BackgroundDespite evidence from neuroimaging research, diagnosis and early prognosis in the vegetative (VS/UWS) and minimally conscious (MCS) states still depend on the observation of clinical signs of responsiveness. Multiple testing has documented a systematic variability during the day in the incidence of established signs of responsiveness. Spontaneous fluctuations of the Coma Recovery Scale-revised (CRS-r) scores are conceivable.MethodsWe retrospectively analyzed the CRS-r repeatedly administered to 7 VS/UWS and 12 MCS subjects undergoing systematic observation during a conventional 13 weeks. rehabilitation plan.ResultsThe CRS-r global, visual and auditory scores were found higher in the morning than at the afternoon administration in both VS/UWS and MCS subgroups over the entire period of observation. The probability for a VS/UWS subject of being classified as MCS at the morning testing at least once during the 13 weeks. observation was as high as 30 %, i.e., compatible with the reported misdiagnosis rate between the two clinical conditions.ConclusionsMultiple CRS-r testing is advisable to minimize the risk of misclassification; estimates of spontaneous variability could be used to characterize with greater accuracy patients with disorder of consciousness and possibly help optimize the rehabilitation plan.

Visual pursuit marks substantial recuperation from a vegetative state and evolution into a minimally-conscious state, but its incidence in different studies suggests some unreliability in contrast with its established prognostic relevance. Subjects in vegetative (n=9) or minimally-conscious (n=13) states were tested for visual pursuit 6 times/day (9:30, 10:30, and 11:30 am, and 2:00, 3:00, and 4.00 pm, for a total of 132 determinations). Visual pursuit was observed at all testing times in 8 minimally-conscious patients, and never in 5 subjects in a vegetative state. Its incidence per subject ranged from 50-100% of testing times in the minimally-conscious state (83±23%), and 0-33% in a vegetative state (7%±12), with spontaneous fluctuations during the day and maximal levels at 10.30 am and 3.00 pm, and was never observed at the post-prandial time point (2:00 pm). The overall chance of observing visual tracking at least once during the day was ∼33% in the vegetative state, whereas that of not observing it in the minimally-conscious state was ∼38%. These percentages are congruent with the reported misdiagnosis rate between the two conditions, and document spontaneous variability possibly related to circadian rhythms.

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity.Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality.Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN).Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.

Measures of heart rate variability (HRV) are major indices of the sympathovagal balance in cardiovascular research. These measures are thought to reflect complex patterns of brain activation as well and HRV is now emerging as a descriptor thought to provide information on the nervous system organization of homeostatic responses in accordance with the situational requirements. Current models of integration equate HRV to the affective states as parallel outputs of the central autonomic network, with HRV reflecting its organization of affective, physiological, “cognitive,” and behavioral elements into a homeostatic response. Clinical application is in the study of patients with psychiatric disorders, traumatic brain injury, impaired emotion-specific processing, personality, and communication disorders. HRV responses to highly emotional sensory inputs have been identified in subjects in vegetative state and in healthy or brain injured subjects processing complex sensory stimuli. In this respect, HRV measurements can provide additional information on the brain functional setup in the severely brain damaged and would provide researchers with a suitable approach in the absence of conscious behavior or whenever complex experimental conditions and data collection are impracticable, as it is the case, for example, in intensive care units.