Piperacillin-Tazobactam in Intensive Care Units: A Review of Population Pharmacokinetic Analyses.
Ibrahim El-HaffafJean-Alexandre CaissyAmélie MarsotPublished in: Clinical pharmacokinetics (2021)
Piperacillin-tazobactam is a potent β-lactam/β-lactamase inhibitor antibiotic commonly prescribed in the intensive care unit setting. Admitted patients often show large variability in treatment response due to multiple pathophysiological changes present in this population that alter the drug's pharmacokinetics. This review summarizes the population pharmacokinetic models developed for piperacillin-tazobactam and provides comprehensive data on current dosing strategies while identifying significant covariates in critically ill patients. A literature search on the PubMed database was conducted, from its inception to July 2020. Relevant articles were retained if they met the defined inclusion/exclusion criteria. A total of ten studies, published between 2009 and 2020, were eligible. One- and two-compartment models were used in two and eight studies, respectively. The lowest estimated piperacillin clearance value was 3.12 L/h, and the highest value was 19.9 L/h. The estimations for volume of distribution varied between 11.2 and 41.2 L. Tazobactam clearance values ranged between 5.1 and 6.78 L/h, and tazobactam volume of distribution values ranged between 17.5 and 76.1 L. The most frequent covariates were creatinine clearance and body weight, each present in four studies. Almost all studies used an exponential approach for the interindividual variability. The highest variability was observed in piperacillin central volume of distribution, at a value of 75.0%. Simulations showed that continuous or extended infusion methods performed better than intermittent administration to achieve appropriate pharmacodynamic targets. This review synthesizes important pharmacokinetic elements for piperacillin-tazobactam in an intensive care unit setting. This will help clinicians better understand changes in the drug's pharmacokinetic parameters in this specific population.
Keyphrases
- gram negative
- intensive care unit
- body weight
- case control
- multidrug resistant
- escherichia coli
- systematic review
- end stage renal disease
- ejection fraction
- adverse drug
- palliative care
- emergency department
- metabolic syndrome
- mechanical ventilation
- randomized controlled trial
- machine learning
- anti inflammatory
- deep learning
- meta analyses