The quality of medical care in a round-the-clock hospital during the COVID-19 pandemic

Violations in the provision of medical care are detected by controlling the volume, timing, quality and conditions of medical care. The objective of the work is assessment of the activities of the round-the-clock hospital from the standpoint of the quality of medical care during the COVID-19 pandemic. Material and methods. A database of indicators reflecting the activity of round-the-clock hospital for four years, from 2017 to 2020 (Omsk) was formed. Analytical, statistical methods and the method of expert assessments were used to analyze the required indicators. Results. Evaluation of inpatient hospital activities during the COVID-19 pandemic compared to the "pre-pandemic” years showed a 1.9-fold and 2.9-fold decrease in the total number of quality examinations performed and the number of defects detected, respectively. The number of defects that were grounds for denial or reduction of payment for medical care found in the "before-COVID-19” years was 2.1 times higher than in 2020. In 2020, the weight of the share of those defects that directly reflect the quality of medical care increased significantly. The quantitative composition of the inpatient hospital staff changed insignificantly during the analyzed period – the number of physicians increased by only 5% over four years, with no dynamics in the qualitative characteristics of the staff. The number of medical equipment increased by 27.6%. Due to re-profiling in 2020, there was a decrease in the number of hospitalized patients, with an increase in the proportion of patients admitted by emergency care (up to 91%) and an increase in mortality by 2.7 times. Conclusions. One of the conditions for maintaining high quality of medical care is a balance between the main components of quality: accessibility, timeliness, sufficiency, efficiency and safety and the speed of its achievement, which in turn depends on the amount of resources and reserves. © 2023, Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences. All rights reserved.

Reproduction of the Control Group in REMDACTA Trial Using the Millennial Medical Record, an Electric Health Record Database, in Japan

Objectives: Developing a control group of a clinical trial using real world data is desirable and ethically sound despite challenges pertaining to internal validity. To examine the internal validity, we reproduced the control group in a Randomized Controlled Trial (RCT) using Electric Health Record (EHR) data and evaluated the difference between the outcome of the original trial and that of the reproduced analysis. Method(s): We selected an RCT, REMDACTA trial, that was performed to evaluate the efficacy of tocilizumab plus remdesivir against placebo plus remdesivir in patients with severe COVID-19 pneumonia. We reproduced its control group (patients with severe COVID-19 pneumonia taking only remdesivir), using Japanese EHR data, Millennial Medical Record provided by Life Data Initiative. Target patients for the main analysis were those prescribed remdesivir within 2 days after admission and diagnosed with COVID-19 (defined by ICD-10 code, U07.1) and/or with COVID-19 pneumonia (defined by diagnosis name). Patients in the sub analysis included only those with COVID-19 pneumonia diagnosis. Among the target patients, those undergoing image inspection, oxygen administration, and not taking any medicines for pneumonia before the first remdesivir prescription were eligible for the analyses. Median length of stay was compared in the reproduced group and in REMDACTA trial. Result(s): The database included 676 and 110 target patients for the main and sub analyses, respectively. However, only 57 and 14 patients met the eligibility criteria for the main and sub analyses, respectively. The reduction in the number of patients is attributed to the criteria of image inspection and oxygen administration. Median length of stay in the reproduced group were 13 and 11 days in the main and sub analyses, respectively. In REMDACTA trial, 95% CI of median time was 11.0-16.0. Conclusion(s): We successfully reproduced the median time of the control group by EHR data.Copyright © 2023

Criteria Clustering and Supplier Segmentation Based on Sustainable Shared Value Using BWM and PROMETHEE

With the advent of healthy visions, two of the trends that have become extremely important in the supply chain in recent decades are corporate social responsibility (CSR) and sustainability, which have affected the activities of buyers and suppliers. The next trend that is emerging is the vision of creating shared value (CSV), which wants to move the supply chain toward solving social problems in a completely strategic way. This research intends to develop a step-by-step framework for evaluating and segmenting suppliers based on CSV criteria in the supply chain. In the first stage, the criteria for creating sustainable shared value (CSSV) are obtained through existing activities in the field of CSR. The obtained criteria are then divided into two categories, strategic and critical, and then the weight of each criterion is obtained using the best–worst method (BWM). In the next step, based on the Kraljic model, the suppliers are divided into four clusters using the preference ranking organization method for enrichment evaluation (PROMETHEE) technique. This framework helps the buyer to conclude and select purchasing decisions and relationships with suppliers through the lenses of CSV and sustainability.

An Integrated Approach to Evaluating Eco-Innovation Strategies from the Perspective of Strategic Green Transformation: A Case of the Lithuanian Furniture Industry

Evaluation and selection of eco-innovation strategies is a significant and complex strategic decision, and despite the relevance and interest in the field of eco-innovation, the area of eco-innovation strategies has not been explored in depth in the scientific literature. Therefore, in this study, we propose an integrated approach to evaluating eco-innovation strategies from the perspective of strategic green transformation that helps decision-makers evaluate and select eco-innovation strategy aiming to achieve a competitive advantage. For this study, we adopted a validated multi-criteria decision-making methodology (MCDM) by combining Analytical Hierarchy Process (AHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The reliability of the proposed framework was tested and applied in the context of the Lithuanian furniture industry. This study offers three contributions and provides a comprehensive and profound insights into eco-innovation strategies. First, this study conceptualizes eco-innovation strategy from the perspective of strategic green transformation and proposed a novel definition and classification of eco-innovation strategies leading to competitive advantage. Second, this study proposes a novel approach to the evaluation of eco-innovation strategies taking into account micro-, meso-, and macro-level environmental factors. Third, the findings of this study provide implications for scholars and decision-makers in the field of eco-innovation strategy and set an agenda for future research.

Barriers to in-Person Focus Group Participation during the Third-Year of COVID-19 Pandemic: A Case Study of Colorectal Cancer (CRC) Screening in Underrepresented Groups

Objectives: In the process of conducting research to understand barriers to colorectal cancer (CRC) screening in underrepresented groups such as Blacks and Hispanics, it became evident that there were also barriers to recruitment in this population. This study assesses the challenges faced in recruitment of focus group participants regarding CRC screening practices among underrepresented groups. Since the COVID-19 pandemic, qualitative research participants have primarily been interviewed through online video or audio interactions. However, as restrictions on in-person interactions have been lifted, in-person focus groups are being increasingly considered. Method(s): The study investigators began recruitment through community health workers in August 2022, when COVID-19 vaccines were available for all adults (age>18 years). Eligible individuals were: age 45-75, Black or Hispanic, with Medicaid or no insurance, and no family history of CRC or diagnosis of certain colon-related diseases. We combined in-person and virtual recruitment strategies, including posting flyers in communities, advertising our study at health fairs, and on social media. Participants would receive a $50 gift card. Result(s): Fifty-five met the eligibility criteria among 144 respondents, and 45 subjects (29 women and 16 men) agreed to be contacted. An average of 2.5 attempts were made per eligible subject. Unfortunately, we were able to recruit only four women (3 Hispanic and one non-Hispanic black). Traveling to the research site was a barrier to participation. Many subjects (49%) requested virtual participation (online video or audio interactions);some declined because the topic was too sensitive (considered taboo), and eligible men were reluctant to participate in-person. Conclusion(s): The requirement of in-person participation affected our recruitment goals, suggesting that COVID-19 has shifted the preferences of research participants to virtual interaction. In response to the eligible participant preferences, the study protocol has been revised to re-contact patients and schedule virtual FG sessions.Copyright © 2023

Preliminary results from phase 2 of CC-92480- MM- 001: Mezigdomide plus dexamethasone in relapsed/refractory multiple myeloma (RRMM)

In phase 1 of CC-92480- MM- 001 (NCT03374085), the recommended phase 2 dose (RP2D) of mezigdomide plus dexamethasone (MEZI-d) was selected at 1 mg once daily for 21/28 days. Here we report preliminary results from the MEZI-d dose-expansion cohort in patients with heavily pretreated RRMM. Key eligibility criteria were: RRMM;>=3 prior lines of therapy;disease progression <=60 days of last myeloma therapy;refractoriness to lenalidomide/pomalidomide, a proteasome inhibitor, a glucocorticoid, and an anti-CD38 monoclonal antibody. Oral mezigdomide 1 mg was given on days 1-21 of each 28-day cycle, plus weekly dexamethasone (40 mg;20 mg if >75 years of age). Primary objective was to evaluate efficacy (overall response rate [ORR]);secondary objectives included safety/tolerability and additional efficacy assessments. Pharmacodynamics was an exploratory objective. As of 16/Sep/2022, 101 patients had received MEZI-d at the RP2D. Median age was 67 (range 42-85) years, median time since initial diagnosis was 7.4 (1.1-37.0) years;39.6% of patients had plasmacytomas and 37/101 patients had high-risk cytogenetics (56/101 not evaluable). Median number of prior regimens was 6 (3-15);prior therapies included stem cell transplantation (77.2%) and anti-BCMA therapy (29.7%). All patients were refractory to last myeloma regimen and triple-class refractory. Median follow-up was 7.5 (0.5-21.9) months, with a median of 4 (1-20) cycles;10.0% of patients continued treatment;progressive disease was the main reason for discontinuation (60.4%). ORR was 40.6% for all patients. Whilst data are not mature yet, median PFS was 4.4 (95% CI 3.0-5.5) months and median duration of response was 7.6 (95% CI 5.4-9.5) months. ORR was 30.0% in patients with plasmacytomas (N = 40) and 50.0% in patients with prior anti-BCMA therapy (N = 30). Ninety-one (91.1%) patients experienced a grade 3/4 treatment-emergent adverse event (TEAE). Most frequent hematologic grade 3/4 TEAEs were neutropenia (75.2%), anaemia (35.6%), and thrombocytopenia (27.7%);34.7% of patients had grade 3/4 infections, including grade 3/4 pneumonia (15.8%) and COVID-19 (7.0%). Occurrence of other grade 3/4 non-hematologic TEAEs was generally low. Due to TEAEs, 76.2% and 29.7% of patients had mezigdomide dose interruptions and reductions, respectively;90.1% of patients discontinued mezigdomide. Mezigdomide induced substrate degradation and increases in activated and proliferating T cells in patients, including those directly refractory to pomalidomide-based therapies. MEZI-d had a manageable safety profile with encouraging efficacy in patients with triple-class refractory RRMM, including patients with prior BCMA-targeted therapies. These results strongly support the continued development of mezigdomide in MM, and especially in combination.

The analysis of risk assessment for the transmission of COVID-19 by using PROMETHEE and ELECTRE methods

Multi-Criteria Decision Making (MCDM) methods help researchers in solving many prob-lems in terms of numerical analysis. However, MCDM methods have not been very popular in the health sector. In this study, five ones of Turkey's most intense and highly populated cities were selected and the risk of the spread of Covid-19 disease was evaluated on the basis of seven criteria. The PROMETHEE and the ELECTRE methods were conducted to rank the cities in terms of the spread of Covid-19. The PROMETHEE method correctly ranked the most risky city as Istanbul, but ELECTRE ranked Istanbul the second most risky. The results of the meth-ods are compared with real data. PROMETHEE gave more convenient results than ELECTRE. Also, this paper offers a new field of study to the literature.Cite this article as: Pekel ozmen E, Demir B. The analysis of risk assessment for the trans-mission of COVID-19 by using PROMETHEE and ELECTRE methods. Sigma J Eng Nat Sci 2023;41:2:232-242.

Research COVID-19 and its Outcomes in Multiple Sclerosis Patients

Background: Coronavirus Disease 2019 (COVID-19) is a highly contagious disease that resulted in 4533645 deaths until September first, 2021. Multiple Sclerosis (MS) patients receive immunosuppressive drugs. Thus, there is a concern that these drugs will reduce the patient's immune system resistance against COVID19. Objective(s): This study aimed to evaluate the epidemiology of COVID19 and its impact on MS patients in our university hospital in Tehran City, Iran. Material(s) and Method(s): A cross-sectional study was conducted based on hospital-based registry data from May 2020 to March 2021. Among more than 500 registered MS patients in Imam Khomeini Hospital in Tehran City, Iran, referring within our study period, 84 patients reported SARS-COV2 infection. The diagnosis of MS was confirmed by the McDonald criteria. Moreover, the diagnosis of COVID-19 in MS patients was established by the real-time-PCR technique and chest computed tomography. Result(s): Out of 84 MS patients with SARS-COV2 infection, 55(65.5%) were women, and their mean age was 37.48 years. The most commonly used medications by MS patients were Rituximab 20 (26.3%) and Dimethyl Fumarate 14(18.4%). Totally, 9(10.8%) of the patients needed to be hospitalized due to COVID-19, with a mean hospitalization duration of 5.88 days. A total of 1 (1.2%) death was reported. Conclusion(s): Compared to the healthy population, COVID-19 is not more serious in MS patients. Most MS patients with COVID-19 infection were not hospitalized and continued their medication during the infection.Copyright © 2022 The Authors. This is an open access article under the CC-By-NC license. All Rights Reserved.

Identifying Clinical Subtypes of Long COVID: An Unsupervised Machine Learning Approach

Objectives: The symptoms of patients with post-acute COVID-19 syndrome are heterogenous, impact multiple systems, and are often non-specific. To better understand the symptomatic profile of this population, this study used real-world data and unsupervised machine learning techniques to identify distinct groupings of long COVID patients. Method(s): Children/adolescents (age 0-17) and adults (age 18-64 and >=65) with >=2 primary diagnoses for U09.9 "Post COVID-19 condition" from 10/01/2021 (ICD-10 code introduction) until 03/31/2022 were selected from Optum's de-identified Clinformatics Data Mart Database, with the first diagnosis deemed index. Included patients had >=1 diagnosis for COVID-19 at least 4 weeks before index and continuous enrollment during the 12 months prior to index. Diagnoses recorded +/-2 weeks from index that were not present prior to the initial COVID-19 diagnosis were captured and used as patient features for k-means clustering. Final cluster assignments were selected based on silhouette coefficient and clinical relevancy of groupings. Result(s): 3,587 patients met eligibility criteria, yielding three clusters. Concurrent symptom domains surrounding index included breathing, fatigue, pain, cognitive, and cardiovascular diagnoses. The first cluster (N=2,578, 71.8%) was characterized by patients with only a single symptom domain (33% breathing, 33% cardiovascular, 20% fatigue, 11% cognitive). The second cluster (N=651, 18.1%) all presented with breathing symptoms accompanied by one additional domain (cardiovascular 40%, fatigue 28%, pain 18%). The final cluster (N=358, 9.9%) experienced breathing symptoms accompanied by two additional domains (fatigue and cardiovascular 34%, cardiovascular and cognitive 34%). Cluster 3 was slightly older than clusters 1 or 2 (mean age 66 vs. 58 years, respectively). Conclusion(s): Unsupervised machine learning identified distinct groups of long COVID patients, which may help inform multidisciplinary care needs. Our analysis suggests that many patients with long COVID may experience symptoms from only a single domain, and multi-system illness may generally include breathing complications accompanied by fatigue and/or cardiovascular complications.Copyright © 2023

Characteristics of Patients Diagnosed with Long COVID: Early Findings from Real-World Data

Objectives: While persistent and relapsing symptoms of COVID-19 are increasingly documented, limited data exist on the post-acute population. The objective of this analysis is to identify the characteristics of patients diagnosed with long COVID using real-world data. Method(s): Children/adolescents (age 0-17) and adults (age 18-39, 40-64 and >=65) with >=2 primary diagnoses for U09.9 "Post COVID-19 condition" from 10/01/2021 (ICD-10 code introduction) until 03/31/2022 were selected from Optum's de-identified Clinformatics Data Mart Database, with the first diagnosis deemed index. Included patients had >=1 diagnosis for COVID-19 and continuous enrollment 12 months prior to index (baseline). To ensure alignment with most institutional definitions, >=4 weeks between initial COVID-19 infection and index was required. Diagnoses recorded +/-2 weeks from index that were not present prior to the initial COVID-19 diagnosis were summarized. Newly prescribed treatments and total medical costs were evaluated during the month following index (continuous enrollment required). Result(s): 3,587 patients met eligibility criteria (mean age 59.02, 57.56% female) with a median time from initial COVID-19 infection to long COVID diagnosis of 83 days (IQR: 46-201 days). The most common concurrent diagnoses included breathing complications such as dyspnea (20.38%) and respiratory failure (15.23%);malaise and fatigue (15.31%);symptoms related to cognitive functioning/anxiety (11.35%);and chest pain (7.67%). Children/adolescents had the highest prevalence of chest pain, while patients >=65 years of age had the highest prevalence of issues with coordination. The average total medical cost during the month following long COVID diagnosis was $4,267 (SD $14,662), with common prescriptions including albuterol (4.42%), prednisone (3.51%), and methylprednisolone (2.01%). Conclusion(s): This retrospective analysis confirms clinically documented symptoms of long COVID in a large, real-world population. Once more data become available, further research on the long term economic and clinical outcomes among patients diagnosed with post-acute COVID-19 syndrome are warranted.Copyright © 2023

Upskilling haematological services for WGS and germline assessments through a regional skin biopsy training programme

NHS England Genomics introduced whole genome sequencing (WGS) with standard-of- care (SoC) genetic testing for haemato-oncology patients who meet eligibility criteria, including patients with acute leukaemia across all ages, and exhausted SoC testing. Alongside, the role of germline mutations in haematological cancers is becoming increasingly recognised. DNA samples are required from the malignant cells (somatic sample) via a bone marrow aspirate, and from non-malignant cells (germline sample) for comparator analysis. Skin biopsy is considered the gold-standard tissue to provide a source of fibroblast DNA for germline analysis. Performing skin punch biopsies is not within the traditional skillset for haematology teams and upskilling is necessary to deliver WGS/germline testing safely, independently and sustainably. A teaching programme was designed and piloted by the dermatology and haematology teams in Sheffield and delivered throughout the NHS trusts in North East & Yorkshire Genomic Laboratory Hub. The training programme consisted of a 90-min session, slides, video and practical biopsy on pork belly or synthetic skin, designed to teach up to six students at one time. To disseminate best practice, the standard operating procedure and patient information used routinely in Sheffield were shared, to be adapted for local service delivery. From January 2021 to December 2022, 136 haematology staff from 11 hospitals, including 34 consultants, 41 registrars, 34 nurses and 8 physician associates, across the NEY GLH region completed the skin biopsy training programme. Feedback from the course was outstanding, with consistently high scores in all categories. Practical components of the course were especially valued;98.6% (71/72) trainees scored the practical element of the programme a top score of 5 out of 5, highlighting that despite the challenges of delivering face-to- face teaching due to COVID-19, teaching of practical skills was highly valued;training in this way could not have been replicated virtually. Costs of the programme have been approximately 16 000, including consultant input and teaching/educational materials. Recent support has been provided by a separately funded Genomic Nurse Practitioner (GNP), with succession planning for the GNP to take over leadership from the consultant dermatologist. Plans are in place to use the remaining budget to disseminate the programme nationally. Our training programme has shown that skin biopsy can be formally embedded into training for haematology consultants, trainees, nursing team, and physician associates. Delivery of training can be effective and affordable across regional GLHs with appropriate leadership and inter-speciality coordination, and ultimately sustainable with specialist nursing staff, including GNPs.

A GROUP DECISION-MAKING METHOD FOR RANKING PROBLEMS UNDER SUSTAINABILITY, RISKS, AND INTUITIONISTIC FUZZY ENVIRONMENT

This paper presents a group decision-making mechanism to properly manage ranking problems in an intuitionistic fuzzy environment. TOPSIS ranking multi-criteria decision-making (MCDM) methods is utilized under the intuitionistic fuzzy set theory. This solution technique examines the sets of criteria employed in decision-making problems, the preferences of a group of decision-makers, and the importance levels of decision-makers. Managers use the ranking methods as a reliable technique for making supplier evaluation decisions. Furthermore, the supply chain suffers from the shortage of materials, transportation problems, etc. In the post COVID-19 era, the need for a practical and exhaustive tool is explicit. An illustrative case on a supplier selection problem considering sustainability and risks in the post-COVID-19 era is used to demonstrate the applicability of the proposed technique by detailing the procedure step by step. A comparative analysis of the results is carried out. The results are compared with the results of the MARCOS method. The results show that the presented methodology is applicable to the other areas as well. (English) [ FROM AUTHOR] Bu makale, sezgisel bulanık bir ortamda sıralama problemlerini düzgün bir şekilde yönetmek için bir grup karar verme mekanizması sunmaktadır. Sezgisel bulanık küme teorisi kapsamında çok kriterli karar verme (ÇKKV) yöntemi olan TOPSIS kullanılmaktadır. Bu çözüm tekniğinde karar verme problemlerinde kullanılan birtakım kriterler, karar vericiler grubunun tercihleri ve karar vericilerin önem düzeyleri incelenmektedir. Yöneticiler, sıralama yöntemlerini tedarikçi değerlendirme kararlarını vermek için güvenilir bir teknik olarak kullanır. Ayrıca, COVID-19 döneminden sonra tedarik zinciri malzeme sıkıntısı, ulaşım sorunları vb. sıkıntılardan muzdariptir, pratik ve kapsamlı bir araca olan ihtiyaç açıktır. Prosedürü adım adım detaylandırarak önerilen tekniğin uygulanabilirliğini göstermek için, COVID-19 sonrası dönemde sürdürülebilirliği ve riskleri dikkate alan bir tedarikçi seçimi sorununa ilişkin örnek bir vaka kullanılmıştır. Sonuçların karşılaştırmalı analizi gerçekleştirilmiştir. Sonuçlar, MARCOS yönteminin sonuçları ile karşılaştırılmıştır. Sonuçlar, sunulan metodolojinin diğer alanlara da uygulanabilir olduğunu göstermektedir. (Turkish) [ FROM AUTHOR] Copyright of Pamukkale University Journal of Social Sciences Institute / Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi is the property of Pamukkale University, Social Sciences Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Severe coronavirus disease 2019: Is it acute respiratory distress syndrome?.

The outbreak of coronavirus disease 2019 (COVID-19) poses a major global threat. Although we have learned a lot about COVID-19 from clinical studies and autopsy findings, there is still a lot of confusion. One of the biggest controversies is whether severe COVID-19 can be diagnosed as acute respiratory distress syndrome (ARDS). Severe COVID-19 may meet ARDS Berlin criteria, but it differs from ARDS caused by other etiologies and is characterized by later onset time, relatively normal lung compliance in some cases, significant hypercapnia, lung CT findings, and significant coagulation activation in lungs. Some reports classify COVID-19-related ARDS into different phenotypes, but most of them are based on observational studies, with high bias. To date, we have not fully understood the pathophysiology of COVID-19-related ARDS. Premature phenotyping may mislead mechanical ventilation strategies. We expect evidence from large clinical studies.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Bringing digital resource decision-making up to date: preparing the inaugural class of digitalised preservice teachers for informed evaluation of digital resources

The virtualised schools and universities of the Covid-19 pandemic became rely heavily on educational digital resources (EDRs), so that it has made the selection and use of high-quality EDRs even more critical for quality education. This qualitative case study aims to examine decision-making criteria used by preservice teachers (PTs) in selecting and evaluating EDRs. Twenty senior PTs participated in the study, and each evaluated four EDRs using guided prompts. Open coding and text analysis on 77 EDR evaluations were conducted. Results indicate that 41 EDRs were selected for the evaluation, and PTs' prior experience in the field, both as a teacher or an observer, influenced their selection process. Features of EDRs considered in decision-making process included types of EDRs, pedagogical and maths skill purpose, ready-made or adaptable, interactive or one-way, and cost. Also, five decision-making criteria used by PTs in EDR selection and use were the primary benefit holder, function of EDRs, opportunity for improving mathematical skill, affordances, and constraints. Findings urged framing a new generations' perspective on evaluating EDRs. The ways to support PTs for better informed selection and implementation of EDRs were discussed. [ FROM AUTHOR] Copyright of Journal of Education for Teaching is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

COVID-19 and sepsis: clinical parallels of clinical course and treatment options

The article analyzes syndrome complex in sepsis and severe COVID-19, identifies the main pathophysiological priorities in the diagnosis and differences in treatment. Adap-tation of existing treatment regimens for diseases with similar pathogenesis may help to improve treatment outcomes and reduce SARS-CoV-2-related mortality. However, when discussing the parallels between COVID-19 and sepsis, focusing on their similarities in immunopathogenesis and pathophysiology, the proposed treatment options should be reviewed based on the patient's clinical assessment and laboratory parameters individually. © 2022, Zaslavsky Publishing House. All rights reserved.

Evaluation of the Updated French Autorisation D'Acces Precoce (AAP) Early Access Authorization Pathway

Objectives: To evaluate products reviewed by the Transparency Committee (TC) of the Haute Authorite de Sante (HAS) under the Autorisation d'Acces Precoce (AAP) Early Access Authorization (EAA) pathway and investigate any trends. Method(s): All 97 AAP submissions are publicly available from HAS and were evaluated on or before January 4th, 2023. The TC's opinion was reviewed to obtain the outcome, decision date, therapeutic area, and reasons for rejection. Results were tabulated and descriptive statistics were compiled. Result(s): In total, 79 of the 97 (81%) submissions evaluated were approved for EAA, including renewals of previously granted authorization (6 of 79);18 were rejected. Of the 97 submissions, 35% were indicated for the treatment of solid cancers, 14% for haematological cancers, 10% for ultra-rare diseases, 10% for infectious diseases, 4% for rare diseases, 4% for autoimmune diseases, 4% for skin diseases, and 2% for weight management. Notable approved submissions including those indicated for rare diseases, cancer, autoimmune diseases, and COVID-19, with 93%, 90%, 75%, and 63% of these submissions being granted EAA, respectively. Across the 18 unsuccessful submissions, the main reasons cited for rejection were insufficient efficacy and safety data (78%), lack of innovation compared to existing treatment options (61%), the availability of existing treatment options (56%), and the treatment not being rare enough to qualify for special consideration (28%). Conclusion(s): Since its inception in July 2021, the AAP has proven to be a popular program. As awareness of the program grows and more information becomes available about its benefits and eligibility criteria, it is likely that the number of submissions will continue to increase. However, given the link between submission success and the quality of available data (including a data collection plan), it is recommended manufacturers provide robust evidence to bolster their submissions.Copyright © 2023

Updated Real-World Safety of the Pfizer-BioNTech COVID-19 Vaccine in Pregnancy: Data from the Organization of Teratology Information Specialists (OTIS) Pregnancy Registry

Purpose: Preliminary data indicate that pregnant women infected with COVID-19 are at increased risk of pregnancy complications (US Centers for Disease Control and Prevention, October 2022). Information on the real-world safety of COVID-19 vaccination in pregnancy is essential. We sought to describe preliminary results for pregnancy status among pregnancy registry participants enrolled in an ongoing safety study of the Pfizer-BioNTech COVID-19 vaccine to date. Method(s): This study uses data from the Organization of Teratology Information Specialists (OTIS) Pregnancy Registry as part of the Vaccines and Medications in Pregnancy Surveillance System (VAMPSS) which enrolls pregnant women residing in the US or Canada. Data are captured through maternal interviews and the ion of medical records. The study population for this descriptive analysis includes Registry participants who met eligibility criteria on or after December 11, 2020, the date the US Food and Drug Administration granted emergency-use authorization for the Pfizer-BioNTech vaccine. The target sample size is 1,100 pregnant women who received any dose of the Pfizer-BioNTech vaccine from 30 days prior to the last menstrual period through the end of pregnancy, and 900 comparison women who received no COVID-19 vaccine in pregnancy. Result(s): Among pregnant women participating in the Registry between 11 December 2020 and 22 July 2022, 1,100/1,100 participants (100.0% of the target sample) were enrolled as part of the Pfizer-BioNTech COVID-19 vaccine exposure cohort, and 635/900 participants (70.6% of the target sample) were enrolled in the comparator cohort. As of 22 July 2022, 858 (78.0%) in the vaccine exposure cohort and 313 (34.8%) in the comparator cohort had completed pregnancies. Descriptive data indicated numerically similar percentages of pregnancies ending in at least one liveborn infant, spontaneous abortions, stillbirths, and elective terminations across the exposed cohort stratified by trimester of the earliest dose of the Pfizer-BioNTech COVID-19 vaccine received in pregnancy, and overall in the unexposed comparator cohort. Conclusion(s): Preliminary data have not identified any new safety concerns thus far for pregnant women who receive the Pfizer-BioNTech COVID-19 vaccine during pregnancy. Funding(s): This study was conducted as a collaboration between the University of California San Diego and Pfizer. Pfizer is the study sponsor.

Remote teaching in the pandemic: Opportunities fora transformative learning

The Covid-19 pandemic has reinforced remote teaching (RT) as a trend in management education. This research reflects on the central elements that make RT a transformative learning (TL) experience, based on a case study of a TL-anchored sustainability discipline that was migrated to RL during the pandemic. Theoretically, we propose a framework or reference that combines TL, education for sustainability (EfS), and communicative ecosystem (CE) theories;we also extend the concept of RL, coining the term 'transformative remote teaching' (TRT). With regard to practice, students' feedback points to three elements that are key for TRT: exploring different windows of knowledge;rethinking the teaching role;and adapting tools to support the teaching-learning process. We conclude by highlighting the need to approach education in ways anchored in epistemological, paradigmatic, and transformative changes.

Air cargo company selection under a state of chaos: An integrated bayesian BWM and WASPAS approach.

Depending on whether or not there is a chaotic condition, the outcomes of decision problems and the factors determining the outcomes of the problem may differ. Different criteria can be introduced for decision makers' preferences in chaotic conditions, and the importance levels of the criterion can fluctuate. Despite the fact that the COVID-19 epidemic has had an impact on the aviation industry, air cargo transportation has performed well during this time. From this perspective, the impact of chaotic events on the selection of an air freight firm is investigated in this study. With Multi-Criteria Decision Making (MCDM) methodologies, a new decision-making framework is proposed, which is an effective solution method for choice makers to finalize decision problems. The Bayesian BWM (Best-Worst) method, which is one of the new ways, is used to establish the criterion weights, while the WASPAS method is utilized to rank the air cargo businesses, due to the more sensitive reaction of the newly proposed methods. As a result, these two approaches are combined, and the ranking results are compared to the TOPSIS and COPRAS methods, with the outcomes examined. As a result, in a chaotic environment, the most essential consideration for selecting an air freight company appears to be economic criteria. (English) [ FROM AUTHOR] Karar problemlerinin sonuçları ve bu sonuçları etkileyen faktörler, herhangi bir kaos durumunun bulunup bulunmamasına göre değişiklik gösterebilmektedir. Kaos durumları altında, karar alıcıların tercihleri için farklı kriterler eklenebilmekte ve kriterlerin önem düzeyleri değişebilmektedir. COVID-19 pandemisi her alanda olduğu gibi havacılık sektörünü de etkilemiş olmasına rağmen hava kargo taşımacılığı bu dönemde güçlü bir performans göstermektedir. Bu noktadan hareketle, bu çalışmada kaos durumlarının hava kargo şirketi seçimine yansıması incelenmektedir. Karar vericilerin, karar problemlerini sonuçlandırmasında etkili bir çözüm yöntemi olan Çok Kriterli Karar Verme (ÇKKV) yöntemleri ile yeni bir karar verme çerçevesi önerilmektedir. Yeni önerilen yöntemlerin daha hassas yanıt vermesinden dolayı, hava kargo şirketi seçiminde etkili olan kriter ağırlıklarının belirlenmesinde yeni yöntemlerden olan Bayesian BWM (En Íyi-En Kötü) yöntemi kullanılırken, hava kargo şirketlerinin sıralanmasında ise WASPAS yöntemi kullanılmaktadır. Böylece bu iki yöntem bütünleştirilmekte ve aynı zamanda sıralama sonuçları TOPSIS ve COPRAS yöntemi ile kıyaslanarak sonuçlar analiz edilmektedir. Elde edilen sonuçlara göre, kaos ortamında hava kargo şirketi seçimi için en önemli kriter ekonomik kriterler olarak görünmektedir. (Turkish) [ FROM AUTHOR] Copyright of Journal of the Faculty of Engineering & Architecture of Gazi University / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, is the property of Gazi University, Faculty of Engineering & Architecture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Novel pythagorean fuzzy entropy-distance measures using MCDM in the selection of face masks

Wearing a face mask can help reduce the spread of infection and contamination from airborne harmful germs. The requirement to wear a face mask is perhaps one of the most noticeable lifestyle changes brought on by the COVID-19 pandemic. COVID-19 transmission can be slowed down by wearing a mask, especially while in close contact with others. Choosing the best face mask is a cumbersome task from the available alternatives in India. Several multi-criteria decision-making (MCDM) techniques and approaches have been suggested to choose the optimally probable options. The purpose of this article is to deliver an entropy-distance measure for Pythagorean fuzzy sets. To validate these measures, some of the properties were also proved. A multi-criteria decision-making approach is used to rank and hence select the best face mask for wearing. The proposed research allows the ranking of face masks based on specified criteria in a Pythagorean fuzzy environment to aid in the selection process. The results suggest that the proposed model provides a realistic way to select the best mask in the pool of considered brands. A case study on the selection process and its experimental results using Pythagorean fuzzy sets are discussed. © 2023 River Publishers. All rights reserved.