Impact of Magnetic Resonance Imaging Markers on the Diagnostic Performance of the International Parkinson and Movement Disorder Society Multiple System Atrophy Criteria.

BACKGROUND: Multiple system atrophy is a neurodegenerative disease with α-synuclein aggregation in glial cytoplasmic inclusions, leading to dysautonomia, parkinsonism, and cerebellar ataxia. OBJECTIVE: The aim of this study was to validate the accuracy of the International Parkinson and Movement Disorder Society Multiple System Atrophy clinical diagnostic criteria, particularly considering the impact of the newly introduced brain magnetic resonance imaging (MRI) markers. METHODS: Diagnostic accuracy of the clinical diagnostic criteria for multiple system atrophy was estimated retrospectively in autopsy-confirmed patients with multiple system atrophy, Parkinson's disease, progressive supranuclear palsy, and corticobasal degeneration. RESULTS: We identified a total of 240 patients. Sensitivity of the clinically probable criteria was moderate at symptom onset but improved with disease duration (year 1: 9%, year 3: 39%, final ante mortem record: 77%), whereas their specificity remained consistently high (99%-100% throughout). Sensitivity of the clinically established criteria was low during the first 3 years (1%-9%), with mild improvement at the final ante mortem record (22%), whereas specificity remained high (99%-100% throughout). When MRI features were excluded from the clinically established criteria, their sensitivity increased considerably (year 1: 3%, year 3: 22%, final ante mortem record: 48%), and their specificity was not compromised (99%-100% throughout). CONCLUSIONS: The International Parkinson and Movement Disorder Society multiple system atrophy diagnostic criteria showed consistently high specificity and low to moderate sensitivity throughout the disease course. The MRI markers for the clinically established criteria reduced their sensitivity without improving specificity. Combining clinically probable and clinically established criteria, but disregarding MRI features, yielded the best sensitivity with excellent specificity and may be most appropriate to select patients for therapeutic trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Prediction of patient survival following postanoxic coma using EEG data and clinical features.

Electroencephalography (EEG) is an effective and non-invasive technique commonly used to monitor brain activity and assist in outcome prediction for comatose patients post cardiac arrest. EEG data may demonstrate patterns associated with poor neurological outcome for patients with hypoxic injury. Thus, both quantitative EEG (qEEG) and clinical data contain prognostic information for patient outcome. In this study we use machine learning (ML) techniques, random forest (RF) and support vector machine (SVM) to classify patient outcome post cardiac arrest using qEEG and clinical feature sets, individually and combined. Our ML experiments show RF and SVM perform better using the joint feature set. In addition, we extend our work by implementing a convolutional neural network (CNN) based on time-frequency images derived from EEG to compare with our qEEG ML models. The results demonstrate significant performance improvement in outcome prediction using non-feature based CNN compared to our feature based ML models. Implementation of ML and DL methods in clinical practice have the potential to improve reliability of traditional qualitative assessments for postanoxic coma patients.

Virtual Care for Neurological Practice.

The COVID-19 crisis has worsened the pre-existing barriers to accessing neurological specialist care in Low and middle income countries. Telemedicine has been available for well over 2 decades but has not been widely adopted in LMIC's due to issues around cost, feasibility, infrastructure and regulation. Virtual care is an offshoot of traditional telemedicine leveraging the widely available internet enabled devices to connect patients with their healthcare providers. In this manuscript, we provide an overview of the virtual care, relevance to neurology and some guidance on implementing virtual care in an Indian context.

Relationship Between Near-Infrared Spectroscopy-Derived Cerebral Oxygenation and Delirium in Critically Ill Patients: A Systematic Review.

BACKGROUND: A common neurological complication of critical illness is delirium, defined as an acute change in level of consciousness, with impaired attention and disorganized thinking. Patients with delirium have increased risk of long-term cognitive dysfunction and mortality. The cause is unknown, which limits our ability to design therapeutic interventions. In patients undergoing surgery, low regional cerebral oxygenation (rSO2), as measured by near-infrared spectroscopy (NIRS), is associated with postoperative neurological dysfunction (eg delirium and long-term cognitive impairment). However, the relationship between NIRS-derived rSO2 and neurological outcomes in critically ill patients is unclear. The objective of this study was to assess the utilization of NIRS-derived rSO2 in critically ill patients outside the operating theater. We aimed to examine the relationship between rSO2 and neurological outcomes as well as to report rSO2 values in this population. METHODS: The following databases were searched from inception to August 14, 2017: Ovid MedLine, Embase, Cochrane Library, and Web of Science. RESULTS: Of 1410 articles identified by the search strategy, 8 were ultimately selected for final review. Most (7 of 8) were published since 2014. These studies included a total of 213 patients primarily with shock or respiratory failure. A variety of devices were used to measure rSO2, including INVOS and FORESIGHT. The duration of recording varied from 5 minutes to 72 hours. Four of the 8 studies reported on neurological outcomes. In all 4 studies, rSO2 was lower in critically ill patients who were delirious compared to controls, but this was only statistically significant in 2 of the studies. The heterogeneity in devices and duration of recording precluded meta-analysis. CONCLUSIONS: There is limited literature describing rSO2 in critically ill patients outside the operating room. Although there may be a slight signal of an association between low rSO2 and delirium, more study is needed to explore this relationship.