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Background and purpose: Among the most common post-COVID symptoms, many patients experienced subjective cognitive deficit, commonly named "brain fog," that might be present also in those individuals without severe acute COVID-19 respiratory involvement. Some studies have investigated some of the mechanisms that might be associated with the brain fog with objective techniques including transcranial magnetic stimulation and neuroimaging. Methods: The aim of this study was to investigate the presence of electroencephalographic (EEG) alterations in people with post-COVID self-reported cognitive deficit. Results: Out of the 90 patients attending the post-COVID neurology ambulatory service, twenty patients presenting brain fog at least 4 weeks after acute non-severe COVID-19 infection, and without previous history of epilepsy, were investigated with 19-channel EEG, Montreal Cognitive Assessment (MoCA), and magnetic resonance imaging (MRI). EEG was found altered in 65% of the sample, among which 69% presented a slowing activity and 31% were characterized by epileptic discharges principally in the frontal areas. None of the patients showed DWI MRI lesions. Conclusions: These findings highlight the usefulness of EEG analysis to objectively describe possible neurophysiological abnormalities in post-COVID patients presenting subjective cognitive deficit.

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs’ motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5–9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units.

The autonomic nervous system (ANS) can be affected by COVID-19, and dysautonomia may be a possible complication in post-COVID individuals. Orthostatic hypotension (OH) and postural tachycardia syndrome (POTS) have been suggested to be common after SARS-CoV-2 infection, but other components of ANS function may be also impaired. The Composite Autonomic Symptom Scale 31 (COMPASS-31) questionnaire is a simple and validated tool to assess dysautonomic symptoms. The aim of the present study was to administer the COMPASS-31 questionnaire to a sample of post-COVID patients with and without neurological complaints. Participants were recruited among the post-COVID ambulatory services for follow-up evaluation between 4 weeks and 9 months from COVID-19 symptoms onset. Participants were asked to complete the COMPASS-31 questionnaire referring to the period after COVID-19 disease. Heart rate and blood pressure were manually taken during an active stand test for OH and POTS diagnosis. One-hundred and eighty participants were included in the analysis (70.6% females, 51 ± 13 years), and OH was found in 13.8% of the subjects. Median COMPASS-31 score was 17.6 (6.9–31.4), with the most affected domains being orthostatic intolerance, sudomotor, gastrointestinal and pupillomotor dysfunction. A higher COMPASS-31 score was found in those with neurological symptoms (p p p p p

Owing to the large inter-subject variability, early post-stroke prognosis is challenging, and objective biomarkers that can provide further prognostic information are still needed. The relation between quantitative EEG parameters in pre-thrombolysis hyper-acute phase and outcomes has still to be investigated. Hence, possible correlations between early EEG biomarkers, measured on bedside wireless EEG, and short-term/long-term functional and morphological outcomes were investigated in thrombolysis-treated strokes. EEG with a wireless device was performed in 20 patients with hyper-acute (

COVID-19 may increase the risk of heat-related symptoms during hot weather since vulnerable populations, including the elderly and those with neurological disabilities, must continue to self-isolate, often indoors. Within the chronic neurological patient population, indoor conditions in summer months present a hazard because of impaired and/or altered thermoregulation, including poor hydration status due to both autonomic and behavioral dysfunction(s). To address this increased risk, telemedicine protocols should include an assessment of the patient's environmental parameters, and when combined with physiological data from wearable devices, identify those with neurological diseases who are at higher risk of heat illness. Personalized medicine during times of self-isolation must be encouraged, and using smart technology in ambient assisted living solutions, including e-health to monitor physiological parameters are highly recommended, not only during extreme weather conditions but also during times of increased isolation and vulnerability.

Background: Migrainous aura (MA) represents the third most common stroke mimic (SM). Advanced neuroimaging is pivotal in the assessment of patients with focal neurological acute symptoms. We investigated brain perfusion alterations in MA-SM patients using a novel CT perfusion (CTP)-based quantitative approach in order to improve differential diagnosis between MA and acute stroke. Methods: We processed and analysed the clinical and neuroimaging CTP data, acquired within 4.5 h from symptom onset, of patients with acute focal neurological symptoms receiving a final diagnosis of MA. The differences between ROI, compatible with MA symptoms, and contralateral side were automatically estimated in terms of asymmetry index (AI%) by the newly developed tool for mean transit time (MTT), CBF, and cerebral blood volume (CBV) CTP parameters. The AI% ≥ 10% was considered significant. Results: Out of 923 admitted patients, 14 patients with MA were included. In 13 out of 14 cases, a significant pattern of hypoperfusion was observed by quantitative analysis in at least one of the CTP maps. In 7 patients, all three CTP maps were significantly altered. In particular, MTT-AI% increased in 11 (79%) cases, while CBF-AI% and CBV-AI% decreased in 12 (86%) and in 9 (64%) patients, respectively. All CBV values were above ischemic stroke core threshold and all MTT-AI were below ischemic penumbra threshold. Conclusions: Our data suggest that a novel CTP-quantitative approach may detect during MA a moderate hypoperfusion pattern in the cerebral regions compatible with aura symptoms. The use of this novel tool could support differential diagnosis between MA and acute stroke.

Neural networks are dynamic, and the brain has the capacity to reorganize itself. This capacity is named neuroplasticity and is fundamental for many processes ranging from learning and adaptation to new environments to the response to brain injuries. Measures of brain plasticity involve several techniques, including neuroimaging and neurophysiology. Electroencephalography, often used together with other techniques, is a common tool for prognostic and diagnostic purposes, and cortical reorganization is reflected by EEG measurements. Changes of power bands in different cortical areas occur with fatigue and in response to training stimuli leading to learning processes. Sleep has a fundamental role in brain plasticity, restoring EEG bands alterations and promoting consolidation of learning. Exercise and physical inactivity have been extensively studied as both strongly impact brain plasticity. Indeed, EEG studies showed the importance of the physical activity to promote learning and the effects of inactivity or microgravity on cortical reorganization to cope with absent or altered sensorimotor stimuli. Finally, this chapter will describe some of the EEG changes as markers of neural plasticity in neurologic conditions, focusing on cerebrovascular and neurodegenerative diseases. In conclusion, neuroplasticity is the fundamental mechanism necessary to ensure adaptation to new stimuli and situations, as part of the dynamicity of life.

Ocular following eye movements have provided insights into how the visual system of humans and monkeys processes motion. Recently, it has been shown that they also reliably reveal stereoanomalies, and, thus, might have clinical applications. Their translation from research to clinical setting has however been hindered by their small size, which makes them difficult to record, and by a lack of data about their properties in sizable populations. Notably, they have so far only been recorded in adults. We recorded ocular following responses (OFRs)–defined as the change in eye position in the 80–160 ms time window following the motion onset of a large textured stimulus–in 14 school-age children (6 to 13 years old, 9 males and 5 females), under recording conditions that closely mimic a clinical setting. The OFRs were acquired non-invasively by a custom developed high-resolution video-oculography system, described in this study. With the developed system we were able to non-invasively detect OFRs in all children in short recording sessions. Across subjects, we observed a large variability in the magnitude of the movements (by a factor of 4); OFR magnitude was however not correlated with age. A power analysis indicates that even considerably smaller movements could be detected. We conclude that the ocular following system is well developed by age six, and OFRs can be recorded non-invasively in young children in a clinical setting.

Outcome prediction in wake-up ischemic stroke (WUS) is important for guiding treatment strategies, in order to improve recovery and minimize disability. We aimed at producing an interpretable model to predict a good outcome (NIHSS 7-day

Objective Orthostatic hypotension (OH) represents a frequent but under-recognized phenomenon in Parkinson’s disease (PD). During COVID-19 pandemic, Information and Communication Technologies (ICT) have become pivotal in the management of chronic diseases like PD, not only to assess motor impairment, but also for vital signs monitoring. This pilot study aimed to propose a real-time remote home-monitoring system and protocol for PD patients with OH. Methods Vital parameters were acquired by wireless devices and transmitted to an ICT platform, providing data and smart notifications to the healthcare provider through an interactive web portal. Eight patients with idiopathic PD and OH underwent 5-day monitoring. Data about OH episodes, therapeutic interventions, impact on daily activities, and patient satisfaction were collected and analyzed. Results The proposed solution allowed the identification of 65 OH episodes and subsequent medical interventions. Thirty-five episodes were asymptomatic, especially in the postprandial and in the afternoon recordings. Systolic-blood-pressure (SBP) and diastolic-blood-pressure (DBP) were significantly lower in symptomatic episodes, while the pressure drops resulted significantly higher in presence of symptoms. High usability and patient satisfaction scores were observed. Conclusion The proposed home-monitoring system and protocol have proved to provide useful information and to allow prompt interventions in the management of PD patients with OH during COVID-19 pandemic.

Neural networks are dynamic, and the brain has the capacity to reorganize itself. This capacity is named neuroplasticity and is fundamental for many processes ranging from learning and adaptation to new environments to the response to brain injuries. Measures of brain plasticity involve several techniques, including neuroimaging and neurophysiology. Electroencephalography, often used together with other techniques, is a common tool for prognostic and diagnostic purposes, and cortical reorganization is reflected by EEG measurements. Changes of power bands in different cortical areas occur with fatigue and in response to training stimuli leading to learning processes. Sleep has a fundamental role in brain plasticity, restoring EEG bands alterations and promoting consolidation of learning. Exercise and physical inactivity have been extensively studied as both strongly impact brain plasticity. Indeed, EEG studies showed the importance of the physical activity to promote learning and the effects of inactivity or microgravity on cortical reorganization to cope with absent or altered sensorimotor stimuli. Finally, this chapter will describe some of the EEG changes as markers of neural plasticity in neurologic conditions, focusing on cerebrovascular and neurodegenerative diseases. In conclusion, neuroplasticity is the fundamental mechanism necessary to ensure adaptation to new stimuli and situations, as part of the dynamicity of life.

Diagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of classification and regression tree (CART) modeling, the predictive power of heart rate variability (HRV) features together with clinical parameters to support the diagnosis in the early stage of IHD and DCM. The study included 263 IHD and 181 DCM patients, as well as 689 healthy subjects. A 24 h Holter monitoring was used and linear and non-linear HRV parameters were extracted considering both normal and ectopic beats (heart rate total variability signal). We used a CART algorithm to produce classification models based on HRV together with relevant clinical (age, sex, and left ventricular ejection fraction, LVEF) features. Among HRV parameters, MeanRR, SDNN, pNN50, LF, LF/HF, LFn, FD, Beta exp were selected by the CART algorithm and included in the produced models. The model based on pNN50, FD, sex, age, and LVEF features presented the highest accuracy (73.3%). The proposed approach based on HRV parameters, age, sex, and LVEF features highlighted the possibility to produce clinically interpretable models capable to differentiate IHD, DCM, and healthy subjects with accuracy which is clinically relevant in first steps of the IHD and DCM diagnostic process. Graphical abstract

Background: Diagnosis of prodromal Alzheimer's disease (AD) still represents a hot topic and there is a growing interest for the detection of early and non-invasive biomarkers. Although progressive episodic memory impairment is the typical predominant feature of AD, communicative difficulties can be already present at the early stages of the disease. Objective: This study investigated the narrative discourse production deficit as a hallmark of CSFdefined prodromal AD and its correlation with cerebral hypoperfusion pattern. Method: Narrative assessment with a multilevel procedure for discourse analysis was conducted on 28 subjects with Mild Cognitive Impairment (15 MCI due to AD; 13 MCI non-AD) and 28 healthy controls. The diagnostic workup included CSF AD biomarkers. Cerebral hypoperfusion pattern was identified by SPECT image processing. Results: The results showed that the discourse analysis of global coherence and lexical informativeness indexes allowed to identify MCI due to AD from MCI non-AD and healthy subjects. These findings allow to hypothesize that the loss of narrative efficacy could be a possible early clinical hallmark of Alzheimer’s disease. Furthermore, a significant correlation of global coherence and lexical informativeness reduction with the SPECT hypoperfusion was found in the dorsal aspect of the anterior part of the left inferior frontal gyrus, supporting the hypothesis that this area has a significant role in communicative efficacy, and in particular, in semantic selection executive control. Conclusion: This study contributes to the understanding of the neural networks for language processing and their involvement in prodromal Alzheimer's disease. It also suggests an easy and sensitive tool for clinical practice that can help identifying individuals with prodromal Alzheimer’s disease.

Motor-Imagery based BCI (MI-BCI) neurorehabilitation can improve locomotor ability and reduce the deficit symptoms in Parkinson's Disease patients. Advanced Motor-Imagery BCI methods are needed to overcome the accuracy and time-related MI BCI calibration challenges in such patients. In this study, we proposed a Multi-session FBCSP (msFBCSP) based on inter-session transfer learning and we investigated its performance compared to the single-session based FBSCP. The main result of this study is the significantly improved accuracy obtained by proposed msFBCSP compared to single-session FBCSP in PD patients (median 81.3%, range 41.2-100.0% vs median 61.1%, range 25.0-100.0%, respectively; p

Autoimmune limbic encephalitis (LE) is a neurological condition characterized by seizures and cognitive dysfunction. Fluorine-18 fluorodeoxyglucose (18F-FDG-PET) has recently proved to be an important diagnostic tool in this condition since it may highlight brain metabolism abnormalities in a very early stage of the disease. Two main 18F-FDG-PET patterns have been described: the mixed hypermetabolic/hypometabolic and the neurodegenerative one. Arterial spin labeling (ASL) is an MRI technique showing brain perfusion, rarely used in autoimmune neurological conditions. The aim of the present study was to study patients with LE with both techniques, in order to compare their results. Two patients with LE underwent to 18F-FDG-PET and ASL MRI scans using the pseudo-continuous arterial spin labeling (PCASL) technique. Areas of altered perfusion and metabolism were analyzed by visual inspection, and findings were compared between the two techniques. In the first patient, a relapsing LGI-1 LE, right hippocampal hypermetabolism was detected by 18F-FDG-PET (mixed hypermetabolic/hypometabolic pattern), while ASL MRI showed right hippocampal increased perfusion. In the second patient, a seronegative LE, 18F-FDG-PET scan detected a left hemispheric hypoperfusion (neurodegenerative pattern) and ASL MRI yielded similar results. The two 18F-FDG-PET patterns of altered metabolism were similarly detected by ASL imaging. ASL and 18F-FDG-PET findings are strongly concordant in LE. ASL imaging was able to detect the two main 18F-FDG-PET patterns previously described in patients with LE.

Over the years motor deficit in Parkinson's Disease (PD) patients was largely studied, however, no consistent pattern of relations between quantitative electroencephalography (qEEG) and motor scales emerged. There is a general lack of information on the relation between EEG changes and scales related to specific motor deficits. Therefore, the study aimed to investigate the relation between brain oscillatory activity alterations (EEG power bands) and most used PD-related motor deficit scales. A positive correlation was found between the freezing of the gait questionnaire (FOGQ) and delta spectral power band (rho=0.67; p=0.008), while a negative correlation with the same scale was observed in the alpha spectral power band (rho=-0.59, p=0.027). Additionally, motor scores measure by motor part of Unified Parkinson's Disease Rating Scale (UPDRS) correlated directly with theta (rho=0.55, p=0.040) and inversely with beta EEG power band (rho=-0.77, p=0.001). No significant correlation was found between spectral powers and Hoehn and Yahr (H&Y), BERG (Berg K. et. al. 1995), Modified Parkinson Activity Scale (MPAS), Six-Minute Walk Test (6MWT) and Timed Up and Go Test (TUG). In conclusion, our study supports the earlier findings suggesting a link between EEG slowing and motor decline, providing more insight into the relation between EEG alteration and deficits in different motor domains. These findings indicate that EEG assessment may be a useful biomarker for objective monitoring of progression and neurophysiological effect of rehabilitation approaches in PD's.

The accurate measurement of blood pressure (BP) is an important prerequisite for the reliable diagnosis and efficient management of hypertension and other medical conditions. Office Blood Pressure Measurement (OBP) is a technique performed in-office with the sphygmomanometer, while Ambulatory Blood Pressure Monitoring (ABPM) is a technique that measures blood pressure during 24h. The BP fluctuations also depend on other factors such as physical activity, temperature, mood, age, sex, any pathologies, a hormonal activity that may intrinsically influence the differences between OBP and ABPM. The aim of this study is to examine the possible influence of sex on the discrepancies between OBP and ABPM in 872 subjects with known or suspected hypertension. A significant correlation was observed between OBP and ABPM mean values calculated during the day, night and 24h (ABPMday, ABPMnight, ABPM24h) in both groups (p

Space analogs, such as bed rest, are used to reproduce microgravity-induced morphological and physiological changes and can be used as clinical models of prolonged inactivity. Nevertheless, nonuniform decreases in muscle mass and function have been frequently reported, and peripheral nerve adaptations have been poorly studied, although some of these mechanisms may be explained. Ten young healthy males (18–33 yr) underwent 10 days of horizontal bed rest. Peripheral neurophysiological assessments were performed bilaterally for the dominant (DL) and nondominant upper and lower limbs (N-DL) on the 1st and 10th day of bed rest, including ultrasound of the median, deep peroneal nerve (DPN), and common fibular nerve (CFN) , as well as a complete nerve conduction study (NCS) of the upper and lower limbs. Consistently, reduced F waves, suggesting peripheral nerve dysfunction, of both the peroneal (DL: P = 0.005, N-DL: P = 0.013) and tibial nerves (DL: P = 0.037, N-DL: P = 0.005) were found bilaterally, whereas no changes were observed in nerve ultrasound or other parameters of the NCS of both the upper and lower limbs. In these young healthy males, only the F waves, known to respond to postural changes, were significantly affected by short-term bed rest. These preliminary results suggest that during simulated microgravity, most changes occur at the muscle or central nervous system level. Since the assessment of F waves is common in clinical neurophysiological examinations, caution should be used when testing individuals after prolonged immobility.

Brain electrical activity in acute ischemic stroke is related to the hypoperfusion of cerebral tissue as manifestation of neurovascular coupling. EEG could be applicable for bedside functional monitoring in emergency settings. We aimed to investigate the relation between hyper-acute ischemic stroke EEG changes, measured with bedside wireless-EEG, and hypoperfused core-penumbra CT-perfusion (CTP) volumes. In addition, we investigated the association of EEG and CTP parameters with neurological deficit measured by NIHSS. We analyzed and processed EEG, CTP and clinical data of 31 anterior acute ischemic stroke patients registered within 4.5 h from symptom onset. Delta/alpha ratio (DAR), (delta + theta)/(alpha + beta) ratio (DTABR) and relative delta power correlated directly (ρ = 0.72; 0.63; 0.65, respectively), while alpha correlated inversely (ρ = − 0.66) with total hypoperfused volume. DAR, DTBAR and relative delta and alpha parameters also correlated with ischemic core volume (ρ = 0.55; 0.50; 0.59; − 0.51, respectively). The same EEG parameters and CTP volumes showed significant relation with NIHSS at admission. The multivariate stepwise regression showed that DAR was the strongest predictor of NIHSS at admission (p < 0.001). The results of this study showed that hyper-acute alterations of EEG parameters are highly related to the extent of hypoperfused tissue highlighting the value of quantitative EEG as a possible complementary tool in the evaluation of stroke severity and its potential role in acute ischemic stroke monitoring.

Changes in physiological functions after spaceflight and simulated spaceflight involve several mechanisms. Microgravity is one of them and it can be partially reproduced with models, such as head down bed rest (HDBR). Yet, only a few studies have investigated in detail the complexity of neurophysiological systems and their integration to maintain homeostasis. Central nervous system changes have been studied both in their structural and functional component with advanced techniques, such as functional magnetic resonance (fMRI), showing the main involvement of the cerebellum, cortical sensorimotor, and somatosensory areas, as well as vestibular-related pathways. Analysis of electroencephalography (EEG) led to contrasting results, mainly due to the different factors affecting brain activity. The study of corticospinal excitability may enable a deeper understanding of countermeasures' effect, since greater excitability has been shown being correlated with better preservation of functions. Less is known about somatosensory evoked potentials and peripheral nerve function, yet they may be involved in a homeostatic mechanism fundamental to thermoregulation. Extending the knowledge of such alterations during simulated microgravity may be useful not only for space exploration, but for its application in clinical conditions and for life on Earth, as well.

Neurological manifestations may be common in COVID-19 patients. They may include several syndromes, such as a suggested autoimmune abnormal response, which may result in encephalitis and new-onset refractory status epilepticus (NORSE). Quickly recognizing such cases and starting the most appropriate therapy is mandatory due to the related rapid worsening and bad outcomes. This case series describes two adult patients admitted to the university hospital and positive to novel coronavirus 2019 (SARS-CoV-2) infection who developed drug-resistant status epilepticus. Both patients underwent early electroencephalography (EEG) assessment, which showed a pathological EEG pattern characterized by general slowing, rhythmic activity and continuous epileptic paroxysmal activity. A suspected autoimmune etiology, potentially triggered by SARS-CoV-2 infection, encouraged a rapid work-up for a possible autoimmune encephalitis diagnosis. Therapeutic approach included the administration of 0.4 g/kg intravenous immunoglobulin, which resulted in a complete resolution of seizures after 5 and after 10 days, respectively, without adverse effects and followed by a normalization of the EEG patterns.

Purpose The fear of COVID-19 infection may discourage patients from going to the hospital even in case of sudden onset of disabling symptoms. There is growing evidence of the reduction of stroke admissions and higher prevalence of severe clinical presentation. Yet, no studies have investigated the perfusion pattern of acute strokes admitted during the lockdown. We aimed to evaluate the effects of the COVID-19 pandemic on hyper-acute stroke CT perfusion (CTP) pattern during the first months of the pandemic in Italy. Methods In this retrospective observational study, we analyzed CTP images and clinical data of ischemic stroke patients admitted between 9 March and 2 June 2020 that underwent CTP (n = 30), to compare ischemic volumes and clinical features with stroke patients admitted during the same period in 2019 (n = 51). In particular, CTP images were processed to calculate total hypoperfused volumes, core volumes, and mismatch. The final infarct volumes were calculated on follow-up CT. Results Significantly higher total CTP hypoperfused volume (83.3 vs 18.5 ml, p = 0.003), core volume (27.8 vs 1.0 ml, p < 0.001), and unfavorable mismatch (0.51 vs 0.91, p < 0.001) were found during the COVID-19 period compared to no-COVID-19 one. The more unfavorable perfusion pattern at admission resulted in higher infarct volume on follow-up CT during COVID-19 (35.5 vs 3.0 ml, p < 0.001). During lockdown, a reduction of stroke admissions (− 37%) and a higher prevalence of severe clinical presentation (NIHSS ≥ 10; 53% vs 36%, p = 0.029) were observed. Conclusion The results of CTP analysis provided a better insight in the higher prevalence of major severity stroke patients during the COVID-19 period.

There is growing research interest on identification of CT Perfusion (CTP) parameters that predict the outcome in acute ischemic stroke patients. The aim of this study is to produce the model, based on core-penumbra related parameters assessed by CTP processing and commonly used clinical prediction factors, to predict the final infarct volume in thrombolysis-treated anterior circulation wake-up stroke (WUS) patients. The study was conducted on 51 consecutive wake-up ischemic stroke patients. The model for the predictive estimation of final ischemic volume was determined by using the Least Absolute Shrinkage and Selection Operator (LASSO) regularized least-squares regression. The results showed that CTP core volume and CTP total ischemic volume at admission, together with ASPECT score predict the final infarct lesion volume. In particular, the identified model presented 5-fold cross-validation root mean square error RMSE of 8.1 ml and the coefficient of determination (R2=0.94) on our dataset. The results should be confirmed in a lager study. In conclusion, in this study we preliminarily identified a predictive model to estimate final ischemic lesion volume in thrombolysis treated wake-up stroke patients.

BACKGROUND: The worldwide lockdown in response to COVID-19 pandemics has often led to physical inactivity and social distancing. When combined, these factors may affect quality and life and increase the risk of different diseases. Therefore, assessment of physical activity levels should be encouraged to monitor and identify those at a higher risk of inactivity. Smart technology is a promising tool to assess physical activity and health, and may be particularly useful during a period of general lockdown. METHODS: An online survey was developed and shared among the Italian general population to collect data about physical activity and daily routine changes between January 2020 and the lockdown period from 23rd to 29th of March. Participants were asked to provide data such as daily step count (Steps) or heart rate (HR) measured and collected by their smart technology devices. RESULTS: Four hundred participants were included in the final analysis. During the lockdown, the number of steps dropped from 8,284±4,390 to 3,294±3,994 steps (p< 0.001), while mean peak HR decreased from 61.3±18.2% to 55.9±17.3% (p< 0.001). CONCLUSIONS: These findings provide objective data about the effects of the COVID-19 lockdown on physical activity, thus encouraging the use of smart devices to monitor and promote healthy lifestyles while faced with a confinement condition.

Hypohydration may be associated with vascular diseases, poor prognosis and worse outcomes in stroke. The underlying mechanisms have not yet been completely investigated, although some studies suggested potential associations with brain perfusion and collaterals status. Despite the potentially different mechanisms promoting serum or urine biomarkers of hypohydration, few studies have investigated both markers separately. A prospective descriptive study was conducted in stroke patients admitted to a stroke unit 15 and “underhydrated” (UND) if urine osmolality was >500 mOsm/kg. CTP images were processed to calculate core, penumbra, their mismatch and total hypoperfused volume. Forty-six patients were included and were grouped according to hydration status. Despite no different NIHSS at baseline, at CTP HYP was independently associated with core-penumbra mismatch (β: −0.157, 95% CI: −0.305 to −0.009; p =.04), while UND was independently associated with the total hypoperfused volume (β: 31.502, 95% CI: 8.522‒54.481; p =.01). Using CTP imaging, this study proposes a physiological insight of some possible mechanisms associated with the better outcomes observed in acute stroke patients when properly hydrated. These results suggest different associations between hydration status and CTP parameters depending on serum or urine biomarkers in the hyper-acute phase and encourage the association between hydration status and stroke characteristics.

Background: When it comes to critical early post-acute TIA/stroke phase, there is a lack of a comprehensive multi-parametric telemonitoring system. The COVID-19 emergency, its related global mobility restrictions and fear of hospitalization further highlighted the need of a comprehensive solution. Objective: We aimed to design and test a pragmatic e-Health system based on multiparametric telemonitoring to support of TIA/stroke patients in sub-acute phase during the COVID-19 pandemic. Methods: We proposed a telemonitoring system and protocol for TIA/minor stroke patients during COVID-19 pandemic for patients at risk of stroke recurrence. This system involves the use of portable devices for BP/HR/SpO2/temperature sensing, panic-button, gateway, and a dedicated ICT platform. The protocol is a 14-day multiparametric telemonitoring, therapy, and emergency intervention based on vital sign alteration notifications. We conducted a proof-of-concept validation test on 8 TIA/minor stroke patients in the early post-acute phase (< 14 days from ischemic event). Results: The proposed solution allowed to promptly and remotely identify vital sign alterations at home during the early post-acute phase, allowing therapy and behavioral intervention adjustments. Also, we observed a significant improvement of quality of life, as well as a significant reduction of anxiety and depression status. TUQ showed ease of use, good interface quality and high user satisfaction of the proposed solution. The 3-month follow-up showed total adherence of prescribed therapy and no stroke/TIA recurrence or other emergency department admissions. Conclusion: The proposed e-Health solution and telemonitoring protocol may be highly useful for early post-acute remote patient management, thus supporting constant monitoring and patient adherence to the treatment pathway, especially during the COVID-19 emergency.

The human central nervous system integrates different sensory modalities with the visual information to produce a coherent mental representation of our own body, making us capable not only to process sensory events but also to plan and executes movements in the surrounding space. The basis of Mirror Therapy (MT) is the use of a mirror to create a visual reflection of an affected limb to create an illusion of movement of the paretic part of the limb. One of the uses of the MT is in motor recovery in post-stroke hemiparesis and even thought that it is valuable rehabilitation tool, its underlying neurophysiological manifestations and interaction with Motor Imagery (MI) are still unknown. Our study aim is to assess the effect of the MT by applying Forearm Bisection Test (FBT) and EEG measurement of the Event-related (de)synchronisation (ERD/S). Our results show that FBT scores were significantly higher in experimental Mirror Box (MB) group compared to control (CN) group (median 13.54 vs 0.00, respectively; p = 0.003). Furthermore, ΔERD/S (post-pre) differed significantly between the hemispheres in the MB group in the Mu, betalow and betahigh EEG bands, whilst did not differ in the CN group in the Mu and betalow bands. The results demonstrate improvement in ERD/S MI and an update of the body representation caused by MT. Moreover, findings suggest that the reflection of the moving hand in the mirror created an illusion of concomitant movement in the opposite hand that modulate the arm length representation which is detectable even during MI at EEG level. Our findings of neural basis and link of the MT and MI supports MT as favourable neurorehabilitation tool for motor recovery affecting not only the areas governing the moving hand but also the corresponding regions of the other hemisphere.

We investigated brain cortical activity alterations, using a resting-state 256-channel high-density EEG (hd-EEG), in Alzheimer's (AD) and Parkinson's (PD) disease subjects with mild cognitive impairment (MCI) and correlations between quantitative spectral EEG parameters and the global cognitive status assessed by Montreal Cognitive Assessment (MoCA) score.Fifteen AD-MCI, eleven PD-MCI and ten age-matched healthy-controls (HC) underwent hd-EEG recordings and neuropsychological assessment. Cerebrospinal fluid biomarker analysis was performed to obtain well-characterized groups. EEG spectral features were extracted and the differences between the three groups, as well as correlations with MoCA, were investigated.The results showed significantly lower alpha2 power and alpha2/alpha1 ratio in both AD-MCI and PD-MCI compared to controls. The significantly higher theta and lower beta power and alpha/theta ratio were observed in PD-MCI compared to AD-MCI and HC. MoCA score correlated inversely with theta power and directly with alpha2 and beta powers, as well as with alpha2/alpha1 and alpha/theta ratios.This study highlighted significant differences in EEG patterns in AD-MCI and PD-MCI patients and remarked the role of EEG parameters as possible surrogate markers of cognitive status in both neurodegenerative diseases.In addition to well-established biomarkers, our findings could support early detection of cognitive dysfunction in neurodegenerative disorders and could help to monitor disease progression and therapeutic responses.

The diagnosis of heart diseases is a difficult task generally addressed by an appropriate examination of patients’ clinical data. Recently, the use of heart rate variability (HRV) analysis as well as of some machine learning algorithms, has proved to be a valuable support in the diagnosis process. However, till now, ischemic heart disease (IHD) has been diagnosed on the basis of Artificial Neural Networks (ANN) applied only to signs, symptoms and sequential ECG and coronary angiography, an invasive tool, while could be probably identified in a non-invasive way by using parameters extracted from HRV, a signal easily obtained from the ECG. In this study, 18 non-invasive features (age, gender, left ventricular ejection fraction and 15 obtained from HRV) of 243 subjects (156 normal subjects and 87 IHD patients) were used to train and validate a series of several ANN, different for number of input and hidden nodes. The best result was obtained using 7 input parameters and 7 hidden nodes with an accuracy of 98.9% and 82% for the training and validation dataset, respectively.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) is rapidly spreading worldwide, and the WHO declared its pandemic nature on 11th March 20201. The outbreak has hit Europe and, as of April 19, 2020, Italy has the third largest number of confirmed cases, namely a total of 175,925 cases and 23,227 deaths according to the John Hopkins University 2. This is the largest health and economic emergency of our country since the post‐war period, and many hospitals are now dedicated exclusively to COVID‐19 assistance. Our University Hub Stroke Unit of Cattinara Hospital is in the northeaster Italian region of Friuli Venezia Giulia which enlisted 2,731 cases and 222 deaths at the time of writing3.

Objective: Advanced neuroimaging has proved to be pivotal in the management of acute ischemic stroke. The use of CT perfusion (CTP) core and penumbra parameters to predict the outcome in wake-up stroke (WUS) patients in everyday clinical scenarios has not yet been investigated. The aim of our study was to investigate the predictive power of CTP parameters on functional and morphological outcomes in WUS patients treated with recombinant tissue plasminogen activator (rTPA). Approach: We analyzed clinical data and processed CTP images of 83 consecutive WUS patients treated with rTPA. The predictive power of whole-brain CTP features and of the clinical stroke-related parameters to predict the National Institutes of Health Stroke Scale (NIHSS) score at the seventh day and ischemic lesion volume outcome was investigated by means of multivariate regression analysis as well as least absolute shrinkage and selection operator (LASSO) modeling. Main results: Multivariate analysis showed that CTP core volume (β = 0.403, p = 0.000), NIHSS at admission (β = 0.323, p = 0.005) and Alberta Stroke Program Early CT (ASPECT) score (β = -0.224, p = 0.012) predict NIHSS at 7 days, while total hypoperfused volume (β = 0.542, p = 0.000) and core volume on CTP (β =0.441, p = 0.000) predict infarct lesion volume at follow-up CT. The LASSO modeling approach confirmed the significant predictive power of CTP core volume, total hypoperfused CTP volume, NIHSS at baseline and ASPECT score, producing a sparse model with adequate reliability (the root mean square error on a previously unseen testing dataset was 3.68). Significance: Our findings highlight the importance of CT multimodal imaging features for decision-making and prediction in the hyperacute phase of WUS. The predictive model supports the hypothesis that an irreversible necrotic core rather than the extent of the penumbra is the main prognostic factor in WUS patients treated with rTPA.

Background and purpose: Diagnosis of posterior circulation stroke may be challenged. National Institutes of Health Stroke Scale (NIHSS) and brain imaging (non-contrast brain computed tomography-CT) are used for diagnosis; evaluation on posterior circulation stroke remains a limit of NIHSS, and the value of non-contrast CT (NCCT) is limited due to artifacts caused by the bones of the base of the skull. We tested the validity and prognostic value of posterior circulation Alberta Stroke Program Early CT Score (pc-ASPECTS) in patients with posterior circulation stroke. Methods: Pc-ASPECTS allots the posterior circulation 10 points. We studied 50 patients with posterior circulation stroke. We applied pc-ASPECTS to NCCT, CT angiography, and CT Perfusion. We evaluated the correlation of pc-ASPECT with outcome parameters for stroke. Results: Out of 50 patients, CTP showed abnormalities in 34 cases. The pc-ASPECT score calculated on brain CT and on the brain CT + angio CT had a sensibility of 24%, calculated on brain CT, angio CT and CTPerfusion gain a sensibility of 72%. Pc-ASPECT MTT resulted to be the more reliable parameter: outcome given by NIHSS score at discharge, mRS at discharge, and at 3 months was more severe in patients with Pc-ASPECT MTT alteration. Outcome given by NIHSS score at discharge and mRS at discharge and 1 at 3 months was more severe in patients with higher NIHSS score at admission. Conclusion: We evaluated the usefulness of pc-ASPECTS on CTP in predicting functional outcome in acute posterior circulation stroke that appears to be a powerful marker for predicting functional outcome.

Background: One of the most frequently adopted strategies to counterbalance the risk of exercise-induced hypoglycemia in patients with type 1 diabetes is carbohydrates supplement. Nevertheless, the estimation of its amount is still challenging. We investigated the efficacy of the personalized Exercise Carbohydrate Requirement Estimation System (ECRES) method compared to a tabular approach to estimate the glucose supplement needed for the prevention of exercise-related glycemic imbalances. Method: Twenty-six patients performed two one-hour constant intensity exercises one week apart; the amount of extra carbohydrates was estimated, in random order, by the personalized ECRES method or through the tabular approach; glycemia was determined every 30 minutes. Continuous glucose monitoring (CGM) metrics were calculated over the 48 hours preceding, and the afternoon and night following the trials. Results: Applying the personalized ECRES method, a significantly lower amount of carbohydrates was administered to the active patients compared to the tabular approach, median (interquartile range): 9.0 (0.5-21.0) g vs 23.0 (21.0-25.0) g; P < .01; the two methods were similar for the sedentary patients, 18 (13.5-36.0) g vs 23.0 (21.0-27.0) g; P = NS. After overlapping CGM metrics before the exercises, both methods avoided hypoglycemia and resulted in similar glucose levels throughout them. The ECRES method led to CGM metrics within the guidelines for either the afternoon and the night just following the trials, whereas the tabular approach resulted in a significantly greater time below range in the afternoon (11.8% ± 18.2%; P < .05) and time above range during the night (39.3% ± 29.8%; P < .05). Conclusions: The results support the validity of the personalized ECRES method: although the estimated amounts of carbohydrates were lower, patients’ glycemia was maintained within safe clinical limits.

EEG has a central role in the diagnosis of epileptiform abnormalities helpful in diagnosing epilepsy. Since irregularities are random and sporadic events, easily activated in the initial phase of sleep but difficult to observe in a standard EEG examination, sleep deprivation is a frequent condition to be used. Thus, in this study the EEG monitoring of 44 subjects, 14 without epilepsy and 30 with epilepsy, afferent to the IRCCS Centro Neurolesi “Bonino Pulejo” of Messina were examined after sleep deprivation the day before performing the registration. EEGs were recorded according to the international setting system using nineteen channels. The normalized power spectral densities in delta (2–4 Hz), theta (4–8 Hz), alpha (8–13 Hz) and beta (13–30 Hz) band were computed and the non-linear parameters such as beta exponent, fractal dimension and zero crossing were considered. The differences between the sleep and awake were significant in almost all the channels in the beta band and in posterior areas for beta exponent, fractal dimension and zero crossing in normal subjects. In epileptic patients they were significant in all the channels in the delta band and for the non-linear parameters, and in several ones in theta and beta bands. Even if in posterior areas all the spectral and the non-linear parameters showed different values between epileptic and healthy subjects, no significant differences were found. The results suggest that analysis of spectral power as well as of complexity, obtained by non-linear parameters, could be used to identify differences between healthy and epileptic patients.

The study reports the performance of Parkinson's disease (PD) patients to operate Motor-Imagery based Brain-Computer Interface (MI-BCI) and compares three selected pre-processing and classification approaches. The experiment was conducted on 7 PD patients who performed a total of 14 MI-BCI sessions targeting lower extremities. EEG was recorded during the initial calibration phase of each session, and the specific BCI models were produced by using Spectrally weighted Common Spatial Patterns (SpecCSP), Source Power Comodulation (SPoC) and Filter-Bank Common Spatial Patterns (FBCSP) methods. The results showed that FBCSP outperformed SPoC in terms of accuracy, and both SPoC and SpecCSP in terms of the false-positive ratio. The study also demonstrates that PD patients were capable of operating MI-BCI, although with lower accuracy.

Dilated cardiomyopathy (DCM) is a heart muscle disease characterized by left ventricular (LV) or biventricular dilatation and systolic dysfunction in the absence of either pressure or volume overload or coronary artery disease sufficient to explain the dysfunction. The use of heart rate variability (HRV) analysis as well as of some machine learning algorithms, proved to be a valuable support in the diagnosis of cardiovascular disease. However, till now, only single beats or electrocardiogram segments of subjects affected by DCM were identified using machine learning techniques applied to HRV parameters. In this study, we used linear and non-linear HRV parameters and some clinical parameters (age, sex and left ventricular ejection fraction) evaluated on a large cohort of 972 subjects to early identify subjects suffered from DCM and to find which features could be selected as predictors for a correct diagnosis. By using principal component analysis and stepwise regression, we reduced the original parameters used as inputs for a series of classification and regression trees (CART). The highest accuracy of 97% and Area Under the Curve (AUC) of 95% were achieved using the ratio between low frequency and high frequency (LF/HF), sex and left ventricular ejection fraction (LVEF) parameters as inputs of the classifier.

Prognosis in Wake-up ischemic stroke (WUS) is important for guiding treatment and rehabilitation strategies, in order to improve recovery and minimize disability. For this reason, there is growing interest on models to predict functional recovery after acute ischemic events in order to personalize the therapeutic intervention and improve the final functional outcome. The aim of this preliminary study is to evaluate the possibility to predict a good functional outcome, in terms of modified Rankin Scale (mRS ≤ 2), in thrombolysis treated WUS patients by Bayesian analysis of clinical, demographic and neuroimaging data at admission. The study was conducted on 54 thrombolysis treated WUS patients. The Variational Bayesian logistic regression with Automatic Relevance Determination (VB-ARD) was used to produce model and select informative features to predict a good functional outcome (mRS ≤ 2) at discharge. The produced model showed moderately high 10 × 5-fold cross validation accuracy of 71% to predict outcome. The sparse model highlighted the relevance of NIHSS at admission, age, TACI stroke syndrome, ASPECTs, ischemic core CT Perfusion volume, hypertension and diabetes mellitus. In conclusion, in this preliminary study we assess the possibility to model the prognosis in thrombolysis treated WUS patients by using VB ARD. The identified features related to initial neurological deficit, history of diabetes and hypertension, together with necrotic tissue relate ASPECT and CTP core volume neuroimaging features, were able to predict outcome with moderately high accuracy.

The study reports the performance of stroke patients to operate Motor-Imagery based Brain-Computer Interface (MI-BCI) in early post-stroke neurorehabilitation and compares three different BCI spatial filtering techniques. The experiment was conducted on five stroke patients who performed a total of 15 MI-BCI sessions targeting paretic limbs. The EEG data were collected during the initial calibration phase of each session, and the individual BCI models were made by using Source Power Co-Modulation (SPoC), Spectrally weighted Common Spatial Patterns (SpecCSP), and Filter-Bank Common Spatial Patterns (FBCSP) BCI approaches. The accuracy of FBCSP was significantly higher than the accuracy of SPoC (85.1±1.9 % vs. 83.0±1.9 %; p=0.002), while the accuracy of FBCSP was slightly higher than the accuracy of SpecCSP (85.1±1.9 % vs. 83.8±2.0 %; p=0.068). No significant difference was found between SPoC and SpecCSP (p=0.616). The average false positive ratio was 16.9%, 17.1%, 14.3%, while the average false negative was 15.5 %, 16.9 %, 15.5 % for SpecCSP, SPoC, FBCSP, respectively. In conclusion, we demonstrated that the stroke patients were capable of controlling MI-BCI, with high accuracy and that FBCSP may be used as the MI-BCI approach for complementary neurorehabilitation during early stroke phases.

Neuroimaging is crucial for stroke diagnosis and to establish the feasibility of reperfusion therapy, but is not practical for the assessment of continuous evolution of brain ischemia. Electroencephalography (EEG) in the early phase of brain ischemia could be a feasible instrument of functional monitoring. In this context, it would be of great research and clinical interest to assess the relation between EEG parameters and the hypoperfused volume measured by Computed Tomography Perfusion (CTP), as possible real-time surrogate parameters for extent of brain ischemia. This preliminary study aimed at investigating the relation between stroke-related EEG changes, measured on bedside with wireless EEG device, and the extent of hypoperfused volume assessed on CTP during the hyper-acute phase. We studied 12 consecutive ischemic stroke patients who underwent CTP assessment and EEG recording with wireless device within 4.5 hours from symptom onset. Total hypoperfused volume correlated significantly with the delta/alpha power ratio (ρ=0.72; p

LGI1 encephalitis is an autoimmune disorder characterized by cognitive symptoms and seizures, which rarely respond to common antiepileptic drugs (AEDs). Rituximab (RTX) is a CD-20-depleting monoclonal antibody which has been used for the treatment of LGI1 encephalitis, however, its efficacy remains controversial. A 54-year-old woman came to our attention due to memory loss and gambling. Brain MRI revealed areas of bilateral hippocampal hyperintensity and LGI1 antibodies were found in both serum and cerebrospinal fluid. Immunotherapy with steroids was started, followed by intravenous immunoglobulins with partial improvement. The patient developed multiple generalized tonic-clonic seizures. She was then administered intravenous rituximab with significant improvement for both cognitive symptoms and seizure control. High-density EEG was recorded before treatment, seven days after the first dose and seven days after the second dose. Topoplot and power spectrum analysis were performed for each recording. Interictal epileptiform discharges, as well as theta power bands, were significantly reduced after each dose, while topoplot analysis showed reduced spreading over posterior and frontal electrodes for interictal epileptiform discharges of temporal origin. Our experience indicates that rituximab is a valid treatment for LGI1 encephalitis, demonstrating efficacy for both cognitive symptoms and seizure control. High-density EEG could represent a novel, safe and reproducible method to study epileptogenesis in autoimmune limbic encephalitis.

Hypohydration has been suggested increasing the risk of vascular diseases, and it is associated with poor prognosis and worse functional outcome in stroke. Most studies have used blood parameters to determine patients’ hydration status. The aim of this study was to measure urine osmolality (uOsm) and its influence on stroke severity and independence. A prospective descriptive study was conducted in stroke patients admitted to a stroke unit. All patients underwent neurological evaluation at admission and discharge using the National Institute of Health Stroke Scale (NIHSS). Independence at discharge was evaluated with the Barthel Index (BI) and the modified Rankin Scale (mRS). uOsm was measured at admission. Patients were grouped in “poor fluid intake” (PF) and “euhydration” (EU), the latter if uOsm ≤ 500 mOsm/kg. Among 119 included patients, the prevalence of PF was 52%, with no difference observed between groups in demographics or blood samples analyses. PF had higher chances of NIHSS > 8 at admission (OR: 4.7 95% CI: 1.3–17.0; p = 0.02), lower BI at discharge (β: −15.3 95% CI: −26.7 to −3.8; p = 0.01), and worse mRS at discharge (OR: 4.01 95% CI: 1.2–14.0; p = 0.02). These findings are consistent with previous results, suggesting that uOsm may be a factor significantly associated with stroke severity and independence outcome after acute ischemic stroke.

To provide an in vitro estimation of the pressure drop across tracheal tubes (ΔPTT) in the face of given pulsatile frequencies and peak pressures (Pwork) delivered by a high-frequency percussive ventilator (HFPV) applied to a lung model. Tracheal tubes (TT) 6.5, 7.5 and 8.0 were connected to a test lung simulating the respiratory system resistive (R = 5, 20, 50 cmH2O/L/s) and elastic (C = 10, 20, and 50 mL/cmH2O) loads. The model was ventilated by HFPV with a pulse inspiratory peak pressure (work pressure Pwork) augmented in 5-cmH2O steps from 20 to 45 cmH2O, yielding 6 diverse airflows. The percussive frequency (f) was set to 300, 500 and 700 cycles/min, respectively. Pressure (Paw and Ptr) and flow (V’) measurements were performed for all 162 possible combinations of loads, frequencies, and work pressures for each TT size, thus yielding 486 determinations. For each respiratory cycle ΔPTT was calculated by subtracting each peak Ptr from its corresponding peak Paw. A non-linear model was constructed to assess the relationships between single parameters. Performance of the produced model was measured in terms of root mean square error (RMSE) and the coefficient of determination (r2). ΔPTT was predicted by Pwork (exponential Gaussian relationship), resistance (quadratic and linear terms), frequency (quadratic and linear terms) and tube diameter (linear term), but not by compliance. RMSE of the model on the testing dataset was 1.17 cmH2O, r2 was 0.79 and estimation error was lower than 1 cmH2O in 68% of cases. As a result, even without a flow value, the physician would be able to evaluate ΔPTT pressure. If the present results of our bench study could be clinically confirmed, the use of a nonconventional ventilatory strategy as HFPV, would be safer and easier.