ABSTRACT
This research attempts to study the Supplier Selection and Order Allocation Problem (SSOAP) considering three crucial concepts, namely responsiveness, sustainability, and resilience. To do so, the current research develops a Multi-Stage Decision-Making Framework (MSDMF) to select potential suppliers and determine the quantity of orders. The first stage aims at computing the scores of the suppliers based on several indicators. To do this, a novel decision-making approach named the Stochastic Fuzzy Best–Worst Method (SFBWM) is developed. Then, in the second stage, a Multi-Objective Model (MOM) is suggested to deal with supplier selection and order allocation decisions. In the next step, a data-driven Fuzzy Robust Stochastic (FRS) optimization approach, based on the fuzzy robust stochastic method and the Seasonal Autoregressive Integrated Moving Average (SARIMA) methods, is employed to efficiently treat the hybrid uncertainty of the problem. Afterwards, a novel solution method named the developed Chebyshev Multi-Choice Goal Programming with Utility Function (CMCGP-UF) is developed to obtain the optimal solution. Moreover, given the crucial role of the Medical Equipment (ME) industry in society's health, especially during the recent Coronavirus disease, this important industry is taken into account. The outcomes of the first stage demonstrate that agility, cost, GHG emission, quality, robustness, and Waste Management (WM), respectively, are the most important criteria. The outcomes of the second stage determine the selected suppliers, utilized transportation systems, and established sites. It is also revealed that demand directly affects all the objective functions while increasing the rate of disruptions has a negative effect on the sustainability measures.
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Background Multiple sclerosis (MS) is an immune-mediated disease that has been related to several risk factors such as various viral infections. We carried out this study in order to establish a relationship between COVID-19 infection and MS severity. Methods In a case–control study, we recruited patients with relapsing–remitting multiple sclerosis (RRMS). Patients were divided into two groups based on positive COVID-19 PCR at the end of the enrollment phase. Each patient was prospectively followed for 12 months. Demographical, clinical, and past medical history were collected during routine clinical practice. Assessments were performed every six months;MRI was performed at enrollment and 12 months later. Results Three hundred and sixty-two patients participated in this study. MS patients with COVID-19 infection had significantly higher increases in the number of MRI lesions (p: 0.019, OR(CI): 6.37(1.54–26.34)) and EDSS scores (p: 0.017), but no difference was found in total annual relapses or relapse rates. COVID-19 infections were positively correlated with EDSS progression (p: 0.02) and the number of new MRI lesions (p: 0.004) and predicted the likelihood of the number of new MRI lesions by an odds of 5.92 (p: 0.018). Conclusion COVID-19 may lead to higher disability scores in the RRMS population and is associated with developing new Gd-enhancing lesions in MRI imaging. However, no difference was observed between the groups regarding the number of relapses during follow-up.
ABSTRACT
BACKGROUND: Multiple sclerosis (MS) is an immune-mediated disease that has been related to several risk factors such as various viral infections. We carried out this study in order to establish a relationship between COVID-19 infection and MS severity. METHODS: In a case-control study, we recruited patients with relapsing-remitting multiple sclerosis (RRMS). Patients were divided into two groups based on positive COVID-19 PCR at the end of the enrollment phase. Each patient was prospectively followed for 12 months. Demographical, clinical, and past medical history were collected during routine clinical practice. Assessments were performed every six months; MRI was performed at enrollment and 12 months later. RESULTS: Three hundred and sixty-two patients participated in this study. MS patients with COVID-19 infection had significantly higher increases in the number of MRI lesions (p: 0.019, OR(CI): 6.37(1.54-26.34)) and EDSS scores (p: 0.017), but no difference was found in total annual relapses or relapse rates. COVID-19 infections were positively correlated with EDSS progression (p: 0.02) and the number of new MRI lesions (p: 0.004) and predicted the likelihood of the number of new MRI lesions by an odds of 5.92 (p: 0.018). CONCLUSION: COVID-19 may lead to higher disability scores in the RRMS population and is associated with developing new Gd-enhancing lesions in MRI imaging. However, no difference was observed between the groups regarding the number of relapses during follow-up.
ABSTRACT
Antecedentes: la esclerosis múltiple (EM) es una enfermedad inmunomediada que se ha relacionado con varios factores de riesgo, como diversas infecciones virales. Realizamos este estudio para establecer una relación entre la infección por COVID-19 y la gravedad de la EM. Métodos: En un estudio de casos y controles, reclutamos pacientes con esclerosis múltiple remitente-recurrente (EMRR). Los pacientes se dividieron en dos grupos según la PCR positiva para COVID-19 al final de la fase de inscripción. Cada paciente fue seguido prospectivamente durante 12 meses. Los antecedentes demográficos, clínicos y médicos anteriores se recogieron durante la práctica clínica habitual. Las evaluaciones se realizaron cada seis meses;La resonancia magnética se realizó en el momento de la inscripción y 12 meses después. Resultados: Trescientos sesenta y dos pacientes participaron en este estudio. Los pacientes con EM con infección por COVID-19 tuvieron aumentos significativamente más altos en el número de lesiones de resonancia magnética (p: 0.019, OR (IC): 6.37 (1.54-26.34)) y puntajes EDSS (p: 0.017), pero no se encontraron diferencias en total recaídas anuales o tasas de recaída. Las infecciones por COVID-19 se correlacionaron positivamente con la progresión de EDSS (p: 0,02) y la cantidad de nuevas lesiones en la resonancia magnética (p: 0,004) y predijeron la probabilidad de la cantidad de nuevas lesiones en la resonancia magnética con una probabilidad de 5,92 (p: 0,018). Conclusión: COVID-19 puede conducir a puntajes de discapacidad más altos en la población de RRMS y está asociado con el desarrollo de nuevas lesiones realzadas con Gd en imágenes de resonancia magnética. Sin embargo, no se observó diferencia entre los grupos en cuanto al número de recaídas durante el seguimiento.
ABSTRACT
Introduction: Although neurologic involvement and neuroimaging abnormalities have been frequently identified in COVID-19 patients, the underlying factors remain unclear. In this study, we assessed the association of the neurological manifestations and neuroimaging features of hospitalized COVID-19 patients with their clinical, laboratory, and imaging characteristics. Methods: This multicenter cross-sectional study was conducted between September 2020 and March 2021 at two large academic hospitals in Tehran, Iran. We used census sampling from medical records to enroll hospitalized patients with a positive COVID-19 Polymerase chain reaction (PCR) test who underwent brain imaging due to presenting any acute neurologic symptom during hospital stay. Results: Of the 4372 hospitalized patients with COVID-19, only 211 met the inclusion criteria (35.5% with severe infection). Central nervous system and psychiatric manifestations were significantly more common in severe cases (p ≤ 0.044). Approximately, 30% had a new abnormality on their neuroimaging, with ischemic (38/63) and hemorrhagic (16/63) insults being the most common. The most frequent reasons that provoked cranial imaging were headache (27%), altered consciousness (25.6%), focal neurologic signs (19.9%), and delirium (18%). Analysis revealed a positive correlation for age, neutrophilia, lymphopenia, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) with the emergence of neuroimaging abnormalities (p ≤ 0.018). In addition, patients with new neuroimaging abnormalities had a significantly higher lung CT score than those without any pathologic findings (11.1 ± 4.8 vs. 5.9 ± 4.8, p < 0.001). Conclusion: Approximately 30% of the study population had various acute neuroimaging findings. The lung CT score, neutrophil count, and age were strong predictors of acute neuroimaging abnormalities in hospitalized COVID-19 patients.