Heart rate variability for the evaluation of patients with disorders of consciousness

A neurophysiological profiling of the heartbeat-evoked potential in severe acquired brain injuries: A focus on unconsciousness

Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non-behavioural diagnosis of consciousness. In this prospective observational study, we conducted a comparative analysis of the topological patterns of heartbeat-evoked potentials (HEP) between patients experiencing a prolonged disorder of consciousness (pDoC) and patients emerging from a minimally consciousness state (eMCS). A total of 219 sABI patients were enrolled, each undergoing a synchronous EEG-ECG resting-state recording, together with a standardized consciousness diagnosis. A number of graph metrics were computed before/after the HEP (Before/After) using the R-peak on the ECG signal. The peak value of the global field power of the HEP was found to be significantly higher in eMCS patients with no difference in latency. Power spectrum was not able to discriminate consciousness neither Before nor After. Node assortativity and global efficiency were found to vary with different trends at unconsciousness. Lastly, the Perturbational Complexity Index of the HEP was found to be significantly higher in eMCS patients compared with pDoC. Given that cortical elaboration of peripheral inputs may serve as a non-behavioural determinant of consciousness, we have devised a low-cost and translatable technique capable of estimating causal proxies of brain functionality with an endogenous, non-invasive stimulus. Thus, we present an effective means to enhance consciousness assessment by incorporating the interaction between the autonomic nervous system (ANS) and central nervous system (CNS) into the loop.

Uncovering sympathetic nervous system dysfunction in disorders of consciousness via heart rate variability during head-up tilt test

Few standardized tools are available for evaluation of disorders of consciousness (DOC). The potential of heart rate variability (HRV) during head-up tilt (HUT) test was investigated as a complementary evaluation tool. Twenty-one DOC patients and 21 healthy participants were enrolled in this study comparing clinical characteristics and HRV time- and frequency-domain outcomes and temporal changes during HUT test. During the 1st-5th min of the HUT, DOC group showed a significant increase and decrease in log low frequency (LF) (p = 0.045) and log normalized high frequency (nHF) (p = 0.02), respectively, compared to the supine position and had lower log normalized LF (nLF) (p = 0.004) and log ratio of low-to-high frequency (LF/HF) (p = 0.001) compared to healthy controls. As the HUT continued from the 6th to the 20th min, DOC group exhibited a significant increase in log LF/HF (16th-20th min) (p < 0.05), along with a decrease in log nHF (6th-10th and 16th-20th min) (p < 0.05) and maintained lower log LF, log nLF, and log LF/HF than controls (p < 0.05). 1st-10th min after returning to the supine position, DOC group demonstrated a significant decrease in log nHF (p < 0.01) and increases in log LF/HF (p < 0.01) and had lower log LF (p < 0.01) and log nLF (p < 0.05) compared to controls. In contrast, the control group exhibited a significant decrease in log nHF (p < 0.05) and increase in log LF/HF (p < 0.05) throughout the entire HUT test. Notably, no significant differences were observed when comparing time-domain outcomes reflecting parasympathetic nervous system between the two groups. HRV during HUT test indicated a delayed and attenuated autonomic response, particularly in the sympathetic nervous system, in DOC patients compared with healthy individuals.

Central autonomic network and early prognosis in patients with disorders of consciousness

The central autonomic network (CAN) plays a crucial role in modulating the autonomic nervous system. Heart rate variability (HRV) is a valuable marker for assessing CAN function in disorders of consciousness (DOC) patients. We used HRV analysis for early prognosis in 58 DOC patients enrolled within ten days of hospitalization. They underwent a five-minute electrocardiogram during baseline and acoustic/visual stimulation. The coma recovery scale-revised (CRS-R) was used to define the patient's consciousness level and categorize the good/bad outcome at three months. The high-frequency Power Spectrum Density and the standard deviation of normal-to-normal peaks in baseline, the sample entropy during the stimulation, and the time from injury features were used in the support vector machine analysis (SVM) for outcome prediction. The SVM predicted the patients' outcome with an accuracy of 96% in the training test and 100% in the validation test, underscoring its potential to provide crucial clinical information about prognosis.

Covert consciousness

Covert consciousness is a state of residual awareness following severe brain injury or neurological disorder that evades routine bedside behavioral detection. Patients with covert consciousness have preserved awareness but are incapable of self-expression through ordinary means of behavior or communication. Growing recognition of the limitations of bedside neurobehavioral examination in reliably detecting consciousness, along with advances in neurotechnologies capable of detecting brain states or subtle signs indicative of consciousness not discernible by routine examination, carry promise to transform approaches to classifying, diagnosing, prognosticating and treating disorders of consciousness. Here we describe and critically evaluate the evolving clinical category of covert consciousness, including approaches to its diagnosis through neuroimaging, electrophysiology, and novel behavioral tools, its prognostic relevance, and open questions pertaining to optimal clinical management of patients with covert consciousness recovering from severe brain injury.

Multidimensional assessment of heartbeat-evoked responses in disorders of consciousness

Because consciousness does not necessarily translate into overt behaviour, detecting residual consciousness in noncommunicating patients remains a challenge. Bedside diagnostic methods based on EEG are promising and cost-effective alternatives to detect residual consciousness. Recent evidence showed that the cortical activations triggered by each heartbeat, namely, heartbeat-evoked responses (HERs), can detect through machine learning the presence of minimal consciousness and distinguish between overt and covert minimal consciousness. In this study, we explore different markers to characterize HERs to investigate whether different dimensions of the neural responses to heartbeats provide complementary information that is not typically found under standard event-related potential analyses. We evaluated HERs and EEG average non-locked to heartbeats in six types of participants: healthy state, locked-in syndrome, minimally conscious state, vegetative state/unresponsive wakefulness syndrome, comatose and brain-dead patients. We computed a series of markers from HERs that can generally separate the unconscious from the conscious. Our findings indicate that HER variance and HER frontal segregation tend to be higher in the presence of consciousness. These indices, when combined with heart rate variability, have the potential to enhance the differentiation between different levels of awareness. We propose that a multidimensional evaluation of brain-heart interactions could be included in a battery of tests to characterize disorders of consciousness. Our results may motivate further exploration of markers in brain-heart communication for the detection of consciousness at the bedside. The development of diagnostic methods based on brain-heart interactions may be translated into more feasible methods for clinical practice.