 ms or less. The area under the receiver operating characteristic curves for SDNN and RMSSD as a predictor of postoperative atrial fibrillation was 0.764 and 0.696, respectively.

CONCLUSIONS

Reduced time-domain factors in preoperative 24-hour heart rate variability are independently associated with a lower risk of atrial fibrillation after off-pump coronary artery bypass surgery.

Heart rate variability response to standing in men and women receiving d,l-sotalol following coronary artery bypass graft surgery

Heart rate variability (HRV), a quantitative marker of autonomic control of heart rate (HR), declines in men and women following coronary artery bypass graft (CABG) surgery. Although d,l-sotalol is prescribed following CABG surgery primarily for its antiarrhythmic effect, its effects on HRV have not been reported; the β-adrenergic antagonist effect of d,l-sotalol may attenuate sympathetically mediated HR and blood pressure (BP) responses to standing, resulting in postural hypotension. In this study, the HRV response to standing 4 days following CABG surgery in men and women prescribed d,l-sotalol was measured to examine the influence of d,l-sotalol on previously reported HRV responses, taking age and gender into consideration. Participants included 28 men and 10 women who completed testing in supine and standing postures; all had received low-dose d,l-sotalol daily since the first postoperative day. Data included continuous electrocardiograph recording of R-R interval for 10 min in each posture. Participants showed significant effects of standing on the autonomic modulation of HR, as seen by a decrease in parasympathetic indices and R-R interval and an increase in BP. In men, standing decreased parasympathetic modulation and increased the sympathetic nervous system indicator, but previously reported age effects were not seen. In women, standing decreased low frequency power and R-R interval and increased BP, with older women having a smaller increase in BP, suggesting an attenuated response. The differential autonomic nervous system modulation of HR as a function of gender and age after CABG surgery may be attenuated by d,l-sotalol.

The analysis and utilization of cycling training data

Most mathematical models of athletic training require the quantification of training intensity and quantity or 'dose'. We aim to summarize both the methods available for such quantification, particularly in relation to cycle sport, and the mathematical techniques that may be used to model the relationship between training and performance. Endurance athletes have used training volume (kilometres per week and/or hours per week) as an index of training dose with some success. However, such methods usually fail to accommodate the potentially important influence of training intensity. The scientific literature has provided some support for alternative methods such as the session rating of perceived exertion, which provides a subjective quantification of the intensity of exercise; and the heart rate-derived training impulse (TRIMP) method, which quantifies the training stimulus as a composite of external loading and physiological response, multiplying the training load (stress) by the training intensity (strain). Other methods described in the scientific literature include 'ordinal categorization' and a heart rate-based excess post-exercise oxygen consumption method. In cycle sport, mobile cycle ergometers (e.g. SRM and PowerTap) are now widely available. These devices allow the continuous measurement of the cyclists' work rate (power output) when riding their own bicycles during training and competition. However, the inherent variability in power output when cycling poses several challenges in attempting to evaluate the exact nature of a session. Such variability means that average power output is incommensurate with the cyclist's physiological strain. A useful alternative may be the use of an exponentially weighted averaging process to represent the data as a 'normalized power'. Several research groups have applied systems theory to analyse the responses to physical training. Impulse-response models aim to relate training loads to performance, taking into account the dynamic and temporal characteristics of training and, therefore, the effects of load sequences over time. Despite the successes of this approach it has some significant limitations, e.g. an excessive number of performance tests to determine model parameters. Non-linear artificial neural networks may provide a more accurate description of the complex non-linear biological adaptation process. However, such models may also be constrained by the large number of datasets required to 'train' the model. A number of alternative mathematical approaches such as the Performance-Potential-Metamodel (PerPot), mixed linear modelling, cluster analysis and chaos theory display conceptual richness. However, much further research is required before such approaches can be considered as viable alternatives to traditional impulse-response models. Some of these methods may not provide useful information about the relationship between training and performance. However, they may help describe the complex physiological training response phenomenon.

Automatic detection and classification of human epicardial atrial unipolar electrograms

This paper describes an unsupervised signal processing method applied to three-channel unipolar electrograms recorded from human atria. These were obtained by epicardial wires sutured on the right and left atria after coronary artery bypass surgery. Atrial (A) and ventricular (V) activations had to be detected and identified on each channel, and gathered across the channels when belonging to the same global event. The algorithm was developed and optimized on a training set of 19 recordings of 5 min. It was assessed on twenty-seven 2 h recordings taken just before the onset of a prolonged atrial fibrillation for a total of 1593697 activations that were validated and classified as normal atrial or ventricular activations (A, V) and premature atrial or ventricular activations (PAA, PVA). 99.93% of the activations were detected, and amongst these, 99.89% of the A and 99.75% of the V activations were correctly labelled. In the subset of the 39705 PAA, 99.83% were detected and 99.3% were correctly classified as A. The false positive rate was 0.37%. In conclusion, a reliable fully automatic detection and classification algorithm was developed that can detect and discriminate A and V activations from atrial recordings. It can provide the time series needed to develop a monitoring system aiming to identify dynamic predictors of forthcoming cardiac events such as postoperative atrial fibrillation.