Articles producció científicaMedicina i Cirurgia

A Real-World Data Observational Analysis of the Impact of Liposomal Amphotericin B on Renal Function Using Machine Learning in Critically Ill Patients

  • Datos identificativos

    Identificador:  imarina:9380974
    Autores:  Sacanella, Ignasi; Esteve-Pitarch, Erika; Guevara-Chaux, Jessica; Berrueta, Julen; Garcia-Martinez, Alejandro; Gomez, Josep; Casarino, Cecilia; Ales, Florencia; Canadell, Laura; Martin-Loeches, Ignacio; Grau, Santiago; Candel, Francisco Javier; Bodi, Maria; Rodriguez, Alejandro
    Resumen:
    Background: Liposomal amphotericin B (L-AmB) has become the mainstay of treatment for severe invasive fungal infections. However, the potential for renal toxicity must be considered. Aims: To evaluate the incidence of acute kidney injury (AKI) in critically ill patients receiving L-AmB for more than 48 h. Methods: Retrospective, observational, single-center study. Clinical, demographic and laboratory variables were obtained automatically from the electronic medical record. AKI incidence was analyzed in the entire population and in patients with a "low" or "high" risk of AKI based on their creatinine levels at the outset of the study. Factors associated with the development of AKI were studied using random forest models. Results: Finally, 67 patients with a median age of 61 (53-71) years, 67% male, a median SOFA of 4 (3-6.5) and a crude mortality of 34.3% were included. No variations in serum creatinine were observed during the observation period, except for a decrease in the high-risk subgroup. A total of 26.8% (total population), 25% (low risk) and 13% (high risk) of patients developed AKI. Norepinephrine, the SOFA score, furosemide (general model), potassium, C-reactive protein and procalcitonin (low-risk subgroup) were the variables identified by the random forest models as important contributing factors to the development of AKI other than L-AmB administration. Conclusions: The development of AKI is multifactorial and the administration of L-AmB appears to be safe in this group of patients.
  • Otros:

    Enlace a la fuente original: https://www.mdpi.com/2079-6382/13/8/760
    Referencia de l'ítem segons les normes APA: Sacanella, Ignasi; Esteve-Pitarch, Erika; Guevara-Chaux, Jessica; Berrueta, Julen; Garcia-Martinez, Alejandro; Gomez, Josep; Casarino, Cecilia; Ales, (2024). A Real-World Data Observational Analysis of the Impact of Liposomal Amphotericin B on Renal Function Using Machine Learning in Critically Ill Patients. Antibiotics, 13(8), 760-. DOI: 10.3390/antibiotics13080760
    Referencia al articulo segun fuente origial: Antibiotics. 13 (8): 760-
    DOI del artículo: 10.3390/antibiotics13080760
    Año de publicación de la revista: 2024
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2025-03-22
    Autor/es de la URV: Bodi Saera, Maria Amparo / Gómez Alvarez, Josep / Rodríguez Oviedo, Alejandro Hugo
    Departamento: Medicina i Cirurgia
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    Autor según el artículo: Sacanella, Ignasi; Esteve-Pitarch, Erika; Guevara-Chaux, Jessica; Berrueta, Julen; Garcia-Martinez, Alejandro; Gomez, Josep; Casarino, Cecilia; Ales, Florencia; Canadell, Laura; Martin-Loeches, Ignacio; Grau, Santiago; Candel, Francisco Javier; Bodi, Maria; Rodriguez, Alejandro
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Pharmacology, toxicology and pharmaceutics (miscellaneous), Pharmacology, toxicology and pharmaceutics (all), Pharmacology (medical), Pharmacology & pharmacy, Microbiology (medical), Microbiology, Infectious diseases, General pharmacology, toxicology and pharmaceutics, Engenharias ii, Biochemistry
    Direcció de correo del autor: josep.gomez@urv.cat, alejandrohugo.rodriguez@urv.cat, mariaamparo.bodi@urv.cat, mariaamparo.bodi@urv.cat
  • Palabras clave:

    Therap
    Scedosporium-prolificans
    Random forest
    Random fores
    Machine learning
    Liposomal amphotericin b
    Lipid complex
    Infection
    Critical care
    Antifungal agents
    Acute kidney injury
    Biochemistry
    Infectious Diseases
    Microbiology
    Microbiology (Medical)
    Pharmacology & Pharmacy
    Pharmacology (Medical)
    Pharmacology
    Toxicology and Pharmaceutics (Miscellaneous)
    toxicology and pharmaceutics (all)
    General pharmacology
    toxicology and pharmaceutics
    Engenharias ii
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