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Predictive performance of pharmacokinetic models for target concentration-controlled infusion of cefoxitin as a prophylactic antibiotic in patients with colorectal surgery.

Hyun-Uk KangKyung Mi KimJae Moon ChoiEun-Kyung LeeByung-Moon ChoiGyu-Jeong NohSeok Hwan Lee
Published in: Clinical and experimental pharmacology & physiology (2022)
We aimed to evaluate the predictive performance of previously constructed free (C free ) and total (C total ) cefoxitin pharmacokinetic models and the possibility of administering cefoxitin via the target-controlled infusion (TCI) method in clinical practice. Two external validation studies (N = 31 for C free model, N = 30 for C total model) were conducted sequentially. Cefoxitin (2 g) was dissolved in 50 mL of normal saline to give a concentration of 40 mg mL -1 . Before skin incision, cefoxitin was infused with a TCI syringe pump. Target concentrations of free concentration and total concentration were set to 25 and 80 μg mL -1 , respectively, which were administered throughout the surgery. Three arterial blood samples were collected to measure the total and free plasma concentrations of cefoxitin at 30, 60 and 120 min, after the start of cefoxitin administration. The predictive performance was evaluated using four parameters: inaccuracy, divergence, bias and wobble. The pooled median (95% confidence interval) biases and inaccuracies were - 45.9 (-47.3 to -44.5) and 45.9 (44.5 to 47.3) for C free model (Choi_F model), and - 16.6 (-18.4 to -14.8) and 18.5 (16.7 to 20.2) for C total model (Choi_T old model), respectively. The predictive performance of the newly constructed model (Choi_T new model), developed by adding the total concentration data measured in the external validation, was better than that of the Choi_T old model. Models constructed with total concentration data were suitable for clinical use. Administering cefoxitin using the TCI method in patients maintained the free concentration above the minimal inhibitory concentration (MIC) breakpoints of the major pathogens causing surgical site infection throughout the operation period.
Keyphrases
  • low dose
  • clinical practice
  • minimally invasive
  • coronary artery disease
  • newly diagnosed
  • surgical site infection
  • machine learning
  • percutaneous coronary intervention
  • antimicrobial resistance