No genetic causal association between systemic lupus erythematosus and COVID-19.

Objective: Emerging evidence suggests an increased prevalence of coronavirus disease 2019 (COVID-19) in patients with systemic lupus erythematosus (SLE), the prototype of autoimmune disease, compared to the general population. However, the conclusions were inconsistent, and the causal relationship between COVID-19 and SLE remains unknown. Methods: In this study, we aimed to evaluate the bidirectional causal relationship between COVID-19 and SLE using bidirectional Mendelian randomization (MR) analysis, including MR-Egger, weighted median, weighted mode, and the inverse variance weighting (IVW) method. Results: The results of IVW showed a negative effect of SLE on severe COVID-19 (OR = 0.962, p = 0.040) and COVID-19 infection (OR = 0.988, p = 0.025), which disappeared after Bonferroni correction. No causal effect of SLE on hospitalized COVID-19 was observed (OR = 0.983, p = 0.148). In the reverse analysis, no causal effects of severe COVID-19 infection (OR = 1.045, p = 0.664), hospitalized COVID-19 (OR = 0.872, p = 0.109), and COVID-19 infection (OR = 0.943, p = 0.811) on SLE were found. Conclusion: The findings of our bidirectional causal inference analysis did not support a genetically predicted causal relationship between SLE and COVID-19; thus, their association observed in previous observational studies may have been caused by confounding factors.

Hindering and enabling factors for young employees with common mental disorder to remain at or return to work affected by the Covid-19 pandemic - a qualitative interview study with young employees and managers.

BACKGROUND: During the COVID-19 pandemic, changes in working life occurred, even in Sweden, where there was no general lockdown. The aim of this study was to examine how the COVID-19 pandemic was perceived as affecting the hindering and enabling factors among young employees with CMD to remain at or return to work, here as investigated from the perspective of young employees and managers. MATERIAL AND METHODS: A qualitative design was applied with semistructured interviews with 23 managers and 25 young employees (20-29 years old). The interviews were recorded and transcribed verbatim, and the parts of the interviews related to the aim of this article were analysed using conventional content analysis. RESULTS: The hindering factors were changed working conditions, decreased well-being when spending more time at home, and uncertainty. The enabling factors were decreased demands, increased balance, and well-functioning work processes. For managers it is important to be aware of warning signals indicating blurred boundaries between work and private life, to create and maintain well-functioning communication, and leave room for recovery. CONCLUSION: The hindering and enabling factors can be described as two sides of the same coin. Changes in the working conditions during the pandemic led to difficulties for both young employees and managers when the margins of maneuver were insufficient.

Innate and adaptive immunity to SARS-CoV-2 and predisposing factors.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2), has affected all countries worldwide. Although some symptoms are relatively mild, others are still associated with severe and even fatal clinical outcomes. Innate and adaptive immunity are important for the control of SARS-CoV-2 infections, whereas a comprehensive characterization of the innate and adaptive immune response to COVID-19 is still lacking and the mechanisms underlying immune pathogenesis and host predisposing factors are still a matter of scientific debate. Here, the specific functions and kinetics of innate and adaptive immunity involved in SARS-CoV-2 recognition and resultant pathogenesis are discussed, as well as their immune memory for vaccinations, viral-mediated immune evasion, and the current and future immunotherapeutic agents. We also highlight host factors that contribute to infection, which may deepen the understanding of viral pathogenesis and help identify targeted therapies that attenuate severe disease and infection.

Target Trial Emulation: A Framework for Causal Inference From Observational Data.

This Guide to Statistics and Methods describes the use of target trial emulation to design an observational study so it preserves the advantages of a randomized clinical trial, points out the limitations of the method, and provides an example of its use.

Causality Network of Infectious Disease Revealed With Causal Decomposition.

Causal inference in the field of infectious disease attempts to gain insight into the potential causal nature of an association between risk factors and diseases. Simulated causality inference experiments have shown preliminary promise in improving understanding of the transmission of infectious diseases but still lack sufficient quantitative causal inference studies based on real-world data. Here, we investigate the causal interactions between three different infectious diseases and related factors, using causal decomposition analysis, to characterize the nature of infectious disease transmission. We show that the complex interactions between infectious disease and human behavior have a quantifiable impact on transmission efficiency of infectious diseases. Our findings, by shedding light on the underlying transmission mechanism of infectious diseases, suggest that causal inference analysis is a promising approach to determine epidemiological interventions.

Excess mortality from all causes during the COVID-19 pandemic in the city of Rio de Janeiro, Brazil.

OBJECTIVE: To evaluate excess mortality in the city of Rio de Janeiro, Brazil, due to the COVID-19 pandemic (March 2020 to January 2022). METHODS: Ecological study using secondary data from the Brazilian Mortality Information System, having the city of Rio de Janeiro as the unit of analysis. Excess mortality was estimated by the difference between the mean number of all expected deaths and the mean number of observed deaths, considering the 2015-2019 period. The quantile regression method was adjusted. The total value of cases above that expected by the historical series was estimated. Among all deaths, cases of COVID-19 and Influenza as underlying causes of death were selected. The ratio between excess mortality and deaths due to COVID-19 was calculated. RESULTS: We identified an excess of 31,920 deaths by the mean (increase of 26.8%). The regression pointed to 31,363 excess deaths. We found 33,401 deaths from COVID-19 and 176 deaths from Influenza. The ratio between the verified excess mortality and deaths due to COVID-19 was 0.96 by the mean and 0.95 by the regression. CONCLUSION: The study pointed to large excess deaths during the COVID-19 pandemic in the city of Rio de Janeiro distributed in waves, including the period of the Influenza outbreak.

Love and Infidelity: Causes and Consequences.

This is a narrative review addressing the topic of romantic infidelity, its causes and its consequences. Love is commonly a source of much pleasure and fulfillment. However, as this review points out, it can also cause stress, heartache and may even be traumatic in some circumstances. Infidelity, which is relatively common in Western culture, can damage a loving, romantic relationship to the point of its demise. However, by highlighting this phenomenon, its causes and its consequences, we hope to provide useful insight for both researchers and clinicians who may be assisting couples facing these issues. We begin by defining infidelity and illustrating the various ways in which one may become unfaithful to their partner. We explore the personal and relational factors that enhance an individual's tendency to betray their partner, the various reactions related to a discovered affair and the challenges related to the nosological categorization of infidelity-based trauma, and conclude by reviewing the effects of COVID-19 on unfaithful behavior, as well as clinical implications related to infidelity-based treatment. Ultimately, we hope to provide a road map, for academicians and clinicians alike, of what some couples may experience in their relationships and how can they be helped.

Towards a Better Understanding of the Complexities of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex condition arising in susceptible people, predominantly following viral infection, but also other stressful events. The susceptibility factors discussed here are both genetic and environmental although not well understood. While the dysfunctional physiology in ME/CFS is becoming clearer, understanding has been hampered by different combinations of symptoms in each affected person. A common core set of mainly neurological symptoms forms the modern clinical case definition, in the absence of an accessible molecular diagnostic test. This landscape has prompted interest in whether ME/CFS patients can be classified into a particular phenotype/subtype that might assist better management of their illness and suggest preferred therapeutic options. Currently, the same promising drugs, nutraceuticals, or behavioral therapies available can be beneficial, have no effect, or be detrimental to each individual patient. We have shown that individuals with the same disease profile exhibit unique molecular changes and physiological responses to stress, exercise and even vaccination. Key features of ME/CFS discussed here are the possible mechanisms determining the shift of an immune/inflammatory response from transient to chronic in ME/CFS, and how the brain and CNS manifests the neurological symptoms, likely with activation of its specific immune system and resulting neuroinflammation. The many cases of the post viral ME/CFS-like condition, Long COVID, following SARS-CoV-2 infection, and the intense research interest and investment in understanding this condition, provide exciting opportunities for the development of new therapeutics that will benefit ME/CFS patients.

Associations between mortality from COVID-19 and other causes: A state-level analysis.

BACKGROUND: During the COVID-19 pandemic, the high death toll from COVID-19 was accompanied by a rise in mortality from other causes of death. The objective of this study was to identify the relationship between mortality from COVID-19 and changes in mortality from specific causes of death by exploiting spatial variation in these relationships across US states. METHODS: We use cause-specific mortality data from CDC Wonder and population estimates from the US Census Bureau to examine relationships at the state level between mortality from COVID-19 and changes in mortality from other causes of death. We calculate age-standardized death rates (ASDR) for three age groups, nine underlying causes of death, and all 50 states and the District of Columbia between the first full year of the pandemic (March 2020-February 2021) and the year prior (March 2019-February 2020). We then estimate the relationship between changes in cause-specific ASDR and COVID-19 ASDR using linear regression analysis weighted by the size of the state's population. RESULTS: We estimate that causes of death other than COVID-19 represent 19.6% of the total mortality burden associated with COVID-19 during the first year of the COVID-19 pandemic. At ages 25+, circulatory disease accounted for 51.3% of this burden while dementia (16.4%), other respiratory diseases (12.4%), influenza/pneumonia (8.7%) and diabetes (8.6%) also contribute. In contrast, there was an inverse association across states between COVID-19 death rates and changes in death rates from cancer. We found no state-level association between COVID-19 mortality and rising mortality from external causes. CONCLUSIONS: States with unusually high death rates from COVID-19 experienced an even larger mortality burden than implied by those rates alone. Circulatory disease served as the most important route through which COVID-19 mortality affected death rates from other causes of death. Dementia and other respiratory diseases made the second and third largest contributions. In contrast, mortality from neoplasms tended to decline in states with the highest death rates from COVID-19. Such information may help to inform state-level responses aimed at easing the full mortality burden of the COVID-19 pandemic.

Neurological Manifestations and Clinical Outcomes of Patients with COVID-19 in the Aseer Region, Saudi Arabia.

COVID-19 patients also present with rheumatological problems, cardiac problems, and even neurological manifestations. However, the data are still insufficient at present to fill the gaps in our understanding of the neurological presentations of COVID-19. Therefore, the present study was undertaken to reveal the various neurological manifestations of patients with COVID-19 and to find the association between neurological manifestations and the clinical outcome. This cross-sectional study was conducted in Abha, in the Aseer region of the Kingdom of Saudi Arabia, among COVID-19 patients aged 18 years or older who were admitted with the neurological manifestations of COVID-19 to the Aseer Central Hospital and Heart Center Hospital Abha. Non-probability convenient sampling was used. All the information was gathered by the principal investigator using a questionnaire including sociodemographic information, disease characteristics of COVID-19, neurological manifestations, and other complications. Data were analyzed using the Statistical Package for Social Sciences, version 16.0 (SPSS, Inc., Chicago, IL, USA). A total of 55 patients were included in the present study. About half of the patients were admitted to the ICU, and 18 (62.1%) patients died after 1 month of follow-up. Patients aged over 60 years had a 75% mortality rate. About 66.66% of patients with pre-existing neurological disorders died. Statistically significant associations were found between neurological symptoms such as cranial nerve symptoms and a poor outcome. A statistically significant difference was also found between laboratory parameters such as the absolute neutrophil count (ANC), activated partial thromboplastin time (aPTT), total cholesterol (TC), creatinine, urea, and lactate dehydrogenase (LDH) level and the outcome. A statistically significant difference was also found between the use of medications such as antiplatelets, anticoagulants, and statins at the baseline and after a 1-month follow-up. Neurological symptoms and complications are not uncommon among COVID-19 patients. Most of these patients had poor outcomes. Further studies are required to provide more data and knowledge about this issue, including the possible risk factors and the long-term neurological consequences of COVID-19.

Modeling the enigma of complex disease etiology.

BACKGROUND: Complex diseases often present as a diagnosis riddle, further complicated by the combination of multiple phenotypes and diseases as features of other diseases. With the aim of enhancing the determination of key etiological factors, we developed and tested a complex disease model that encompasses diverse factors that in combination result in complex diseases. This model was developed to address the challenges of classifying complex diseases given the evolving nature of understanding of disease and interaction and contributions of genetic, environmental, and social factors. METHODS: Here we present a new approach for modeling complex diseases that integrates the multiple contributing genetic, epigenetic, environmental, host and social pathogenic effects causing disease. The model was developed to provide a guide for capturing diverse mechanisms of complex diseases. Assessment of disease drivers for asthma, diabetes and fetal alcohol syndrome tested the model. RESULTS: We provide a detailed rationale for a model representing the classification of complex disease using three test conditions of asthma, diabetes and fetal alcohol syndrome. Model assessment resulted in the reassessment of the three complex disease classifications and identified driving factors, thus improving the model. The model is robust and flexible to capture new information as the understanding of complex disease improves. CONCLUSIONS: The Human Disease Ontology's Complex Disease model offers a mechanism for defining more accurate disease classification as a tool for more precise clinical diagnosis. This broader representation of complex disease, therefore, has implications for clinicians and researchers who are tasked with creating evidence-based and consensus-based recommendations and for public health tracking of complex disease. The new model facilitates the comparison of etiological factors between complex, common and rare diseases and is available at the Human Disease Ontology website.

Highlights of the drug-induced liver injury literature for 2021.

INTRODUCTION: In 2021, over 3,000 articles on Drug-Induced Liver Injury (DILI) were published, nearly doubling the annual number compared to 2011. This review selected DILI articles from 2021 we felt held the greatest interest and clinical relevance. AREAS COVERED: A literature search was conducted using PubMed between 1 March 2021 and 28 February 2022. 86 articles were included. This review discusses new and established cases of hepatotoxins, including new FDA approvals and COVID-19 therapeutics. Developments in biomarkers and causality assessment methods are discussed. Updates from registries are also explored. EXPERT OPINION: DILI diagnosis and prognostication remain challenging. Roussel Uclaf Causality Assessment Method (RUCAM) is the best option for determining causality and has been increasingly accepted by clinicians. Revised Electronic Causality Assessment Method (RECAM) may be more user-friendly and accurate but requires further validation. Quantitative systems pharmacology methods, such as DILIsym, are increasingly used to predict hepatotoxicity. Oncotherapeutic agents represent many newly approved and described causes of DILI. Such hepatotoxicity is deemed acceptable relative to the benefit these drugs offer. Drugs developed for non-life-threatening disorders may not show a favorable benefit-to-risk ratio and will be more difficult to approve. As the COVID-19 landscape evolves, its effect on DILI deserves further investigation.

Analysis of the excess mortality and factors associated with deaths from COVID-19 versus other causes in Central Tuscany (Italy) in 2020.

OBJECTIVES: to assess the extent of the excess mortality from all causes in 2020 compared to 2015-2019 in Central Tuscany (Italy) as a proxy to estimate COVID-19-related excess mortality and to identify demographic and clinical differences between subjects who died from COVID-19 and those who died from other causes in 2020. DESIGN: descriptive analysis of the temporal trend of general mortality. SETTING AND PARTICIPANTS: the study population is represented by the 1.6 million residents living in the territory of the Central Tuscany Healthcare Authority in Central Italy, i.e., little less than half of the population of Tuscany, in an area of just over one fifth of the entire region, where the provinces of Florence, Pistoia, and Prato are comprised. MAIN OUTCOME MEASURES: using the Italian National Resident Population Registry (ANPR) as a source of mortality data, standardized mortality ratios with 95% confidence intervals were calculated to compare the number of deaths in 2020 with the number of deaths expected on the basis of mortality data from 2015 to 2019. Furthermore, after record linkage with data from the integrated surveillance of cases of SARS-CoV-2 virus infection and with the MaCro dataset of comorbidities, the characteristics of subjects who died from COVID-19 were compared with those of patients who died from other causes using a multivariate logistic regression model; odds ratios with 95% confidence intervals were calculated. RESULTS: a statistically significant excess mortality was observed during the first pandemic wave in March and April, and during the second wave in the fall; it ranged between +9% in March and +51% in November. On the contrary, in January, February, and May, all-cause mortality was significantly lower than in previous years. The male gender, dyslipidaemia, and dementia were positively associated with death from COVID-19 rather than from all other causes. On the contrary, heart failure and recent tumours were more represented among deaths from other causes. CONCLUSIONS: much of the over-mortality observed in spring is attributable to the harvesting effect COVID-19 exerted on a segment of population with serious underlying chronic conditions and who in the previous months had survived a mild winter and a flu season of medium intensity. In the second pandemic wave, in autumn, the impact of both direct and indirect effects of COVID-19 was substantially higher. Consistently with the available evidence, death from COVID-19 was related to the male gender and to clinical conditions such as dyslipidaemia and dementia.

Multivariate Pharma Technology Transfer Analysis: Civilization Diseases and COVID-19 Perspective.

The importance of studying civilization diseases manifests itself in the impact of changing lifestyles, on the number of deaths and causes of death. Technology transfer plays an important role in the prevention and treatment of these diseases. Through this, it is possible to transfer new treatments and diagnostics to clinics and hospitals more quickly and effectively, which leads to better healthcare for patients. Technology transfer can also aid in the development of new drugs and therapies that can be effective in the treatment of civilization diseases. The paper aims to evaluate the technology transfer process in the field of civilization diseases, using COVID-19 as an example of a pandemic that requires quick development and transfer of technology. To achieve the assumed goal, we propose a multivariate synthetic ratio in the field of civilization diseases (SMTT-Synthetic Measure of Technology Transfer) to analyze data from the Global Data database. We used sub-measures like SMTT_value (Synthetic Measure of Technology Transfer_value) and SMTT_quantity (Synthetic Measure of Technology Transfer_quantity) to measure technology transfer and put the data into a graph. Our analysis focuses on 14 diseases over a period of 10 years (2012-2021) and includes nine forms of technology transfer, allowing us to create a tool for analysing the process in multiple dimensions. Our results show that COVID-19 is similar in terms of technology transfer to diseases such as diabetes, cardiovascular diseases, neurodegenerative diseases, and breast cancer, even though data for COVID-19 is available for only 2 years.

[Advances in epidemiology, etiology, and treatment of community-acquired pneumonia].

Community-acquired pneumonia (CAP) is the third leading cause of death worldwide and one of the most commonly infectious diseases. Its epidemiological characteristics vary with host and immune status, and corresponding pathogen spectrums migrate over time and space distribution. Meanwhile, with the outbreak of COVID-19, some unconventional treatment strategies are on the rise. This article reviewed the epidemiological characteristics, pathogen spectrum and treatment direction of CAP in China over the years, and aimed to provide guidance for the diagnosis and treatment of CAP in clinical practice.

Predisposing, Enabling, and Reinforcing Factors of COVID-19 Prevention Behavior in Indonesia: A Mixed-methods Study.

OBJECTIVES: To prevent the spread of coronavirus disease 2019 (COVID-19), behaviors such as mask-wearing, social distancing, decreasing mobility, and avoiding crowds have been suggested, especially in high-risk countries such as Indonesia. Unfortunately, the level of compliance with those practices has been low. This study was conducted to determine the predisposing, enabling, and reinforcing factors of COVID-19 prevention behavior in Indonesia. METHODS: This cross-sectional study used a mixed-methods approach. The participants were 264 adults from 21 provinces in Indonesia recruited through convenience sampling. Data were collected using a Google Form and in-depth interviews. Statistical analysis included univariate, bivariate, and multivariate logistic regression. Furthermore, qualitative data analysis was done through content analysis and qualitative data management using Atlas.ti software. RESULTS: Overall, 44.32% of respondents were non-compliant with recommended COVID-19 prevention behaviors. In multivariate logistic regression analysis, low-to-medium education level, poor attitude, insufficient involvement of leaders, and insufficient regulation were also associated with decreased community compliance. Based on in-depth interviews with informants, the negligence of the Indonesian government in the initial stages of the COVID-19 pandemic may have contributed to the unpreparedness of the community to face the pandemic, as people were not aware of the importance of preventive practices. CONCLUSIONS: Education level is not the only factor influencing community compliance with recommended COVID-19 prevention behaviors. Changing attitudes through health promotion to increase public awareness and encouraging voluntary community participation through active risk communication are necessary. Regulations and role leaders are also required to improve COVID-19 prevention behavior.