RT journal article
T1 Datos abiertos e inteligencia artificial: una ventana de oportunidad para pacientes sépticos en los servicios de urgencias
T2 Open data and artificial intelligence: a window of opportunity for septic patients in emergency departments
A1 Estella García, Ángel
A1 Armengol de la Hoz, Miguel Ángel
A1 González del Castillo, Juan
A2 Cirugía
A2 Medicina
K1 Sepsis
K1 Emergency
K1 Artificial intelligence
K1 Open data
K1 Early detection
K1 Urgencias
K1 Inteligencia artificial
K1 Datos abiertos
K1 Detección precoz
AB Sepsis remains one of the leading causes of mortality in emergency departments (EDs). Despite advances in definitions and management protocols, early identification continues to be a critical challenge due to the nonspecific presentation of the disease. Early management is based on 3 fundamental pillars: source control, antibiotics, and hemodynamic resuscitation, all of which require early intervention. Tools such as the SOFA score, biomarkers (C-reactive protein, procalcitonin, lactate), and protocols like the Sepsis Code have improved detection and management. However, the clinical heterogeneity of sepsis and limitations of current models hinder their universal implementation. Artificial intelligence (AI) is emerging as a key tool to improve early detection of sepsis through the analysis of large volumes of clinical data. Open data, following FAIR principles (Findable, Accessible, Interoperable, Reusable), facilitate the development of robust and personalized algorithms, minimizing bias and enhancing scientific collaboration. Spain generates vast amounts of clinical data in its EDs but lacks a unified database. The creation of an open system with data use agreements would enable the development of predictive models specific to its population. The use of A.I. in combination with specific databases promises to improve treatment personalization, reduce mortality, and optimize resources in sepsis care, changing the current paradigm of clinical management.
PB Saned
SN 2386-5857
YR 2025
FD 2025-06
LK http://hdl.handle.net/10498/39554
UL http://hdl.handle.net/10498/39554
LA spa
DS Repositorio Institucional de la Universidad de Cádiz
RD 07-nov-2026