Objective.This international multi-center, prospective, observational study aimed at identifying predictors of short-term clinical outcome in patients with prolonged Disorders of Consciousness (DoC) due to acquired severe brain injury.Methods.Patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS) or in minimally conscious state (MCS) were enrolled within 3 months from their brain injury in 12 specialized medical institutions. Demographic, anamnestic, clinical and neurophysiological data were collected at study entry. Patients were then followed-up for assessing the primary outcome, i.e. clinical diagnosis according to standardized criteria at 6 months post-injury.Results.We enrolled 147 patients (44 women; mean age: 49.4 [95% confidence intervals: 46.1-52.6] years; VS/UWS= 71, MCS= 76; traumatic= 55, vascular= 56, anoxic= 36; mean time post-injury= 59.6 [55.4-63.6] days). The 6-month follow-up was complete for 143 patients (VS/UWS= 70; MCS= 73). With respect to study entry, the clinical diagnosis improved in 72 patients (VS/UWS= 27; MCS= 45). Younger age, shorter time post-injury, higher Coma Recovery Scale-Revised total score and presence of EEG reactivity to eye opening at study entry predicted better outcome, whereas etiology, clinical diagnosis, Disability Rating Scale score, EEG background activity, acoustic reactivity and P300 on event related potentials were not associated with outcome.Conclusions.Multimodal assessment could identify patients with higher likelihood of clinical improvement in order to help clinicians, families and funding sources with various aspects of decision-making. This multi-center, international study aims to stimulate further research that drives international consensus regarding standardization of prognostic procedures for patients with DoC.

Background and purpose Patients with prolonged disorders of consciousness (pDoC) have a high mortality rate due to medical complications. Because an accurate prognosis is essential for decision‐making on patients' management, we analysed data from an international multicentre prospective cohort study to evaluate 2‐year mortality rate and bedside predictors of mortality. Methods We enrolled adult patients in prolonged vegetative state/unresponsive wakefulness syndrome (VS/UWS) or minimally conscious state (MCS) after traumatic and nontraumatic brain injury within 3 months postinjury. At enrolment, we collected demographic (age, sex), anamnestic (aetiology, time postinjury), clinical (Coma Recovery Scale–Revised [CRS‐R], Disability Rating Scale, Nociception Coma Scale–Revised), and neurophysiologic (electroencephalogram [EEG], somatosensory evoked and event‐related potentials) data. Patients were followed up to gather data on mortality up to 24 months postinjury. Results Among 143 traumatic (n = 55) and nontraumatic (n = 88) patients (VS/UWS, n = 68, 19 females; MCS, n = 75, 22 females), 41 (28.7%) died within 24 months postinjury. Mortality rate was higher in VS/UWS (42.6%) than in MCS (16%; p < 0.001). Multivariate regression in VS/UWS showed that significant predictors of mortality were older age and lower CRS‐R total score, whereas in MCS female sex and absence of alpha rhythm on EEG at study entry were significant predictors. Conclusions This study demonstrated that a feasible multimodal assessment in the postacute phase can help clinicians to identify patients with pDoC at higher risk of mortality within 24 months after brain injury. This evidence can help clinicians and patients' families to navigate the complex clinical decision‐making process and promote an international standardization of prognostic procedures for patients with pDoC.

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Previous evidence suggests that changes in spontaneous eye blink rate (EBR) in human adults might reflect the amount of attentional demand (i.e. cognitive load) during cognitive tasks. However, the actual direction of this relation is uncertain, since most studies investigated the role of cognitive load on EBR by employing visual tasks only. Here we aimed at elucidating the relationship between EBR and cognitive load in non-visual tasks.Sixteen healthy participants performed two auditory oddball tasks, i.e. passive listening to auditory tones versus active counting of target tones; each oddball task was immediately followed by a rest phase. Throughout the oddball tasks we assessed EBR and recorded the P300 on ERPs as an electrophysiological measure of attention.The results showed that participants' EBR increased during the active task compared to the respective rest phase. Amplitude and latency of the P300 too differed between passive and active tasks, but changes in EBR and P300 features were not correlated with each other.Our findings demonstrated that an increase in cognitive load is associated with an increase in EBR in cognitive tasks not involving visual attention. These findings are consistent with previous evidence suggesting shared neurobiological bases between attention and EBR. tasks [19,20] and found that EBR decreased when task difficulty

Patients with severe acquired brain injury and prolonged disorders of consciousness (pDoC) are characterized by high clinical complexity and high risk to develop medical complications. The present multi-center longitudinal study aimed at investigating the impact of medical complications on the prediction of clinical outcome by means of machine learning models. Patients with pDoC were consecutively enrolled at admission in 23 intensive neurorehabilitation units (IRU) and followed-up at 6 months from onset via the Glasgow Outcome Scale—Extended (GOSE). Demographic and clinical data at study entry and medical complications developed within 3 months from admission were collected. Machine learning models were developed, targeting neurological outcomes at 6 months from brain injury using data collected at admission. Then, after concatenating predictions of such models to the medical complications collected within 3 months, a cascade model was developed. One hundred seventy six patients with pDoC (M: 123, median age 60.2 years) were included in the analysis. At admission, the best performing solution (k-Nearest Neighbors regression, KNN) resulted in a median validation error of 0.59 points [IQR 0.14] and a classification accuracy of dichotomized GOS-E of 88.6%. Coherently, at 3 months, the best model resulted in a median validation error of 0.49 points [IQR 0.11] and a classification accuracy of 92.6%. Interpreting the admission KNN showed how the negative effect of older age is strengthened when patients’ communication levels are high and ameliorated when no communication is present. The model trained at 3 months showed appropriate adaptation of the admission prediction according to the severity of the developed medical complexity in the first 3 months. In this work, we developed and cross-validated an interpretable decision support tool capable of distinguishing patients which will reach sufficient independence levels at 6 months (GOS-E > 4). Furthermore, we provide an updated prediction at 3 months, keeping in consideration the rehabilitative path and the risen medical complexity.

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Background Symptoms of obsessive-compulsive disorder (OCD) have been reported to increase during the COVID-19 lockdowns because of the hygiene requirements related to the pandemic. Patients with adjustment disorder (AD) may, in turn, represent a vulnerable population for identifiable stressors. In this study, we aimed at assessing potential symptoms changes in OCD patients during the lockdown in comparison with AD patients as well as versus healthy controls (HC). Methods During the COVID-related lockdown, we enrolled 65 patients and 29 HC. Participants were tested with four clinical rating scales (Yale–Brown obsessive-compulsive scale and Brown Assessment of Beliefs Scale for OCD patients; Beck Depression Inventory-II and State–Trait Anxiety Inventory-Y for each group) that had been also administered just before the Italian lockdown. Results Our results showed that during the lockdown: (i) the symptoms of depression and anxiety increased in all groups, but this increase was most pronounced in HC (p < 0.001); (ii) OCD symptoms severity did not increase, but the insight worsened (p = 0.028); (iii) the proportion of OCD patients showing hygiene-related symptoms increased (p = 0.031 for obsessions of contamination), whereas that of patients with checking-related symptoms decreased. Conclusions The lockdown-induced psychological distress apparently changed the characteristics and the pattern of OCD symptoms expression but not their overall severity. This evidence confirms the heterogeneity and changing nature of OCD symptoms, strongly depending on the environmental circumstances.

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