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.

Incidence of Cerebral Venous Thrombosis Following SARS-CoV-2 Infection vs mRNA SARS-CoV-2 Vaccination in Singapore.

Importance: Reports of cerebral venous thrombosis (CVT) after messenger RNA (mRNA)-based SARS-CoV-2 vaccination has caused safety concerns, but CVT is also known to occur after SARS-CoV-2 infection. Comparing the relative incidence of CVT after infection vs vaccination may provide a better perspective of this complication. Objective: To compare the incidence rates and clinical characteristics of CVT following either SARS-CoV-2 infection or mRNA-based SARS-CoV-2 vaccines. Design, Setting, and Participants: Between January 23, 2020, and August 3, 2021, this observational cohort study was conducted at all public acute hospitals in Singapore, where patients hospitalized with CVT within 6 weeks of SARS-CoV-2 infection or after mRNA-based SARS-CoV-2 vaccination (BNT162b2 [Pfizer-BioNTech] or mRNA-1273 [Moderna]) were identified. Diagnosis of SARS-CoV-2 infection was based on quantitative reverse transcription-polymerase chain reaction or positive serology. National SARS-CoV-2 infection data were obtained from the National Centre for Infectious Disease, Singapore, and vaccination data were obtained from the National Immunisation Registry, Singapore. Exposures: SARS-CoV-2 infection or mRNA-based SARS-CoV-2 vaccines. Main Outcomes and Measures: Clinical characteristics, crude incidence rate (IR), and incidence rate ratio (IRR) of CVT after SARS-CoV-2 infection and after mRNA SARS-CoV-2 vaccination. Results: Among 62 447 individuals diagnosed with SARS-CoV-2 infections included in this study, 58 989 (94.5%) were male; the median (range) age was 34 (0-102) years; 6 CVT cases were identified (all were male; median [range] age was 33.5 [27-40] years). Among 3 006 662 individuals who received at least 1 dose of mRNA-based SARS-CoV-2 vaccine, 1 626 623 (54.1%) were male; the median (range) age was 50 (12-121) years; 9 CVT cases were identified (7 male individuals [77.8%]; median [range] age: 60 [46-76] years). The crude IR of CVT after SARS-CoV-2 infections was 83.3 per 100 000 person-years (95% CI, 30.6-181.2 per 100 000 person-years) and 2.59 per 100 000 person-years (95% CI, 1.19-4.92 per 100 000 person-years) after mRNA-based SARS-CoV-2 vaccination. Six (66.7%) received BNT162b2 (Pfizer-BioNTech) vaccine and 3 (33.3%) received mRNA-1273 (Moderna) vaccine. The crude IRR of CVT hospitalizations with SARS-CoV-2 infection compared with those who received mRNA SARS-CoV-2 vaccination was 32.1 (95% CI, 9.40-101; P < .001). Conclusions and Relevance: The incidence rate of CVT after SARS-CoV-2 infection was significantly higher compared with after mRNA-based SARS-CoV-2 vaccination. CVT remained rare after mRNA-based SARS-CoV-2 vaccines, reinforcing its safety.

Glial fibrillary acidic protein astrocytopathy in a patient with recent mRNA SARS-CoV-2 vaccination: COVERSHEET

Background Literature describing triggers of GFAP astrocytopathy (GFAP-A) is limited. We report a case of GFAP-A in a patient with recent messenger ribonucleic acid (mRNA) severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) vaccination and discuss the possible pathogenesis. Case description A 45-year-old gentleman presented with features of meningoencephalitis 31 days after the first dose and 4 days after the second dose of mRNA SARS-CoV-2 vaccination. He sequentially developed brainstem/cerebellar, autonomic and cord dysfunction. Cerebrospinal fluid was positive for GFAP autoantibody. Clinical improvement occurred after intravenous methylprednisolone and immunoglobulins. Conclusion Although we are uncertain of a causal link of GFAP-A to mRNA vaccine, indirect activation of an underlying dysregulated immune milieu is plausible.

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.

Acute Ischemic Stroke During the Convalescent Phase of Asymptomatic COVID-2019 Infection in Men.

Importance: Acute ischemic stroke (AIS) is a known neurological complication in patients with respiratory symptoms of COVID-19 infection. However, AIS has not been described as a late sequelae in patients without respiratory symptoms of COVID-19. Objective: To assess AIS experienced by adults 50 years or younger in the convalescent phase of asymptomatic COVID-19 infection. Design, Setting, and Participants: This case series prospectively identified consecutive male patients who received care for AIS from public health hospitals in Singapore between May 21, 2020, and October 14, 2020. All of these patients had laboratory-confirmed asymptomatic COVID-19 infection based on a positive SARS-CoV-2 serological (antibodies) test result. These patients were individuals from South Asian countries (India and Bangladesh) who were working in Singapore and living in dormitories. The total number of COVID-19 cases (54 485) in the worker dormitory population was the population at risk. Patients with ongoing respiratory symptoms or positive SARS-CoV-2 serological test results confirmed through reverse transcriptase-polymerase chain reaction nasopharyngeal swabs were excluded. Main Outcomes and Measures: Clinical course, imaging, and laboratory findings were retrieved from the electronic medical records of each participating hospital. The incidence rate of AIS in the case series was compared with that of a historical age-, sex-, and ethnicity-matched national cohort. Results: A total of 18 male patients, with a median (range) age of 41 (35-50) years and South Asian ethnicity, were included. The median (range) time from a positive serological test result to AIS was 54.5 (0-130) days. The median (range) National Institutes of Health Stroke Scale score was 5 (1-25). Ten patients (56%) presented with a large vessel occlusion, of whom 6 patients underwent intravenous thrombolysis and/or endovascular therapy. Only 3 patients (17%) had a possible cardiac source of embolus. The estimated annual incidence rate of AIS was 82.6 cases per 100 000 people in this study compared with 38.2 cases per 100 000 people in the historical age-, sex-, and ethnicity-matched cohort (rate ratio, 2.16; 95% CI, 1.36-3.48; P < .001). Conclusions and Relevance: This case series suggests that the risk for AIS is higher in adults 50 years or younger during the convalescent period of a COVID-19 infection without respiratory symptoms. Acute ischemic stroke could be part of the next wave of complications of COVID-19, and stroke units should be on alert and use serological testing, especially in younger patients or in the absence of traditional risk factors.

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.