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1.
IEEE Transactions on Engineering Management ; : 1-15, 2022.
Article in English | Scopus | ID: covidwho-2107855

ABSTRACT

COVID-19 pandemic has created disruptions and risks in global supply chains. Big data analytics (BDA) has emerged in recent years as a potential solution for provisioning predictive and pre-emptive information to companies in order to preplan and mitigate the impacts of such risks. The focus of this article is to gain insights into how BDA can help companies combat a crisis like COVID-19 via a multimethodological scientific study. The advent of a crisis like COVID-19 brings with it uncertainties, and information processing theory (IPT) provides a perspective on the ways to deal with such uncertainties. We use IPT, in conjunction with the Crisis Management Theory, to lay the foundation of the article. After establishing the theoretical basis, we conduct two surveys towards supply chain managers, one before and one after the onset of the COVID-19 pandemic in India. We follow it up with qualitative interviews to gain further insights. The application of multiple methods helps ensure the triangulation of results and, hence, enhances the research rigor. Our research finds that although the current adoption of BDA in the Indian industry has not grown to a statistically significant level, there are serious future plans for the industry to adopt BDA for crisis management. The interviews also highlight the current status of adoption and the growth of BDA in the Indian industry. The article interestingly identifies that the traditional barriers to implementing new technologies (like BDA for crisis management) are no longer present in the current times. The COVID-19 pandemic has hence accelerated technology adoption and at the same time uncovered some BDA implementation challenges in practice (e.g., a lack of data scientists). IEEE

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5.
Infect Dis Now ; 52(5): 286-293, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1930875

ABSTRACT

OBJECTIVES: We aimed to compare the outcomes of COVID-19 Renal Transplant Recipients (RTRs) managed on an ambulatory basis to that of inpatient management. DESIGN, SETTING, MATERIALS, AND METHODS: We performed a retrospective study in Lucknow, India, comparing the ambulatory management with the historical cohort managed in the hospital.R RTRs with mild COVID-19 were managed by supervised home-based self-monitoring (HBSM), a strategy to manage this high-risk group on an outpatient basis during the second wave of the pandemic. The primary outcome was the clinical deterioration to a higher severity category among RTRs with mild COVID-19 managed by HBSM compared to hospitalized patients within two weeks of disease onset. RESULTS: Of the 149 RTRs with mild COVID-19, 94 (63%) and 55 (37%) were managed by HBSM and in the hospital, respectively. The proportion of RTRs who clinically deteriorated to a higher severity category (moderate or severe category) was similar among both groups (28.7% versus 27.2%, P=0.849). Among RTRs with clinical deterioration, COVID-19-related death was reported in two patients of the HBSM group and in none of the patients of the hospitalized group. Graft dysfunction was higher in the hospitalized group (7.4% versus 27.2%, P=0.002). Median time to complete clinical recovery (7 days in both groups), secondary bacterial infections (25% versus 33.3%, P=0.41), and the mean decline in EQ-5D score from baseline at six weeks (-6.6 versus-4.3, P=0.105) were found to be similar in both groups.


Subject(s)
COVID-19 , Clinical Deterioration , Kidney Transplantation , COVID-19/epidemiology , Humans , Retrospective Studies , SARS-CoV-2
6.
Rheumatology (United Kingdom) ; 61(SUPPL 1):i140, 2022.
Article in English | EMBASE | ID: covidwho-1868422

ABSTRACT

Background/Aims Treatment guidelines for psoriatic arthritis consider both skin and joint involvement and recommend collaborative multidisciplinary team (MDT) working when selecting therapy. However, multidisciplinary practice for psoriatic disease (PD) has not been well studied, with little data on service models and current practice. This survey explored collaborative working in PD treatment by rheumatology and dermatology healthcare professionals (HCPs) to provide a better understanding of current working patterns, collaborating specialties, as well as benefits and challenges of combined clinics for PD management. Methods An online survey was emailed to rheumatology and dermatology HCPs using professional networks. We requested information on role, collaborating specialties, benefits and barriers to collaborative working in PD, and the impact of COVID-19. The ideal service model and additional comments completed the survey. Results We received 80 responses between October 2020 and April 2021, covering England, Wales, Scotland and Northern Ireland. Of these, 56 respondents (70.0%) were consultants, 22 (27.5%) clinical nurse specialists and one each a lead pharmacist (1.3%) and specialist registrar (1.3%). Rheumatology HCPs accounted for 40.0% of respondents (n=32) and dermatology HCPs for 60.0% (n=48). As part of their PD MDT, most respondents (n=60, 75.0%) worked collaboratively with other specialties. Combined clinics, whether virtual, face to face or an MDT, accounted for 51.5% of collaborative working for rheumatology HCPs and 58.9% for dermatology HCPs. Collaboration with other specialists mainly occurred by email or written referrals (Table 1). The most important perceived benefits of combined clinics were shared knowledge, better patient outcomes and patient satisfaction. The biggest challenges to setting up combined clinics were job plan time (rated as 'difficult' or 'very difficult' by 78.8% of respondents), logistics (67.5%) and unsupportive senior management (66.3%), while 77.5% felt COVID-19 had partial or significant impact on combined clinics. Conclusion This is the first survey to explore UK collaborative working in PD. Approaches varied, with different models of working and little consistency. While HCPs appreciated the benefits of collaborative working, numerous challenges in establishing formal arrangements were identified. More evidence is needed to demonstrate the perceived benefits of collaborative working in improving patient outcomes by standardising best practice.

8.
IEEE International Conference on Communications (ICC) ; 2021.
Article in English | Web of Science | ID: covidwho-1559839

ABSTRACT

The ongoing pandemic of COVID-19 has shown the limitations of our current medical institutions. There is a need for research in automated diagnosis for speeding up the process while maintaining accuracy and reducing computational requirements. In this work, an IoT and edge computing based framework is proposed to automatically diagnose COVID-19 from CT scans of the patients using Deep Learning techniques. The proposed method requires less computational power and uses ensemble learning to increase the models' overall predictive performance. In the simulation, it was found that each model performs better in some areas than the other. The proposed scheme uses ensemble learning to take advantage of such an occurrence and achieved an accuracy of 86.2% and an AUC score of 89.8% on the COVID-CT-Dataset. This accuracy is achieved keeping the hardware accessibility in mind by training the models using a labeled dataset of CT-scans of the patients. Unlike other works, we were able to train models on a single enterprise-level GPU. It can easily be provided on the edge of the network, which reduces communication overhead and latency. This work aims to demonstrate a less hardware-intensive approach for COVID-19 detection with excellent performance combined with medical equipment and help ease the examination procedure.

9.
2021 IEEE International Conference on Communications, ICC 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1447821

ABSTRACT

The ongoing pandemic of COVID-19 has shown the limitations of our current medical institutions. There is a need for research in automated diagnosis for speeding up the process while maintaining accuracy and reducing computational requirements. In this work, an IoT and edge computing based framework is proposed to automatically diagnose COVID-19 from CT scans of the patients using Deep Learning techniques. The proposed method requires less computational power and uses ensemble learning to increase the models' overall predictive performance. In the simulation, it was found that each model performs better in some areas than the other. The proposed scheme uses ensemble learning to take advantage of such an occurrence and achieved an accuracy of 86.2% and an AUC score of 89.8% on the COVIDCT-Dataset. This accuracy is achieved keeping the hardware accessibility in mind by training the models using a labeled dataset of CT-scans of the patients. Unlike other works, we were able to train models on a single enterprise-level GPU. It can easily be provided on the edge of the network, which reduces communication overhead and latency. This work aims to demonstrate a less hardware-intensive approach for COVID19 detection with excellent performance combined with medical equipment and help ease the examination procedure. © 2021 IEEE.

10.
Nephrology Dialysis Transplantation ; 36(SUPPL 1):i467, 2021.
Article in English | EMBASE | ID: covidwho-1402477

ABSTRACT

BACKGROUND AND AIMS: Asymptomatic maintenance hemodialysis patients with SARS-COV-2are missed with pre-dialysis screening without testing. The possible ideal strategy of testing each patient before each shift with RT-PCR was not feasible. We aimed to study the effectiveness of fortnightly screening with RT-PCR for SARSCoV-2 in curbing transmission. METHOD: Between July 1, 2020, and September 30, 2020, all 273 patients receiving hemodialysis were subjected to fortnightly testing for SARS-Cov-2 in the unit to detect asymptomatic patients. The cost and effectiveness of universal testing in preventing transmission were analyzed using Susceptible-Infectious-Removed (SIR) modeling assuming R0 of 2.2. RESULTS: Of 273 MHD patients, 55 (20.1%) got infected with SARS-CoV-2 over three months. Six (10.9%) were symptomatic, and 49 (89.1%) asymptomatic at the time of testing. Six (10.9%) asymptomatic patients develop symptoms later;and 43 (78.2%) remained asymptomatic. A total of 7(6.1%) HCWs also tested positive for the virus. With an assumption of R0 2.2 and isolation of symptomatic patients only, all 273 patients could have been affected by September 30, 2020;with the isolation of both symptomatic patients and those testing positive after pre-dialysis screen, only 52 (19%) infections could have been prevented. However, at the end of the study period, 218 (80%) patients remained uninfected of SARS-CoV-2. Fortnightly universal testing is cost-effective, and SIR modeling proved effective in preventing person-to-person transmission. CONCLUSION: Repeated universal testing in maintenance hemodialysis patients detected 89% of asymptomatic SARS-CoV-2 patients over three months and appeared to be an effective strategy to prevent person-to-person transmission in the dialysis unit.

11.
Indian Journal of Transplantation ; 14(3):250-254, 2020.
Article in English | EMBASE | ID: covidwho-890488

ABSTRACT

Coronavirus disease-19 (COVID-19) affected everyone on the globe, including renal transplant recipients who are at increased risk of infection. The clinical manifestations, immunosuppressive modifications, and treatment protocol are not well defined. We are reporting a case of renal transplant recipient and reviewed all case reports and series (a total of 100 patients) published to date to comprehend the clinical manifestations, immunosuppression modifications, treatment given, and outcomes of the patients. A 57-year-old male kidney transplant recipient had a fever, headache, weakness, and positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. He became asymptomatic with the treatment of hydroxychloroquine, azithromycin, and oseltamivir. However, he remained persistently positive by reverse transcriptase-polymerase chain reaction for SARS-CoV-2 for 4 weeks and became negative only after Ivermectin therapy, a safer medicine than antivirals/antiretrovirals used for COVID therapy in renal transplant recipients. Of the 100 patients review of case series, fever was noted in 85%, cough 71%, diarrhea 10%, and radiographic abnormalities in 75% of cases. Only in 3% of cases, steroid was stopped, and in the rest of the cases, 63% either continued in the same doses or changed to methylprednisolone in 34%. Calcineurin inhibitors were temporarily stopped in 42% of cases, reduced in 9% of cases, and continued in the same doses in 49% of cases. The anti-metabolites were discontinued in 83%, reduced in 9% of cases, and not changed in 8% of cases. SARI was observed in 18% and acute kidney injury (AKI) in 26% of cases. Of all the AKI, 11% required renal replacement therapy. Mortality was observed in 21% of cases. COVID in renal transplant recipients may show an unusually longer positivity. Ivermectin may be used in the absence of any conclusive SARS-CoV-2 antivirals. Mortality is high in renal transplant recipients.

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