Low incidence of neurological recurrent side-effects following COVID-19 reimmunization.

BACKGROUND: Individuals who suffered a neurological adverse event after COVID-19 vaccine could hesitate and defer reimmunization. AIM: We examine the risk of recurrence following reimmunization among patients who developed a neurological event after first dose of COVID-19 mRNA vaccine. DESIGN: Observational study. METHODS: Individuals who developed an adjudicated neurological adverse event (based on Brighton Collaboration criteria) within 6 weeks of first dose of COVID-19 vaccine requiring hospitalization were enrolled into a multi-center national registry in Singapore. Neurological recurrence, defined by development of another neurological event within 6 weeks of second vaccine dose, was reviewed. Clinical characteristics were compared between patients who chose to proceed or withhold further vaccination, and between those who received timely (3-6 weeks) or delayed (>6 weeks) reimmunization. RESULTS: From 235 patients (median age, 67 years; 63% men) who developed an adjudicated neurological event after their first dose of mRNA vaccine between 30 December 2020 and 20 April 2021, 181 (77%) chose to undergo reimmunization. Those who decided against reimmunization were older (median age, 74 vs 66 years) and had greater physical disability following their primary neurological event (46% vs 20%, p < 0.001). Patients who suffered greater physical disability were 3 times more likely to delay their reimmunization (odds ratio 3.36, 95% CI: 1.76-6.40). Neurological recurrence was observed in only 4 individuals (3 with seizures and 1 with myasthenia gravis exacerbation). CONCLUSION: A prior neurological event should not necessarily preclude reimmunization and the decision to proceed with reimmunization should consider the overwhelming benefits conferred by vaccination towards ending this pandemic.

Corrigendum to "Encephalopathy in COVID-19 patients; viral, parainfectious, or both?" [eNeurologicalScic(Volume 21), December 2020, 100275].

[This corrects the article DOI: 10.1016/j.ensci.2020.100275.].

Impact of Covid-19 on the therapeutic plasma exchange service within the South East Asian region: Consensus recommendations and global perspectives.

INTRODUCTION: Therapeutic plasma exchange (TPE) for neuroimmunological disorders has played an increasingly important role within the Southeast Asian (SEA) region. The South East Asian Therapeutic Plasma exchange Consortium (SEATPEC) was formed in 2018 to promote education and research on TPE within the region. The advent of the Covid-19 pandemic has produced challenges for the development and expansion of this service. METHODOLOGY: A qualitative and semi-quantitative questionnaire-based survey was conducted by SEATPEC member countries from January to June 2020 (Phase 1) and then from July 2020 to January 2021 in (Phase 2) to assess the impact of Covid-19 on regional TPE. OBJECTIVES: The study's main objectives were to explore the challenges experienced and adaptations/adjustments taken by SEATPEC countries in order to continue safe and efficient TPE during the Covid-19 pandemic. RESULTS: The pandemic was found to disrupt the delivery of TPE services in all SEATPEC countries. Contributing factors were multifactorial due to overstretched medical services, staff shortages, quarantines and redeployments, fear of acquiring Covid-19, movement restriction orders, and patient's psychological fear of attending hospitals/testing for Covid-19. All SEATPEC countries practiced careful stratification of cases for TPE (electives vs emergencies, Covid-19 vs non-Covid-19 cases). SEATPEC countries had to modify TPE treatment protocols to include careful preprocedure screening of patient's for Covid-19, use of personal protective equipment (PPE) and post-TPE sanitization of machines and TPE suites. CONCLUSION: Based on the responses of the survey, SEATPEC countries produced a consensus statement with five recommendations for safe and effective TPE within the region.

The Implementation of AI and AI-Empowered Imaging System to Fight Against COVID-19—A Review Implementation of Machine Learning Techniques for the Analysis of Transmission Dynamics of COVID-19 Data-Driven Decision Making in IoT Healthcare Systems—COVID-19: A Case Study Touch and Voice-Assisted Multilingual Communication Prototype for ICU Patients Specific to COVID’19 Cerebral Venous Thrombosis post BNT162b2 mRNA SARS-CoV-2 vaccination: A Black Swan Event

Summary COVID-19 has already affected the world with this deadly virus, resulting in over 3.5 lakh deaths. The behavior of this virus is extraordinarily peculiar and mutates frequently. So, the scientific community faces the problems to analyze and forecast the virus's growth and transmission capability. The combined effort of powerful Artificial intelligence and Image processing techniques to predict the initial pattern of COVID-19 disease identifies the most affected areas in each country through social networking information and predicts drug-protein interactions for making new drugs vaccines. However, AI-empowered X-Ray and computed tomography image acquisition and segmentation techniques help us identify and diagnose the COVID-19 affected patients with minimal contact. In this chapter, our primary motivation is to sum up the essential roles of some AI-driven techniques (Machine learning, Deep learning, etc.) and AI-empowered imaging techniques to analyze, predict, and diagnose against COVID-19 disease. An essential set of open challenges and future research issues on AI-empowered procedures for handling COVID-19 are also discussed in this chapter. Summary This paper mainly deals with the design of Machine Learning model for the analysis of transmission dynamics of Covid 19. The entire globe is affected because of Corona virus. Ventilator dependent, Severe Acute respiratory and quarantine care ICU patients frequently face difficulties for their most basic human interactions, namely communication due to either respiratory illness, language problem or intubated. ICU patients have serious implications with respect to physical and psychological due to non communication problems. Researchers have developed different types of services like Speech language Pathologist so that Augmentative and alternative communication assistance can be given to all health professionals and caretakers. A probabilistic model is designed to analyse the new cases and death cases. Using machine learning approach Regression model is designed and future predications are displayed. The adequacy of the model is discussed along with the residuals of new cased and death cases. PCF and APCAF are obtained. This paper mainly deals with a probabilistic model to analyse and predict the new cases and deaths of covid 19. A new transformation of analyzing stationarity is carried out and based on this forecasting is executed. Summary This research express an impression of automated decision-making techniques that have been suggested for scrutiny of data from IoT based healthcare systems. IoT data analytics plays a vital role in this modern era since data from connected devices reveal meaningful results with better insights for the future. The chapter involves the design of a decision-making system that collects data from IoT based healthcare systems, preprocess and analyzes data, and generates detailed information reports for better diagnosis. Data preprocessing methods such as data cleaning, munging, normalization, reduction, and removing noisy data are applied. The blend of IoT data with analytics technique results to be beneficial in healthcare systems. The collected IoT information like pulse rate, temperature, oxygen level and heart rate from connected devices can be used to analyze the need and severity in the preliminary stage itself using appropriate machine learning techniques. Multi Criteria Decision Making (MCDM) techniques such as SMART, WPM, and TOPSIS are also applied for conclusion production procedure to generate detailed informative diagnostic reports. Being healthcare data, the overall objective is to aid business organizations with better decision making processes through data analytics thereby deploying the right IoT strategy. The result of the next-generation expert systems can utilize the results for further analysis in diagnosis and treatment. Summary The proposed work deals with the design and development of touch and native voice-assisted prototype to enable the intuitive communication & interaction between health professionals and patients who are affected with Severe Acute Respiratory Infection (SARI), Ventilator-dependent and admitted in Quarantine care. It also ensures the development of the multilingual capability to communicate effectively in most speaking ten Indian languages, so that the patients will be relieved from pains etc., as their queries are being addressed by health professionals. In this prototype, touch based gesture patterns can be effectively used as an interactive module and helps the doctors to monitor and answer to the queries of ICU patients regularly by updating it to the caretakers such that the patients are at ease to express their emotions or pains. The proposed prototype will be made available and accessible in an open software repository. As per the existing methods patients express their needs through non-verbal communication methods and they could be missed out or misinterpreted resulting in symptoms that are poorly understood and the clinicians overestimate their ability to understand their communication feelings. These situations are eradicated by employing the use of ?Touch Voice of SARI? Application. Hence this can be considered as an assistive communication tool which replaces the nonverbal communication to a meaningful communication for ventilator patients and healthcare professionals.

Corrigendum to 'Encephalopathy in COVID-19 patients; viral, parainfectious, or both?' [eNeurologicalScic(Volume 21), December 2020, 100275].

[This corrects the article DOI: 10.1016/j.ensci.2020.100275.].

Covert Subclinical Neurocognitive Sequelae During the Rehabilitation Course of Severe Coronavirus Disease 2019.

ABSTRACT: Apart from respiratory symptoms, encephalopathy and a range of central nervous system complications have been described in coronavirus disease 2019. However, there is a lack of published literature on the rehabilitative course and functional outcomes of severe coronavirus disease 2019 with encephalopathy. In addition, the presence of subclinical neurocognitive sequelae during postacute rehabilitation has not been described and may be underrecognized by rehabilitation providers. We report the rehabilitative course of a middle-aged male patient with severe coronavirus disease 2019 who required intensive care and mechanical ventilation. During postacute inpatient rehabilitation for severe intensive care unit-related weakness, an abnormal cognitive screen prompted brain magnetic resonance imaging, which revealed destructive leukoencephalopathy. Subsequently, detailed psychometric evaluation revealed significant impairments in the domains of processing speed and executive function. After 40 days of intensive inpatient rehabilitation, he was discharged home with independent function. This report highlights the need for an increased awareness of covert subclinical neurocognitive sequelae, the role of comprehensive rehabilitation, and value of routine cognitive screening therein and describes the neurocognitive features in severe COVID-19.

Delayed Acute Ischemic Stroke as a Late Manifestation of Asymptomatic COVID-19: The Silent 'Long Haul' Wave of the Pandemic? (preprint)

Background: Multiple neurological manifestations have been associated with acute Coronavirus disease 2019 (COVID-19) infections, however the late sequelae of COVID-19 are less well described. We describe a series of consecutive young men who present with ischemic stroke in the convalescent phase of asymptomatic COVID-19 infection.Methods: We included consecutive young acute ischemic stroke patients (≤50 years old) with laboratory confirmed COVID-19 infections based on positive SARS-CoV-2 serology, without any respiratory symptoms. We reviewed their clinical course, imaging, and laboratory findings.Findings: Eighteen young male patients, aged 35-50 years old, who were diagnosed with asymptomatic COVID-19 based on positive SARS-CoV-2 serology, presented with acute ischemic stroke from 21 May 2020 to 14 October 2020. The median time from positive serology to stroke was 54·5 days (range 0-130). The median age of the patients was 41 (range 35-50), with a median National Institutes of Health Stroke Scale of five (range 1-25). Ten (55·6%) patients presented with large vessel occlusions, of which 6 patients underwent acute recanalization treatment. Only three patients had a possible cardiac source of embolus. The annual incidence rate ischemic stroke was 2·16 (95% CI 1·36 – 3·48, p<0.001) times more compared to an age, sex, ethnicity-matched historical cohort.Interpretation: Eighteen young patients, with laboratory confirmed COVID-19, presented with acute ischemic strokes in the convalescent period. We report what could be the next wave of complications from the COVID-19 pandemic. Larger prospective studies are needed to identify young patients with cryptogenic stroke who may have had COVID-19 infections.Funding: There was no funding for this study.Declaration of Interests: No authors report any conflict of interest related to this study.Ethics Approval Statement: The study was approved by our institutional ethics review board and a waiver of consent was permitted in view of the observational nature of the study.

Encephalopathy in COVID-19 patients; viral, parainfectious, or both?

We describe the clinical, laboratory and radiological features of 3 critically ill patients with COVID-19 who developed severe encephalopathy. The first patient did not regain consciousness when sedation was removed at the end of 2 weeks of intensive care. He had received treatment with convalescent plasma. His clinical examination was remarkable for intact brainstem reflexes, roving eye movements, later transient ocular flutter; and then what appeared to be slow ocular dipping. He had no coherent volitional response to the environment. The second patient recovered with measurable cognitive deficits after a prolonged period of encephalopathy. He had received combination treatment with interferon beta 1b and lopinavir/ritonavir. The third patient remained in persistent, severe agitated delirium and died 3 months into his illness. The MRI of the 3 patients showed multifocal abnormalities predominantly in the cerebral white matter, with varying involvement of the grey matter, brainstem and spinal cord. Case 1's MRI changes were consistent with acute disseminated encephalomyelitis. The patients also displayed blood markers, to varying degree, of autoimmunity and hypercoagulability. We were not able to convincingly show, from microbiological as well as immunological evaluation, if the effects of COVID-19 on these patients' nervous system were a direct consequence of the virus, proinflammatory-thrombotic state or a combination. Patient 1 responded partially to empirical, albeit delayed, therapy with intravenous immunoglobulins. Patient 2 recovered with no specific treatment. These cases illustrate the need to understand the full spectrum of encephalopathy associated with COVID-19 so as to better guide its management.

Neurology of COVID-19 in Singapore.

PURPOSE: To describe the spectrum of COVID-19 neurology in Singapore. METHOD: We prospectively studied all microbiologically-confirmed COVID-19 patients in Singapore, who were referred for any neurological complaint within three months of COVID-19 onset. Neurological diagnoses and relationship to COVID-19 was made by consensus guided by contemporaneous literature, refined using recent case definitions. RESULTS: 47,572 patients (median age 34 years, 98% males) were diagnosed with COVID-19 in Singapore between 19 March to 19 July 2020. We identified 90 patients (median age 38, 98.9% males) with neurological disorders; 39 with varying certainty of relationship to COVID-19 categorised as: i) Central nervous system syndromes-4 acute disseminated encephalomyelitis (ADEM) and encephalitis, ii) Cerebrovascular disorders-19 acute ischaemic stroke and transient ischaemic attack (AIS/TIA), 4 cerebral venous thrombosis (CVT), 2 intracerebral haemorrhage, iii) Peripheral nervous system-7 mono/polyneuropathies, and a novel group, iv) Autonomic nervous system-4 limited dysautonomic syndromes. Fifty-one other patients had pre/co-existent neurological conditions unrelated to COVID-19. Encephalitis/ADEM is delayed, occurring in critical COVID-19, while CVT and dysautonomia occurred relatively early, and largely in mild infections. AIS/TIA was variable in onset, occurring in patients with differing COVID-19 severity; remarkably 63.2% were asymptomatic. CVT was more frequent than expected and occurred in mild/asymptomatic patients. There were no neurological complications in all 81 paediatric COVID-19 cases. CONCLUSION: COVID-19 neurology has a wide spectrum of dysimmune-thrombotic disorders. We encountered relatively few neurological complications, probably because our outbreak involved largely young men with mild/asymptomatic COVID-19. It is also widely perceived that the pandemic did not unduly affect the Singapore healthcare system.