ABSTRACT
BackgroundAcute and chronic alcohol abuse have adverse impacts on both the innate and adaptive immune response, which may result in reduced resistance to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and promote the progression of coronavirus disease 2019 (COVID-19). However, there are no large population-based data evaluating potential causal associations between alcohol consumption and COVID-19. MethodWe conducted a Mendelian randomization study using data from UK Biobank to explore the association between alcohol consumption and risk of SARS-CoV-2 infection and serious clinical outcomes in patients with COVID-19. A total of 12,937 participants aged 50-83 who tested for SARS-CoV-2 between 16 March to 27 July 2020 (12.1% tested positive) were included in the analysis. The exposure factor was alcohol consumption. Main outcomes were SARS-CoV-2 positivity and death in COVID-19 patients. We generated weighted and unweighted allele scores using three genetic variants (rs1229984, rs1260326, and rs13107325) and applied the allele scores as the instrumental variables to assess the effect of alcohol consumption on outcomes. Analyses were conducted separately for white participates with and without obesity. ResultsOf the 12,937 participants, 4,496 were never or infrequent drinkers and 8,441 were frequent drinkers. (including 1,156 light drinkers, 3,795 moderate drinkers, and 3,490 heavy drinkers). Both logistic regression and Mendelian randomization analyses found no evidence that alcohol consumption was associated with risk of SARS-CoV-2 infection in participants either with (OR=0.963, 95%CI 0.800-1.159; q =1.000) or without obesity (OR=0.891, 95%CI 0.755-1.053; q =.319). However, frequent drinking (HR=1.565, 95%CI 1.012-2.419; q =.079), especially heavy drinking (HR=2.071, 95%CI 1.235-3.472; q =.054), was associated with higher risk of death in patients with obesity and COVID-19, but not in patients without obesity. Notably, the risk of death in frequent drinkers with obesity increased slightly with the average amount of alcohol consumed weekly (HR=1.480, 95%CI 1.059-2.069; q =.099). ConclusionsOur findings suggested alcohol consumption may had adverse effects on the progression of COVID-19 in white participants with obesity, but was not associate with susceptibility to SARS-CoV-2 infection.
Subject(s)
COVID-19ABSTRACT
Background. Risk scores are urgently needed to assist clinicians in predicting the risk of death in severe patients with SARS-CoV-2 infection in the context of millions of people infected, rapid disease progression, and shortage of medical resources.Method. A total of 139 severe patients with SARS-CoV-2 from China and Iran were included. Using data from China (training dataset, n = 96), prediction models were developed based on logistic regression models, nomogram and risk scoring system for simplification. Leave-one-out cross validation was used for internal validation and data from Iran (test dataset, n = 43) for external validation. Results. The NSL model (Area under the curve (AUC) 0.932) and NL model (AUC 0.903) were developed based on neutrophil percentage (NE), lactate dehydrogenase (LDH) with or without oxygen saturation (SaO2) using the training dataset. Compared with the training dataset, the predictability of NSL model (AUC 0.910) and NL model (AUC 0.871) were similar in the test dataset. The risk scoring systems corresponding to these two models were established for clinical application. The AUCs of the NSL and NL scores were 0.928 and 0.901 in the training dataset, respectively. At the optimal cut-off value of NSL score, the sensitivity was 94% and specificity was 82%. In addition, for NL score, the sensitivity and specificity were 94% and 75%, respectively.Conclusion. NSL and NL score are straightforward means for clinicians to predict the risk of death in severe patients. NL score could be used in selected regions where patients’ SaO2 cannot be tested.
Subject(s)
COVID-19ABSTRACT
Objectives : A pneumonia associated with 2019 novel coronavirus (2019-nCoV, subsequently named SARS-CoV2) emerged worldwide since December, 2019. We aimed to describe the epidemiological characteristics of 2019 coronavirus disease (COVID-19) in Shaanxi province of China. Results: 1. Among the 245 patients, 132 (53.9%) were males and 113 (46.1%) were females. The average age was 46.15±16.43 years, ranging from 3 to 89 years. 2. For the clinical type, 1.63% (4/245) patients were mild type , 84.90% (208/245) were moderate type, 7.76% (19/245) were severe type, 5.31% (13/245) were critical type and only 0.41% (1/245) was asymptomatic. 3. Of the 245 patients, 116 (47.35%) were input case, 114 (46.53%) were non-input case , and 15 (6.12%) were unknown exposure. 4. 48.57% (119/245) cases were family cluster , involving 42 families. The most common pattern of COVID-19 family cluster was between husband and wife or between parents and children.