Alterations in heart rate variability in patients with peripheral arterial disease requiring surgical revascularization have limited association with postoperative major adverse cardiovascular and cerebrovascular events

ObjectiveObstructive sleep apnea (OSA) is common in peripheral arterial disease (PAD) and associates with high mortality after surgery. Since abnormal heart rate variability (HRV) is predictive of postoperative complications, we investigated the relations of HRV with PAD, OSA and major adverse cardiovascular and cerebrovascular events (MACCE).Materials and methodsSeventy-five patients (67 +/- 9 years) scheduled for sub-inguinal revascularization and 15 controls (63 +/- 6 years) underwent polysomnography and HRV analyses. OSA with an apnea-hypopnea index (AHI) >= 20/hour was considered significant. HRV was measured during wakefulness, S2, S3-4 and rapid eye movement (REM) sleep with time and frequency domain methods including beat-to-beat variability, low frequency (LF) and high frequency (HF) power, and detrended fluctuation analysis (DFA). MACCE was defined as cardiac death, myocardial infarction, coronary revascularization, hospitalized angina pectoris and stroke.ResultsThirty-six patients (48%) had AHI >= 20/hour. During follow-up (median 52 months), 22 patients (29%) suffered a MACCE. Compared to controls, fractal correlation of HRV (scaling exponent alpha 1 measured with DFA) was weaker during S2 and evening wakefulness in all subgroups (+/-AHI >= 20/hour, +/-MACCE)but only in patients with AHI >= 20/hour during morning wakefulness. The LF/HF ratio was lower in all subgroups during S2 but only in patients with AHI >= 20/hour during evening or morning wake. In the covariance analysis adjusted for age, body mass index, coronary artery disease and PAD duration, the alpha 1 during morning wakefulness remained significantly lower in patients with AHI >= 20/hour than in those without (1.12 vs. 1.45; p = 0.03). Decreased HF during REM (p = 0.04) and S3-4 sleep (p = 0.03) were predictive of MACCE. In analyses with all sleep stages combined, mean heart rate as well as very low frequency, LF, HF and total power were associated with OSA of mild-to-moderate severity (AHI 10-20/hour).ConclusionsHRV is altered in patients with PAD. These alterations have a limited association with OSA and MACCE

Comparison of the prognostic value of early-phase proton magnetic resonance spectroscopy and diffusion tensor imaging with serum neuron-specific enolase at 72 h in comatose survivors of out-of-hospital cardiac arrest-a substudy of the XeHypotheca trial

Purpose: We compared the predictive accuracy of early-phase brain diffusion tensor imaging (DTI), proton magnetic resonance spectroscopy (1H-MRS), and serum neuron-specific enolase (NSE) against the motor score and epileptic seizures (ES) for poor neurological outcome after out-of-hospital cardiac arrest (OHCA).Methods: The predictive accuracy of DTI, 1H-MRS, and NSE along with motor score at 72 h and ES for the poor neurological outcome (modified Rankin Scale, mRS, 3 - 6) in 92 comatose OHCA patients at 6 months was assessed by area under the receiver operating characteristic curve (AUROC). Combined models of the variables were included as exploratory.Results: The predictive accuracy of fractional anisotropy (FA) of DTI (AUROC 0.73, 95% CI 0.62-0.84), total N-acetyl aspartate/total creatine (tNAA/tCr) of 1H-MRS (0.78 (0.68 - 0.88)), or NSE at 72 h (0.85 (0.76 - 0.93)) was not significantly better than motor score at 72 h (0.88 (95% CI 0.80-0.96)). The addition of FA and tNAA/tCr to a combination of NSE, motor score, and ES provided a small but statistically significant improvement in predictive accuracy (AUROC 0.92 (0.85-0.98) vs 0.98 (0.96-1.00), p = 0.037).Conclusion: None of the variables (FA, tNAA/tCr, ES, NSE at 72 h, and motor score at 72 h) differed significantly in predicting poor outcomes in this patient group. Early-phase quantitative neuroimaging provided a statistically significant improvement for the predictive value when combined with ES and motor score with or without NSE. However, in clinical practice, the additional value is small, and considering the costs and challenges of imaging in this patient group, early-phase DTI/MRS cannot be recommended for routine use.</p

Complex systems and the technology of variability analysis

Characteristic patterns of variation over time, namely rhythms, represent a defining feature of complex systems, one that is synonymous with life. Despite the intrinsic dynamic, interdependent and nonlinear relationships of their parts, complex biological systems exhibit robust systemic stability. Applied to critical care, it is the systemic properties of the host response to a physiological insult that manifest as health or illness and determine outcome in our patients. Variability analysis provides a novel technology with which to evaluate the overall properties of a complex system. This review highlights the means by which we scientifically measure variation, including analyses of overall variation (time domain analysis, frequency distribution, spectral power), frequency contribution (spectral analysis), scale invariant (fractal) behaviour (detrended fluctuation and power law analysis) and regularity (approximate and multiscale entropy). Each technique is presented with a definition, interpretation, clinical application, advantages, limitations and summary of its calculation. The ubiquitous association between altered variability and illness is highlighted, followed by an analysis of how variability analysis may significantly improve prognostication of severity of illness and guide therapeutic intervention in critically ill patients