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1.
National Medical Journal of India ; 35(5):290-292, 2022.
Article in English | Web of Science | ID: covidwho-2310458
2.
Expert Systems ; 2023.
Article in English | Scopus | ID: covidwho-2234519

ABSTRACT

In medical science, imaging is the most effective diagnostic and therapeutic tool. Almost all modalities have transitioned to direct digital capture devices, which have emerged as a major future healthcare option. Three diseases such as Alzheimer's (AD), Haemorrhage (HD), and COVID-19 have been used in this manuscript for binary classification purposes. Three datasets (AD, HD, and COVID-19) were used in this research out of which the first two, that is, AD and HD belong to brain Magnetic Resonance Imaging (MRI) and the last one, that is, COVID-19 belongs to Chest X-Ray (CXR) All of the diseases listed above cannot be eliminated, but they can be slowed down with early detection and effective medical treatment. This paper proposes an intelligent method for classifying brain (MRI) and CXR images into normal and abnormal classes for the early detection of AD, HD, and COVID-19 based on an ensemble deep neural network (DNN). In the proposed method, the convolutional neural network (CNN) is used for automatic feature extraction from images and long-short term memory (LSTM) is used for final classification. Moreover, the Hill-Climbing Algorithm (HCA) is implemented for finding the best possible value for hyper parameters of CNN and LSTM, such as the filter size of CNN and the number of units of LSTM while fixing the other parameters. The data-set is pre-processed (resized, cropped, and noise removed) before feeding the train images to the proposed models for accurate and fast learning. Forty-five MR images of AD, Sixty MR images of HD, and 600 CXR images of COVID-19 were used for testing the proposed model ‘CNN-LSTM-HCA'. The performance of the proposed model is evaluated using six types of statistical assessment metrics such as;Accuracy, Sensitivity, Specificity, F-measure, ROC, and AUC. The proposed model compared with the other three types of hybrid models such as CNN-LSTM-PSO, CNN-LSTM-Jaya, and CNN-LSTM-GWO and also with state-of-art techniques. The overall accuracy of the proposed model received was 98.87%, 85.75%, and 99.1% for COVID-19, Haemorrhage, and Alzheimer's data sets, respectively. © 2023 John Wiley & Sons Ltd.

3.
Multiple Sclerosis Journal ; 28(3 Supplement):354-355, 2022.
Article in English | EMBASE | ID: covidwho-2138866

ABSTRACT

Introduction: The long-term benefit-risk profile of ocrelizumab (OCR) in patients (pts) with multiple sclerosis (MS) can be evaluated by regular safety reporting of clinical trial (CT) and post-marketing (PM) data. Safety/efficacy of OCR have been characterised in Phase II (NCT00676715) and Phase III (NCT01247324;NCT01412333;NCT01194570) trials and related open-label extension (OLE) periods, in relapsing-remitting MS, relapsing MS (RMS) and primary progressive MS (PPMS). It is important to understand the long-term safety profile of OCR and consider the impact of COVID-19. Aim(s): To report the continuity in safety by reporting longer-term safety evaluations from OCR CT and OLE periods over a 9-year follow-up period (up to November 2021). Method(s): Safety outcomes, with and without COVID-19, are reported for the OCR all-exposure population from 11 ongoing CTs in MS. Rates per 100 patient years (PY) are presented. Result(s): Over more than 9 years of follow-up, 5,848 pts with MS received OCR treatment in 11 CTs (25,153 PY of exposure;November 2021). Reported rates per 100 PY (95% CI) were: Adverse events (AEs), 232.71 (230.83-234.60), [excluding COVID-19 (EX COV) 230.12 (228.25-232.01)];infections, 69.89 (68.86-70.93), [EX COV 67.37 (66.36-68.39)];serious AEs, 7.61 (7.27-7.96), [EX COV 6.90 (6.58-7.23)];serious infections (SI), 2.74 (2.54-2.96), [EX COV 2.04 (1.87-2.22)];malignancies, 0.41 (0.34-0.50);SI leading to withdrawal, 0.12 (0.08-0.18), [EX COV 0.08 (0.05-0.13)];and AEs leading to discontinuation, 0.97 (0.85-1.10), [EX COV 0.93 (0.81-1.06)]. As of March 2022, over 250,000 pts with MS initiated OCR globally in the PM setting. Data remain generally consistent with those observed in CTs factoring in the impact of the COVID-19 pandemic. Conclusion(s): AE rates in the OCR all-exposure population remain generally consistent with the controlled treatment period in RMS/PPMS populations. Serious infection and malignancy rates remain within the range reported for pts with MS in realworld registries. COVID-19 did not lead to increased treatment withdrawal. Over a 9-year follow-up period, no new or unexpected safety signal was seen in pts treated with OCR in ongoing CTs. OCR continues to exhibit a stable and favourable safety profile. Regular reporting of longer-term safety data will continue.

4.
Research and Practice in Thrombosis and Haemostasis Conference ; 6(Supplement 1), 2022.
Article in English | EMBASE | ID: covidwho-2128101

ABSTRACT

Background: COVID-19 pandemic has evolved dramatically over the past 2 years and literature on COVID coagulopathy has been overwhelming. Understanding literature and assessing the quality of data available is a challenge which is furthermore complicated by the difficulty in defining the 'waves of infection' across the globe. Aim(s): To provide highlights on literature regarding coagulation impairments, thrombotic complications, and anticoagulation use in severe COVID-19 patients, over the past 2 years of the pandemic. Method(s): Performed a systematic search on MEDLINE, EMBASE and EPUB Ahead of Print AND Other Non-Indexed Citations (from inception to 18th July 2021). Studies were eligible for inclusion if written in English, reporting severe COVID-19/ hospitalized patients and reporting coagulopathy data and thrombotic complications. Articles had to be published in journals with impact factor 3 or above. Data ed on country, total number of patients, age and sex, coagulation parameters, thrombotic complications, and anticoagulation data. Result(s): Identified 62 studies (PRISMA in Figure 1). A total of 18,581 patients reported from 16 different countries (Figure 2) published between March 2020 to July 2021 were included in this review. Coagulation lab parameters were reported in most studies with considerable heterogeneity on data reported. A key finding is a pro-coagulant profile with hypercoagulability more pronounced in ICU patients. Controversy existed around thrombocytopenia in association with severe or late disease. Elevated fibrinogen was reported in 37/41 (90%) studies. Elevated D-dimer was consistently reported and was predictive of thrombosis and poor outcome. 46 (74%) studies reported VTE which occurred despite guideline-recommended thromboprophylaxis. Anticoagulation was reported in all studies, but practices were diverse. Conclusion(s): Evident heterogeneity of clinical and laboratory findings of reported studies with inconsistent reporting on coagulation parameters, units of measurement and relationship to disease outcomes. This study can help investigators carefully design future studies related to coagulopathy in COVID-19. (Figure Presented).

5.
Orphan Crops for Sustainable Food and Nutrition Security: Promoting Neglected and Underutilized Species ; : 319-326, 2021.
Article in English | Scopus | ID: covidwho-2100096

ABSTRACT

This chapter examines the acceptability and viability of millets as a component of a Farming Systems for Nutrition (FSN) approach, and in the public distribution system (PDS). Millets were promoted as nutrient-dense crops under a study to demonstrate the feasibility of an FSN approach to address malnutrition in the Wardha district in Maharashtra and the Koraput district in Odisha, India. With improved crop varieties and better agronomic practices, such as line sowing, timely weeding, and proper application of fertilizers, along with nutrition awareness, both the production and consumption of finger millets increased in Koraput. Political commitment is also important, as seen from the case of millet distribution through the PDS of Karnataka. It is necessary to streamline procurement mechanisms in line with the harvest period, equip officials with proper training in quality assessment, and reduce the time between procurement and payment to farmers. With an emphasis on production, consumption and distribution, this climate-resistant, nutrient-dense crop can be a healthy and sustainable component of the food systems of people - a point reinforced by the COVID-19 pandemic that is affecting the food and nutrition security of many. © 2022 selection and editorial matter, Stefano Padulosi, E.D. Israel Oliver King, Danny Hunter and M.S. Swaminathan.

7.
Chest ; 162(4):A830-A831, 2022.
Article in English | EMBASE | ID: covidwho-2060698

ABSTRACT

SESSION TITLE: Critical Care Management of COVID-19 SESSION TYPE: Original Investigations PRESENTED ON: 10/17/2022 01:30 pm - 02:30 pm PURPOSE: Acute respiratory distress syndrome (ARDS), due to Coronavirus disease 2019 (COVID-19) Is associated with a significant rate of mortality. The ideal sedative(s) of choice in mechanically ventilated COVID-19 patients is still unclear. Here we report the clinical outcomes of using propofol for more than 48 hours vs any other sedative in such patients. METHODS: This was a retrospective study of patients admitted to an intensive care unit (ICU) at Trumbull Regional Medical Centre and Sharon Regional Medical Centre between February 2020 and January 2022 with COVID-19 viral pneumonia. Our study consisted of 176 patients with moderate to severe ARDS as per Berlin’s criteria who were mechanically ventilated for atleast 48 hours. The primary outcome was mortality at 28 days from the date of intubation. Secondary outcomes included ventilator free days during the first 28 days after intubation (defined as being alive and free from mechanical ventilation), mortality at the end of hospitalization, length of stay, and readmission rate. RESULTS: Out of 176 patients, 100 patients received sedation with propofol for more than 48 hours (test group) and 76 patients received other sedative agents or received propofol for less than 48 hours (control group). We compared the outcomes of the two different groups using paired t-test. The average age of the study population (63 vs 67 p=0.061), gender((0.44 vs 0.49 females p=0.54), BMI (34.93 vs 34.08 p=0.54), and oxygen requirement on admission (0.73 vs 0.64 p= 0.227) were not statistically different between the test and control groups respectively. Prevalence of comorbidities including diabetes, hypertension, chronic kidney disease, active cancer, and COPD were not significantly different between the two groups. There was a significant difference in the primary outcome of mortality at day 28 from intubation between the test and control group (0.62 vs 0.84 p=0.001). A significant difference in the secondary outcome of mortality at the end of hospitalization between the test group and control group (0.67 vs 0.84 p =0.009) was also observed. There were no statistically significant differences in the rest of secondary outcomes. CONCLUSIONS: In this retrospective study, using propofol for more than 48 hours was associated with decreased mortality at day 28 (22%) as well as at end of hospitalization (17%) in mechanically ventilated COVID-19 patients. Propofol is known to have antiviral effects as well as immunosuppressive effects on biosynthesis of inflammatory cytokines by macrophages which is likely responsible for the mortality benefits that we encountered in this study. CLINICAL IMPLICATIONS: Even though we found mortality benefits with using propofol in our study population, further investigations using prospective studies with a larger study population are required and clinicians need to be cautious with the complications associated with long term use of propofol. DISCLOSURES: No relevant relationships by Arooj Ahmed no disclosure submitted for Manuel Bautista;No relevant relationships by Apeksha Gupta No relevant relationships by Anirudh Jaglan no disclosure on file for Saman Karki;no disclosure submitted for Ritha Kartan;No relevant relationships by Tamandeep Kaur No relevant relationships by Sanjay Mahat No relevant relationships by Krutarth Pandya No relevant relationships by Stuti Patel No relevant relationships by Janki Patel no disclosure on file for Kim Porter;No relevant relationships by Aayush Pradhan No relevant relationships by Arun Pyakuryal No relevant relationships by Pratik Saha No relevant relationships by Parth Shah

8.
Journal of Scientometric Research ; 11(1):47-54, 2022.
Article in English | Web of Science | ID: covidwho-1897066

ABSTRACT

This study aims to analyze the dynamics of the published articles and preprints of Covid-19 related literature from different scientific databases and sharing platforms. The PubMed, ScienceDirect, and ResearchGate (RG) databases were under consideration in this study over a specific time. Analyses were carried out on the number of publications as (a) function of time (day), (b) journals and (c) authors. Doubling time of the number of publications was analyzed for PubMed "all articles" and ScienceDirect published articles. Analyzed databases were (1A) PubMed (01/12/2019-12/06/2020) "all_articles" (16) PubMed Review articles) and (1C) PubMed Clinical Trials (2) ScienceDirect all publications (01/12/2019- 25/05/2020) (3) RG (Article, Pre Print, Technical Report) (15/04/2020 - 30/4/2020). Total publications in the observation period for PubMed, ScienceDirect, and RG were 23000, 5898 and 5393 respectively. The average number of publications/day for PubMed, ScienceDirect and RG were 70.0 +/- 128.6, 77.6 +/- 125.3 and 255.6 +/- 205.8 respectively. PubMed shows an avalanche in the number of publications around May 10, the number of publications jumped from 6.0 +/- 8.4/day to 282.5 +/- 110.3/ day. The average doubling time for PubMed, ScienceDirect, and RG was 10.3 +/- 4 days, 20.6 days, and 2.3 +/- 2.0 days respectively. The average number of publications per author for PubMed, ScienceDirect, and RG was 1.2 +/- 1.4, 1.3 +/- 0.9, and 1.1 +/- 0.4 respectively. Subgroup analysis, PubMed review articles mean review <0 vertical bar 17 +/- 17 vertical bar 77> days: and reducing at a rate of -0.21 days (count)/day. The number of publications related to the COVID-19 until now is huge and growing very fast with time. It is essential to rationalize and limit the publications.

9.
Journal of Facilities Management ; : 18, 2022.
Article in English | Web of Science | ID: covidwho-1799388

ABSTRACT

Purpose The stock market has shown fluctuating degrees of volatility because of the recent COVID-19 pandemic in India. The present research aims to investigate the effect of the COVID-19 on the stock market volatility, and whether the economic package can control the market volatility or not, measured by a set of certain sector-level economic features and factors such as resilience variables. Design/methodology/approach We examine the correlation matrix, basic volatility model and robustness tests to determine the sector-level economic features and macroeconomic factors helpful in diminishing the volatility rising because of the COVID-19. Findings The outcomes of this study are significant as policymakers and financial analysts can apply these economic factors to set policy replies to handle the unexpected fluctuation in the stock market in sequence to circumvent any thinkable future financial crisis. Originality/value The originality of the paper is to measure the variables affecting the stock market volatility due to COVID-19, and understand the impact of capital market macroeconomic variables and dummy variables to theoretically explain the COVID-19 impact on stock market volatility.

10.
7th IEEE International Symposium on Smart Electronic Systems, iSES 2021 ; : 450-455, 2021.
Article in English | Scopus | ID: covidwho-1759115

ABSTRACT

The COVID-19 outbreak highlighted the smart healthcare infrastructure requirement to speed up vaccination and treatment. Present vaccination supply chain models are fragmented in nature, and they are suitable for a pandemic like COVID-19. Most of these vaccination supply chain models are cloud-centric and depend on humans. Due to this, the transparency in the supply chain and vaccination process is questionable. Moreover, we con't trace where the vaccination programs are facing issues in real-time. Furthermore, traditional supply chain models are vulnerable to a single point of failure and lack people-centric service capabilities. This paper has proposed a novel supply chain model for COVID-19 using robust technologies such as Blockchain and the Internet of Things. Besides, it automates the entire vaccination supplication chain, and it records management without compromising data integrity. We have evaluated our proposed model using Ethereum based decentralized application (DApp) to showcase its real-time capabilities. The DApp contains two divisions to deal with internal (intra) and worldwide (inter) use cases. From the system analysis, it is clear that it provides digital records integrity, availability, and system scalability by eliminating a single point of failure. Finally, the proposed system eliminates human interference in digital record management, which is prone to errors and alternation. © 2021 IEEE.All rights reserved.

11.
Journal of Computational Neuroscience ; 49(SUPPL 1):S146-S147, 2021.
Article in English | Web of Science | ID: covidwho-1610194
12.
Multiple Sclerosis Journal ; 27(2 SUPPL):607-608, 2021.
Article in English | EMBASE | ID: covidwho-1495999

ABSTRACT

Introduction: Ongoing consistent safety reporting is crucial to understand the long-term benefit-risk profile of ocrelizumab (OCR) in patients with multiple sclerosis (MS), in both clinical trials and globally, in the post-marketing (PM) setting. Safety/efficacy of OCR have been characterised in Phase II (NCT00676715) and Phase III (NCT01247324;NCT01412333;NCT01194570) trials and related open-label extension (OLE) periods, in patients with relapsing-remitting MS, relapsing MS (RMS) and primary progressive MS (PPMS). It is important to understand the longterm safety profile of OCR independent of any impact of COVID- 19 infections. Aims: To maintain continuity in the safety update by reporting longer-term safety evaluations from OCR clinical trials and OLE periods up to November 2020 and selected PM data, excluding COVID-19 cases;the latter will be communicated in a separate late-breaking abstract. Methods: Safety outcomes, excluding COVID-19, are reported for the OCR all-exposure population in Phase II/III trials and associated OLEs plus ongoing Phase IIIb trials in MS (VELOCE, CHORDS, CASTING, OBOE, ENSEMBLE, LIBERTO and CONSONANCE). To account for different exposure lengths, rates per 100 patient years (PY) are presented. The number of postmarketing OCR-treated patients is based on estimated number of vials sold and US claims data. Results: In clinical trials, 5,688 patients with MS received OCR (21,675 PY of exposure;Nov 2020). Reported rates per 100 PY (95% confidence interval) were: Adverse events (AEs), 238 (236- 240);infections, 71.8 (70.7-73.0);serious AEs, 7.05 (6.71-7.42);serious infections, 2.0 (1.82-2.20);malignancies, 0.42 (0.34- 0.52);and AEs leading to discontinuation, 0.96 (0.83-1.10). As of December 2020, over 200,000 patients with MS initiated OCR globally in the PM setting. Data remain generally consistent with those observed in clinical trials. Conclusions: AE rates in the OCR all-exposure population and PM settings, excluding COVID-19 infections, remain generally consistent with the controlled treatment period in RMS/PPMS populations. Serious infection and malignancy rates remain within the range reported for patients with MS in real-world registries. In patients with RMS and PPMS, OCR demonstrates a consistent and favourable safety profile;these longer-term data are in accordance with the safety outcomes initially observed during the controlled treatment periods. Regular reporting of longer-term safety data will continue.

13.
Journal of General Internal Medicine ; 36(SUPPL 1):S434-S435, 2021.
Article in English | Web of Science | ID: covidwho-1348989
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