Background: Piperacillin/tazobactam is one of the most common antibiotics prescribed in the ICU and the combination of piperacillin/tazobactam with vancomycin has been associated with acute kidney injury (AKI) in critically ill patients. However, data on the risk of AKI with piperacillin/tazobactam, despite vancomycin co-exposure, are lacking.

Objectives: To investigate the association of piperacillin/tazobactam with AKI and renal replacement therapy (RRT) among adult ICU patients.

Methods: We analysed data from patients included in two open access databases (MIMIC-IV and eICU). Critically ill patients who received piperacillin/tazobactam or cefepime (a cephalosporin with similar broad-spectrum activity to piperacillin/tazobactam) during their first ICU stay were eligible for the study. Marginal structural Cox models, accounting for time-fixed covariates and time-dependent covariates were performed. The primary outcomes were AKI and need of RRT.

Results: A total of 20 107 patients were included, with 11 213 in the piperacillin/tazobactam group and 8894 in the cefepime group. Exposure to piperacillin/tazobactam was associated with AKI (HR 1.77; 95% CI 1.51-2.07; P < 0.001) and with need of RRT (HR 1.31; 95% CI 1.08-1.57; P = 0.005). Tests for interaction were not statistically significant for occurrence of AKI and RRT in the subgroup of patients exposed to vancomycin or not (P = 0.26 and P = 0.6, respectively).

Conclusions: In critically ill patients, exposure to piperacillin/tazobactam was associated with increased risk of AKI and with increased risk of RRT, regardless of combination therapy with vancomycin.

Download full-text PDF

Source
http://dx.doi.org/10.1093/jac/dkae001DOI Listing

Publication Analysis

Top Keywords

critically ill
16
ill patients
16
piperacillin/tazobactam
9
association piperacillin/tazobactam
8
acute kidney
8
kidney injury
8
risk aki
8
patients included
8
exposure piperacillin/tazobactam
8
piperacillin/tazobactam associated
8

Similar Publications

Background: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by physical exam, which can be intermittent and subjective. Reliable, continuous methods are needed. We hypothesized that our computer vision method to track movement, pose artificial intelligence (AI), could predict neurologic changes in the neonatal intensive care unit (NICU).

View Article and Find Full Text PDF

Digital health interventions in adult intensive care and recovery after critical illness to promote survivorship care.

J Intensive Care Soc

January 2025

Department of Physiotherapy, Faculty of Medicine, Dentistry and Health Sciences, School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia.

Digital health refers to the field of using and developing technology to improve health outcomes. Digital health and digital health interventions (DHIs) within the area of intensive care and critical illness survivorship are rapidly evolving. Digital health interventions refer to technologies in clinical interventional format.

View Article and Find Full Text PDF

Introduction The pediatric intensive care unit (PICU) is a specialized area for treating critically ill infants and children. However, some of these children may experience poor outcomes, including death. However, it is necessary to predict the prognosis for critically ill patients as early as possible to commence triage as well as an early and effective intervention to prevent mortality.

View Article and Find Full Text PDF

Extension of an ICU-based noninvasive model to predict latent shock in the emergency department: an exploratory study.

Front Cardiovasc Med

December 2024

Emergency Center, Hubei Clinical Research Center for Emergency and Resuscitaion, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.

Background: Artificial intelligence (AI) has been widely adopted for the prediction of latent shock occurrence in critically ill patients in intensive care units (ICUs). However, the usefulness of an ICU-based model to predict latent shock risk in an emergency department (ED) setting remains unclear. This study aimed to develop an AI model to predict latent shock risk in patients admitted to EDs.

View Article and Find Full Text PDF

Introduction: The Sequential Organ Failure Assessment (SOFA) score is a widely utilized clinical tool for evaluating the severity of organ failure in critically ill patients and assessing their condition and prognosis in the intensive care unit (ICU). Research has demonstrated that higher SOFA scores are associated with poorer outcomes in these patients. However, the predictive value of the SOFA score for acute kidney injury (AKI), a common complication of diabetic ketoacidosis (DKA), remains uncertain.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!