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Predictive Factors of Piperacillin Exposure and the Impact on Target Attainment after Continuous Infusion Administration to Critically Ill Patients.

Javier Martínez-CasanovaErika Esteve-PitarchHelena Colom-CodinaVíctor Daniel Gumucio-SanguinoSara Cobo-SacristánEvelyn ShawKristel Maisterra-SantosJoan Sabater-RieraXosé L Pérez-FernandezRaül Rigo-BonninFe Tubau-QuintanoJordi CarratalaAriadna Padullés-Zamora
Published in: Antibiotics (Basel, Switzerland) (2023)
Critically ill patients undergo significant pathophysiological changes that affect antibiotic pharmacokinetics. Piperacillin/tazobactam administered by continuous infusion (CI) improves pharmacokinetic/pharmacodynamic (PK/PD) target attainment. This study aimed to characterize piperacillin PK after CI administration of piperacillin/tazobactam in critically ill adult patients with preserved renal function and to determine the empirical optimal dosing regimen. A total of 218 piperacillin concentrations from 106 patients were simultaneously analyzed through the population PK approach. A two-compartment linear model best described the data. Creatinine clearance (CL CR ) estimated by CKD-EPI was the covariate, the most predictive factor of piperacillin clearance (CL) interindividual variability. The mean (relative standard error) parameter estimates for the final model were: CL: 12.0 L/h (6.03%); central and peripheral compartment distribution volumes: 20.7 L (8.94%) and 62.4 L (50.80%), respectively; intercompartmental clearance: 4.8 L/h (26.4%). For the PK/PD target of 100% f T >1×MIC , 12 g of piperacillin provide a probability of target attainment > 90% for MIC < 16 mg/L, regardless of CL CR , but higher doses are needed for MIC = 16 mg/L when CL CR > 100 mL/min. For 100% f T >4×MIC , the highest dose (24 g/24 h) was not sufficient to ensure adequate exposure, except for MICs of 1 and 4 mg/L. Our model can be used as a support tool for initial dose guidance and during therapeutic drug monitoring.
Keyphrases
  • end stage renal disease
  • chronic kidney disease
  • ejection fraction
  • low dose
  • gram negative
  • peritoneal dialysis
  • machine learning
  • prognostic factors
  • multidrug resistant
  • artificial intelligence
  • metabolic syndrome