IgG4-Related Neurological Disease: A Single Center Ambispective Study from South India.

IgG4-related disease (IgG4-RD) is an immune-mediated multi-system disorder. The nervous system (IgG4-RND) is rarely affected. We describe a short case series. We performed an ambispective analysis of IgG4-RND patients admitted at our centre between January 2016 and December 2022. Eight patients (M: F-2:6) were included with a mean age at presentation of 40.63 ± 17.88 years and disease duration of 5.16 ± 4.08 years. The common diseased sites were pachymeninges (7), orbits (4), paranasal sinuses (3), frontal lobe (1), hypophysis (1), leptomeninges (1), and middle ear (1). Common symptoms were headache and cranial neuropathy. The common nerves involved were the optic nerve, followed by the third, fifth, sixth, and seventh. Cerebrospinal fluid showed lymphocytic pleocytosis. Histopathology showed lymphoplasmacytic infiltrate (8), fibrosis (5), >10 IgG4 + cells (7), and IgG4/IgG >40% (6). Six had a relapsing course. The rituximab-based treatment regimen showed a favourable response.

First-Ever Ischemic Stroke In Covid-19: How Is It Different? - A Stroke Registry-Based Study From South India.

BACKGROUND AND AIMS: Stroke associated with COVID-19 has been characterised in several multicentre retrospective studies and meta-analyses. However, they did not distinguish first-ever ischemic strokes (F-AIS). Therefore, we aimed to study the incidence, clinical characteristics, and outcomes of a cohort of F-AIS associated with COVID-19 during the first wave of the pandemic and compare this cohort with those of F-AIS without COVID-19, COVID-19 without stroke. We also sought to compare the stroke admissions and mechanisms during the pandemic and immediate prepandemic periods.

Guillain-Barré syndrome associated with SARS-CoV-2 vaccination: how is it different? a systematic review and individual participant data meta-analysis.

Purpose: An association between Guillain-Barré syndrome (GBS) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) vaccination has been reported. We aimed to summarize the clinical features of GBS associated with SARS-CoV-2 vaccination and determine the contrasting features from coronavirus disease-19 (COVID-19) associated GBS and GBS following other causes. Materials and Methods: We performed PubMed search for articles published between 1 December 2020 and 27 January 2022 using search terms related to "SARS-CoV-2 vaccination" and "GBS". Reference searching of the eligible studies was performed. Sociodemographic and vaccination data, clinical and laboratory features, and outcomes were extracted. We compared these findings with post-COVID-19 GBS and International GBS Outcome Study (IGOS) (GBS from other causes) cohorts. Results: We included 100 patients in the analysis. Mean age was 56.88 years, and 53% were males. Six-eight received non-replicating virus vector and 30 took messenger RNA (mRNA) vaccines. The median interval between the vaccination and the GBS onset was 11 days. Limb weakness, facial palsy, sensory symptoms, dysautonomia, and respiratory insufficiency were seen in 78.65%, 53.3%, 77.4%, 23.5%, and 25%, respectively. The commonest clinical and electrodiagnostic subtype were sensory-motor variant (68%) and acute inflammatory demyelinating polyneuropathy (61.4%), respectively. And 43.9% had poor outcome (GBS outcome score ≥3). Pain was common with virus vector than mRNA vaccine, and the latter had severe disease at presentation (Hughes grade ≥3). Sensory phenomenon and facial weakness were common in vaccination cohort than post-COVID-19 and IGOS. Conclusion: There are distinct differences between GBS associated with SARS-CoV-2 vaccination and GBS due to other causes. Facial weakness and sensory symptoms were commonly seen in the former and outcomes poor.

Predictors of COVID-19 vaccination rate in USA: A machine learning approach.

In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors' political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. Results from these checks confirm our original findings regarding workplace travels and political affiliation. The accuracy under different model specifications ranges from 80%-88%, whereas the sensitivity is between 92.5%-100%. Our findings provide actionable policy insights to increase vaccination rates and combat the COVID-19 pandemic.

Economic resilience in times of public health shock: The case of the US states.

Does adopting social distancing policies amid a health crisis, e.g., COVID-19, hurt economies? Using a machine learning approach at the intermediate stage, we applied a generalized synthetic control method to answer this question. We utilize state policy response differences. Cross-validation, a machine learning approach, is used to produce the "counterfactual" for adopting states-how they "would have behaved" without lockdown orders. We categorize states with social distancing as the treatment group and those without as the control. We employ the state time-period for fixed effects, adjusting for selection bias and endogeneity. We find significant and intuitively explicable impacts on some states, such as West Virginia, but none at the aggregate level, suggesting that social distancing may not affect the entire economy. Our work implies a resilience index utilizing the magnitude and significance of the social distancing measures to rank the states' resilience. These findings help governments and businesses better prepare for shocks.

Temporal association between SARS-CoV-2 and new-onset myasthenia gravis: is it causal or coincidental?

Several case reports of COVID-19 in patients with myasthenia gravis (MG) have been documented. However, new-onset autoimmune MG following COVID-19 has been reported very rarely. We report one such case here. A 65-year-old man presented to us with dysphagia 6 weeks following mild COVID-19. He was evaluated and diagnosed as antiacetylcholine receptor antibody (AchR) positive, non-thymomatous, generalised MG. He subsequently developed myasthenic crisis and improved after treatment with intravenous immunoglobulin, prednisolone and pyridostigmine. Systematic literature review showed eight more similar cases. Analysis of all cases including the one reported here showed these features: mean age 55.8 years, male gender (5), time interval between COVID-19 and MG (5-56 days), generalised (5), bulbar and/or ocular symptoms (4), anti-AchR antibodies (7) and antimuscle-specific kinase antibodies (2). All have improved with immunotherapy. Although, many hypothesis are proposed to explain causal relationship between the two, it could as well be sheer coincidence.

COVID-19 in Patients with Myasthenia Gravis: Mechanisms of Respiratory Failure.

This report describes a patient with thymomatous myasthenia gravis (MG) with aplastic anemia in pharmacological remission and COVID-19 who developed respiratory failure in the course of the disease and reviews the published literature on this topic. Analysis of the clinical characteristics of the eight patients with MG including our patient suggests two possible mechanisms for respiratory failure: myasthenic crisis (MC) or pulmonary complications of COVID-19. Patients with MC were young women in high-grade MGFA Class whereas patients with respiratory failure due to pulmonary complications of COVID-19 were elderly men in pharmacological remission or MGFA Class I. These observations suggest that COVID-19, like other infections, may precipitate MC in patients with severe grade MG before COVID-19. The only differentiating feature between the two types of failure was severity myasthenic weakness. This clinical distinction has management implications. These observations need to be validated in a larger sample.

Dataset of computed N-value and factual N-value traced for Soil Subsurface Profiling.

Soil requires load bearing impact assessment for stability. Therefore, this study aims to utilize the multi-channel analysis surface wave (MASW) for soil subsurface investigation and profiling around Peninsular Malaysia. The standard penetration test (SPT) was conducted for comparison between factual N-value and computed N-value from shear wave velocity (Vs ) obtained from MASW using the Imai and Tonouchi equation. The correlation coefficient (R) and coefficient of determination, (R2 ), showed strong relationship between factual N-value and computed N-value. The model of Vs and factual N-value data distribution is non-normal but the analyzed relationship shows a significant level of p-value < 0.05. The R2 for each location of Vs -N-value relationship are ranging from 0.5 to 0.9.