Viral infections cause metabolic dysregulation in the infected organism. The present study used metabolomics techniques and machine learning algorithms to retrospectively analyze the alter-ations of a broad panel of metabolites in the serum and urine of a cohort of 126 patients hospi-talized with COVID-19. Results were compared with those of 50 healthy subjects and 45 COVID-19 negative patients but with bacterial infectious diseases. Metabolites were analyzed by gas chro-matography coupled to quadrupole time-of-flight mass spectrometry. The main metabolites al-tered in the sera of COVID-19 patients were those of pentose glucuronate interconversion, ascorbate and fructose metabolism, nucleotide sugars, and nucleotide and amino acid metabolism. Alterations in serum maltose, mannonic acid, xylitol, or glyceric acid metabolites segregated positive patients from the control group with high diagnostic accuracy, while succinic acid seg-regated positive patients from those with other disparate infectious diseases. Increased lauric acid concentrations were associated with severity of infection and death. Urine analyses could not discriminate between groups. Targeted metabolomics and machine learning algorithms facilitated the exploration of the metabolic alterations underlying COVID-19 infection, and to identify po-tential biomarkers for the diagnosis and prognosis of the disease.

.Background: Clostridioides difficile infections (CDI) vary in severity from mild diarrhea to life-threatening conditions like pseudomembranous colitis or toxic megacolon, often leading to sepsis and death. The COVID-19 pandemic prompted changes in healthcare practices, potentially affecting CDI incidence, though reported data are inconclusive. We studied factors influencing CDI incidence and outcomes at a university hospital throughout the COVID-19 pandemic years. Methods: We conducted a retrospective study on all adult hospitalized CDI cases from January 1, 2020, to December 31, 2022. We collected demographic information, comorbid conditions, and concurrent infections. Results: While overall CDI and COVID-19 rates decreased in 2022, a nota-ble increase in CDI infections was observed among oncological patients and those undergoing some aggressive treatments, such as colon or gastroscopies. The prevalence of comorbidities remained unmodified, and there were declines in prior gastrointestinal surgeries and proton pump inhibitor prescriptions. Factors associated with patient fatality or prolonged hospitaliza-tion included older age, cancer, chronic kidney disease, higher Charlson and McCabe indices, elevated C-reactive protein, and low albumin concentrations. Conclusion: Our study shows the evolving landscape of CDI during the COVID-19 pandemic and emphasizes the impact of de-layed diagnoses and treatments exacerbated by telemedicine adoption. Identified risk factors for CDI-related mortality or prolonged hospital stays underscore the importance of targeted inter-ventions in high-risk populations.