Examinando por Autor "Moreno Cuerda, Victor"

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Biomarkers for SARS-CoV-2 infection. A narrative review
(Frontiers, 2025-03-26) Snopkowska Lesniak, Sara Weronika; Maschio, Diego; Henriquez-Camacho, Cesar; Moreno Cuerda, Victor
COVID-19 is an infectious disease caused by SARS-CoV-2 with devastating effects on health-care systems. The magnitude of the problem has moved physicians and investigators to identify strategies to detect patients at a high risk of severe disease. The aim of this study was to identify the most relevant biomarkers in the published literature and their correlation with clinical outcomes. To this end, we performed a revision of studies that investigated laboratory abnormalities in patients with COVID-19, comparing non-severe and severe patients. Blood biomarkers were classified into five main categories: hematological, coagulation related to the liver or kidney, and inflammatory. From our analysis, the most relevant biomarkers associated with severe infection for each category were increased levels of leukocytes, neutrophils, and neutrophil-to-lymphocyte ratio; decreased platelet count; and high levels of aspartate transaminase, alanine transaminase, creatine kinase, troponin, creatinine, and blood urea nitrogen, C-reactive protein, ferritin, and IL-6. Moreover, lactate dehydrogenase and D-dimer levels were independent risk factors for death.
Novel Biomarkers for SARS-CoV-2 Infection: A Systematic Review and Meta-Analysis
(MDPI, 2025-06-01) Snopkowska Lesniak, Sara Weronika; Maschio, Diego; Neria, Fernando; Rey-Delgado, Beatriz; Moreno Cuerda, Victor; Henriquez-Camacho, Cesar
COVID-19, caused by SARS-CoV-2, has posed significant challenge to global healthcare systems, necessitating reliable biomarkers to predict disease severity and mortality. This systematic review and meta-analysis evaluated the prognostic value of novel biomarkers in COVID-19 patients. The aim of this study was to identify and prioritize the most prognostically relevant novel biomarkers associated with COVID-19 outcomes. We conducted a systematic review and meta-analysis of the available evidence. A systematic search of PubMed and Web of Science was performed to identify studies on the COVID-19 biomarkers. Observational studies that compared poor (severe disease/mortality) and good outcomes were included. For continuous measures, standard mean differences (SMDs) with 95% confidence intervals (CIs) were calculated. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve analyses for the biomarkers were used. The risk of bias was assessed using the Newcastle-Ottawa scale. Of the 2907 screened studies, 38 were included (21 in the meta-analysis). MR-proADM showed higher levels of prediction for poor outcomes (SMD = 1.40, 95% CI: 1.11-1.69; AUC 0.74-0.96; sensitivity, 85%; specificity, 71%). The neutrophil-to-lymphocyte ratio (NLR) showed a high correlation with disease severity (SMD = 1.07, 95% CI: 0.79-1.35; AUC 0.73-0.98; sensitivity, 86%; specificity, 78%). Increased KL-6 levels were associated with lung injury (SMD = 1.22, 95% CI: 0.24-2.19; AUC 0.85-0.95). Other biomarkers (suPAR, miR-155, Galectin-3) showed promise but lacked sufficient data for pooled analysis. Heterogeneity was observed among the included studies in terms of diagnostic accuracy. These findings indicate that elevated levels of MR-proADM, NLR, and KL-6 are significantly associated with COVID-19 prognostic accuracy to guide patient management. MR-proADM, NLR, and KL-6 levels demonstrated strong prognostic value for COVID-19 severity and mortality. These biomarkers can enhance clinical decision-making.