Preprint Article Version 1 This version is not peer-reviewed

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

Ignasi Sacanella
,
Erika Esteve-Pitarch
,
Jessica Guevara-Chaux
,
Julen Berrueta
,
Alejandro García-Martínez
,
Josep Gómez
,
Cecilia Casarino
,
Florencia Alés
,
Laura Canadell
,
Ignacio Martin-Loeches
,
Santiago Grau
,
Francisco Javier Candel
,
María Bodí
,
Alejandro Rodríguez
*
Version 1 : Received: 11 July 2024 / Approved: 11 July 2024 / Online: 15 July 2024 (15:52:44 CEST)

How to cite: Sacanella, I.; Esteve-Pitarch, E.; Guevara-Chaux, J.; Berrueta, J.; García-Martínez, A.; Gómez, J.; Casarino, C.; Alés, F.; Canadell, L.; Martin-Loeches, I.; Grau, S.; Candel, F. J.; Bodí, M.; Rodríguez, A. A Real-World Data Analysis of the Impact of Liposomal Amphotericin B on Renal Function Using Machine Learning in Critical Ill Patients. Preprints 2024, 2024071002. https://doi.org/10.20944/preprints202407.1002.v1 Sacanella, I.; Esteve-Pitarch, E.; Guevara-Chaux, J.; Berrueta, J.; García-Martínez, A.; Gómez, J.; Casarino, C.; Alés, F.; Canadell, L.; Martin-Loeches, I.; Grau, S.; Candel, F. J.; Bodí, M.; Rodríguez, A. A Real-World Data Analysis of the Impact of Liposomal Amphotericin B on Renal Function Using Machine Learning in Critical Ill Patients. Preprints 2024, 2024071002. https://doi.org/10.20944/preprints202407.1002.v1

Abstract

Liposomal amphotericin B (L-AmB) has become the cornerstone for the treatment of severe invasive fungal infections. However, renal toxicity may be an associated risk. Our aim was to evaluate the incidence of acute kidney injury (AKI) in critically ill patients receiving L-AmB for more than 48 hours. Clinical, demographic and laboratory variables were obtained retrospectively from electronic health record. Follow-up of the patients was for 7 days after L-AmB infusion. Patients were analyzed globally and differentiated between patients with "low" and "high" risk of developing AKI with machine learning techniques. Sixty-seven patients were included: 61 years, 67% male, with mean SOFA score of 4 (3-6.5) and a crude intensive care unit mortality of 34.3%. No significant variations in serum creatinine were observed during the observation period, except for the decrease in the high-risk subgroup. Overall, 26.8% of patients developed AKI-I, while 25% and 13% of patients at low and high risk of AKI developed AKI-I, respectively. The random forest models performed in overall and low-risk subgroup identified several major contributor’s factors to the development of AKI other than L-AmB administration. The development of AKI is multifactorial and the administration of L-AmB appears to be safe in this group of patients.

Keywords

Liposomal amphotericin B; Acute Kidney Injury; Machine learning; Critical Care; Antifungal agents; Random Forest

Subject

Medicine and Pharmacology, Pharmacology and Toxicology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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