About two-thirds of patients who are comatose after resuscitation from cardiac arrest die before hospital discharge, of whom two-thirds die from neurological injury 1. In these patients, ...prognostication is crucial in informing clinicians and patient’s relatives so that appropriate care can be provided.
Background
During COVID-19 lockdown, non-urgent medical procedures were suspended. Grade of urgency of electroencephalography (EEG) may vary according to the clinical indication, setting, and status ...of infection of SARS-CoV-2 virus. “Italian Society of Clinical Neurophysiology” (SINC), “Italian League Against Epilepsy” (LICE), and the “Italian Association of Neurophysiology Technologists” (AITN) aimed to provide clinical and technical recommendation for EEG indications and recording standards in this pandemic era.
Methods
Presidents of SINC, LICE, and AITN endorsed three members per each society to formulate recommendations: classification of the degree of urgency of EEG clinical indications, management and behavior of physicians and neurophysiology technologists, hygiene and personal protection standards, and use of technical equipment.
Results
Scientific societies endorsed a paper conveying the recommendation for EEG execution in accordance with clinical urgency, setting (inpatients/outpatients), status of SARS-CoV-2 virus infection (positive, negative and uncertain), and phase of governmental restrictions (phase 1 and 2). Briefly, in phase 1, EEG was recommended only for those acute/subacute neurological symptoms where EEG is necessary for diagnosis, prognosis, or therapy. Outpatient examinations should be avoided in phase 1, while they should be recommended in urgent cases in phase 2 when they could prevent an emergency room access. Reduction of staff contacts must be encouraged through rescheduling job shifts. The use of disposable electrodes and dedicated EEG devices for COVID-19-positive patients are recommended.
Conclusions
During the different phases of COVID-19 pandemic, the EEG should be reserved for patients really benefiting from its execution in terms of diagnosis, treatment, prognosis, and avoidance of emergency room access.
Patients with Disorder of Consciousness (DoC) entering Intensive Rehabilitation Units after a severe Acquired Brain Injury have a highly variable evolution of the state of consciousness which is a ...complex aspect to predict. Besides clinical factors, electroencephalography has clearly shown its potential into the identification of prognostic biomarkers of consciousness recovery. In this retrospective study, with a dataset of 271 patients with DoC, we proposed three different Elastic-Net regressors trained on different datasets to predict the Coma Recovery Scale-Revised value at discharge based on data collected at admission. One dataset was completely EEG-based, one solely clinical data-based and the last was composed by the union of the two. Each model was optimized, validated and tested with a robust nested cross-validation pipeline. The best models resulted in a median absolute test error of 4.54 IQR = 4.56, 3.39 IQR = 4.36, 3.16 IQR = 4.13 for respectively the EEG, clinical and hybrid model. Furthermore, the hybrid model for what concerns overcoming an unresponsive wakefulness state and exiting a DoC results in an AUC of 0.91 and 0.88 respectively. Small but useful improvements are added by the EEG dataset to the clinical model for what concerns overcoming an unresponsive wakefulness state. Data-driven techniques and namely, machine learning models are hereby shown to be capable of supporting the complex decision-making process the practitioners must face.
Purpose
COVID-19 pandemic has affected most components of health systems including rehabilitation. The study aims to compare demographic and clinical data of patients admitted to an intensive ...rehabilitation unit (IRU) after severe acquired brain injuries (sABIs), before and during the pandemic.
Materials and methods
In this observational retrospective study, all patients admitted to the IRU between 2017 and 2020 were included. Demographics were collected, as well as data from the clinical and functional assessment at admission and discharge from the IRU. Patients were grouped in years starting from March 2017, and the 2020/21 cohort was compared to those admitted between March 2017/18, 2018/19, and 2019/20. Lastly, the pooled cohort March 2017 to March 2020 was compared with the COVID-19 year alone.
Results
This study included 251 patients (
F
: 96 (38%): median age 68 years IQR = 19.25, median time post-onset at admission: 42 days, IQR = 23). In comparison with the pre-pandemic years, a significant increase of hemorrhagic strokes (
p
< 0.001) and a decrease of traumatic brain injuries (
p
= 0.048), a reduction of the number of patients with a prolonged disorder of consciousness admitted to the IRU (
p
< 0.001) and a lower length of stay (
p
< 0.001) were observed in 2020/21.
Conclusions
These differences in the case mix of sABI patients admitted to IRU may be considered another side-effect of the pandemic. Facing this health emergency, rehabilitation specialists need to adapt readily to the changing clinical and functional needs of patients’ addressing the IRUs.
Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. ...With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years IQR = 20, MCS +: 29, MCS -: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS -). EEG-ECG MI, besides clearly discriminating patients in an MCS - and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions.
Cocaine use disorder (CUD) is a global health issue with no effective treatment. Repetitive Transcranial Magnetic Stimulation (rTMS) is a recently proposed therapy for CUD.
We conducted a ...single-center, randomised, sham-controlled, blinded, parallel-group research with patients randomly allocated to rTMS (15 Hz) or Sham group (1:1) using a computerised block randomisation process. We enrolled 62 of 81 CUD patients in two years. Patients were followed for eight weeks after receiving 15 15 Hz rTMS/sham sessions over the left dorsolateral prefrontal cortex (DLPFC) during the first three weeks of the study. We targeted the DLFPC following the 5 cm method. Cocaine lapses in twice a week urine tests were the primary outcome. The secondary outcomes were craving severity, cocaine use pattern, and psychometric assessments.
We randomly allocated patients to either an active rTMS group (32 subjects) or a sham treatment group (30 subjects). Thirteen (42%) and twelve (43.3%) of the subjects in rTMS and sham groups, respectively, completed the full trial regimen, displaying a high dropout rate. Ten/30 (33%) of rTMS-treated patients tested negative for cocaine in urine, in contrast to 4/27 of placebo controls (p = 0.18, odd ratio 2.88, CI 0.9-10). The Kaplan-Meier survival curve did not state a significant change between the treated and sham groups in the time of cocaine urine negativisation (p = 0.20). However, the severity of cocaine-related cues mediated craving (VAS peak) was substantially decreased in the rTMS treated group (p<0.03) after treatment at T1, corresponding to the end of rTMS treatment. Furthermore, in the rTMS and sham groups, self-reported days of cocaine use decreased significantly (p<0.03). Finally, psychometric impulsivity parameters improved in rTMS-treated patients, while depression scales improved in both groups.
In CUD, rTMS could be a useful tool for lowering cocaine craving and consumption.
The study number on clinicalTrials.gov is NCT03607591.
Multisensory human–machine interfaces for virtual- or augmented-reality systems are lacking wearable actuated devices that can provide users with tactile feedback on the softness of virtual objects. ...They are needed for a variety of uses, such as medical simulators, tele-operation systems and tele-presence environments. Such interfaces require actuators that can generate proper tactile feedback, by stimulating the fingertips via quasi-static (non-vibratory) forces, delivered through a deformable surface, so as to control both the contact area and the indentation depth. The actuators should combine a compact and lightweight structure with ease and safety of use, as well as low costs. Among the few actuation technologies that can comply with such requirements, pneumatic driving appears to be one of the most promising. Here, we present an investigation on a new type of pneumatic wearable tactile displays of softness, recently described by our group, which consist of small inflatable chambers arranged at the fingertips. In order to objectively assess the perceptual response that they can elicit, a systematic electroencephalographic study was conducted on ten healthy subjects. Somatosensory evoked potentials (SEPs) were recorded from eight sites above the somatosensory cortex (Fc2, Fc4, C2 and C4, and Fc1, Fc3, C1 and C3), in response to nine conditions of tactile stimulation delivered by the displays: stimulation of either only the thumb, the thumb and index finger simultaneously, or the thumb, index and middle finger simultaneously, each repeated at tactile pressures of 10, 20 and 30 kPa. An analysis of the latency and amplitude of the six components of SEP signals that typically characterise tactile sensing (P50, N100, P200, N300, P300 and N450) showed that this wearable pneumatic device is able to elicit predictable perceptual responses, consistent with the stimulation conditions. This proved that the device is capable of adequate actuation performance, which enables adequate tactile perceptual performance. Moreover, this shows that SEPs may effectively be used with this technology in the future, to assess variable perceptual experiences (especially with combinations of visual and tactile stimuli), in objective terms, complementing subjective information gathered from psychophysical tests.
•EEG reveals differences between prodromal stages of Alzheimer’s Disease.•Microstates analysis yield more inter-condition differences than spectral and network metrics.•Microstate C topography ...differs significantly in patients positive to cerebrospinal fluid Alzheimer’s biomarkers.
Alzheimer’s disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.
As disease-modifying therapies (DMTs) for Alzheimer's disease (AD) are becoming a reality, there is an urgent need to select cost-effective tools that can accurately identify patients in the earliest ...stages of the disease. Subjective Cognitive Decline (SCD) is a condition in which individuals complain of cognitive decline with normal performances on neuropsychological evaluation. Many studies demonstrated a higher prevalence of Alzheimer's pathology in patients diagnosed with SCD as compared to the general population. Consequently, SCD was suggested as an early symptomatic phase of AD. We will describe the study protocol of a prospective cohort study (PREVIEW) that aim to identify features derived from easily accessible, cost-effective and non-invasive assessment to accurately detect SCD patients who will progress to AD dementia.
We will include patients who self-referred to our memory clinic and are diagnosed with SCD. Participants will undergo: clinical, neurologic and neuropsychological examination, estimation of cognitive reserve and depression, evaluation of personality traits, APOE and BDNF genotyping, electroencephalography and event-related potential recording, lumbar puncture for measurement of Aβ
, t-tau, and p-tau concentration and Aβ
/Aβ
ratio. Recruited patients will have follow-up neuropsychological examinations every two years. Collected data will be used to train a machine learning algorithm to define the risk of being carriers of AD and progress to dementia in patients with SCD.
This is the first study to investigate the application of machine learning to predict AD in patients with SCD. Since all the features we will consider can be derived from non-invasive and easily accessible assessments, our expected results may provide evidence for defining cost-effective and globally scalable tools to estimate the risk of AD and address the needs of patients with memory complaints. In the era of DMTs, this will have crucial implications for the early identification of patients suitable for treatment in the initial stages of AD.
NCT05569083.
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