Dataset Information

Plasma Metabolome Alterations Discriminate between COVID-19 and Non-COVID-19 Pneumonia.

ABSTRACT: Pneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the plasma metabolome of 43 cases of COVID-19 pneumonia, 23 cases of non-COVID-19 pneumonia, and 26 controls using a non-targeted approach. Metabolic alterations differentiating the three groups were detected, with specific metabolic changes distinguishing the two types of pneumonia groups. A comparison of venous and arterial blood plasma samples from the same subjects revealed the distinct metabolic effects of pulmonary pneumonia. In addition, a machine learning signature of four metabolites was predictive of the disease outcome of COVID-19 subjects with an area under the curve (AUC) of 86 ± 10 %. Overall, the results of this study uncover systemic metabolic changes that could be linked to the etiology of COVID-19 pneumonia and non-COVID-19 pneumonia.

SUBMITTER: More TH

PROVIDER: S-EPMC9693035 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Plasma Metabolome Alterations Discriminate between COVID-19 and Non-COVID-19 Pneumonia.

More Tushar H TH Mozafari Bahareh B Märtens Andre A Herr Christian C Lepper Philipp M PM Danziger Guy G Volk Thomas T Hoersch Sabrina S Krawczyk Marcin M Guenther Katharina K Hiller Karsten K Bals Robert R

Metabolites 20221102 11

Pneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the pl ...[more]

PMID: 36355140

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Project description:BackgroundPrevious studies that assessed the risk of cardiovascular outcomes in survivors of coronavirus disease 2019 (COVID-19) were likely limited by lack of generalizability and selection of controls nonrepresentative of a counterfactual situation regarding COVID-19-related hospitalization. This study determined whether COVID-19 hospitalization was associated with incident cardiovascular outcomes compared to non-COVID-19 pneumonia hospitalization.MethodsNationwide population-based study conducted using the Korean National Health Insurance Service database. A cohort of 132,784 inpatients with COVID-19 (October 8, 2020-September 30, 2021) and a cohort of 31,173 inpatients with non-COVID-19 pneumonia (January 1-December 31, 2019) were included. The primary outcome was the major adverse cardiovascular event (MACE; a composite of myocardial infarction and stroke). Hazard ratios (HRs) with 95% confidence intervals (CIs) of all outcomes of interest were estimated between inverse probability of treatment-weighted patients with COVID-19 and non-COVID-19 pneumonia.ResultsAfter weighting, the COVID-19 and non-COVID-19 pneumonia groups included 125,810 (mean [SD] age, 47.2 [17.6] years; men, 49.3%) and 28,492 patients (mean [SD] age, 48.6 [18.4] years; men, 47.2%), respectively. COVID-19 hospitalization was not associated with an increased risk of the MACE (HR, 0.84; 95% CI 0.69-1.03). However, the MACE (HR, 7.30; 95% CI 3.29-16.21), dysrhythmia (HR, 1.88; 95% CI 1.04-3.42), acute myocarditis (HR, 11.33; 95% CI 2.97-43.20), myocardial infarction (HR, 6.78; 95% CI 3.03-15.15), congestive heart failure (HR, 1.95; 95% CI 1.37-2.77), and thrombotic disease (HR, 8.26; 95% CI 4.06-16.83) risks were significantly higher in patients with COVID-19 aged 18-39 years. The findings were consistent after adjustment for preexisting cardiovascular disease. COVID-19 hospitalization conferred a higher risk of acute myocarditis (HR, 6.47; 95% CI 2.53-16.52) or deep vein thrombosis (HR, 1.97; 95% CI 1.38-2.80), regardless of vaccination status.ConclusionsHospitalized patients with COVID-19 were not at an increased risk of cardiovascular outcomes compared to patients with non-COVID-19 pneumonia. Further studies are needed to evaluate whether the increased risk of cardiovascular outcomes is confined to younger patients.

Project description:BackgroundThe COVID-19 pandemic has caused the relocation of huge financial resources to departments dedicated to infected patients, at the expense of those suffering from other pathologies.AimTo compare clinical features and outcomes in COVID-19 pneumonia and non-COVID-19 pneumonia patients.Patients and methods53 patients (35 males, mean age 61.5 years) with COVID-19 pneumonia and 50 patients (32 males, mean age 72.7 years) with non-COVID-19 pneumonia, consecutively admitted between March and May 2020 were included. Clinical, laboratory and radiological data at admission were analyzed. Duration of hospitalization and mortality rates were evaluated.ResultsAmong the non-COVID patients, mean age, presence of comorbidities (neurological diseases, chronic kidney disease and chronic obstructive pulmonary disease), Charlson Comorbidity Index and risk factors (tobacco use and protracted length of stay in geriatric healthcare facilities) were higher than in COVID patients. The non-COVID-19 pneumonia group showed a higher (24% vs. 17%), although not statistically significant in-hospital mortality rate; the average duration of hospitalization was longer for COVID patients (30 vs. 9 days, p = .0001).ConclusionsIn the early stages of the COVID pandemic, our centre noted no statistical difference in unadjusted in-hospital mortality between COVID and non-COVID patients. Non-COVID patients had higher Charlson Comorbidity Scores, reflecting a greater disease burden in this population.Key MessagesIn March 2020, the COVID-19 disease was declared a pandemic, with enormous consequences for the organization of health systems and in terms of human lives; this has caused the relocation of huge financial resources to departments dedicated to infected patients, at the expense of those suffering from other pathologies.Few published reports have compared COVID-19 and non-COVID-19 pneumonia. In our study, performed in a geographic area with a low prevalence of SARS-CoV-2 infection, we found few statistically significant differences in terms of clinical characteristics between the two groups analyzed.In the early stages of the COVID pandemic, our centre noted no statistical difference in unadjusted in-hospital mortality between COVID and non-COVID patients. Non-COVID patients had higher Charlson Comorbidity Scores, reflecting a greater disease burden in this population.

Project description:Coronavirus disease-2019, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was a disaster in 2020. Accurate and early diagnosis of coronavirus disease-2019 (COVID-19) is still essential for health policymaking. Reverse transcriptase-polymerase chain reaction (RT-PCR) has been performed as the operational gold standard for COVID-19 diagnosis. We aimed to design and implement a reliable COVID-19 diagnosis method to provide the risk of infection using demographics, symptoms and signs, blood markers, and family history of diseases to have excellent agreement with the results obtained by the RT-PCR and CT-scan. Our study primarily used sample data from a 1-year hospital-based prospective COVID-19 open-cohort, the Khorshid COVID Cohort (KCC) study. A sample of 634 patients with COVID-19 and 118 patients with pneumonia with similar characteristics whose RT-PCR and chest CT scan were negative (as the control group) (dataset 1) was used to design the system and for internal validation. Two other online datasets, namely, some symptoms (dataset 2) and blood tests (dataset 3), were also analyzed. A combination of one-hot encoding, stability feature selection, over-sampling, and an ensemble classifier was used. Ten-fold stratified cross-validation was performed. In addition to gender and symptom duration, signs and symptoms, blood biomarkers, and comorbidities were selected. Performance indices of the cross-validated confusion matrix for dataset 1 were as follows: sensitivity of 96% [confidence interval, CI, 95%: 94-98], specificity of 95% [90-99], positive predictive value (PPV) of 99% [98-100], negative predictive value (NPV) of 82% [76-89], diagnostic odds ratio (DOR) of 496 [198-1,245], area under the ROC (AUC) of 0.96 [0.94-0.97], Matthews Correlation Coefficient (MCC) of 0.87 [0.85-0.88], accuracy of 96% [94-98], and Cohen's Kappa of 0.86 [0.81-0.91]. The proposed algorithm showed excellent diagnosis accuracy and class-labeling agreement, and fair discriminant power. The AUC on the datasets 2 and 3 was 0.97 [0.96-0.98] and 0.92 [0.91-0.94], respectively. The most important feature was white blood cell count, shortness of breath, and C-reactive protein for datasets 1, 2, and 3, respectively. The proposed algorithm is, thus, a promising COVID-19 diagnosis method, which could be an amendment to simple blood tests and screening of symptoms. However, the RT-PCR and chest CT-scan, performed as the gold standard, are not 100% accurate.

Dataset Information

Plasma Metabolome Alterations Discriminate between COVID-19 and Non-COVID-19 Pneumonia.

Publications

Plasma Metabolome Alterations Discriminate between COVID-19 and Non-COVID-19 Pneumonia.

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