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Objective:To explore the differences in laboratory indicators test results of coronavirus disease 2019 (COVID-19) and influenza A and to establish a differential diagnosis model for the two diseases, and to clarify the clinical significance of the model for distinguishing the two diseases. Methods :A total of 56 common COVID-19 patients and 54 influenza A patients were enrolled , and 24 common COVID-19 patients and 30 influenza A patients were used for model validation. The average values of the laboratory indicators of the patients 5 d after admission were calculated,and the elastic network model and the stepwise Logistic regression model were used to screen the indicators for identifying COVID-19 and influenza A. Elastic network models were used for the first round of selection,in which the optimal cutoff of lambda was chosen by performing 10-fold cross validations. With different random seeds,the elastic net models were fit for 200 times to select the high-frequency indexes ( frequency>90% ). A Logistic regression model with AIC as the selection criterions was used in the second round of screening uses;a nomogram was used to represent the final model;an independent data were used as an external validation set,and the area under the curve (AUC) of the validation set were calculate to evaluate the predictive the performance of the model. Results:After the first round of screening, 16 laboratory indicators were selected as the high-frequency indicators. After the second round of screening,albumin/ globulin (A/G),total bilirubin (TBIL) and erythrocyte volume (HCT) were identified as the final indicators. The model had good predictive performance , and the AUC of the verification set was 0. 844 (95% CI:0. 747-0. 941). Conclusion:A differential diagnosis model for COVID-19 and influenza A based on laboratory indicators is successfully established,and it will help clinical and timely diagnosis of both diseases.Copyright © 2022 Jilin University Press. All rights reserved.
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BackgroundRheumatoid arthritis (RA) and spondyloarthritis, including either Psoriatic Arthritis (PsA) and Ankylosing Spondylitis (AS), are some of the most diagnosed autoimmune rheumatic diseases (AIRDs) in rheumatologists' routine clinical practice [1]. Understanding patients' health and functional status is crucial to provide personalized management strategies to optimize disease control and enhance the quality of life.ObjectivesWe aimed to compare disease burden in patients with RA, PsA or AS by assessing Patient-Reported Outcome Measurement Information System (PROMIS) Physical Health, Global Mental Health, Physical Function and Fatigue 4a together with VAS Pain.MethodsData were obtained in the international COVID vaccination in autoimmune rheumatic diseases study second e-survey (COVAD study). Demographics, AIRD diagnosis, disease activity, PROMIS Global Physical health, PROMIS Global Mental Health, PROMIS Physical Function SF10 and PROMIS Fatigue 4a score were extracted from the COVAD study database. For this study, we only included patients with self-reported RA or spondyloarthritis (either PsA or AS) undergoing active treatment with conventional synthetic disease-modifying drugs (DMARDs) and/or biologic DMARDs, who answered all the survey questions. Active disease was defined as the patient's perception of their disease as active in the four weeks before their first COVID-19 vaccine shot. Analysis of Variance with Bartlett's and Tukey's test was used to compare continuous variables between groups.ResultsFrom January to June 2022, n.1907 patients with RA, female 87.62% (1671/1907), with mean age (±SD) 50.95 ±13.67, n.311 patients with PsA, female 67.20% (209/311), with a mean age of 50.42 ±12.70, and n.336 patients with AS, male 51.31% (209/311), with a mean age of 43.13 ±12.75 years, responded to the COVAD e-survey.In those with active disease, neither physical health, global mental health, physical function, fatigue, nor pain were different among groups (Table 1, Figure 1). Patients with inactive AS had higher mean global physical health scores than RA patients (13.13 ±2.93 VS RA 12.48 ±2.90, p=0.01, Table 1). Those with inactive RA or PsA showed more severe fatigue (PsA 10.58 ±2.22, RA 10.45 ±4.08 VS 9.4 ±4.13, p =0.01 for both). Patients with inactive RA also reported poorer physical function and more residual pain than those with AS (37.79 ±8.86 VS 41.13 ±7.79, p<0.001;3.87 ±2.45 VS 3.34 ±2.39, p=0.01, respectively). Similarly, residual pain was perceived as higher in patients with inactive PsA than those with AS (4.04 ±2.50 VS 3.34 ±2.39, p=0.01)ConclusionDisease burden is roughly comparable in patients with active RA, PsA or AS. Patients with inactive RA and PsA suffer higher disease burden than those with inactive AS.Reference[1]Mease PJ, Liu M, Rebello S, Kang H, Yi E, Park Y, Greenberg JD. Comparative Disease Burden in Patients with Rheumatoid Arthritis, Psoriatic Arthritis, or Axial Spondyloarthritis: Data from Two Corrona Registries. Rheumatol Ther. 2019 Dec;6(4):529-542.Table 1.Patient-Reported Outcome Measures between groups.Inactive diseaseAS (n.185)PsA (n.179)RA (n.1167)MeanSDMeanSDMeanSDPROMIS Global Physical Health13.13*2.9512.433.2712.482.90p=0.01, VS RAPROMIS Global Mental Health13.313.3612.973.3312.843.17PROMIS Fatigue 4a9.44.1310.58*4.2210.45*4.08p=0.01, bothPROMIS Physical Function SF10 Score41.137.3939.279.0137.79*8.86p<0.001, VS ASVAS Pain3.342.394.04*2.503.87*2.45p=0.01, bothActive DiseaseAS (n.35)PsA (n.38)RA (n.189)MeanSDMeanSDMeanSDPROMIS Global Physical Health11.053.1910.102.7611.243.41PROMIS Global Mental Health11.313.2610.843.6311.893.30PROMIS Fatigue 4a12.944.8712.844.4211.754.68PROMIS Physical Function SF10 Score35.829.6233.528.7634.909.80VAS Pain4.682.775.02.544.682.61Figure 1.Violin plots showing kernel densities, quartiles and median for Patient-Reported Outcome Measures for patients with RA, PsA and AS, stratified by disease activity status.[Figure omitted. See PDF]Acknowledgements:NIL.Disclosure of InterestsVincenzo Venerito: None declared, Marc Fornaro: None declared, Florenzo Iannone: None declared, Lorenzo Cavagna: None declared, Masataka Kuwana: None declared, Vishwesh Agarwal: None declared, Naveen Ravichandran: None declared, Jessica Day Grant/research support from: JD has received research funding from CSL Limited., Mrudula Joshi: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Parikshit Sen: None declared, James B. Lilleker Speakers bureau: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Consultant of: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Arvind Nune: None declared, John Pauling: None declared, Chris Wincup: None declared, Ai Lyn Tan Speakers bureau: ALT has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB., Nelly Ziade Speakers bureau: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Grant/research support from: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Marcin Milchert: None declared, Abraham Edgar Gracia-Ramos: None declared, Carlo Vinicio Caballero: None declared, COVAD Study: None declared, Vikas Agarwal: None declared, Rohit Aggarwal Speakers bureau: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Grant/research support from: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Latika Gupta: None declared.
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Objectives: Potential cutaneous adverse drug reactions (cADRs) associated with COVID-19 vaccinations are well-known. However, comprehensive evaluation including detailed patient characteristics, vaccine types, signs and symptoms, treatments and outcomes from such cADRs are still lacking in Taiwan. Method(s): A cross-sectional study was conducted from December 2019 to October 2022 to analyze spontaneous ADR reporting data from Taiwan's largest multi-institutional healthcare system. Physicians and pharmacists initially ensured the data quality and completeness of the reported ADR records. Subsequently, we applied descriptive statistics to analyze the patient cohort based on demographic characteristics, administered COVID-19 vaccines, clinical manifestations, and patient management. Result(s): We identified 242 cADRs from 759 reported COVID-19 vaccine-related ADRs, 88.3% of which were judged as "possible" using the Naranjo Scale. The mean age of patients with cADRs was 48.1+/-17.5 years, with the majority (44.2%) of cADRs reported in the 40-64yr old age group. cADRs were more common in women (68.2%) and most of the patients had no history of allergy to vaccines (99.6%). Oxford/AstraZeneca (58.6%) accounted for the most reported brand of COVID-19 vaccines. Patients developed cADRs within 1 to 198 days (median = 5.5 days), and mostly after first-dose vaccination (77.8%). The most frequently reported cADR was rash/eruption (18.7%), followed by itchiness/pruritus (11.7%) and urticaria (9.2%), mainly affecting the lower limbs (23.8%) and upper limbs (22.6%). Medications were prescribed for 65.1% of the cADRs, and signs and symptoms were resolved within 1 to 167 days (median = 7 days) after treatment with oral antihistamines (23.0%), topical corticosteroids (14.6%) or oral corticosteroids (14.4%). Conclusion(s): Our findings provide comprehensive details regarding COVID-19 vaccine-related cADRs in Taiwan. Certain groups, especially women and the middle-aged, who reported a relatively higher rate of cADRs, may benefit from pre-vaccination counseling about the risks of cADRs and the use of appropriate medications.Copyright © 2023
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In automated scientific fact-checking, machine learning models are trained to verify scientific claims given evidence. A major bottleneck of this task is the availability of large-scale training datasets on different domains, due to the required domain expertise for data annotation. However, multiple-choice question-answering datasets are readily available across many different domains, thanks to the modern online education and assessment systems. As one of the first steps towards addressing the fact-checking dataset scarcity problem in scientific domains, we propose a pipeline for automatically converting multiple-choice questions into fact-checking data, which we call Multi2Claim. By applying the proposed pipeline, we generated two large-scale datasets for scientific-fact-checking: Med-Fact and Gsci-Fact for the medical and general science domains, respectively. These two datasets are among the first examples of large-scale scientific-fact-checking datasets. We developed baseline models for the verdict prediction task using each dataset. Additionally, we demonstrated that the datasets could be used to improve performance measured by weighted F1 on existing fact-checking datasets such as SciFact, HEALTHVER, COVID-Fact, and CLIMATE-FEVER. In some cases, the improvement in performance was up to a 26% increase. The generated datasets are publicly available. © 2023 Association for Computational Linguistics.
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COVID-19 has spread around the world since 2019. Approximately 6.5% of COVID-19 a risk of developing severe disease with high mortality rate. To reduce the mortality rate and provide appropriate treatment, this research established an integrated models with to predict the clinical outcome of COVID-19 patients with clinical, deep learning and radiomics features. To obtain the optimal feature combination for prediction, 9 clinical features combination was selected from all available clinical factors after using LASSO, 18 deep learning features from U-Net architecture, and 9 radiomics features from segmentation result. A total of 213 COVID-19 patients and 335 non-COVID-19 patients from 5 hospitals were enrolled and used as training and test sample in this research. The proposed model obtained an accuracy, precision, recall, specificity, F1-score and ROC curve of 0.971, 0.943, 0.937, 0.974, 0.941 and 0.979, respectively, which exceeds the related work using only clinical, deep learning or radiomics factors. © 2023 SPIE.
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BackgroundAlthough many studies have been conducted on COVID-19 in recent years, there are still unanswered questions regarding breakthrough infections (BTIs), particularly in patients with systemic lupus erythematosus (SLE).ObjectivesThis study aimed to determine the occurrence of breakthrough COVID-19 infections in patients with SLE versus other autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HCs).MethodsThe study was based on data from the COVAD questionnaire which amassed a total of 10,783 complete responses from patients with SLE, AIRD, or nrAIRD, and HCs. After exclusion of individuals who were unvaccinated, those who received one vaccine dose only, and those with uncertain responses regarding the vaccine doses, a total of 9,595 patients formed the study population of the present investigation. If a COVID-19 infection occurred after the initial two vaccine doses and at least one booster dose (at least three doses in total, herein termed full vaccination), it was considered a BTI. Data were analysed using multivariable regression models. Statistically significant results were denoted by p values <0.05.ResultsA total of 7,016/9,595 (73.1%) individuals were fully vaccinated. Among those, 1,002 (14.2%) reported at least one BTI, and 166 (2.3%) reported at least two BTIs. Among SLE patients, 867/1,218 (71.2%) were fully vaccinated. Among fully vaccinated SLE patients, 137 (15.8%) reported at least one BTI while 28 (3.2%) reported at least two BTIs. BTI frequencies in fully vaccinated SLE patients were comparable to those of other AIRDs (OR: 1.0;95% CI: 0.8–1.3;p=0.447) and nrAIDS (OR: 0.9;95% CI: 0.6–1.3;p=0.856) but higher compared with HCs (OR: 1.2;95% CI: 1.0–1.6;p=0.022).For SLE patients with three vaccine doses, 113/137 (82.5%) reported at least one BTI while the corresponding number for four vaccine doses was 24/137 (17.5%). Compared with HCs (OR: 10.6;95% CI: 1.2–93.0;p=0.032) and other AIRDs (OR: 3.5;95% CI: 1.08–11.5;p=0.036), SLE patients showed higher frequencies of hospitalisation.AID multimorbidity was associated with a 15-fold increased risk for a need of advanced treatment for COVID-19 (OR: 15.3;95% CI: 2.6–88.2;p=0.002).ConclusionCOVID-19 BTIs occurred in nearly 1 every 6th fully vaccinated patient with SLE, and 20% more frequently in this patient population compared with fully vaccinated HCs. Moreover, BTIs in SLE patients were more severe compared with BTIs in HCs or patients with AIRDs other than SLE, resulting in a greater need for hospitalisation. AID multimorbidity contributed to a more severe COVID-19 BTI requiring advanced management. These insights call for greater attention to vaccination in the vulnerable group of SLE patients, with appropriate risk stratification towards optimised vaccination strategies.Figure 1.Survival analysis across patients with SLE, AIRDs, or nrAIDs, and HCs. SLE: systemic lupus erythematosus;AIRD: autoimmune rheumatic disease;nrAID: non-rheumatic autoimmune disease;HC: healthy control.[Figure omitted. See PDF]AcknowledgementsThe authors thank all survey respondents, as well as patient associations and all members of the COVAD study group for their invaluable role in the data collection.Disclosure of InterestsEmelie Kihlgren Olsson: None declared, Naveen Ravichandran: None declared, Elena Nikiphorou Speakers bureau: EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly., Consultant of: EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly., Grant/research support from: EN holds research grants from Pfizer and Lilly., Julius Lindblom: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Kshitij Jagtap: None declared, James B. Lilleker Speakers bureau:
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Objective To investigate the clinical significance of serum interleukin 6 (IL-6) in elderly patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant and its correlation with underlying diseases. Methods A total of 22 elderly patients (80 years old) infected with omicron variant, who were admitted to Department of Infectious Diseases, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. to Jun. 2022 and tested positive for SARS-CoV-2 RNA, were included. The level of serum IL-6 was measured by flow cytometry, and the level of serum C reactive protein (CRP) was measured by immunonephelometry. Patients were divided into pneumonia group (16 cases) and non-pneumonia group (6 cases) according to the imaging examination results, and were divided into severe group (severe and critical type, 5 cases) and non-severe group (mild and normal type, 17 cases) according to the condition. Binary logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the correlation between serum IL-6 and CRP levels and the severity of the disease and whether it would progress to pneumonia. Meanwhile, the relationships between underlying diseases and serum IL-6 level were explored. Results Among the 22 patients, 6 were mild, 11 were normal, 3 were severe, and 2 were critical. The baseline serum IL-6 level in the pneumonia group was significantly higher than that in the non-pneumonia group (20.16+/-12.36pg/mL vs 5.42+/-1.57 pg/mL, P=0.009), and there was no significant difference in baseline serum CRP level between the 2 groups (P0.05). There were no significant differences in baseline serum IL-6 or CRP levels between the severe group and the non-severe group (both P0.05). Logistic regression analysis showed that the baseline serum IL-6 and CRP might be related to pneumonia after infection with omicron variant (odds ratio OR=2.407, 95% confidence interval CI0.915-6.328;OR=1.030, 95% CI 0.952-1.114). ROC curve analysis showed that the area under curve values of serum IL-6 and CRP in predicting the progression to pneumonia were 0.969 (95% CI 0.900-1.000) and 0.656 (95% CI 0.380-0.932), respectively, with statistical significance (Z=2.154, P=0.030). There were no significant differences in the baseline serum IL-6 level or proportions of severe patients or pneumonia patients among patients with or without hypertension, diabetes mellitus, coronary heart disease, chronic kidney disease or chronic obstructive pulmonary disease (all P0.05). The baseline serum IL-6 levels of the omicron variant infected elderly patients with 1, 2, and 3 or more underlying diseases were 12.50 (9.15, 21.75), 23.55 (9.63, 50.10), and 10.90 (5.20, 18.88) pg/mL, respectively, with no statistical significance (P0.05). Conclusion For omicron variant infected patients, serum IL-6 level is significantly increased in patients with pneumonia manifestations and is correlated with disease progression. Serum IL-6 level is of great guiding significance to judge disease progression and evaluate efficacy and prognosis of elderly coronavirus disease 2019 patients.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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The multiple comparison method refers to the hypothesis test of whether there is a significant difference between the means of each sample after the analysis of variance is performed on the samples of each group to be tested. In data analysis, the multiple comparison method can perform a more precise difference analysis based on the analysis of variance. Therefore, this study will select the LSD (Least significant difference) test method in the multiple comparison method to analyze the physical fitness test scores of males and females in the three grades from 2019 to 2021 in the investigated schools. In this way, we can understand the substantial impact of students' home-based learning on students' physical health during the new crown epidemic, so as to make targeted development plans for students' physical health in the current special period, and minimize the adverse impact of the new crown epidemic on students' physical health. © 2023 SPIE.
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In the midst of the COVID-19 pandemic, new requirements for clean air supply are introduced for heating, ventilation, and air conditioning (HVAC) systems. One way for HVAC systems to efficiently remove airborne viruses is by filtering them. Unlike disposable filters that require repeated purchases of consumables, the electrostatic precipitator (ESP) is an alternative option without the drawback of reduced dust collection efficiency in high-efficiency particulate air (HEPA) filters due to dust buildup. The majority of viruses have a diameter ranging from 0.1 μm to 5 μm. This study proposed a two-stage ESP, which charged airborne viruses and particles via positive electrode ionization wire and collected them on a collecting plate with high voltage. Numerical simulations were conducted and revealed a continuous decrease in collection efficiencies between 0.1 μm and 0.5 μm, followed by a consistent increase from 0.5 μm to 1 μm. For particles larger than 1 μm, collection efficiencies exceeding 90% were easily achieved with the equipment used in this study. Previous studies have demonstrated that the collection efficiency of suspended particles is influenced by both the ESP voltage and turbulent flow at this stage. To improve the collection efficiency of aerosols ranging from 0.1 μm to 1 μm, this study used a multi-objective genetic algorithm (MOGA) in combination with numerical simulations to obtain the optimal parameter combination of ionization voltage and flow speed. The particle collection performance of the ESP was examined under the Japan Electrical Manufacturers' Association (JEMA) standards and showed consistent collection performance throughout the experiment. Moreover, after its design was optimized, the precipitator collected aerosols ranging from 0.1 μm to 3 μm, demonstrating an efficiency of over 95%. With such high collection efficiency, the proposed ESP can effectively filter airborne particles as efficiently as an N95 respirator, eliminating the need to wear a mask in a building and preventing the spread of droplet infectious diseases such as COVID-19 (0.08 μm–0.16 μm). © 2023 by the authors.
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This paper examines the social, technological, and emotional labor of maintaining China's data-driven governance broadly, and dynamic zero-COVID management in particular. Drawing on ethnographic research in China, we examine the sociotechnical work of maintenance during the 2022 Shanghai lockdown. This labor included coordinating mass testing, quarantine, and lockdown procedures as well as implementing ad-hoc technological workarounds and managing public sentiments. We demonstrate that, far from being effected from the top down, China's data-driven governance relies on the circumscribed participation of citizens. During Shanghai's lockdown, citizens with relevant expertise helped to maintain technological stability by fixing or programming data systems, but also to ensure the ongoing production of"positive feelings"about social stability through data-driven governance. In so doing, such citizens simultaneously enacted an ambivalent and circumscribed form of agency, and maintained social and by extension political stability. This article sheds light on data-driven governance and political processes of maintenance. © 2023 ACM.
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Multiple comparisons are general term for hypothesis testing of whether there is a significant difference between the means of each sample after analysis of variance. ANOVA can only determine whether there is a difference between the population means, and multiple comparisons can further test the differences between the sample means. This study will select the LSD (Least significant difference) test method in the multiple comparison method to conduct a differential test on the physical fitness test data of four different grades from 2018 to 2021 since the COVID-19 epidemic, and analyze the physical fitness of Chinese students under the background of new coronavirus epidemic. Change characteristics of health level, and summarize relevant experience, urge relevant personnel to make targeted improvements to the future work of students' physical health training, and scientifically improve the physical health level of Chinese students. © 2023 SPIE.
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During the Covid-19 pandemic, more guidelines were created to teach people how to facilitate meetings online, but few were designed from a cognition-oriented perspective. Additionally, solving complex problems is essential in many occupations. However, the influence of online and face-to-face discussion formats on the performance in complex problem-solving tasks is unclear, even though remote working has become common over the past several few years. Hence, this study aims to answer two research questions: (a) Does problem-solving performance differ between online and face-to-face meetings? and (b) Does facilitation improve problem-solving performance when different formats are used? We conducted experiments with 40 groups using a 2 × 2 factorial design, which were controlled for both facilitation and format. Each group comprised two randomly selected participants, and each problem-solving discussion lasted between 1.5-2 h. The obtained evidence showed that format can influence the performance of balancing intercorrelated factors in a complex scenario, but it does not affect the performance of achieving a predefined goal. Instead, it we found that facilitation is helpful for achieving a predefined goal. Based on the results obtained, we propose future design directions for problem-solving centric computer-supported cooperative work systems from a cognition-oriented perspective. © 2023 Owner/Author.
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Background:COVID-19 vaccine hesitancy among pregnant and breastfeeding women with autoimmune diseases (AID) is often attributed to the fear of adverse events (AE) and disease flares (DF). No data are available regarding COVID-19 vaccine safety in this population.Objectives:We aimed at describing delayed-onset (>7 days) vaccine-related AE (minor and major), DF, and related AID treatment modifications from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) study.Methods:Among complete responses from 9201 participants as of June 21, 2022, 6787 (73.8%) were women. Six subgroups were identified upon diagnosis of AID vs healthy controls (HC) and their pregnancy/breastfeeding status at the time of any dose of vaccine (Figure 1).Figure 1.Flowchart of the study. AID: autoimmune diseases;HC: healthy controls;rAID: rheumatic AID;nrAID: non-rheumatic AID.[Figure omitted. See PDF]ResultsForty pregnant and 52 breastfeeding AID patients were identified and their vaccination rates (at least one dose) was 100% and 96.2%, respectively (Table 1). Overall AE, minor AE, and major AE were reported significantly more frequently by pregnant than non-pregnant patients (45% vs. 26%, p=0.01;40% vs. 25.9%, p=0.03;17.5% vs. 4.6%, p<0.01), but no difference was found in comparison with pregnant HC. No difference was observed between breastfeeding patients and HC. Post-vaccination DF were reported by 17.5% of pregnant and 20% of breastfeeding patients, and by 18% of age- and disease-matched control patients (n=2315). All DF in pregnant/breastfeeding patients were managed with glucocorticoids and a fifth of them required initiation or change in immunosuppressive treatment.Table 1.Characteristics of female subjects according to groups. Percentages in parenthesis. *Pregnancy/breastfeeding status at the time of the survey and/or at the time of at least one dose of COVID-19 vaccine. Chi squared test: ~ p=0.01;° p=0.03;§ p<0.01.Total Women (n=6787)Group A Non-pregnant, non-breastfeeding with AID (n=4862)Group B Pregnant with AID* (n=40)Group C Breastfeeding with AID* (n=52)Group D Non-pregnant, non-breastfeeding HC (n=1749)Group E Pregnant HC* (n=31)Group F Breastfeeding HC* (n=53)Age (median, IQR)47, 35-5850, 38-6134, 31-35.2533, 30-3539, 29-4934, 30-36.533, 30-36Caucasian3225 (47.5)2634 (54.1)12 (30)22 (42.3)538 (30.8)7 (22.6)12 (22.6)No comorbidities3027 (44.6)1815 (37.3)19 (47.5)36 (69.2)1102 (63)17 (54.8)38 (71.7)Number of vaccinated women, n (%)6632 (97.7)4753 (97.8)40 (100)50 (96.2)1710 (97.8)30 (96.8)49 (92.5)≥3 doses4850 (71.5%)3583 (73.7%)26 (65%)33 (63.5%)1155 (66%)23 (74.2%)30 (56.6%)No AE4950 (74.6)3517 (74)~22 (55)~36 (72)1312 (76.7)22 (73.3)36 (73.5)Injection site (arm) pain and soreness630 (9.5)471 (9.9)7 (17.5)7 (14)138 (8.1)2 (6.7)5 (10.2)Minor AE1614 (24.3)1232 (25.9)°16 (40)°12 (24)338 (19.8)7 (23.3)10 (20.4)Major AE285 (4.3)196 (4.6)§7 (17.5)§1 (2)77 (4.5)1 (3.3)3 (6.1)Hospitalization74 (1.1)51 (1.1)2 (5)0 (0)20 (1.2)0 (0)1 (2)ConclusionThis study provides the first insights into the safety of COVID-19 vaccination during the antenatal period in women with AID. While AEs were more commonly reported by pregnant patients with AID, these were no higher than among pregnant healthy controls without AID. These observations are reassuring, likely to strengthen physician-patient communication and overcome hesitancy as the benefits for the mother and fetus by passive immunization are likely to overweigh the potential risks of AE and DF.Reference[1]Fazal ZZ, et al;COVAD Study Group. COVAD survey 2 long-term outcomes: unmet need and protocol. Rheumatol Int 2022;42:2151-2158.AcknowledgementsThe authors are grateful to all respondents, to all patients support groups, and to all COVAD Study Group collaborators from 106 Countries.Disclosure of InterestsNone Declared.
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The outbreak of the COVID-19 pandemic brought unrelenting waves of xenophobia against people representing vulnerable populations, among them those identified as Asians or more specifically as Chinese. Although previous studies have found that some discriminatory actions against overseas Chinese were closely related to mask use during the pandemic, there is not much evidence that explicates what might be the social-cultural triggers or impact of self-other mask discrepancy. The current study aims to examine how a mask use gap impacts perceived discrimination and anxiety during the first outbreak of COVID-19, and how perceived discrimination mediates the mask gap-anxiety relationship. This was operationalized by developing a new "mask gap" variable to capture the incongruent mask use norms between Chines and others around them in the host country. Data were collected from a cross-sectional sample of Chinese (n = 745) residing in 21 countries from March to May 2020 during the first wave of the pandemic. Results showed the newly explicated "mask gap" variable was associated with a higher level of anxiety. In addition, perceived discrimination mediated the mask gap-anxiety relationship. These findings advance both theoretical and practical understandings of how incongruent social norms impact discrimination and mental health during health threat events like the COVID-19 pandemic. The results also suggest important implications for both societal responses and the mental health of sojourners or immigrants during pandemics.
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The outbreak of COVID-19 pandemic in northern Taiwan led to the implementation of Level 3 alert measures during 2021 and thereby impacted the air quality significantly, which provided an unprecedented opportunity to better understand the control strategies on air pollutants in the future. This study investigated the variations in sources, chemical characteristics and human health risks of PM2.5 comprehensively. The PM2.5 mass concentrations decreased from pre-alert to Level 3 alert by 49.4%, and the inorganic ions, i.e., NH4+, NO3- and SO42-, dropped even more by 71%, 90% and 52%, respectively. Nonetheless, organic matter (OM) and elemental carbon (EC) simply decreased by 36% and 13%, which caused the chemical composition of PM2.5 to change so that the carbonaceous matter in PM2.5 dominated instead of the inorganic ions. Correlation-based hierarchical clustering analysis further showed that PM2.5 was clustered with carbonaceous matter during the Level 3 alert, while that clustered with inorganic ions during both pre-alert and post-alert periods. Moreover, 6 sources of PM2.5 were identified by positive matrix factorization (PMF), in which secondary nitrate (i.e., aging traffic aerosols) exhibited the most significant decrease and yet primary traffic-related emissions, dominated by carbonaceous matter, changed insignificantly. This implied that secondary traffic-related aerosols could be easily controlled when traffic volume declined, while primary traffic source needs more efforts in the future, especially for the reduction of carbonaceous matter. Therefore, cleaner energy for vehicles is still needed. Assessments of both carcinogenic risk and non-carcinogenic risk induced by the trace elements in PM2.5 showed insignificant decrease, which can be attributed to the factories that did not shut down during Level 3 alert. This study serves as a metric to underpin the mitigation strategies of air pollution in the future and highlights the importance of carbonaceous matter for the reduction in PM2.5.
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Objective To investigate the clinical significance of serum interleukin 6 (IL-6) in elderly patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant and its correlation with underlying diseases. Methods A total of 22 elderly patients (>80 years old) infected with omicron variant, who were admitted to Department of Infectious Diseases, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. to Jun. 2022 and tested positive for SARS-CoV-2 RNA, were included. The level of serum IL-6 was measured by flow cytometry, and the level of serum C reactive protein (CRP) was measured by immunonephelometry. Patients were divided into pneumonia group (16 cases) and non-pneumonia group (6 cases) according to the imaging examination results, and were divided into severe group (severe and critical type, 5 cases) and non-severe group (mild and normal type, 17 cases) according to the condition. Binary logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the correlation between serum IL-6 and CRP levels and the severity of the disease and whether it would progress to pneumonia. Meanwhile, the relationships between underlying diseases and serum IL-6 level were explored. Results Among the 22 patients, 6 were mild, 11 were normal, 3 were severe, and 2 were critical. The baseline serum IL-6 level in the pneumonia group was significantly higher than that in the non-pneumonia group ([20.16+/-12.36]pg/mL vs [5.42+/-1.57] pg/mL, P=0.009), and there was no significant difference in baseline serum CRP level between the 2 groups (P>0.05). There were no significant differences in baseline serum IL-6 or CRP levels between the severe group and the non-severe group (both P>0.05). Logistic regression analysis showed that the baseline serum IL-6 and CRP might be related to pneumonia after infection with omicron variant (odds ratio [OR]=2.407, 95% confidence interval [CI]0.915-6.328;OR=1.030, 95% CI 0.952-1.114). ROC curve analysis showed that the area under curve values of serum IL-6 and CRP in predicting the progression to pneumonia were 0.969 (95% CI 0.900-1.000) and 0.656 (95% CI 0.380-0.932), respectively, with statistical significance (Z=2.154, P=0.030). There were no significant differences in the baseline serum IL-6 level or proportions of severe patients or pneumonia patients among patients with or without hypertension, diabetes mellitus, coronary heart disease, chronic kidney disease or chronic obstructive pulmonary disease (all P>0.05). The baseline serum IL-6 levels of the omicron variant infected elderly patients with 1, 2, and 3 or more underlying diseases were 12.50 (9.15, 21.75), 23.55 (9.63, 50.10), and 10.90 (5.20, 18.88) pg/mL, respectively, with no statistical significance (P>0.05). Conclusion For omicron variant infected patients, serum IL-6 level is significantly increased in patients with pneumonia manifestations and is correlated with disease progression. Serum IL-6 level is of great guiding significance to judge disease progression and evaluate efficacy and prognosis of elderly coronavirus disease 2019 patients.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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Due to the COVID-19 pandemic in Taiwan, many construction sites must limit the number of people on the jobsite or conduct work independently to avoid the spread of COVID-19. The quality of construction may be in doubt with unclear job handover, especially when workers have COVID-19 infection that should be isolated immediately. On top of that, first-level subcontractor self-inspections are crucial parts of construction process management, and neglecting inspec-tion processes can lead to construction errors and poor quality. To improve current quality inspection methods for private projects, a literature analysis was conducted to identify construction quality management issues that are faced in private housing projects. In-depth interviews with small and medium-sized subcontractors of private housing projects were per-formed to understand the quality management methods that they use in practice. Next, improvement measures for quality management were formulated and a simplified checklist for private project subcontractors, based on the practical feedback obtained, was created. Finally, the AppSheet platform was used to develop an inspection application for construction, and a subcontractor was invited to confirm its feasibility. The paperless design avoids redundant human contact, and the re-sults of this study greatly facilitate construction practice, particularly during the pandemic. The main contribution of this study is its investigation of the procedures that are used by private project subcontractors to inspect their work for quality management;its results can serve as a reference for academics in evaluating construction quality management levels and improving the management of work by subcontractors to promote safety and health.
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Intro: Oral antiviral agents with differing modes of action are now available for the treatment of COVID-19. However, potentially life-threatening drug-drug interactions (DDIs) may occur if patients' underlying co-morbidities are treated with medications that are contraindicated with ritonavir-containing antivirals. This study evaluated the prevalence and severity of potential DDIs (pDDIs) with ritonavir-containing COVID-19 oral antiviral therapy among the Australian population. Method(s): Adult patients supplied with >=1 medication between January 1, 2019, and December 31, 2019, were identified in the PBS10 dataset, a longitudinal, random 10% sample of the national Pharmaceutical Benefits Scheme (PBS) data for supplied prescriptions. Patients receiving medications that have pDDIs with a ritonavir-containing COVID-19 antiviral treatment were classified as the pDDI group, using data sources from University of Liverpool, Lexicomp, or the US Food and Drugs Administration. Finding(s): Over 1,434,000 patients in the PBS10 were supplied with >=1 medication during the study period. The majority (58.8%) had been prescribed at least one medication with pDDI with ritonavir-containing treatment. Among all patients with pDDIs, 43.3% of them were major or contraindicated, followed by moderate (15.1%), and minor pDDIs (1.9%). Patients with cancer had the highest prevalence of contraindicated or major pDDIs (79.5%), followed by dementia and/or Alzheimer's (77.2%), and diabetes (73.8%). Elderly patients (>=60 years old) also had a higher prevalence of contradicted or major pDDI (65.4%) than the general patient population. Conclusion(s): Our results demonstrated that one-third of the Australian adult population in the PBS10 dataset may be classified as contraindicated with ritonavir-containing COVID-19 therapies. The prevalence of pDDI is much higher in elderly patients and in patients with certain co-morbidities. Health care providers will need to evaluate patients carefully should they be eligible for COVID-19 oral antiviral treatments. Alternative therapies should be considered as patients may be precluded from being treated with ritonavir-containing therapies owing to pDDIs.Copyright © 2023
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The continued outbreak of the novel coronavirus pneumonia (COVID-19) has had a huge impact on people's lives. In the context of the ongoing epidemic and the limited distribution capacity due to the multi-regional epidemic closure, it has become an urgent reality to minimise the damage caused to people's daily lives under the epidemic and other emergencies, and to implement safe, fair and economical dispatch of emergency supplies for the epidemic area. The problem. Based on this, a mixed integer linear programming model is constructed to maximise the fairness and minimise the transportation cost of emergency material dispatch. © 2023 SPIE.