RT info:eu-repo/semantics/doctoralThesis
T1 Combinación de información biológica para la estratificación de la gravedad y predicción del pronóstico en la infección
A1 Fuente Vázquez, Amanda de la
A2 Universidad de Valladolid. Escuela de Doctorado
K1 Enfermedades infecciosas - Escalas clínicas
K1 Infection
K1 Infección
K1 Sepsis
K1 COVID-19
K1 32 Ciencias Médicas
AB INTRODUCTIONSevere infectious diseases, such as sepsis and COVID-19, represent a significant threat to public health due to their high mortality rates and clinical complexity. The host response in these infections is characterized by heterogeneity and complexity, making early diagnosis, severity stratification, and effective patient management in clinical settings challenging. The pathophysiological processes of both conditions exhibit significant similarities, as the exaggerated and uncontrolled immune response to the infectious stimulus leads to organ damage and contributes to the high mortality associated with these pathologies.Timely diagnosis—since these conditions are time-sensitive—as well as severity stratification and the identification of patients at risk of poor outcomes, are therefore crucial. In this context, biomarkers have been proposed for many years as promising tools to address these challenges. Biomarkers provide an opportunity to better understand the underlying pathophysiological processes and support patient management. Furthermore, combining several biomarkers from different origins—whether reflecting the host response to the infection or the pathogen itself—can enhance the predictive and prognostic value compared to individual biomarkers.OBJECTIVEThe primary objective of this thesis was to evaluate the utility of specific plasma biomarker combinations to improve early diagnosis, severity prediction, and risk stratification in patients with sepsis and COVID-19.MATERIALS AND METHODSTo achieve this, two main studies were carried out. In the sepsis study, twenty plasma biomarkers involved in biological functions disrupted during infection were evaluated using the SimplePlex ELLA platform in surgical patients with and without infection. The main findings were further validated in a second cohort. In the COVID-19 study, the prognostic value of N antigenemia and anti-S1 antibodies, both individually and in combination, was assessed in patients with SARS-CoV-2 infection treated in emergency services. Their levels were analyzed to predict hospitalization and adverse outcomes.RESULTSIn the sepsis study, only eight of the studied biomarkers demonstrated sufficient capacity to differentiate between infected and non-infected patients. Among these, a combination of four biomarkers involved in innate immunity and endothelial dysfunction, called Dys-4, showed a strong association with the degree of organ failure in infected patients, as measured by the SOFA scale. Additionally, this combination exhibited a stronger correlation with organ failure severity than individual biomarkers, including procalcitonin and C-reactive protein, underscoring its potential for clinical application. Dys-4 showed consistent results in the validation cohort.In the COVID-19 study, the combination of N antigenemia and low levels of anti-S1 antibodies allowed the accurate identification of COVID-19 patients who presented the highest risk of hospitalization and severe outcomes.CONCLUSIONThe findings of this thesis underscore the clinical potential of biomarker combinations to improve diagnosis, severity stratification, and prognosis in patients with sepsis and COVID-19. Integrating these biomarkers into clinical predictive models could revolutionize the management of severe and emerging infections, advancing personalized precision medicine. Future research should focus on validating these findings in larger cohorts and exploring the incorporation of additional biomarkers from diverse origins to further enhance clinical care.
YR 2025
FD 2025
LK https://uvadoc.uva.es/handle/10324/75953
UL https://uvadoc.uva.es/handle/10324/75953
LA spa
NO Escuela de Doctorado
DS UVaDOC
RD 19-jun-2025