Easy-Amanida: An R Shiny application for the meta-analysis of aggregate results in clinical metabolomics using Amanida and Webchem.

Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics is significantly lower compared to other omics disciplines. Metabolomics is the study of small chemical compounds in living organisms, which provides important insights into an organism's phenotype. However, the wide variety of compounds and the different experimental methods used in metabolomics make it challenging to perform a thorough meta-analysis. Additionally, there is a lack of consensus on reporting statistical estimates, and the high number of compound naming synonyms further complicates the process. Easy-Amanida is a new tool that combines two R packages, "amanida" and "webchem", to enable meta-analysis of aggregate statistical data, like p-value and fold-change, while ensuring the compounds naming harmonization. The Easy-Amanida app is implemented in Shiny, an R package add-on for interactive web apps, and provides a workflow to optimize the naming combination. This article describes all the steps to perform the meta-analysis using Easy-Amanida, including an illustrative example for interpreting the results. The use of aggregate statistics metrics extends the use of Easy-Amanida beyond the metabolomics field.

Effectiveness of prolonged versus standard-course of oseltamivir in critically ill patients with severe influenza infection: A multicentre cohort study.

The aim of this study is to investigate the effectiveness of prolonged versus standard course oseltamivir treatment among critically ill patients with severe influenza. A retrospective study of a prospectively collected database including adults with influenza infection admitted to 184 intensive care units (ICUs) in Spain from 2009 to 2018. Prolonged oseltamivir was defined if patients received the treatment beyond 5 days, whereas the standard-course group received oseltamivir for 5 days. The primary outcome was all-cause ICU mortality. Propensity score matching (PSM) was constructed, and the outcome was investigated through Cox regression and RCSs. Two thousand three hundred and ninety-seven subjects were included, of whom 1943 (81.1%) received prolonged oseltamivir and 454 (18.9%) received standard treatment. An optimal full matching algorithm was performed by matching 2171 patients, 1750 treated in the prolonged oseltamivir group and 421 controls in the standard oseltamivir group. After PSM, 387 (22.1%) patients in the prolonged oseltamivir and 119 (28.3%) patients in the standard group died (p = 0.009). After adjusting confounding factors, prolonged oseltamivir significantly reduced ICU mortality (odds ratio [OR]: 0.53, 95% confidence interval [CI]: 0.40-0.69). Prolonged oseltamivir may have protective effects on survival at Day 10 compared with a standard treatment course. Sensitivity analysis confirmed these findings. Compared with standard treatment, prolonged oseltamivir was associated with reduced ICU mortality in critically ill patients with severe influenza. Clinicians should consider extending the oseltamivir treatment duration to 10 days, particularly in higher-risk groups of prolonged viral shedding. Further randomized controlled trials are warranted to confirm these findings.

Diabetic retinopathy predicts cardiovascular disease independently of subclinical atherosclerosis in individuals with type 2 diabetes: A prospective cohort study.

Background: Diabetic retinopathy (DR) and preclinical atherosclerosis are associated with higher cardiovascular risk. However, no studies have investigated the predictive role of DR and preclinical atherosclerosis jointly on cardiovascular events in subjects with type 2 diabetes (T2D). We aimed to assess the contribution of DR and subclinical atherosclerosis on the risk of adverse cardiovascular events in subjects with T2D without previous cardiovascular disease (CVD). Methods: We included two prospective cohorts of subjects with T2D from the same geographical area. Assessment of subclinical atherosclerosis was performed by carotid ultrasound. An ophthalmologist classified DR according to standard criteria. Cardiovascular outcomes considered for analysis were the following: ischemic heart disease, stroke, heart failure, peripheral artery disease, revascularization procedures, and cardiovascular mortality. Bivariable and multivariable predictive models were performed. Results: From a total of 374 subjects with T2D 44 developed cardiovascular events during the 7.1 years of follow-up. Diabetes duration, total cholesterol, and glycated hemoglobin (HbA1c) at baseline were higher in subjects who developed cardiovascular outcomes (p < 0.001, p = 0.026, and p = 0.040, respectively). Compared with subjects without events, those developing cardiovascular events had higher prevalence of retinopathy (65.9% vs. 38.8%, p = 0.001; respectively) and more than mild retinopathy (43.2% vs. 31.8%, p = 0.002; respectively). Furthermore, all-cause mortality was higher in subjects with MACE than those without events (13.6% vs. 3.3%, p = 0.009; respectively). The multivariable analyses showed that HbA1c and the presence of DR at baseline were predictive of cardiovascular outcomes (p = 0.045 and p = 0.023, respectively). However, the burden of subclinical atherosclerosis was not (p = 0.783 and p = 0.071, respectively). Conclusion: DR is a strong predictor of cardiovascular events in T2D individuals at primary CVD prevention, even after accounting for the presence of preclinical carotid atherosclerosis. These results may help to individualize CVD prevention strategies in T2D.

Predictive Value of the Advanced Lipoprotein Profile and Glycated Proteins on Diabetic Retinopathy.

This study aimed to assess whether the advanced characteristics of serum lipoprotein subclasses could better predict the risk of developing diabetic retinopathy (DR) and its severity compared to other established risk factors in subjects with type 1 (T1D) and type 2 (T2D) diabetes. This observational, cross-sectional substudy analyzed DR-related data from 309 T1D and 264 T2D subjects. The advanced lipoprotein and glycoprotein profile was determined by nuclear magnetic resonance (NMR) spectroscopy (Liposcale test). NMR analysis of lipoproteins revealed that T1D subjects with DR showed standard non-HDL particles, despite higher IDL lipid concentrations. Notably, IDL lipids were elevated in T1D subjects with worsened DR. VLDL and LDL were smaller, whereas HDL triglycerides were increased in DR compared with non-DR. On the other hand, the T2D subjects with DR showed altered characteristics in the LDL fraction, mainly revealed by a significant decrease in smaller LDL and a reduction in LDL-C. Moreover, the glycoprotein profile did not reveal significant changes among DR groups, regardless of the type of diabetes. However, lipoprotein characteristics and glycoproteins unveiled by NMR analysis did not improve the predictive value of conventional lipids or other traditional, well-established biomarkers of DR in our cohorts.

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.

Amanida: an R package for meta-analysis of metabolomics non-integral data.

SUMMARY: The combination, analysis and evaluation of different studies which try to answer or solve the same scientific question, also known as a meta-analysis, plays a crucial role in answering relevant clinical relevant questions. Unfortunately, metabolomics studies rarely disclose all the statistical information needed to perform a meta-analysis. Here, we present a meta-analysis approach using only the most reported statistical parameters in this field: P-value and fold-change. The P-values are combined via Fisher's method and fold-changes by averaging, both weighted by the study size (n). The amanida package includes several visualization options: a volcano plot for quantitative results, a vote plot for total regulation behaviours (up/down regulations) for each compound, and a explore plot of the vote-counting results with the number of times a compound is found upregulated or downregulated. In this way, it is very easy to detect discrepancies between studies at a first glance. AVAILABILITY AND IMPLEMENTATION: Amanida code and documentation are at CRAN and https://github.com/mariallr/amanida. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Essential and Non-essential Trace Elements in Milks and Plant-Based Drinks.

Although milk and plant-based drinks are widely consumed foodstuffs with high nutritional value, their consumption may also mean intake of non-essential/toxic elements becoming a risk for human health. This study was aimed at determining the concentrations of essential (Ca, Co, K, Mg, Mn, Na, Ni and P) and non-essential/toxic (Hg, Pb, U and V) elements in milks (cow and goat), plant-based drinks (soy, almond, rice and oat) and infant formulas from organic and conventional production systems. Lactose-free, fresh and ultra-high-temperature (UHT) milks were also included. Chemical analyses were performed by means of inductively coupled plasma-mass spectrometry (ICP-MS). The content of the elements hereby assessed did not depend on the production system and the presence of lactose. However, significant differences were found in the concentrations of multiple elements when comparing sterilization methods, source (animal vs. plant-based) and animal species. Non-essential elements were not detected in milks and plant-based drinks, excepting Pb, which was detected in three samples. While the consumption of goat milk is recommended, considering the global intake of essential elements and the absence of non-essential elements, further studies should be conducted to confirm the absence of non-target toxic elements at very low trace levels. On the other hand, the best plant-based drinks are those made up with almonds (intake of Ca) and soy (K and Mg). The current results should be useful to help the population to balance the benefits and risks from milks and plant-based drinks consumption, as well as to adapt their dietary habits.

Dietary exposure to potentially toxic elements through sushi consumption in Catalonia, Spain.

Although sushi is considered as a healthy food, it can also be a route of exposure to chemical contaminants such as potentially toxic trace elements. In this study, we analysed the concentration of Cd, I, Ni, Pb and total Hg, as well as iAs and MeHg in sushi samples. Iodine levels were higher in samples containing seaweed, while iAs concentrations were greater in rice-containing sushi. In turn, total Hg and MeHg were significantly higher in sushi samples with tuna. Health risks of sushi consumption were assessed for three population groups: children, adolescents and adults. Considering an average intake of 8 sushi pieces for adults and adolescents, and 3 sushi pieces for children, the estimated exposure to MeHg by adolescents exceeded the tolerable daily intake set by EFSA, while MeHg intake by children and adults was below, but close to that threshold. A relatively high daily exposure of Ni and Pb was also found, especially for adolescents. Since this study focused only on the consumption of sushi, the contribution of other food groups to the overall dietary exposure should not be disregarded. It might lead to an exposure to MeHg and other trace elements above the health-based guideline values.

Early oseltamivir treatment improves survival in critically ill patients with influenza pneumonia.

BACKGROUND: The relationship between early oseltamivir treatment (within 48 h of symptom onset) and mortality in patients admitted to intensive care units (ICUs) with severe influenza is disputed. This study aimed to investigate the association between early oseltamivir treatment and ICU mortality in critically ill patients with influenza pneumonia. METHODS: This was an observational study of patients with influenza pneumonia admitted to 184 ICUs in Spain during 2009-2018. The primary outcome was to evaluate the association between early oseltamivir treatment and ICU mortality compared with later treatment. Secondary outcomes were to compare the duration of mechanical ventilation and ICU length of stay between the early and later oseltamivir treatment groups. To reduce biases related to observational studies, propensity score matching and a competing risk analysis were performed. RESULTS: During the study period, 2124 patients met the inclusion criteria. All patients had influenza pneumonia and received oseltamivir before ICU admission. Of these, 529 (24.9%) received early oseltamivir treatment. In the multivariate analysis, early treatment was associated with reduced ICU mortality (OR 0.69, 95% CI 0.51-0.95). After propensity score matching, early oseltamivir treatment was associated with improved survival rates in the Cox regression (hazard ratio 0.77, 95% CI 0.61-0.99) and competing risk (subdistribution hazard ratio 0.67, 95% CI 0.53-0.85) analyses. The ICU length of stay and duration of mechanical ventilation were shorter in patients receiving early treatment. CONCLUSIONS: Early oseltamivir treatment is associated with improved survival rates in critically ill patients with influenza pneumonia, and may decrease ICU length of stay and mechanical ventilation duration.

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.

Corticosteroid treatment in critically ill patients with severe influenza pneumonia: a propensity score matching study.

PURPOSE: To determine clinical predictors associated with corticosteroid administration and its association with ICU mortality in critically ill patients with severe influenza pneumonia. METHODS: Secondary analysis of a prospective cohort study of critically ill patients with confirmed influenza pneumonia admitted to 148 ICUs in Spain between June 2009 and April 2014. Patients who received corticosteroid treatment for causes other than viral pneumonia (e.g., refractory septic shock and asthma or chronic obstructive pulmonary disease [COPD] exacerbation) were excluded. Patients with corticosteroid therapy were compared with those without corticosteroid therapy. We use a propensity score (PS) matching analysis to reduce confounding factors. The primary outcome was ICU mortality. Cox proportional hazards and competing risks analysis was performed to assess the impact of corticosteroids on ICU mortality. RESULTS: A total of 1846 patients with primary influenza pneumonia were enrolled. Corticosteroids were administered in 604 (32.7%) patients, with methylprednisolone the most frequently used corticosteroid (578/604 [95.7%]). The median daily dose was equivalent to 80 mg of methylprednisolone (IQR 60-120) for a median duration of 7 days (IQR 5-10). Asthma, COPD, hematological disease, and the need for mechanical ventilation were independently associated with corticosteroid use. Crude ICU mortality was higher in patients who received corticosteroids (27.5%) than in patients who did not receive corticosteroids (18.8%, p < 0.001). After PS matching, corticosteroid use was associated with ICU mortality in the Cox (HR = 1.32 [95% CI 1.08-1.60], p < 0.006) and competing risks analysis (SHR = 1.37 [95% CI 1.12-1.68], p = 0.001). CONCLUSION: Administration of corticosteroids in patients with severe influenza pneumonia is associated with increased ICU mortality, and these agents should not be used as co-adjuvant therapy.