Many experimental and clinical studies have confirmed a continuous cross-talk between both sympathetic and parasympathetic branches of autonomic nervous system and inflammatory response, in different clinical scenarios. In cardiovascular diseases, inflammation has been proven to play a pivotal role in disease progression, pathogenesis and resolution. A few clinical studies have assessed the possible inter-relation between neuro-autonomic output, estimated with heart rate variability analysis, which is the variability of R-R in the electrocardiogram, and different inflammatory biomarkers, in patients suffering from stable or unstable coronary artery disease (CAD) and heart failure. Moreover, different indices derived from heart rate signals' processing, have been proven to correlate strongly with severity of heart disease and predict final outcome. In this review article we will summarize major findings from different investigators, evaluating neuro-immunological interactions through heart rate variability analysis, in different groups of cardiovascular patients. We suggest that markers originating from variability analysis of heart rate signals seem to be related to inflammatory biomarkers. However, a lot of open questions remain to be addressed, regarding the existence of a true association between heart rate variability and autonomic nervous system output or its adoption for risk stratification and therapeutic monitoring at the bedside. Finally, potential therapeutic implications will be discussed, leading to autonomic balance restoration in relation with inflammatory control.

Heart rate variability (HRV) is an indirect estimator of autonomic modulation of heart rate and is considered a risk marker in critical illness, particularly in heart failure and severe sepsis. A reduced HRV has been found in critically ill patients and has been associated with neuro-autonomic uncoupling or decreased baroreflex sensitivity. However, results from human and animal experimental studies indicate that intracardiac mechanisms might also be responsible for interbeat fluctuations. These studies have demonstrated that different membrane channel proteins and especially the so-called ‘funny’ current (If), an hyperpolarization-activated, inward current that drives diastolic depolarization resulting in spontaneous activity in cardiac pacemaker cells, are altered during critical illness. Furthermore, membrane channels kinetics seem to have significant impact upon HRV, whose early decrease might reflect a cellular metabolic stress. In this review article we present research findings regarding intracardiac origin of HRV, at the cellular level and in both isolated sinoatrial node and whole ex vivo heart preparations. In addition, we will review results from various experimental studies that support the interrelation between If and HRV during endotoxemia. We suggest that reduced HRV during sepsis could also be associated with altered pacemaker cell membrane properties, due to ionic current remodeling.

BackgroundEven though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients.MethodsTwenty-two patients were enrolled in the study. In five, systemic inflammatory response syndrome (SIRS, group 1) developed, 10 had sepsis (group 2), and seven had septic shock (group 3). All temperature curves were studied during the first 24 hours of an inflammatory state. A wavelet transformation was applied, decomposing the signal in different frequency components (scales) that have been found to reflect neurogenic and metabolic inputs on temperature oscillations. Wavelet energy and entropy per different scales associated with complexity in specific frequency bands and multiscale entropy of the whole signal were calculated. Moreover, a clustering technique and a linear discriminant analysis (LDA) were applied for permitting pattern recognition in data sets and assessing diagnostic accuracy of different wavelet features among the three classes of patients.ResultsStatistically significant differences were found in wavelet entropy between patients with SIRS and groups 2 and 3, and in specific ultradian bands between SIRS and group 3, with decreased entropy in sepsis. Cluster analysis using wavelet features in specific bands revealed concrete clusters closely related with the groups in focus. LDA after wrapper-based feature selection was able to classify with an accuracy of more than 80% SIRS from the two sepsis groups, based on multiparametric patterns of entropy values in the very low frequencies and indicating reduced metabolic inputs on local thermoregulation, probably associated with extensive vasodilatation.ConclusionsWe suggest that complexity analysis of temperature signals can assess inherent thermoregulatory dynamics during systemic inflammation and has increased discriminating value in patients with infectious versus noninfectious conditions, probably associated with severity of illness.

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Complex interrelations exist between the master central clock, located in the suprachiasmatic nuclei of the hypothalamus, and several peripheral clocks, such as those found in different immune cells of the body. Moreover, external factors that are called ‘timekeepers’, such as light/dark and sleep/wake cycles, interact with internal clocks by synchronizing their different oscillation phases. Chronobiology is the science that studies biologic rhythms exhibiting recurrent cyclic behavior. Circadian rhythms have a duration of approximately 24 h and can be assessed through chronobiologic analysis of time series of melatonin, cortisol, and temperature. Critically ill patients experience severe circadian deregulation due to not only the lack of effective timekeepers in the intensive care unit (ICU) environment but also systemic inflammation. The latter has been found in both animal and human studies to disrupt circadian rhythmicity of all measured biomarkers. The aims of this article are to describe circadian physiology during acute stress and to discuss the effects of ICU milieu upon circadian rhythms, in order to emphasize the value of considering circadian-immune disturbance as a potential tool for personalized treatment. Thus, besides neoplastic processes, critical illness could be linked to what has been referred as ‘chronomics’: timing and rhythm. In addition, different therapeutic perspectives will be presented in association with environmental approaches that could restore circadian connection and hasten physical recovery.