Effect of statin therapy on SARS-CoV-2 infection-related mortality in hospitalized patients.

AIM: Assessing the effect of statin therapy (ST) at hospital admission for COVID-19 on in-hospital mortality. METHODS AND RESULTS: Retrospective observational study. Patients taking statins were 11 years older and had significantly more comorbidities than patients who were not taking statins. A genetic matching (GM) procedure was performed prior to analysis of the mortality risk. A Cox proportional hazards model was used for the cause-specific hazard (CSH) function, and a competing-risks Fine and Gray (FG) model was also used to study the direct effects of statins on risk. Data from reverse transcription-polymerase chain reaction-confirmed 2157 SARS-CoV-2-infected patients [1234 men, 923 women; age: 67 y/o (IQR 54-78)] admitted to the hospital were retrieved from the clinical records in anonymized manner. Three hundred and fifty-three deaths occurred. Five hundred and eighty-one patients were taking statins. Univariate test after GM showed a significantly lower mortality rate in patients on ST than the matched non-statin group (19.8% vs. 25.4%, χ2 with Yates continuity correction: P = 0.027). The mortality rate was even lower in patients (n = 336) who maintained their statin treatments during hospitalization compared with the GM non-statin group (17.4%; P = 0.045). The Cox model applied to the CSH function [HR = 0.58(CI: 0.39-0.89); P = 0.01] and the competing-risks FG model [HR = 0.60 (CI: 0.39-0.92); P = 0.02] suggest that statins are associated with reduced COVID-19-related mortality. CONCLUSIONS: A lower SARS-CoV-2 infection-related mortality was observed in patients treated with ST prior to hospitalization. Statin therapy should not be discontinued due to the global concern of the pandemic or in patients hospitalized for COVID-19.

Long-term exposure to PM10 above WHO guidelines exacerbates COVID-19 severity and mortality.

BACKGROUND: Age, sex, race and comorbidities are insufficient to explain why some individuals remain asymptomatic after SARS-CoV-2 infection, while others die. In this sense, the increased risk caused by the long-term exposure to air pollution is being investigated to understand the high heterogeneity of the COVID-19 infection course. OBJECTIVES: We aimed to assess the underlying effect of long-term exposure to NO2 and PM10 on the severity and mortality of COVID-19. METHODS: A retrospective observational study was conducted with 2112 patients suffering COVID-19 infection. We built two sets of multivariate predictive models to assess the relationship between the long-term exposure to NO2 and PM10 and COVID-19 outcome. First, the probability of either death or severe COVID-19 outcome was predicted as a function of all the clinical variables together with the pollutants exposure by means of two regularized logistic regressions. Subsequently, two regularized linear regressions were constructed to predict the percentage of dead or severe patients. Finally, odds ratios and effects estimates were calculated. RESULTS: We found that the long-term exposure to PM10 is a more important variable than some already stated comorbidities (i.e.: COPD/Asthma, diabetes, obesity) in the prediction of COVID-19 severity and mortality. PM10 showed the highest effects estimates (1.65, 95% CI 1.32-2.06) on COVID-19 severity. For mortality, the highest effect estimates corresponded to age (3.59, 95% CI 2.94-4.40), followed by PM10 (2.37, 95% CI 1.71-3.32). Finally, an increase of 1 µg/m3 in PM10 concentration causes an increase of 3.06% (95% CI 1.11%-4.25%) of patients suffering COVID-19 as a severe disease and an increase of 2.68% (95% CI 0.53%-5.58%) of deaths. DISCUSSION: These results demonstrate that long-term PM10 burdens above WHO guidelines exacerbate COVID-19 health outcomes. Hence, WHO guidelines, the air quality standard established by the Directive 2008/50/EU, and that of the US-EPA should be updated accordingly to protect human health.

Low HDL and high triglycerides predict COVID-19 severity.

Lipids are indispensable in the SARS-CoV-2 infection process. The clinical significance of plasma lipid profile during COVID-19 has not been rigorously evaluated. We aim to ascertain the association of the plasma lipid profile with SARS-CoV-2 infection clinical evolution. Observational cross-sectional study including 1411 hospitalized patients with COVID-19 and an available standard lipid profile prior (n: 1305) or during hospitalization (n: 297). The usefulness of serum total, LDL, non-HDL and HDL cholesterol to predict the COVID-19 prognosis (severe vs mild) was analysed. Patients with severe COVID-19 evolution had lower HDL cholesterol and higher triglyceride levels before the infection. The lipid profile measured during hospitalization also showed that a severe outcome was associated with lower HDL cholesterol levels and higher triglycerides. HDL cholesterol and triglyceride concentrations were correlated with ferritin and D-dimer levels but not with CRP levels. The presence of atherogenic dyslipidaemia during the infection was strongly and independently associated with a worse COVID-19 infection prognosis. The low HDL cholesterol and high triglyceride concentrations measured before or during hospitalization are strong predictors of a severe course of the disease. The lipid profile should be considered as a sensitive marker of inflammation and should be measured in patients with COVID-19.

High-density lipoprotein concentrations relate to the clinical course of HIV viral load in patients undergoing antiretroviral therapy.

OBJECTIVE: To determine whether levels of HDL are associated with viral load response in HIV-treated patients, and to seek an explanation based on amino acid sequence similarity between the key apolipoprotein A1 and HIV proteins concerned in viral replication. DESIGN: The major HDL lipoprotein is apolipoprotein A1, which is able to inhibit HIV-induced syncytium formation. This retrospective clinical study assessed the relationship between the response to antiretroviral treatment (time of undetectable viral load/duration of viral suppression below the limit of detection) and HDL-cholesterol levels on commencing antiretroviral treatment. PATIENTS AND METHODS: HIV-treated patients with undetectable HIV viral loads were followed every 3 months for 36 months. We measured total cholesterol, HDL-cholesterol, triglycerides, previous responses to antiretroviral treatment, opportunistic infections, sex and age. These variables were assessed in relation to the time of undetectable viral load until viral rebound. Amino acid sequence alignment was performed with HIV proteins and apolipoprotein A1 to detect shared similarity. RESULTS: The Cox proportional hazards model showed a significant association between HDL-cholesterol and the time of undetectable viral load. The other variables studied were not associated. There was 30% sequence similarity in an area of 50 amino acids shared between apolipoprotein A1 and p17 Gag-HIV protein. CONCLUSION: High levels of HDL-cholesterol are associated with a better viral response in treated HIV patients. This association could be related to the sequence similarity and structure homology between apolipoprotein A1 and p17 Gag-HIV protein, which raises the intriguing clinical possibility that inducing an increase in HDL could assist HIV therapy.