This work aims to evaluate the prognostic value of the demographical and clinical data on long-term outcomes (up to 12 months) in patients with severe acquired brain injury with vegetative state/unresponsive wakefulness syndrome (VS/UWS/UWS) or a minimally conscious state (MCS). Patients (n = 211) with VS/UWS/UWS (n = 123) and MCS (n = 88) were admitted to the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology after anoxic brain injury (n = 53), vascular lesions (n = 59), traumatic brain injury (n = 93), and other causes (n = 6). At the beginning of the 12-month study, younger age and a higher score by the Coma Recovery Scale-Revised (CRS-R) predicted a survival. However, no reliable markers of significant positive dynamics of consciousness were found. Based on the etiology, anoxic brain injury has the most unfavorable prognosis. For patients with vascular lesions, the first three months after injury have the most important prognostic value. No correlations were found between survival, increased consciousness, and gender. The demographic and clinical characteristics of patients with chronic DOC can be used to predict long-term mortality in patients with chronic disorders of consciousness. Further research should be devoted to finding reliable predictors of recovery of consciousness.

Analysis of sleep patterns in patients with chronic disorders of consciousness attracts attention from the perspective of the diagnosis and prognosis of the disease as well as the treatment. Yet, the very existence of normal sleep in patients in a vegetative or minimally conscious state is still a matter of debate. This paper presents a retrospective analysis of overnight polysomnographic records of 40 patients with chronic disorders of consciousness aimed at the possibility of establishing the connection between the degree of impaired consciousness and the presence and organization of polysomnographic graphical elements, associated with stages of sleep in normal individuals. Specialized software based on expert system artificial intelligence was developed to calculate indices and parameters that characterize sleep. It was shown that a remarkably low percentage of patients have a rhythmic change in sleep patterns, what indicates the prevalence of violations of the Sleep–Wake cycle in a vegetative state and minimally conscious state. Sleep spindles were not found in records, however, the absence can originate from the limitations of polysomnographic method applied to patients with severe brain damage. A positive correlation between the rhythmic change of sleep patterns, better outcome and CRS-R scores was confirmed.

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