Odds Of Coronavirus Disease 2019 Research Articles

The genetic associations of COVID-19 on genitourinary symptoms.

Recently emerged reports indicated that patients with coronavirus disease 2019 (COVID-19) might experience novo genitourinary symptoms after discharge. Nevertheless, the causal associations and underlying mechanisms remain largely unclear. Genome-wide association study (GWAS) statistics for COVID-19 and 28 genitourinary symptoms with consistent definitions were collected from the COVID-19 Host Genetic Initiative, FinnGen, and UK Biobanks. Mendelian randomization (MR) analyses were applied to explore the causal effects of COVID-19 on genitourinary symptoms by selecting single-nucleotide polymorphisms as instrumental variables. Meta-analyses were conducted to evaluate the combined causal effect. Molecular pathways connecting COVID-19 and its associated disorders were evaluated by weighted gene co-expression network analysis (WGCNA) and enrichment analyses to extract insights into the potential mechanisms underlying the connection. The MR and meta-analyses indicated that COVID-19 was causally associated with increased risk for calculus of the lower urinary tract (LUTC, OR: 1.2984 per doubling in odds of COVID-19, 95% CI: 1.0752-1.5680, p = 0.007) and sexual dysfunction (SD, OR: 1.0931, 95% CI: 1.0292-1.1610, p = 0.004). Intriguingly, COVID-19 might exert a slight causal protective effect on the progression of urinary tract infections (UTIs) and bladder cancer (BLCA). These results were robust to sensitivity analyses. Bioinformatic analyses indicated that the inflammatory-immune response module may mediate the links between COVID-19 and its associated disorders at the molecular level. In response to post-COVID-19 symptoms, we recommend that COVID-19 patients should strengthen the prevention of LUTC and the monitoring of sexual function. Meanwhile, the positive effects of COVID-19 on UTIs and BLCA should attach equal importance.

Influenza vaccine during the 2019-2020 season and COVID-19 risk: A case-control study in Québec.

We carried out a case-control study that examined whether receipt of the inactivated influenza vaccine during the 2019-2020 season impacted on the risk of coronavirus disease 2019 (COVID-19), as there was a concern that the vaccine could be detrimental through viral interference. A total of 920 cases with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (diagnosed between March and October 2020) and 2,123 uninfected controls were recruited from those who were born in Québec between 1956 and 1976 and who had received diagnostic services at two hospitals (Montréal and Sherbrooke, Québec). After obtaining consent, a questionnaire was administered by phone. Data were analyzed by logistic regression. Among healthcare workers, inactivated influenza vaccine received during the previous influenza season was not associated with increased COVID-19 risk (AOR: 0.99, 95% CI: 0.69-1.41). Among participants who were not healthcare workers, influenza vaccination was associated with lower odds of COVID-19 (AOR: 0.73, 95% CI 0.56-0.96). We found no evidence that seasonal influenza vaccine increased the risk of developing COVID-19.

Differentiating coronavirus disease 2019 (COVID-19) from influenza and dengue

The novel coronavirus disease 2019 (COVID-19) presents with non-specific clinical features. This may result in misdiagnosis or delayed diagnosis, and lead to further transmission in the community. We aimed to derive early predictors to differentiate COVID-19 from influenza and dengue. The study comprised 126 patients with COVID-19, 171 with influenza and 180 with dengue, who presented within 5 days of symptom onset. All cases were confirmed by reverse transcriptase polymerase chain reaction tests. We used logistic regression models to identify demographics, clinical characteristics and laboratory markers in classifying COVID-19 versus influenza, and COVID-19 versus dengue. The performance of each model was evaluated using receiver operating characteristic (ROC) curves. Shortness of breath was the strongest predictor in the models for differentiating between COVID-19 and influenza, followed by diarrhoea. Higher lymphocyte count was predictive of COVID-19 versus influenza and versus dengue. In the model for differentiating between COVID-19 and dengue, patients with cough and higher platelet count were at increased odds of COVID-19, while headache, joint pain, skin rash and vomiting/nausea were indicative of dengue. The cross-validated area under the ROC curve for all four models was above 0.85. Clinical features and simple laboratory markers for differentiating COVID-19 from influenza and dengue are identified in this study which can be used by primary care physicians in resource limited settings to determine if further investigations or referrals would be required.

COVID-19 Among US Dialysis Patients: Risk Factors and Outcomes From a National Dialysis Provider

Rationale & ObjectiveDuring the coronavirus disease 2019 (COVID-19) pandemic, patients receiving maintenance dialysis are a highly vulnerable population due to their comorbidities and circumstances that limit physical distancing during treatment. This study sought to characterize the risk factors for and outcomes following COVID-19 in this population.Study DesignRetrospective cohort study.Setting & ParticipantsMaintenance dialysis patients in clinics of a midsize national dialysis provider that had at least 1 patient who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from February to June 2020.PredictorsDemographics, dialysis characteristics, residence in a congregated setting, comorbid conditions, measurements of frailty, and use of selected medications.OutcomesCOVID-19, defined as having a positive SARS-CoV-2 test result, and all-cause mortality among those with COVID-19.Analytical ApproachLogistic regression analyses conducted to identify clinical characteristics associated with COVID-19 and risk factors associated with mortality among patients following COVID-19.Results438 of 7948 (5.5%) maintenance dialysis patients developed COVID-19. Male sex, Black race, in-center dialysis (vs home dialysis), treatment at an urban clinic, residence in a congregate setting, and greater comorbidity were associated with contracting COVID-19. Odds of COVID-19 were 17-fold higher for those residing in a congregated setting (odds ratio [OR], 17.10 [95% CI, 13.51-21.54]). Of the 438 maintenance dialysis patients with COVID-19, 109 (24.9%) died. Older age, heart disease, and markers of frailty were associated with mortality.LimitationsNo distinction was detected between symptomatic and asymptomatic SARS-CoV-2 positivity, with asymptomatic screening limited by testing capacity during this initial COVID-19 surge period.ConclusionsCOVID-19 is common among patients receiving maintenance dialysis, particularly those residing in congregate settings. Among maintenance dialysis patients with COVID-19, mortality is high, exceeding 20%.