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.

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.

EFFECT oF STATIN THERAPY oN SARS-CoV-2 INFECTION-RELATED

Aim

Assessing the effect of statin therapy 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. 353 deaths occurred. 581 patients were taking statins. Univariate test after GM showed a significantly lower mortality rate in patients on statin therapy 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 to 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 statin therapy prior to hospitalization. Statin therapy should not be discontinued due to the global concern of the pandemic or in patients hospitalized for COVID-19.

Immunoglobulin abnormalities are frequent in patients with lupus nephritis

Background

Hypogammaglobulinemia is a complication of B-cell targeting therapies (BCTT), used in vasculitis, rheumatoid arthritis and systemic lupus erythematosus (SLE). Since autoimmune diseases are associated with underlying and induced immune abnormalities, several societies recommend assessing immune function before and during rituximab treatment. In SLE, polyclonal hypergammaglobulinemia is the typical alteration of gammaglobulins, though hypogammaglobulinemia has also been reported.

Methods

This is a cross-sectional study describing immunoglobulin levels measured as part of routine care in patients with lupus nephritis, a group with multiple factors contributing to immunoglobulin abnormalities, including immune dysregulation, immunosuppression and nephrotic syndrome.

Results

Polyclonal hypergammaglobulinemia occurred in 15/83 (18.1%) patients. In contrast, low levels of immunoglobulins were found as follows: selective IgA deficiency 2/83 (2.4%), reduced IgG levels 7/83 (8.4%), reduced IgM 14/83 (16.9%). Only 1 patient required immunoglobulin replacement.

Conclusions

Immunoglobulin abnormalities are frequently found in lupus nephritis, ranging from polyclonal hypergammaglobulinemia to hypogammglobulinemia. Consequently, immunoglobulin levels should be assessed prior to commencing BCTT.