Examinando por Autor "Giglio, Andrés"

Mostrando 1 - 8 de 8
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    Comment on: Is “pre-sepsis” the new sepsis? A narrative review
    (Public Library of Science, 2024-03-26) Giglio, Andrés
    El presente comentario al editor presenta la experiencia clínica con BiAlert Sepsis AI en un hospital, aportando evidencia al concepto de pre-sepsis propuesto por Gerard et al.. Los datos muestran que la mayoría de los pacientes detectados por la IA son infectados sin disfunción orgánica temprana y permiten definir cuatro trayectorias clínicas dentro de la pre-sepsis: pacientes en riesgo que no desarrollan sepsis, evolución abortada, sepsis subumbral y pre-sepsis progresiva con desarrollo de sepsis en 24–48 horas. Estas trayectorias evidencian que la sepsis debe entenderse como un continuo más que como un punto de corte binario y respaldan la necesidad de enfoques diagnósticos y terapéuticos basados en trayectorias para intervenir precozmente en esta ventana crítica.
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    Enhancing medical training through 360-degree evaliation: A review and Proposal for ICU training
    (Elsevier, 22-03-26) Giglio, Andrés
    La formación de médicos residentes requiere estrategias educativas que desarrollen competencias clínicas, comunicacionales y profesionales de manera integral. En este contexto, las evaluaciones de 360 grados han emerido como una alternativa a los métodos tradicionales, al permitir una valoración más completa del desempeño. Esta revisión narrativa tuvo como objeto analizar su implementación, efectividad, desafíos y resultados a largo plazo en la educación médica. Se realizó una búsqueda exhaustiva utilizando términos relacionados con "evaluación de 360°", "retroalimentación multisource" y educación en salud", seleccionándose 34 estudios en distintos entornos formativos. Los hallazgos indican que las evaluaciones de 360 grados ofrecen una perspectiva holística al integrar opiniones de múltiples actores, incluyendo pares, supervisores, pacientes y la autoevaluación. Su aplicación se asocia con mejoras en competencias clínicas, habilidades de comunicación, profesionalismo y desempeño global. Además, la retroalimentación continua favorece la práctica reflexiva y el desarrollo profesional sostenido, con impacto positivo en la calidad de la atención y la satisfacción de los pacientes. No obstante, su implementación enfrenta desafíos relevantes, como el sesgo de los evaluadores, las dificultades loigísticas y la integración efectiva de los resultados en los programas formativos. Las estrategias más eficaces incluyen la capacitación estructurada de evaluadores, el uso de instrumentos estandarizados, la realización de sesiones peródicas de retroalimentación y el soporte institucional mediante plataformas tecnológicas adecuadas.
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    Evaluating in situ Simulation in Critical Care: Insights from Healthcare Professionals
    (Dove Medical Press, DovePress, 2025-08-27) Giglio, Andrés
    Carta al editor relacionado al artículo de Sung TC y Hsu HC que lleva por nombre: Improving Critical Care Teamwork: Simulation-Based Interprofessional Training for Enhanced Communication and Safety.
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    From development to clinical practice: deployment of an interoperable and secure ML-based CDSS to aid in the early detection of sepsis
    (Elsevier, 2026-06-17) Serrano García, Ana; López, David; Macias-Fassio, Eric; Salas-Sosa, Santiago; Pascual, Iván; Pruenza, Cristina; Borges-Sa, Marcio; Giglio, Andrés; Cruz-Rojo, Jaime; Pacheco-Puig, Rodrigo
    Recent research has increasingly focused on machine learning (ML) models for early disease prediction, yet practical frameworks for integrating these models into clinical workflows remain limited. BIAlert is a microservices-based framework designed to operate as a real-time early-warning system for ML-driven disease prediction in hospitalised patients. It can be deployed remotely on physical or virtual servers and is composed of coupled microservices that communicate through Apache Kafka queues, using HL7 FHIR resources as the message format. The system comprises four core components: (1) the Connector, which ingests raw hospital data and converts it into standardised healthcare formats; (2) the Writer, which stores FHIR-formatted data in an internal database and triggers the prediction pipeline; (3) the Predictor, which hosts ML models and generates patient-specific alerts; and (4) the Model Evaluator, which supports prospective monitoring of model performance. Alerts are displayed through the BIAlert user interface and can also be integrated directly into the electronic health record (EHR). BIAlert is currently deployed and operating in real-time clinical settings in two hospitals, demonstrating its feasibility as a scalable and interoperable solution for ML-based clinical decision support.
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    International multidisciplinary consensus statement on sepsis code guidelines: A Delphi approach
    (John Wiley & Sons Ltd, 0004-08-26) Borges-Sa, Marcio; Giglio, Andrés; Martin-Loeches, Ignacio; Nates, Joseph; González del Castillo, Josemaría; Cárdenas, Yenny; Mergulhao, P.; Candel, F. J.; Zaragoza, R.; Larrosa-Escartin, M. N.; Vidal-Cortés, P.; Maseda, E.; Reina, R.; Paiva, J. A.; del Pozo, J. L.; Villegas, M. V.; Salavert, M.; Soriano, C.; Hidalgo, J.; Machuca, I.; Gonçalves-Pereira, J.; Manuel-Vázquez, A.; Lisboa, T.; Pichardo-Viñas, M.; Barberán, J.; Esparza, G.; Castillo-Abrego, G.; Estella, A.; Ortega, K.; Matos, A.; Raimondi, N.; Ferrer, R.; Sanchez, J. R.; Huelmo, I.; Gorordo-Delsol, L. A.; Campozano, V.; Soriano, A.; Perez, J.; Rodriguez, A.
    Background. Sepsis remains a major global health challenge. International guidelines exist, but their implementation is inconsistent, and supporting evidence largely comes from high-income settings. The objective of this study was to generate international, multidisciplinary expert consensus on controversial aspects of sepsis management within the framework of sepsis code programs. Methods. A multinational modified Delphi study was conducted with 164 experts from 22 countries, 12 specialties, and 105 scientific societies. Seven domains were evaluated: early diagnosis, biomarkers, diagnostic microbiology, hemodynamic monitoring, source control, antimicrobial therapy, and hemodynamic management. Consensus was defined as ≥70% agreement across three iterative rounds using Likert scales (Rounds 1–2) and binary format (Round 3). Results. Consensus was achieved for 40 statements. Strong endorsement (82%–95%) was reached for structured hospital sepsis programs, NEWS-2 as the preferred early recognition tool, biomarker use (notably procalcitonin) to complement clinical assessment, urgent source control within 6 h independent of hemodynamic status, rapid molecular diagnostics integrated with antimicrobial stewardship, and norepinephrine as first-line vasopressor therapy. Experts also supported pharmacokinetic- and pharmacodynamic-guided antibiotic dosing, prolonged infusion of time-dependent agents, and dynamic rather than fixed fluid strategies. No consensus was reached on routine reliance on Sepsis-2, Sepsis-3, or qSOFA; high mean arterial pressure targets; or universal combination antimicrobial therapy. Conclusions. These results provide multidisciplinary guidance for sepsis management, with emphasis on rapid recognition, targeted antimicrobial therapy, timely source control, and hemodynamic management guided by patient physiology. The recommendations are applicable to high- and middle-income healthcare systems.
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    Mapping intensive care across Ibero-America: The FEPIMCTI multinational survey of bed capacity, workforce, and pandemic response
    (Elsevier, 0022-07-26) Matos, Alfredo; Giglio, Andrés; Pérez-Fernandez, Javier; Nates, Joseph; Cárdenas, Yenny; Raimondi, Nestor; Sánchez, Jorge; Hidalgo, Jorge; Rezende, Ederlon; Borges-Sa, Marcio
    Background: Intensive care resources are unequally distributed across Ibero-America, and reliable comparable data are scarce, hindering cross-national comparison and health-system planning. Methods: We conducted a cross-sectional survey of the 25 national critical care societies affiliated with FEPIMCTI. Presidents or designated representatives reported country-level data on ICU beds, intensivist and nursing workforce, organizational models, training pathways, and surge capacity before and during the COVID-19 pandemic. Resource density was summarized as the country-level median with IQR and as the population-weighted regional rate. Results: Twenty-one countries, including Spain and Portugal, participated, representing 693.6 million inhabitants. A total of 78,723 ICU beds were reported (country-level median 6.1 per 100,000, IQR 3.3–12.4; population-weighted rate 11.3), with public ICUs accounting for 51.6%. A total of 23,803 intensivists were identified (median 2.6 per 100,000, IQR 1.0–5.0), with five countries below 1 per 100,000. Nurse-to-patient ratios ranged from 1:1 to 1:7, and universal 24/7 intensivist coverage was reported in only a subset of countries. During the pandemic, ICU bed capacity rose 69%; among the 20 countries with data for both periods, physician involvement rose 32%, largely through redeployment of non-intensivists rather than growth of the certified workforce. Conclusions: Critical care capacity, workforce, and organization vary widely across Ibero-America, with many countries below high-income benchmarks and pandemic surges met largely through temporary redeployment. These findings provide the first coordinated regional benchmark to guide workforce development, standardized training, and organizational strengthening.
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    Optimal arterial pressure transducer positioning for neurocritical care patients: a review
    (Sage Publications; Mary Ann Liebert, Inc., 2025) Giglio, Andrés
    This narrative review addresses the critical issue of arterial transducer positioning for cerebral perfusion pressure (CPP) measurement in neurocritical care. Despite CPP’s importance in guiding management, optimal transducer placement remains ambiguous and unaddressed by current guidelines. We synthesized evidence from 20 relevant articles to inform standardization efforts. Key findings include a 10–12 mmHg CPP discrepancy between phlebostatic axis and Monro foramen transducer locations at 30 degree head elevation. There is no consensus on anatomical landmarks for “head-level” measurement, and only one guideline explicitly advises against the phlebostatic axis approach. Limited clinical evidence suggests increased institutionalization rates for patients with measurement discrepancies. Emerging dual-transducer strategies aim to address these challenges. The review highlights significant variability in CPP measurement practices, potentially impacting patient care and research interpretation. We emphasize the urgent need for standardized protocols and improved reporting in research. Addressing this variability is crucial for optimizing neurocritical care management and enhancing research comparability. Our findings underscore the importance of consistent arterial transducer positioning in neurocritical care and call for further research to establish evidence-based standardization, ultimately improving patient outcomes and research quality in this critical field.
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    Service-Specific Heterogeneity in Sepsis Variable Significance and Machine Learning Model Performance: A Stratified Analysis of the BIAlert Cohort
    (MDPI, 2026-06-24) Borges-Sa, Marcio; Macias-Fassio, Eric; Delgado, Alejandro; Santiago Salas Sosa; Aranda, María; Socias, Antonia; del Castillo, Alberto; Giglio, Andrés
    Background/Objectives: Sepsis detection relies on clinical variables and scoring systems assumed to perform uniformly across hospital settings. However, sepsis phenotype distributions shift between clinical environments, suggesting that variable importance may be setting dependent. This study aimed to quantify service-specific variability in the discriminatory capacity of clinical variables for sepsis detection and to evaluate whether this heterogeneity translates into differential performance of machine learning models compared to traditional clinical scoring systems. Methods: This stratified sub-analysis of the BIAlert Sepsis cohort (203,755 patients; 11,864 sepsis episodes, 2014–2018) evaluated 61 structured quantitative variables across nine hospital services (≥90 sepsis episodes each). Within each service, the Mann–Whitney–Wilcoxon test (p < 0.01, Holm-corrected) assessed differences between septic and non-septic episodes. Five machine learning models (Random Forest/BIAlert, XGBoost, CatBoost, SVM, Neural Network) and three clinical rules (NEWS, SIRS, qSOFA) were evaluated globally and stratified across four clinical environments. Results: The proportion of significant variables ranged from 95.1% in the Emergency Department (58/61) to 37.7% in the Intensive Care Unit (23/61). Lactate was the only universally significant variable (9/9 services). Clinical scoring systems collapsed in Critical Care (qSOFA and NEWS AUC 0.459). BIAlert maintained the highest AUC across all environments (0.975–0.857). The Friedman test confirmed significant differences (χ2 = 28.00, p < 0.001), with BIAlert achieving a mean rank of 1.0. Conclusions: The discriminatory capacity of clinical variables for sepsis detection is not uniform across hospital services. ML models, particularly BIAlert, maintained robust performance where fixed-rule scoring systems failed.