Voice Disorder, Job Stress, and COVID-19 in Teachers: Impacts in Times of Pandemic

Introduction: The conditions of teachers' work during the COVID-19 pandemic affected teachers' lives regarding voice disorder and stress, even in emergency remote classroom situation. Objective: To analyze the relationship between the presence of voice disorder, job stress, and COVID-19 in teachers when in emergency remote classroom teaching situation at the time of the pandemic. Method: This is a primary, exploratory, observational cross-sectional study with the use of survey forwarded online during the period of emergency classes after the arrival of COVID-19 pandemic in Brazil. The teachers answered the sociodemographic questions about the presence of COVID-19 and the following instruments: Condition of Vocal Production-Teacher [Condição de Produção Vocal - Professor (CPV-P)], Screening Index for Voice Disorder (SIVD), and Job Stress Scale (JSS). Results: Of the 118 teachers analyzed, 94.1% were female; the average age was 44 years. The SIVD recorded the presence of voice disorder in 66.9% of the participants. Regarding the JSS, which are the findings related to stress at work in the demand domain, the teachers showed high levels, a fact which presupposes the existence of pressure of psychological nature to perform their work. Conclusion: The teachers self-reported the presence of voice disorder even in remote class situation, on the occasion of COVID-19, which were more common in older teachers. When comparing the presence of voice disorders, coronavirus symptoms, and stress domains in relation to demand, control, and social support, there was no significance. It is hoped that this study will help to reflect on the need to improve teachers' working conditions, strengthening work-related voice disorder actions and guiding actions for vocal care and well-being.

Introducción: Las condiciones de trabajo de los profesores durante la pandemia de COVID-19 afectaron sus vidas en lo que respecta al trastorno de la voz y el estrés, incluso en situaciones de emergencia en aulas remotas. Objetivo: Analizar la relación entre la presencia de trastorno de la voz, estrés laboral y COVID-19 en profesores cuando se encontraban en situación de emergencia de enseñanza en aulas remotas en la época de la pandemia. Método: Se trata de un estudio primario, exploratorio, observacional de tipo transversal, con el uso de encuesta remitida online durante el periodo de clases de emergencia tras la llegada de la pandemia de COVID-19 en Brasil. Los profesores respondieron a las preguntas sociodemográficas sobre la presencia de COVID-19 y a los siguientes instrumentos: Condición de Producción Vocal-Profesor (CPV-P), Índice de Detección de los Trastornos de la Voz (SIVD) y Escala de Estrés Laboral (JSS). Resultados: De los 118 profesores analizados, el 94,1% eran mujeres; la mediana de edad era de 44 años. El (SIVD) registró la presencia de trastorno de la voz en el 66,9% de los participantes. En cuanto a la JSS, que son los hallazgos relacionados con el estrés laboral en el dominio de la demanda, los profesores mostraron niveles elevados, hecho que presupone la existencia de presiones de naturaleza psicológica para realizar su trabajo. Conclusión: Los profesores autoinformaron de la presencia de trastornos de la voz incluso en situación de clase a distancia, con ocasión del COVID-19, que fueron más frecuentes en los profesores de más edad. Al comparar la presencia de trastornos de la voz, los síntomas del coronavirus y los dominios de estrés en relación con la demanda, el control y el apoyo social, no hubo resultados significativos. Se espera que este estudio ayude a reflexionar sobre la necesidad de mejorar las condiciones de trabajo de los docentes, fortaleciendo las acciones de Trastorno de la voz relacionado con el trabajo (WRVD) y orientando acciones para el cuidado y bienestar vocal.

Risk factors for acute kidney injury in patients hospitalized with COVID-19 / Fatores de risco para lesão renal aguda em pacientes hospitalizados com COVID-19

Abstract Introduction: Acute kidney injury (AKI) occurs frequently in COVID-19 patients and is associated with greater morbidity and mortality. Knowing the risks of AKI allows for identification, prevention, and timely treatment. This study aimed to identify the risk factors associated with AKI in hospitalized patients. Methods: A descriptive, retrospective, cross-sectional, and analytical component study of adult patients hospitalized with COVID-19 from March 1 to December 31, 2020 was carried out. AKI was defined by the creatinine criteria of the KDIGO-AKI guidelines. Information, regarding risk factors, was obtained from electronic medical records. Results: Out of the 934 patients, 42.93% developed AKI, 60.59% KDIGO-1, and 9.9% required renal replacement therapy. Patients with AKI had longer hospital stay, higher mortality, and required more intensive care unit (ICU) admission, mechanical ventilation, and vasopressor support. Multivariate analysis showed that age (OR 1.03; 95% CI 1.02-1.04), male sex (OR 2.13; 95% CI 1.49-3.04), diabetes mellitus (DM) (OR 1.55; 95% CI 1.04-2.32), chronic kidney disease (CKD) (OR 2.07; 95% CI 1.06-4.04), C-reactive protein (CRP) (OR 1.02; 95% CI 1.00-1.03), ICU admission (OR 1.81; 95% CI 1.04-3.16), and vasopressor support (OR 7.46; 95% CI 3.34-16.64) were risk factors for AKI, and that bicarbonate (OR 0.89; 95% CI 0.84-0.94) and partial pressure arterial oxygen/inspired oxygen fraction index (OR 0.99; 95% CI 0.98-0.99) could be protective factors. Conclusions: A high frequency of AKI was documented in COVID-19 patients, with several predictors: age, male sex, DM, CKD, CRP, ICU admission, and vasopressor support. AKI occurred more frequently in patients with higher disease severity and was associated with higher mortality and worse outcomes.

RESUMO Introdução: Lesão renal aguda (LRA) ocorre frequentemente em pacientes com COVID-19 e associa-se a maior morbidade e mortalidade. Conhecer riscos da LRA permite a identificação, prevenção e tratamento oportuno. Este estudo teve como objetivo identificar fatores de risco associados à LRA em pacientes hospitalizados. Métodos: Realizou-se estudo descritivo, retrospectivo, transversal e de componente analítico de pacientes adultos hospitalizados com COVID-19 de 1º de março a 31 de dezembro, 2020. Definiu-se a LRA pelos critérios de creatinina das diretrizes KDIGO-LRA. Informações sobre fatores de risco foram obtidas de prontuários eletrônicos. Resultados: Dos 934 pacientes, 42,93% desenvolveram LRA, 60,59% KDIGO-1 e 9,9% necessitaram de terapia renal substitutiva. Pacientes com LRA apresentaram maior tempo de internação, maior mortalidade e necessitaram de mais internações em UTIs, ventilação mecânica e suporte vasopressor. A análise multivariada mostrou que idade (OR 1,03; IC 95% 1,02-1,04), sexo masculino (OR 2,13; IC 95% 1,49-3,04), diabetes mellitus (DM) (OR 1,55; IC 95% 1,04-2,32), doença renal crônica (DRC) (OR 2,07; IC 95% 1,06-4,04), proteína C reativa (PCR) (OR 1,02; IC 95% 1,00-1,03), admissão em UTI (OR 1,81; IC 95% 1,04-3,16) e suporte vasopressor (OR 7,46; IC 95% 3,34-16,64) foram fatores de risco para LRA, e que bicarbonato (OR 0,89; IC 95% 0,84-0,94) e índice de pressão parcial de oxigênio arterial/fração inspirada de oxigênio (OR 0,99; IC 95% 0,98-0,99) poderiam ser fatores de proteção. Conclusões: Documentou-se alta frequência de LRA em pacientes com COVID-19, com diversos preditores: idade, sexo masculino, DM, DRC, PCR, admissão em UTI e suporte vasopressor. LRA ocorreu mais frequentemente em pacientes com maior gravidade da doença e associou-se a maior mortalidade e piores desfechos.

Orientações da COREMU SMS SP como estratégia de comunicação efetiva nos programas de Residência em Saúde

Orientações da COREMU SMS SP como estratégia de comunicação efetiva nos programas de Residência em Saúde. 2º Congresso Mineiro de Enfermagem ( 2ª CMENF).

Prognostic significance of the chemerin level in coronavirus disease 2019 patients.

Increased serum chemerin levels have been reported in several inflammatory diseases. Few studies have investigated the relationship between chemerin and clinical features of COVID-19. Thus, chemerin may modulate the development and progression of COVID-19. We compared the serum chemerin concentration between patients with and without SARS-CoV-2 infection and its association with the severity and prognosis of COVID-19 pneumonia. This is a prospective, single-center, cross-sectional study. We enrolled COVID-19 patients who presented to our tertiary hospital and healthy controls. The COVID-19 patients were conducted and the dates of symptom onset were recorded. After admission to the hospital and stabilization, blood samples were obtained for routine hemogram, biochemistry, and chemerin. The chemerin level was 37.93 ±â€…17.3 ng/mL in patients followed in the ICU, 29.41 ±â€…12.79 ng/mL in inpatients, 30.48 ±â€…10.86 ng/mL in outpatients, and 25.12 ±â€…9.82 ng/mL in healthy controls. The difference between patients treated in the ICU and healthy controls was significant (P < .001). The high-sensitivity C-reactive protein (hs-CRP), ferritin, procalcitonin (PCT), and D-dimer levels were significantly higher in the intensive care unit (ICU) group (P < .001). Moreover, the chemerin level of patients who died was significantly higher than that of those who survived (P < .001). The chemerin level was increased in COVID-19 patients and also increased with increasing disease severity. The chemerin level was higher in the COVID-19 patients than healthy controls and was significantly higher in patients who died compared to those who did not.

Enteric coronavirus nsp2 is a virulence determinant that recruits NBR1 for autophagic targeting of TBK1 to diminish the innate immune response.

Non-structural protein 2 (nsp2) exists in all coronaviruses (CoVs), while its primary function in viral pathogenicity, is largely unclear. One such enteric CoV, porcine epidemic diarrhea virus (PEDV), causes high mortality in neonatal piglets worldwide. To determine the biological role of nsp2, we generated a PEDV mutant containing a complete nsp2 deletion (rPEDV-Δnsp2) from a highly pathogenic strain by reverse genetics, showing that nsp2 was dispensable for PEDV infection, while its deficiency reduced viral replication in vitro. Intriguingly, rPEDV-Δnsp2 was entirely avirulent in vivo, with significantly increased productions of IFNB (interferon beta) and IFN-stimulated genes (ISGs) in various intestinal tissues of challenged newborn piglets. Notably, nsp2 targets and degrades TBK1 (TANK binding kinase 1), the critical kinase in the innate immune response. Mechanistically, nsp2 induced the macroautophagy/autophagy process and recruited a selective autophagic receptor, NBR1 (NBR1 autophagy cargo receptor). NBR1 subsequently facilitated the K48-linked ubiquitination of TBK1 and delivered it for autophagosome-mediated degradation. Accordingly, the replication of rPEDV-Δnsp2 CoV was restrained by reduced autophagy and excess productions of type I IFNs and ISGs. Our data collectively define enteric CoV nsp2 as a novel virulence determinant, propose a crucial role of nsp2 in diminishing innate antiviral immunity by targeting TBK1 for NBR1-mediated selective autophagy, and pave the way to develop a new type of nsp2-based attenuated PEDV vaccine. The study also provides new insights into the prevention and treatment of other pathogenic CoVs.Abbreviations: 3-MA: 3-methyladenine; Baf A1: bafilomycin A1; CoV: coronavirus; CQ: chloroquine; dpi: days post-inoculation; DMVs: double-membrane vesicles; GABARAP: GABA type A receptor-associated protein; GFP: green fluorescent protein; GIGYF2: GRB10 interacting GYF protein 2; hpi: hours post-infection; IFA: immunofluorescence assay; IFIH1: interferon induced with helicase C domain 1; IFIT2: interferon induced protein with tetratricopeptide repeats 2; IFITM1: interferon induced transmembrane protein 1; IFNB: interferon beta; IRF3: interferon regulatory factor 3; ISGs: interferon-stimulated genes; mAb: monoclonal antibody; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MAVS: mitochondrial antiviral signaling protein; NBR1: NBR1 autophagy cargo receptor; nsp2: non-structural protein 2; OAS1: 2'-5'-oligoadenylate synthetase 1; PEDV: porcine epidemic diarrhea virus; PRRs: pattern recognition receptors; RIGI: RNA sensor RIG-I; RT-qPCR: reverse transcription quantitative polymerase chain reaction; SQSTM1: sequestosome 1; TBK1: TANK binding kinase 1; TCID50: 50% tissue culture infectious doses; VSV: vesicular stomatitis virus.

COVID-19 fatality and DALYs, and associated metabolic disorders and ambient air pollutants in pre-Omicron era of the pandemic: an international comparative study.

BACKGROUND: Air pollution and a number of metabolic disorders have been reported to increase the risk of severe COVID-19 outcomes. This study explored the association between severe COVID-19 outcomes, metabolic disorders and environmental air pollutants, at regional level, across 38 countries. METHODS: We conducted an ecological study using COVID-19 data related to countries of the Organization for Economic Cooperation and Development (OECD), with an estimated population of 1.4 billion. They were divided into 3 regions: 1. Europe & Middle east; 2. Americas (north, central & south America); 3. East-Asia & West Pacific. The outcome variables were: COVID-19 case-fatality rate (CFR) and disability-adjusted life years (DALYs) at regional level. Freely accessible datasets related to regional DALYs, demographics and other environmental pollutants were obtained from OECD, WHO and the World in Data websites. Generalized linear model (GLM) was performed to determine the regional determinants of COVID-19 CFR and DALYs using the aggregate epidemiologic data (Dec. 2019-Dec. 2021). RESULTS: Overall cumulative deaths were 65,000 per million, for mean CFR and DALYs of 1.31 (1.2)% and 17.35 (2.3) years, respectively. Globally, GLM analysis with adjustment for elderly population rate, showed that COVID-19 CFR was positively associated with atmospheric PM2.5 level (beta = 0.64(0.0), 95%CI: 0.06-1.35; p < 0.05), diabetes prevalence (beta = 0.26(0.1), 95%CI: 0.12-0.41; p < 0.001). For COVID-19 DALYs, positive associations were observed with atmospheric NOx level (beta = 0.06(0.0), 95%CI: 0.02-0.82; p < 0.05) and diabetes prevalence (beta = 0.32(0.2), 95%CI: 0.04-0.69; p < 0.05). At regional level, adjusted GLM analysis showed that COVID-19 CFR was associated with atmospheric PM2.5 level in the Americas and East-Asia & Western Pacific region; it was associated with diabetes prevalence for countries of Europe & Middle east and East-Asia & Western Pacific region. Furthermore, COVID-19 DALYs were positively associated with atmospheric PM2.5 and diabetes prevalence for countries of the Americas only. CONCLUSION: These findings confirm that diabetes and air pollution increase the risk of disability and fatality due to COVID-19, with disparities in terms of their impact. They suggest that efficient preventive and management programs for diabetes and air pollution countermeasures would have curtailed severe COVID-19 outcome rates.

On-site detection of infectious disease based on CaCO3-based magnetic micromotor integrated with graphene field effect transistor.

A new detection platform based on CaCO3-based magnetic micromotor (CaCO3@Fe3O4) integrated with graphene field effect transistor (GFET) was construct and used for on-site SARS-CoV-2 coronavirus pathogen detection. The CaCO3@Fe3O4 micromotor, which was modified with anti-SARS-CoV-2 (labelled antibody, AntiE1), can self-moved in the solution containing hydrochloric acid (HCl) and effective to capture the SARS-CoV-2 coronavirus pathogens. After magnetic field separation, the capture micromotor was detected by GFET, exhibiting a good linear relationship within the range of 1 ag/mL to 100 ng/mL and low detection limit (0.39 ag/mL). Furthermore, the detection platform was also successfully applied to detection of SARS-CoV-2 coronavirus pathogens in soil solution, indicating the potential use in on-site application.

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Bioinformatics and system biology approach to identify the influences among COVID-19, influenza, and HIV on the regulation of gene expression.

Background: Coronavirus disease (COVID-19), caused by SARS-CoV-2, has emerged as a infectious disease, coexisting with widespread seasonal and sporadic influenza epidemics globally. Individuals living with HIV, characterized by compromised immune systems, face an elevated risk of severe outcomes and increased mortality when affected by COVID-19. Despite this connection, the molecular intricacies linking COVID-19, influenza, and HIV remain unclear. Our research endeavors to elucidate the shared pathways and molecular markers in individuals with HIV concurrently infected with COVID-19 and influenza. Furthermore, we aim to identify potential medications that may prove beneficial in managing these three interconnected illnesses. Methods: Sequencing data for COVID-19 (GSE157103), influenza (GSE185576), and HIV (GSE195434) were retrieved from the GEO database. Commonly expressed differentially expressed genes (DEGs) were identified across the three datasets, followed by immune infiltration analysis and diagnostic ROC analysis on the DEGs. Functional enrichment analysis was performed using GO/KEGG and Gene Set Enrichment Analysis (GSEA). Hub genes were screened through a Protein-Protein Interaction networks (PPIs) analysis among DEGs. Analysis of miRNAs, transcription factors, drug chemicals, diseases, and RNA-binding proteins was conducted based on the identified hub genes. Finally, quantitative PCR (qPCR) expression verification was undertaken for selected hub genes. Results: The analysis of the three datasets revealed a total of 22 shared DEGs, with the majority exhibiting an area under the curve value exceeding 0.7. Functional enrichment analysis with GO/KEGG and GSEA primarily highlighted signaling pathways associated with ribosomes and tumors. The ten identified hub genes included IFI44L, IFI44, RSAD2, ISG15, IFIT3, OAS1, EIF2AK2, IFI27, OASL, and EPSTI1. Additionally, five crucial miRNAs (hsa-miR-8060, hsa-miR-6890-5p, hsa-miR-5003-3p, hsa-miR-6893-3p, and hsa-miR-6069), five essential transcription factors (CREB1, CEBPB, EGR1, EP300, and IRF1), and the top ten significant drug chemicals (estradiol, progesterone, tretinoin, calcitriol, fluorouracil, methotrexate, lipopolysaccharide, valproic acid, silicon dioxide, cyclosporine) were identified. Conclusion: This research provides valuable insights into shared molecular targets, signaling pathways, drug chemicals, and potential biomarkers for individuals facing the complex intersection of COVID-19, influenza, and HIV. These findings hold promise for enhancing the precision of diagnosis and treatment for individuals with HIV co-infected with COVID-19 and influenza.

Computational identification and experimental verification of a novel signature based on SARS-CoV-2-related genes for predicting prognosis, immune microenvironment and therapeutic strategies in lung adenocarcinoma patients.

Background: Early research indicates that cancer patients are more vulnerable to adverse outcomes and mortality when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, the specific attributes of SARS-CoV-2 in lung Adenocarcinoma (LUAD) have not been extensively and methodically examined. Methods: We acquired 322 SARS-CoV-2 infection-related genes (CRGs) from the Human Protein Atlas database. Using an integrative machine learning approach with 10 algorithms, we developed a SARS-CoV-2 score (Cov-2S) signature across The Cancer Genome Atlas and datasets GSE72094, GSE68465, and GSE31210. Comprehensive multi-omics analysis, including assessments of genetic mutations and copy number variations, was conducted to deepen our understanding of the prognosis signature. We also analyzed the response of different Cov-2S subgroups to immunotherapy and identified targeted drugs for these subgroups, advancing personalized medicine strategies. The expression of Cov-2S genes was confirmed through qRT-PCR, with GGH emerging as a critical gene for further functional studies to elucidate its role in LUAD. Results: Out of 34 differentially expressed CRGs identified, 16 correlated with overall survival. We utilized 10 machine learning algorithms, creating 101 combinations, and selected the RFS as the optimal algorithm for constructing a Cov-2S based on the average C-index across four cohorts. This was achieved after integrating several essential clinicopathological features and 58 established signatures. We observed significant differences in biological functions and immune cell statuses within the tumor microenvironments of high and low Cov-2S groups. Notably, patients with a lower Cov-2S showed enhanced sensitivity to immunotherapy. We also identified five potential drugs targeting Cov-2S. In vitro experiments revealed a significant upregulation of GGH in LUAD, and its knockdown markedly inhibited tumor cell proliferation, migration, and invasion. Conclusion: Our research has pioneered the development of a consensus Cov-2S signature by employing an innovative approach with 10 machine learning algorithms for LUAD. Cov-2S reliably forecasts the prognosis, mirrors the tumor's local immune condition, and supports clinical decision-making in tumor therapies.

How inclusive were UK-based randomised controlled trials of COVID-19 vaccines? A systematic review investigating enrolment of Black adults and adult ethnic minorities.

OBJECTIVES: To establish if Black adults and adult ethnic minorities, defined as any group except White British, were represented in UK-based COVID-19 vaccination randomised controlled trials (RCTs) when compared to corresponding UK population proportions, based on 2011 census data. DESIGN: Systematic review of COVID-19 Randomised Controlled Vaccine Trials SETTING: United Kingdom PARTICIPANTS: Randomised Controlled Trials of COVID-19 vaccines conducted in the UK were systematically reviewed following PRISMA guidelines. MeSH terms included "Covid-19 vaccine", "Ad26COVS1", and "BNT162 Vaccine" with keywords such as [covishield OR coronavac OR Vaxzevria OR NVX-CoV2373] also used. Studies that provided (A) participant demographics and (B) full eligibility criteria were included. The following key data was extracted for analysis: number of participants analysed, number of Black adults and number of adult minority ethnicity participants. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome is the mean percentage of Black adults randomised to COVID-19 vaccine trials deemed eligible within this review. The secondary outcome is the mean percentage of adult ethnic minorities randomised. RESULTS: The final review included 7 papers and a total of 87 sets of data collated from trial sites across the UK. The standard mean percentage of Black adults included in the trials (0.59%, 95% CI: 0.13% - 1.05%) was significantly lower compared to the recorded Black adult population (2.67%) indicating that they were under-served in UK based COVID-19 vaccine RCTs (p < 0.001). Adult ethnic minority presence (8.94%, 95% CI: 2.07% - 15.80%) was also lower than census data (16.30%), indicating they were also under-served (p = 0.039). CONCLUSION: The findings show that COVID-19 vaccine trials failed to adequately randomise proportionate numbers of Black adults and adult minority ethnicities. More inclusive practices must be developed and implemented in the recruitment of underserved groups to understand the true impact of COVID-19.

Interleukin inhibitors and the associated risk of candidiasis.

Interleukins (ILs) are vital in regulating the immune system, enabling to combat fungal diseases like candidiasis effectively. Their inhibition may cause enhanced susceptibility to infection. IL inhibitors have been employed to control autoimmune diseases and inhibitors of IL-17 and IL-23, for example, have been associated with an elevated risk of Candida infection. Thus, applying IL inhibitors might impact an individual's susceptibility to Candida infections. Variations in the severity of Candida infections have been observed between individuals with different IL inhibitors, necessitating careful consideration of their specific risk profiles. IL-1 inhibitors (anakinra, canakinumab, and rilonacept), IL-2 inhibitors (daclizumab, and basiliximab), and IL-4 inhibitors (dupilumab) have rarely been associated with Candida infection. In contrast, tocilizumab, an inhibitor of IL-6, has demonstrated an elevated risk in the context of coronavirus disease 2019 (COVID-19) treatment, as evidenced by a 6.9% prevalence of candidemia among patients using the drug. Furthermore, the incidence of Candida infections appeared to be higher in patients exposed to IL-17 inhibitors than in those exposed to IL-23 inhibitors. Therefore, healthcare practitioners must maintain awareness of the risk of candidiasis associated with using of IL inhibitors before prescribing them. Future prospective studies need to exhaustively investigate candidiasis and its associated risk factors in patients receiving IL inhibitors. Implementing enduring surveillance methods is crucial to ensure IL inhibitors safe and efficient utilization of in clinical settings.

The impact of the COVID-19 pandemic on renal cancer care.

PURPOSE: To evaluate the impact of the COVID-19 pandemic on renal cell carcinoma (RCC) care in the Netherlands. METHODS: Newly diagnosed RCCs between 2018 and 2021 were selected from the Netherlands Cancer Registry; 2020-2021 was defined as COVID period and 2018-2019 as reference period. Numbers of RCCs were evaluated using 3-week-moving averages, overall and by disease stage and age. Changes in treatment were evaluated with logistic regression analyses. To evaluate possible delays in care, time to start of treatment was assessed. The cumulative number of metastatic RCC (mRCC) over time was assessed to evaluate stage shift. RESULTS: During the 1st COVID wave (weeks 9-22, 2020), the number of new RCC diagnoses decreased with 15%. Numbers restored partially in 2020, but remained 10% lower compared to 2018/2019. The decline was mostly due to a drop in T1a/T1b RCCs and in age > 70 years. 2021 showed similar numbers of new RCC diagnoses compared to 2018/2019 without an increase due to previously missed RCCs. Treatment-related changes during the 1st COVID wave were limited and temporarily; less surgery in T1a RCCs in favor of more active surveillance, and in mRCC targeted therapy was preferred over immunotherapy. Time to start of firstline treatment was not prolonged during the 1st COVID wave. No increase in mRCC was found until the end of 2021. CONCLUSIONS: The COVID-19 pandemic resulted in fewer RCC diagnoses, especially T1a/T1b tumors. Treatment-related changes appeared to be limited, temporarily and in accordance with the adapted guidelines. The diagnostic delay could lead to more advanced RCCs in later years but there are no indications for this yet.

Community health worker outreach to farmworkers in rural North Carolina: Learning from adaptations to the SARS-CoV-2 pandemic.

BACKGROUND: Community health workers represent a critical part of the health outreach and services for migrant and seasonal farmworkers ('farmworkers') in rural areas of the United States. PURPOSE: We sought to identify adaptations to farmworker patient engagement and health outreach made by community health workers during the first 18 months of the COVID-19 pandemic. METHODS: In this qualitative study, we used semi-structured interviews with community health workers from August 2020 to February 2022 (n = 21). Two coders used thematic analysis to identify three themes related to the experiences of community health workers in conducting health education and outreach to farmworkers prior to and following the onset of the pandemic. FINDINGS: We found themes related to pre-pandemic outreach efforts to provide health education resource sharing with farmworkers and pandemic-related outreach efforts that included adoption of porch drops and distanced delivery of health education, adaptation of modes of health education and communication through technology and the internet, and taking on new roles related to COVID-19. Finally, we identified changes that reverted after the pandemic or will continue as adaptations. CONCLUSIONS: Community health workers created practice-based innovations in outreach in response to the COVID-19 pandemic. These innovations included new COVID-19 related roles and new modes of health education and outreach, including the use of digital resources. The changes developed for emergency use in COVID-19, particularly related to internet and technology, have likely altered how community health workers conduct outreach in North Carolina going forward. Funders, community health worker training programs, and researchers should take note of these innovations. PATIENT OR PUBLIC CONTRIBUTION: Community health workers who typically come from patient populations and provide critical navigation and connection with the health care system advised on the design and creation of this research project, including serving on an advisory board. Two authors have experience working as community health workers.

Trust-building in temporary public health partnerships: a qualitative study of the partnership formation process of a Covid-19 test, trace and protect service.

BACKGROUND: Public health initiatives require coordinated efforts from healthcare, social services and other service providers. Organisational theory tells us that trust is essential for reaching collaborative effectiveness. This paper explores the drivers for initiating and sustaining trust in a temporary public health partnership, in response to a sudden health threat. METHODS: This qualitative study analysed the formation process of a multisector partnership for a Covid-19 contact tracing service. Data was collected through 12 interviews, two focus groups, one feedback workshop, and an online survey with workforce members from all seven partner organisations. Purposive maximum variation sampling was used to capture the reflections and experiences of workforce members from all seven partner organisations. A deductive code scheme was used to identify drivers for building and sustaining trust in inter-organisational collaboration. RESULTS: Relational mechanisms emanating from the commitment to the common aim, shared norms and values, and partnership structures affected trust-building. Shared values and the commitment to the common aim appeared to channel partners' behaviour when interacting, resulting in being perceived as a fair, reliable and supportive partner. Shared values were congruent with the design of the partnership in terms of governance structure and communication lines reflecting flat hierarchies and shared decision-making power. Tensions between partner organisations arose when shared values were infringed. CONCLUSIONS: When managing trust in a collaboration, partners should consider structural components like governance structure, organisational hierarchy, and communication channels to ensure equal power distribution. Job rotation, recruitment of candidates with the desired personality traits and attitudes, as well as training and development, encourage inter-organisational networking among employees, which is essential for building and strengthening relationships with partner organisations. Partners should also be aware of managing relational dynamics, channelling behaviours through shared values, objectives and priorities and fostering mutual support and equality among partner organisations.

Changes in long-term care insurance revenue among service providers during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has impacted peoples' health-related behaviors, especially those of older adults, who have restricted their activities in order to avoid contact with others. Moreover, the pandemic has caused concerns in long-term care insurance (LTCI) providers regarding management and financial issues. This study aimed to examine the changes in revenues among LTCI service providers in Japan during the pandemic and analyze its impact on different types of services. METHODS: In this study, we used anonymized data from "Kaipoke," a management support platform for older adult care operators provided by SMS Co., Ltd. Kaipoke provides management support services to more than 27,400 care service offices nationwide and has been introduced in many home-care support offices. The data used in this study were extracted from care plans created by care managers on the Kaipoke platform. To examine the impact of the pandemic, an interrupted time-series analysis was conducted in which the date of the beginning of the pandemic was set as the prior independent variable. RESULTS: The participating providers were care management providers (n = 5,767), home-visit care providers (n = 3,506), home-visit nursing providers (n = 971), and adult day care providers (n = 4,650). The results revealed that LTCI revenues decreased significantly for care management providers, home-visit nursing providers, and adult day care providers after the COVID-19 pandemic began. The largest decrease was an average base of USD - 1668.8 in adult day care. CONCLUSION: The decrease in revenue among adult day care providers was particularly concerning in terms of the sustainability of their business. This decrease in revenue may have made it difficult to retain personnel, and staff may have needed to be laid off as a result. Although this study has limitations, it may provide useful suggestions for countermeasures in such scenarios, in addition to support conducted measures.

Trajectory of cardiac troponin T following moderate-to-severe COVID-19 and the association with cardiac abnormalities.

BACKGROUND: COVID-19 has been associated with cardiac troponin T (cTnT) elevations and changes in cardiac structure and function, but the link between cardiac dysfunction and high-sensitive cardiac troponin T (hs-cTnT) in the acute and convalescent phase is unclear. OBJECTIVE: To assess whether hs-cTnT concentrations are associated with cardiac dysfunction and structural abnormalities after hospitalization for COVID-19, and to evaluate the performance of hs-cTnT to rule out cardiac pathology. METHODS: Patients hospitalized with COVID-19 had hs-cTnT measured during the index hospitalization and after 3-and 12 months, when they also underwent an echocardiographic study. A subset also underwent cardiovascular magnetic resonance imaging (CMR) after 6 months. Cardiac abnormalities were defined as left ventricular hypertrophy or dysfunction, right ventricular dysfunction, or CMR late gadolinium. RESULTS: We included 189 patients with hs-cTnT concentrations measured during hospitalization for COVID-19, and after 3-and 12 months: Geometric mean (95%CI) 13 (11-15) ng/L, 7 (6-8) ng/L and 7 (6-8) ng/L, respectively. Cardiac abnormalities after 3 months were present in 45 (30%) and 3 (8%) of patients with hs-cTnT ≥ and < 5 ng/L at 3 months, respectively (negative predictive value 92.3% [95%CI 88.5-96.1%]). The performance was similar in patients with and without dyspnea. Hs-cTnT decreased from hospitalization to 3 months (more pronounced in intensive care unit-treated patients) and remained unchanged from 3 to 12 months, regardless of the presence of cardiac abnormalities. CONCLUSION: Higher hs-cTnT concentrations in the convalescent phase of COVID-19 are associated with the presence of cardiac pathology and low concentrations (< 5 ng/L) may support in ruling out cardiac pathology following the infection.

Burdens and resources of Austrian clinical psychologists: results of a qualitative study two years into the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic increased the mental health burden in the general population, enhancing the demands placed on mental healthcare professionals. METHODS: This study aimed to assess the burdens and resources of clinical psychologists that emerged since the beginning of the pandemic. N = 172 Austrian clinical psychologists participated in a cross-sectional online survey between April and May 2022. The burdens and the sources of support that emerged during the pandemic were analyzed using qualitative content analysis. RESULTS: Mental health-related issues were identified as the greatest burden, followed by work-related themes and restrictions imposed by the government to combat the spreading of the virus. The most important resources mentioned by the clinical psychologists were social contacts and recreational activities. Practising mindfulness and focusing on inner processes and work-related aspects were further important resources mentioned. CONCLUSION: Overall, it seems that clinical psychologists have a high awareness of mental health-related problems related to the pandemic and use adaptive coping strategies to deal with them.

Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells.

T cells have the ability to eliminate infected and cancer cells and play an essential role in cancer immunotherapy. T cell activation is elicited by the binding of the T cell receptor (TCR) to epitopes displayed on MHC molecules, and the TCR specificity is determined by the sequence of its α and ß chains. Here, we collect and curate a dataset of 17,715 αßTCRs interacting with dozens of class I and class II epitopes. We use this curated data to develop MixTCRpred, an epitope-specific TCR-epitope interaction predictor. MixTCRpred accurately predicts TCRs recognizing several viral and cancer epitopes. MixTCRpred further provides a useful quality control tool for multiplexed single-cell TCR sequencing assays of epitope-specific T cells and pinpoints a substantial fraction of putative contaminants in public databases. Analysis of epitope-specific dual α T cells demonstrates that MixTCRpred can identify α chains mediating epitope recognition. Applying MixTCRpred to TCR repertoires from COVID-19 patients reveals enrichment of clonotypes predicted to bind an immunodominant SARS-CoV-2 epitope. Overall, MixTCRpred provides a robust tool to predict TCRs interacting with specific epitopes and interpret TCR-sequencing data from both bulk and epitope-specific T cells.

Identifying and overcoming COVID-19 vaccination impediments using Bayesian data mining techniques.

The COVID-19 pandemic has profoundly reshaped human life. The development of COVID-19 vaccines has offered a semblance of normalcy. However, obstacles to vaccination have led to substantial loss of life and economic burdens. In this study, we analyze data from a prominent health insurance provider in the United States to uncover the underlying reasons behind the inability, refusal, or hesitancy to receive vaccinations. Our research proposes a methodology for pinpointing affected population groups and suggests strategies to mitigate vaccination barriers and hesitations. Furthermore, we estimate potential cost savings resulting from the implementation of these strategies. To achieve our objectives, we employed Bayesian data mining methods to streamline data dimensions and identify significant variables (features) influencing vaccination decisions. Comparative analysis reveals that the Bayesian method outperforms cutting-edge alternatives, demonstrating superior performance.