ABSTRACT
BACKGROUND: Many studies investigated the association between air pollution and Covid-19 severity but the only study focusing on patients with Multiple Sclerosis (MS) exclusively evaluated exposure to PM2.5. We aim to study, in a sample of MS patients, the impact of long-term exposure to PM2.5, PM10 and NO2 on Covid-19 severity, described as occurrence of pneumonia. METHODS: A 1:2 ratio case-control study was designed, differentiating cases and controls based on Covid-19 pneumonia. Associations between pollutants and outcome were studied using logistic regression. Weighted quantile sum (WQS) logistic regression was used to identify the individual contribution of each pollutant within the mixture; Least Absolute Shrinkage and Selection Operator (LASSO) penalized regression was performed to confirm the variable selection from WQS. All the analyses were adjusted for confounders selected a priori. RESULTS: Of the 615 eligible patients, 491 patients provided detailed place of exposure and were included in the principal analysis. Higher concentrations of air pollutants were associated with increased odds of developing Covid-19 pneumonia (PM2.5: 3rd vs 1st tercile OR(95% CI)=2.26(1.29;3.96); PM10: 3rd vs 1st tercile OR(95% CI)=2.12(1.22;3.68); NO2: 3rd vs 1st tercile OR(95% CI)=2.12(1.21;3.69)). Pollutants were highly correlated with each other; WQS index was associated to an increased risk of pneumonia (ß=0.44; p-value=0.004) and the main contributors to this association were NO2 (41%) and PM2.5 (34%). Consistently, Lasso method selected PM2.5 and NO2. CONCLUSIONS: Higher long-term exposure to PM2.5, PM10 and NO2 increased the odds of Covid-19 pneumonia among MS patients and the most dangerous pollutants were NO2 and PM2.5.
ABSTRACT
The aim of this study is to explore risk factors for in-hospital mortality and describe the effectiveness of different treatment strategies of 205 laboratory-confirmed cases infected with SARS-CoV-2 during the Lombardy outbreak. All patients received the best supportive care and specific interventions that included the main drugs being tested for repurposing to treat COVID-19, such as hydroxychloroquine, anticoagulation and antiviral drugs, steroids, and interleukin-6 pathway inhibitors. Clinical, laboratory, and treatment characteristics were analyzed with univariate and multivariate logistic regression methods to explore their impact on in-hospital mortality. Univariate analyses showed prognostic significance for age greater than 70 years, the presence of two or more relevant comorbidities, a P/F ratio less than 200 at presentation, elevated LDH (lactate dehydrogenase) and CRP (C-reactive protein) values, intermediate- or therapeutic-dose anticoagulation, hydroxychloroquine, early antiviral therapy with lopinavir/ritonavir, short courses of steroids, and tocilizumab therapy. Multivariable regression confirmed increasing odds of in-hospital death associated with age older than 70 years (OR 3.26) and a reduction in mortality for patients treated with anticoagulant (-0.37), antiviral lopinavir/ritonavir (-1.22), or steroid (-0.59) therapy. In contrast, hydroxychloroquine and tocilizumab have not been confirmed to have a significant effect in the treatment of SARS-CoV-2 pneumonia. Results from this real-life single-center experience are in agreement and confirm actual literature data on SARS-CoV-2 pneumonia in terms of both clinical risk factors for in-hospital mortality and the effectiveness of the different therapies proposed for the management of COVID19 disease.