Spatio-Temporal Fractal Dimension Analysis from Resting State EEG Signals in Parkinson's Disease.

Complexity analysis of electroencephalogram (EEG) signals has emerged as a valuable tool for characterizing Parkinson's disease (PD). Fractal dimension (FD) is a widely employed method for measuring the complexity of shapes with many applications in neurodegenerative disorders. Nevertheless, very little is known on the fractal characteristics of EEG in PD measured by FD. In this study we performed a spatio-temporal analysis of EEG in PD using FD in four dimensions (4DFD). We analyzed 42 resting-state EEG recordings comprising two groups: 27 PD patients without dementia and 15 healthy control subjects (HC). From the original resting-state EEG we derived the cortical activations defined by a source reconstruction at each time sample, generating point clouds in three dimensions. Then, a sliding window of one second (the fourth dimension) was used to compute the value of 4DFD by means of the box-counting algorithm. Our results showed a significantly higher value of 4DFD in the PD group (p < 0.001). Moreover, as a diagnostic classifier of PD, 4DFD obtained an area under curve value of 0.97 for a receiver operating characteristic curve analysis. These results suggest that 4DFD could be a promising method for characterizing the specific changes in the brain dynamics associated with PD.

Critical illness polyneuromyopathy: Functional impact after severe acquired brain injuries.

OBJECTIVES: Critical illness polyneuropathy and myopathy (CIPNM) frequently affects critical patients and can occur after severe acquired brain injuries (sABI) influencing the functional recovery. We aimed to assess how the concomitance between CIPNM and sABI might influence the rehabilitative outcomes in terms of functional autonomy, oral feeding recovery and endotracheal tube weaning. MATERIALS AND METHODS: Adult patients with sABI admitted to an intensive rehabilitation unit and underwent an electromyography examination within seven days after admission were included. Assessed rehabilitative outcomes at discharge were decannulation success and its timing, functional autonomy measured by the Functional Independence Measure (FIM) and the Glasgow outcome scale expanded (GOS-E) and oral feeding recovery assessed by the Functional Oral Intake Scale (FOIS) score. RESULTS: Among the 224 included patients (81 (36%) females, age (median[IQR]): 68.73[21.66] years), 119 (53.1%) presented CIPNM at admission. Albeit the change of rehabilitative outcomes between admission and discharge was significant in all the sABI patients (P < .001 for ΔFOIS, ΔFIM and ΔGOS-E), those with a concomitant CIPNM achieved significantly lower scores as evaluated by Mann-Whitney tests (P < .001 for ΔFIM Δ and GOS-E; P < .005 for ΔFOIS). The CIPNM absence was associated with a higher probability to achieve functional autonomy (GOS-E > 4) (OR:4.57 (1.49/14.06); P < .01) and oral feeding recovery (FOIS ≥ 4) (OR:2.07 (1.07/3.99); P = .03) at discharge. CIPNM presence did not influence decannulation success but a longer time to cannula weaning was required (P < .01 in the log-rank test). CONCLUSIONS: CIPMN significantly affects the rehabilitative outcomes after a sABI and should be taken into account for better rehabilitative handling.

EEG and Coma Recovery Scale-Revised prediction of neurological outcome in Disorder of Consciousness patients.

OBJECTIVE: According to electroencephalogram (EEG) descriptors included in the American Clinical Neurophysiology Society (ACNS) terminology, we generated a score, and we compared it to the EEG scores previously proposed in order to identify the one with the best prognostic power for neurological outcome at post-acute stages in patients with severe disorders of consciousness (DoC). MATERIALS AND METHODS: Patients included in the analysis were clinically evaluated with the Coma Recovery Scale-Revised (CRS-R). An EEG was performed within the first week after admission to Intensive Rehabilitation Unit (IRU). EEGs were classified according to the ACNS terminology and to the scores of Bagnato and Estraneo. RESULTS: A total of 260 patients admitted to the IRU were analysed. A total of 160 patients (61%) improved their consciousness level during IRU stay. EEG score based on the ANCS terminology showed higher overall performance (receiver-operating area under the curve = 0.79) and greater sensitivity (65%), at comparable specificities (80%), for clinical improvement as compared to both CRS-R admission score and other EEG scores. Combining our EEG score with CRS-R score at admission, the cumulative sensitivity increased to 76% when at least one good prognostic index test was present in the same patient, whereas specificity increased up to 93% if both the good prognostic patterns of clinical and instrumental parameters were simultaneously present. CONCLUSION: The EEG scored according to the ACNS terminology is the best among those looked at for the prediction of short-term clinical improvement in patients with DoC and represents a useful instrumental test, complementary to clinical evaluation at admission, to be added in post-acute neurological prognostication methods.

Clinical, Neurophysiological, and Genetic Predictors of Recovery in Patients With Severe Acquired Brain Injuries (PRABI): A Study Protocol for a Longitudinal Observational Study.

Background: Due to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of a better outcome very challenging. Identifying the profile of those patients with better prospects of recovery will facilitate clinical and family choices and allow to personalize rehabilitation. This paper describes a multicenter prospective study protocol, to investigate outcomes and baseline predictors or biomarkers of functional recovery, on a large Italian cohort of sABI survivors undergoing postacute rehabilitation. Methods: All patients with a diagnosis of sABI admitted to four intensive rehabilitation units (IRUs) within 4 months from the acute event, aged above 18, and providing informed consent, will be enrolled. No additional exclusion criteria will be considered. Measures will be taken at admission (T0), at three (T1) and 6 months (T2) from T0, and follow-up at 12 and 24 months from onset, including clinical and functional data, neurophysiological results, and analysis of neurogenetic biomarkers. Statistics: Advanced machine learning algorithms will be cross validated to achieve data-driven prediction models. To assess the clinical applicability of the solutions obtained, the prediction of recovery milestones will be compared to the evaluation of a multiprofessional, interdisciplinary rehabilitation team, performed within 2 weeks from admission. Discussion: Identifying the profiles of patients with a favorable prognosis would allow customization of rehabilitation strategies, to provide accurate information to the caregivers and, possibly, to optimize rehabilitation outcomes. Conclusions: The application and validation of machine learning algorithms on a comprehensive pool of clinical, genetic, and neurophysiological data can pave the way toward the implementation of tools in support of the clinical prognosis for the rehabilitation pathways of patients after sABI.

Prognostic value of post-acute EEG in severe disorders of consciousness, using American Clinical Neurophysiology Society terminology.

OBJECTIVE: To evaluate whether electroencephalographic (EEG) features recorded during the post-acute stage in patients with severe disorders of consciousness (DoC) after acute brain injury (ABI), contribute to neurological outcome prediction of these patients at discharge from the intensive rehabilitation unit (IRU). METHODS: We retrospectively evaluated all patients consecutively admitted to the IRU from August 2012 to December 2016. Inclusion criteria were: 1) age >18years, 2) patients with unresponsive wakefulness syndrome (UWS) or in a minimally conscious state (MCS), and 3) EEG and a coma recovery scale-revised (CRS-R) score available within the first week after admission. Clinical evaluation was performed using the Italian version of the CRS-R score. EEGs were classified according to American Clinical Neurophysiology Society (ACNS) terminology. Clinical state at final discharge was evaluated using the CRS-R score. RESULTS: In total, 102 patients were included in the analysis. After a mean of five months of IRU stay, among the 61 UWS subjects, 19 transitioned to MCS and 11 recovered to exit-MCS (E-MCS); twenty-three of the 41 subjects in MCS progressed to E-MCS. Using logistic regression, consciousness level (UWS/MCS-OR=13.4), CRS-R score at admission (OR=1.33) and use of activating drugs (OR=4.7) were significant predictors of clinical improvement. Multivariable analysis showed that specific EEG patterns were independent predictors of improved consciousness at discharge in UWS patients. DISCUSSION: EEG performed within the first week after IRU admission, classified according to ACNS-terminology in patients with UWS at admission, can provide useful prognostic contribution.