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1.
Medicine (Baltimore) ; 101(9): e28976, 2022 Mar 04.
Article in English | MEDLINE | ID: covidwho-1730760

ABSTRACT

ABSTRACT: The Corona Virus Disease 2019 (COVID-19) pandemic has huge impacts on the world, including human health and economic decline. The COVID-19 has severe infectivity, especially the elderly with chronic diseases will cause various complications after infection and accelerate the disease process. In addition, COVID-19 will also affect their mental health. Therefore, the mental health of elderly patients with chronic diseases cannot be ignored. The aim of this study was to investigate the well-being level of elderly people with chronic disease during COVID-19 postpandemic period in Beijing and analysis related influencing factors, so as to provide a basis for improving the well-being level of elderly chronic patients during the postpandemic period.Elderly patients with chronic diseases who met the inclusion criteria in 5 different administrative regions in Beijing were selected to carry out a questionnaire survey. The contents of the questionnaire included general data, the Memorial University of Newfoundland Happiness scale and the awareness situation of the COVID-19 pandemic. A total of 500 questionnaires were distributed by WeChat and 486 valid questionnaires were collected. The t test and one-way analysis of variance were used to compare Memorial University of Newfoundland Happiness scores between 2 or more groups, multiple linear regression analysis was used to conduct multiple factor analysis to explore the related factors about well-being level of elderly chronic patients.A total of 109 cases (22.43%) were evaluated high well-being level, 319 cases (65.64%) were evaluated moderate well-being level and 58 cases (11.93%) were evaluated low well-being according to the Memorial University of Newfoundland Happiness (MUNSH) scores rating. The multiple linear regression indicated that the education level, number of chronic diseases, medical expenses, frequency of children's visits, taking care of grandchildren or not, and group activity frequency significantly affected the well-being of patients with chronic diseases during COVID-19 postpandemic period in Beijing (P < .05).Most elderly patients with chronic diseases had moderate or above sense of well-being during postpandemic period, but we should still pay attention to the mental health of those elderly chronic patients with low education level, much comorbidity, more medical expenses, less visits by children, not take care of grandchildren and never participate in group activities.


Subject(s)
COVID-19/epidemiology , Chronic Disease/epidemiology , Aged , Aged, 80 and over , Child , China/epidemiology , Health Status , Humans , Pandemics , SARS-CoV-2 , Surveys and Questionnaires
2.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-326541

ABSTRACT

We use Direct Coupling Analysis to determine epistatic interactions between loci of variability of the SARS-CoV-2 virus, segmenting genomes by month of sampling. We use full-length, high-quality genomes from the GISAID repository up to October 2021, in total over 3,500,000 genomes. We find that DCA terms are more stable over time than correlations, but nevertheless change over time as mutations disappear from the global population or reach fixation. We discuss the validity of a DCA analysis under these conditions in terms of a transient Quasi-Linkage Equilibrium state. We identify putative epistatic interaction mutations involving loci in Spike.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324960

ABSTRACT

We compute the allele frequencies of the alpha (B.1.1.7), beta (B.1.351) and delta (B.167.2) variants of SARS-CoV-2 from almost two million genome sequences on the GISAID repository. We find that the frequencies of a majority of the defining mutations in alpha rose towards the end of 2020 but drifted apart during spring 2021, a similar pattern being followed by delta during summer of 2021. For beta we find a more complex scenario with frequencies of some mutations rising and some remaining close to zero. Our results point to that what is generally reported as single variants is in fact a collection of variants with different genetic characteristics. For all three variants we further find some alleles with a clearly deviating time series.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324959

ABSTRACT

Genome-wide epistasis analysis is a powerful tool to infer gene interactions, which can guide drug and vaccine development and lead to a deeper understanding of microbial pathogenesis. We have considered all complete SARS-CoV-2 genomes deposited in the GISAID repository until \textbf{four} different cut-off dates, and used Direct Coupling Analysis together with an assumption of Quasi-Linkage Equilibrium to infer epistatic contributions to fitness from polymorphic loci. We find \textbf{eight} interactions, of which three between pairs where one locus lies in gene ORF3a, both loci holding non-synonymous mutations. We also find interactions between two loci in gene nsp13, both holding non-synonymous mutations, and four interactions involving one locus holding a synonymous mutation. Altogether we infer interactions between loci in viral genes ORF3a and nsp2, nsp12 and nsp6, between ORF8 and nsp4, and between loci in genes nsp2, nsp13 and nsp14. The paper opens the prospect to use prominent epistatically linked pairs as a starting point to search for combinatorial weaknesses of recombinant viral pathogens.

5.
World J Emerg Med ; 12(4): 287-292, 2021.
Article in English | MEDLINE | ID: covidwho-1579977

ABSTRACT

BACKGROUND: This study aims to compare the epidemiological, clinical and laboratory characteristics between patients with coronavirus disease (COVID-19) and influenza A (H1N1), and to develop a differentiating model and a simple scoring system. METHODS: We retrospectively analyzed the data from patients with COVID-19 and H1N1. The logistic regression model based on clinical and laboratory characteristics was constructed to distinguish COVID-19 from H1N1. Scores were assigned to each of independent discrimination factors based on their odds ratios. The performance of the prediction model and scoring system was assessed. RESULTS: A total of 236 patients were recruited, including 20 COVID-19 patients and 216 H1N1 patients. Logistic regression revealed that age >34 years, temperature ≤37.5 °C, no sputum or myalgia, lymphocyte ratio ≥20% and creatine kinase-myocardial band isoenzyme (CK-MB) >9.7 U/L were independent differentiating factors for COVID-19. The area under curves (AUCs) of the prediction model and scoring system in differentiating COVID-19 from H1N1 were 0.988 and 0.962, respectively. CONCLUSIONS: There are certain differences in clinical and laboratory features between patients with COVID-19 and H1N1. The simple scoring system may be a useful tool for the early identification of COVID-19 patients from H1N1 patients.

6.
Proc Natl Acad Sci U S A ; 117(49): 31519-31526, 2020 12 08.
Article in English | MEDLINE | ID: covidwho-933770

ABSTRACT

Genome-wide epistasis analysis is a powerful tool to infer gene interactions, which can guide drug and vaccine development and lead to deeper understanding of microbial pathogenesis. We have considered all complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes deposited in the Global Initiative on Sharing All Influenza Data (GISAID) repository until four different cutoff dates, and used direct coupling analysis together with an assumption of quasi-linkage equilibrium to infer epistatic contributions to fitness from polymorphic loci. We find eight interactions, of which three are between pairs where one locus lies in gene ORF3a, both loci holding nonsynonymous mutations. We also find interactions between two loci in gene nsp13, both holding nonsynonymous mutations, and four interactions involving one locus holding a synonymous mutation. Altogether, we infer interactions between loci in viral genes ORF3a and nsp2, nsp12, and nsp6, between ORF8 and nsp4, and between loci in genes nsp2, nsp13, and nsp14. The paper opens the prospect to use prominent epistatically linked pairs as a starting point to search for combinatorial weaknesses of recombinant viral pathogens.


Subject(s)
Epistasis, Genetic/genetics , Genes, Viral/genetics , SARS-CoV-2/genetics , COVID-19/pathology , Coronavirus Nucleocapsid Proteins/genetics , Coronavirus RNA-Dependent RNA Polymerase/genetics , Exoribonucleases/genetics , Genome, Viral/genetics , Humans , Methyltransferases/genetics , RNA Helicases/genetics , Selection, Genetic/genetics , Viral Nonstructural Proteins/genetics , Viral Proteins/genetics , Viroporin Proteins/genetics
7.
Eur J Med Res ; 25(1): 54, 2020 Nov 04.
Article in English | MEDLINE | ID: covidwho-910324

ABSTRACT

BACKGROUND: The novel coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is leading to a worldwide pandemic. Except representative manifestation of pneumonia and acute respiratory symptoms, COVID-19 patients have also shown different levels of liver injury or liver dysfunction. The aim of our study was to explore the probable clinical severity and mortality of COVID-19 patients and their liver dysfunction. METHOD: A combination of computer and manual retrieval was used to search in Medline through PubMed, EMBASE and Web of Science. Review Manager 5.3 software was used to examine the heterogeneity among the studies and to calculate the combined effect value (OR, 95CI). Subgroup analysis, sensitivity analysis, and publication bias test were also performed. RESULTS: We found a significant connection between liver dysfunction and mortality of COVID-19 patients with a pooled OR of 1.98 (95% CI 1.39-2.82; P = 0.0002). There was a significant association between AST and severity of COVID-19 with a pooled OR of 4.48 (95% CI 3.24-7.21; P < 0.001), and a pooled WMD of 3.35 (95% CI, 2.07 to 4.64; P < 0.001). In addition, there was a significant difference between TBIL and severity of COVID-19, with a pooled OR of 1.91 (95% CI 1.40-2.60; P < 0.001), and with a pooled WMD of 1.18 (95% CI, 0.78 to 1.58; P < 0.001). CONCLUSION: The mortality and severity of COVID-19 patients are significantly associated with liver dysfunction. The non-survivors and severe COVID-19 patients have elevated serum AST levels than the survivors and non-severe COVID-19 patients. The results of this study form a basis for better clinical liver management of patients with COVID-19.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Liver Diseases/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , COVID-19 , Comorbidity , Global Health , Humans , SARS-CoV-2 , Survival Rate/trends
8.
J Urol ; 204(5): 918-925, 2020 11.
Article in English | MEDLINE | ID: covidwho-659886

ABSTRACT

PURPOSE: The first case of coronavirus disease 2019 (COVID-19) was identified and confirmed in December 2019 in Wuhan, China. COVID-19 is gradually posing a serious threat to global public health. In this review the characteristics and mechanism of kidney injury caused by SARS-CoV, MERS-CoV and SARS-CoV-2 infection are summarized and contrasted. In particular, urine-oral transmission, prevention and management of the kidney injury caused by SARS-CoV-2 are emphasized. MATERIALS AND METHODS: We searched PubMed® for English language articles published since 2003 with the keywords "SARS," "MERS," "COVID-19" or "kidney injury." ClinicalTrials.gov was queried for ongoing studies. We also used relevant data from websites, including the Centers for Disease Control and Prevention and European Centre for Disease Prevention and Control. RESULTS: Similar to 2 other coronaviruses including SARS-CoV and MERS-CoV, SARS-CoV-2 caused severe respiratory syndrome with rapid progression and kidney injury. The infection process of SARS-CoV-2 is mediated by specifically binding to angiotensin-converting enzyme 2. Cases of COVID-19 combined with kidney impairment are associated with a higher risk of mortality than those without comorbidities. The pathological changes of the kidney are mainly due to local SARS-CoV-2 replication or indirectly by pro-inflammatory cytokine response. In addition, studies have confirmed the isolation of infectious SARS-CoV-2 in urine, raising the possibility of urine-oral transmission. Ultimately this is significant for preventing potential urine-oral transmission and improving the cure rate of acute kidney injury with COVID-19. CONCLUSIONS: Emerging evidence supports that in patients with SARS-CoV-2 infections the prevalence of kidney injury is high and usually leads to a poor prognosis. Optimal prevention and management of kidney injury will benefit patients with COVID-19.


Subject(s)
Acute Kidney Injury/epidemiology , Betacoronavirus/isolation & purification , Coronavirus Infections/epidemiology , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Severe Acute Respiratory Syndrome/epidemiology , Acute Kidney Injury/physiopathology , Acute Kidney Injury/therapy , Acute Kidney Injury/virology , COVID-19 , Coronavirus Infections/complications , Coronavirus Infections/physiopathology , Coronavirus Infections/transmission , Humans , Kidney , Pneumonia, Viral/complications , Pneumonia, Viral/physiopathology , Pneumonia, Viral/transmission , SARS-CoV-2 , Severe Acute Respiratory Syndrome/complications , Severe Acute Respiratory Syndrome/physiopathology
9.
Acta Diabetol ; 58(2): 139-144, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-613158

ABSTRACT

AIMS: Nowadays, the ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. Complications such as hypertension, diabetes, COPD, cardiovascular disease, and cerebrovascular disease are major risk factors for patients with COVID-19. METHODS: No meta-analysis has explored if or not diabetes related to mortality of patients with COVID-19. Therefore, this meta-analysis first aims to explore the possible clinical mortality between diabetes and COVID-19, analyze if diabetes patients infected with SARS-CoV-2 are exposed to the worst clinical prognostic risk, and to evaluate the reliability of the evidence. RESULTS: Our results showed a close relationship between diabetes and mortality of COVID-19, with a pooled OR of 1.75 (95% CI 1.31-2.36; P = 0.0002). The pooled data were calculated with the fixed effects model (FEM) as no heterogeneity appeared in the studies. Sensitivity analysis showed that after omitting any single study or converting a random effect model to FEM, the main results still held. CONCLUSIONS: Our meta-analysis showed that diabetes increases the mortality of patients with COVID-19. These results indicated the disturbance of blood glucose in the COVID-19 patients. More importantly, this meta-analysis grades the reliability of evidence for further basic and clinical research into the diabetes dysfunction in COVID-19 patients.


Subject(s)
COVID-19/mortality , Diabetes Complications/mortality , Diabetes Mellitus/mortality , Blood Glucose/physiology , COVID-19/epidemiology , COVID-19/pathology , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/mortality , Diabetes Mellitus/epidemiology , Humans , Hypertension/epidemiology , Hypertension/mortality , Pandemics , Reproducibility of Results , Risk Factors , SARS-CoV-2/physiology , Severity of Illness Index
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