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The male reproductive health depends on several factors that can be divided into two main groups: the first group, genetic or hereditary (in particular, klinefelter syndrome, etc.), the second acquired factors that depend on the person's lifestyle (bad habits, diet), stress, infectious diseases of the genitourinary system, etc. The presence of infectious and inflammatory diseases of the male reproductive system leads to impaired reproductive and endocrine function, significantly reducing the reproductive potential. In the last three years of our time around the world, including Russia, the number of people who have become ill with a new viral infection (cOVID-19) caused by the new coronavirus (SARS-coV-2), which causes dysfunction and has a negative effect on many organs and organs, body systems. The overview of recent publications is devoted to the study of the effect of SARS-coV-2 on the reproductive health of men. The search was performed using the Medline, PubMed, and EMBASE databases.
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Background: Knowing the prevalence of true asymptomatic coronavirus disease 2019 (COVID-19) cases is critical for designing mitigation measures against the pandemic. We aimed to synthesize all available research on asymptomatic cases and transmission rates. Methods: We searched PubMed, Embase, Cochrane COVID-19 trials, and Europe PMC for primary studies on asymptomatic prevalence in which (1) the sample frame includes at-risk populations, and;(2) follow-up was sufficient to identify pre-symptomatic cases. Meta-analysis used fixed-effects and random-effects models. We assessed risk of bias by combination of questions adapted from risk of bias tools for prevalence and diagnostic accuracy studies. Results: We screened 2,454 articles and included 13 low risk-of-bias studies from seven countries that tested 21,708 at-risk people, of which 663 were positive and 111 asymptomatic. Diagnosis in all studies was confirmed using a real-time reverse transcriptase–polymerase chain reaction test. The asymptomatic proportion ranged from 4% to 41%. Meta-analysis (fixed effects) found that the proportion of asymptomatic cases was 17% (95% CI 14% to 20%) overall and higher in aged care (20%;95% CI 14% to 27%) than in non-aged care (16%;95% CI 13% to 20%). The relative risk (RR) of asymptomatic transmission was 42% lower than that for symptomatic transmission (combined RR 0.58;95% CI 0.34 to 0.99, p = 0.047). Conclusions: Our one-in-six estimate of the prevalence of asymptomatic COVID-19 cases and asymptomatic transmission rates is lower than those of many highly publicized studies but still sufficient to warrant policy attention. Further robust epidemiological evidence is urgently needed, including in subpopulations such as children, to better understand how asymptomatic cases contribute to the pandemic.
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Propose: Due to severe acute respiratory syndrome coronavirus 2(SARS-CoV- 2), novel coronavirus pneumonia (COVID-19) is a systemic viral disease that mostly affects the respiratory tract. Studies have shown that COVID-19 may increase the risk of autoantibody development in patients with connective tissue diseases (CTD) .However, data regarding the impact of COVID-19 pandemic on patients with CTD and drug use were relatively scarce. The prevalence of COVID-19 in CTD patients was estimated by means of meta-analysis, and the effect of the use of anti-rheumatic drugs on the clinical outcome of CTD patients with COVID-19 was investigated. Method(s): Cross-sectional investigations and case series on CTD and COVID-19 published by CBM, CNKI, China Science and Technology Journal Database, Wan Fang Data, PubMed, Embase, Web of Science, Cochrane Library and Medline from its establishment to April 5, 2022 were searched. A random effects model was used to pool data. Heterogeneity and risk of bias was examined with I-squared index (I2) statistic. Inconsistency was evaluated with the I2. Egger tests were used for the evaluation of potential publication bias (STATA v.12.0). Result(s): A total 11 studies involving 75908 participants were included in the meta-analysis (Table 1). The overall prevalence of COVID-19 among CTD patients was 3.3% (95%CI: 2.3%-4.3%) (Figure 1A), the hospitalization rate was 17.6% (95%CI: 7.5%-27.6%;Figure 1B), with the rate of 4.4% (95%CI: 2.8%-6.0%;Figure 1C)in ICU admission, and the mortality rate was 4.5% (95%CI: 2.5%-6.4%;igure 1D). Six of the studies included patients who used hydroxychloroquine as part of their treatment regimen, with 15.5% (95%CI: 5.6%-25.3%) adverse outcome rates (Figure 1E). Conclusion(s): Patients with CTD had a higher risk of COVID-19. Hydroxychloroquine might increase adverse outcome rate of COVID-19.
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Purpose: Novel Coronavirus pneumonia 2019 (COVID-19) caused by the novel coronavirus severe acute respiratory syndrome (SARS) coronavirus- 2 (CoV-2) is a highly contagious infection with high morbidity and mortality1. Patients with systemic lupus erythematosus (SLE) are considered to be susceptible to coronavirus due to impaired immune function2. This study aims to systematically evaluate the prevalence of COVID-19 in SLE patients, and futher explore the impact of antirheumatic drug on the clinical outcome of COVID-19 in SLE patients. Method(s): Systematic searches of PubMed, EMBASE, Web of Science, the Cochrane Library and Medline, CNKI, CBM, China Science and Technology Journal Database and Wan Fang Data were performed. Cross-sectional investigations and case series on SLE and COVID-19 were included. Random effects model was used to pool data. Heterogeneity and risk of bias was examined with I squared index (I2) statistic and Egger tests were used for the evaluation of potential publication bias (STATA v.12.0). Result(s): A total of 14 studies comprising 5115 SLE patients and 698 COVID-19 patients were identified. Overall prevalence of COVID-19 in SLE patients was 6.7% (95%CI: 4.4-9.1%). The hospitalization rate was 31.6% (95%CI: 15.8%-47.3%), with the rate of 22.2% (95%CI: 6.2-38.2%) of patients were admitted to ICU, and the death rate was 19.3% (95%CI: 2.7%-35.9%). Eight of the studies included patients who used hydroxychloroquine as part of their treatment regimen, with 5.7% (95%CI: 3.3%-8.0%) prevalence rate. The hospitalisation rates for SLE patients with COVID-19 infection who received glucocorticoid was 69.2% (95%CI: 46.8%-91.6%). The rates of hospitalisation in patients who received hydroxychloroquine was 59.2% (95%CI: 45.8%-72.6%), and in patients who received biologic disease-modifying anti-rheumatic drugs (b-DMARD) was 61.8% (95%CI: 32.7%-90.9%). The adverse outcome rate due to COVID-19 in patients with SLE was 34.1% (95% CI: 4.3%-64%). The rate of adverse outcome in SLE patients diagnosed with COVID-19 who received glucocorticoid was 22.9% (95%CI: 9%-31.5%), and in patients who received hydroxychloroquine was 22.9% (95%CI: 0.1%-45.7%, Figure 1). Conclusion(s): Patients with SLE had a higher risk of COVID-19. Anti-rheumatic drugs may help reduce the prevalence and overall rate of adverse outcomes of COVID-19. Figure 1.
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Purpose: The pandemic of novel coronavirus disease 2019 (COVID-19) caused by the emerging severe acute respiratory syndrome coronavirus 2 (sars-cov- 2) has become a global health crisis (WHO, 2020b), leading to large number of infections and deaths. Autoimmune rheumatic diseases (ARD) are characterized by immune dysfunction and more susceptible to infection. The prevalence of COVID-19 in ARD patients was estimated by means of meta-analysis, and the effect of the use of anti-rheumatic drugs on the clinical outcome of ARD patients with COVID-19 was investigated. Method(s): Cross-sectional investigations and case series on ARD and COVID-19 published by CBM, CNKI, China Science and Technology Journal Database, Wan Fang Data, PubMed, Embase, Web of Science, Cochrane Library and Medline from its establishment to June 26, 2022 were searched. Random effects model was used to pool data. Heterogeneity and risk of bias was examined with I-squared index (I2) statistic. Egger tests were used for the evaluation of potential publication bias (STATA v.12.0). Result(s): A total of 65 studies comprising 135 515 patients were identified. Overall prevalence of COVID-19 in ARD patients was 5.4% (95%CI: 4.3%-6.5%). The hospitalisation rate due to COVID-19 was 35.9% (95% CI: 28.3%-43.4%). The hospitalisation rates for ARD patients diagnosed with COVID-19 who received glucocorticoid was 35.9% (95%CI: 31.4%-40.4%). The rates of hospitalisation in patients who received hydroxychloroquine was 39.9% (95%CI: 34.5%-45.3%), and in patients who received biologic disease-modifying anti-rheumatic drugs (b-DMARD) was 38.1% (95%CI: 33.6%-42.5%), which were both higher than total hospitalisation. The mortality due to COVID-19 in patients with ARD was 6.0% (95% CI: 5.1%-6.8%). The mortality in ARD patients diagnosed with COVID-19 who received glucocorticoid was 5.3% (95%CI: 4.3%-6.2%), and in patients who received b-DMARD was 5.8% (95%CI: 4.9%-6.7%). Mortality rates for patients who received hydroxychloroquine was 5.2% (95%CI: 4.2%-6.2%) (Figure 1). Conclusion(s): Patients with ARD had a higher risk of COVID-19. Use of glucocorticoids decrease mortality in these patients suffered from COVID-19 infection. Though patients had a higher hospitalisation rates but lower mortality among patients prescribed b-DMARD or hydroxychloroquine. (Figure Presented).
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Background: The Coronavirus pandemic has impact on our community far beyond the acute phase, "Long COVID-19" is recognized as a new medical entity and resembles "fibromyalgia" which, likewise, lacks a clear mechanism. "Fibromyalgia" is a prevalent and misunderstood condition with significant burden and morbidity. "Central sensitization" and biopsychosocial theories describe "fibromyalgia" as the misfortunate neurological fate of traumatized and stressed individuals that have behavioral, cognitive, social, and/or genetic predisposition for an "infinite-positive- feedback of pain with no peripheral organic lesion/injury". Diagnostic criteria seem biologically arbitrary, treatments are insufficient, and physicians are frustrated. This work suggests a theoretical model with an organic mechanical mechanism to help explain "fibromyalgia", "long COVID-19" and "functional psycho/ somatic syndromes", based on cross-disciplinary empirical studies. A practical evidence-based treatment arsenal, which is derived from this model, is discussed briefly. Method(s): Systematically searched multiple phrases in MEDLINE, EMBASE, COCHRANE, PEDro, and medRxiv, majority with no time limit. Inclusion/exclusion based on title and , then full-text inspection. Additional literature added on relevant side topics. Review follows PRISMA-ScR guidelines. Result(s): 831 records included. The theory of "facial-armoring" suggests fibromyalgia-like entities may be a disease of connective-tissue driven by myofibroblast-generated- tensegrity- tension. This mechanism may explain fibromyalgia's pain, distribution of pain, decreased pressure-pain threshold, tender spots, fatigue, cardiovascular and metabolic abnormalities, autonomic abnormalities, absence of clear inflammation, silent imaging investigations, and other phenomena (e.g., complete resolution soon after surgery). "Long-COVID- 19" is predicted to involve fascial armoring. Conclusion(s): "Fibromyalgia" is a mild-moderate- chronic- compartment- like- syndrome- of- the- whole- body. Treatment should focus on lifestyle and non-pharmacological modalities. Early detection is key. The body and the mind are one being.
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Background: The coronavirus, COVID-19, has caused a global pandemic of an unprecedented scale. The efficacy of antivirals and other drugs, considered for repurposing, is assessed in clinical trials. It is not clear, however, whether these treatments, when available, will be cost effective. Purpose(s): To systematically review published economic evaluations of antivirals for the management of pandemic influenza. Method(s): The following databases were searched from inception to 26 March 2020: Medline (EBSCO HOST), EMBASE (OVID), EconLit (OVID), NHS EED (OVID) and HTA (OVID). Citation tracking and reference checking were also used. Only full economic evaluations published in the last ten years were included. Studies were quality assessed using NICE economic evaluation checklist. Data were extracted into standard data extraction tables and narratively summarised. Result(s): Of 709 records identified, 14 studies were included. These were mostly conducted in high income countries. They were seven (50.0%) cost-utility analyses, four (28.6%) cost-effectiveness analyses, two (14.3%) cost-consequences analyses, and one (7.1%) cost-benefit analysis. Antiviral treatment-containing strategies were found to be either cost saving or cost effective. Empirical treatment was more cost effective than test-guided treatment for young adults but less for older adults. Infection rate, prevalence, antiviral efficacy and costs were the key drivers of cost effectiveness Conclusion(s): Antiviral treatment for managing pandemic influenza viruses that have high case fatality rate, similar to the COVID-19 pandemic, has shown to be cost effective, either as standalone intervention or part of a multifaceted strategy.
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Artificial intelligence (AI) refers to the simulation of human intelligence in machines, using machine learning (ML), deep learning (DL) and neural networks (NNs). AI enables machines to learn from experience and perform human-like tasks. The field of AI research has been developing fast over the past five to ten years, due to the rise of 'big data' and increasing computing power. In the medical area, AI can be used to improve diagnosis, prognosis, treatment, surgery, drug discovery, or for other applications. Therefore, both academia and industry are investing a lot in AI. This review investigates the biomedical literature (in the PubMed and Embase databases) by looking at bibliographical data, observing trends over time and occurrences of keywords. Some observations are made: AI has been growing exponentially over the past few years; it is used mostly for diagnosis; COVID-19 is already in the top-3 of diseases studied using AI; China, the United States, South Korea, the United Kingdom and Canada are publishing the most articles in AI research; Stanford University is the world's leading university in AI research; and convolutional NNs are by far the most popular DL algorithms at this moment. These trends could be studied in more detail, by studying more literature databases or by including patent databases. More advanced analyses could be used to predict in which direction AI will develop over the coming years. The expectation is that AI will keep on growing, in spite of stricter privacy laws, more need for standardization, bias in the data, and the need for building trust.