- 著者
- Akihiro Sonoda Yoshitaka Iwashita Yukina Takada Ryu Hamazono Kazuhisa Ishida Hiroshi Imamura
- 出版者
- The Pharmaceutical Society of Japan
- 雑誌
- Biological and Pharmaceutical Bulletin (ISSN:09186158)
- 巻号頁・発行日
- vol.45, no.6, pp.763-769, 2022-06-01 (Released:2022-06-01)
- 参考文献数
- 31
- 被引用文献数
- 1
An administration plan for vancomycin (VCM) in bedridden elderly patients has not been established. This retrospective study aimed to evaluate the prediction accuracy of the area under the concentration–time curve (AUC) of VCM by the Bayesian approach using creatinine-based equations of estimated kidney function in such patients. Kidney function was estimated using the Japanese equation of estimated glomerular filtration rate (eGFR) and the Cockcroft–Gault equation of estimated creatinine clearance (eCCr). eCCr (serum creatinine (SCr) + 0.2) was calculated by substituting the SCr level +0.2 mg/dL into the Cockcroft–Gault equation. For eGFR/0.789, eGFR, eCCr, and eCCr (SCr + 0.2), the AUC values were calculated by the Bayesian approach using the therapeutic drug monitoring (TDM) software, BMs-Pod (ver 8.06) and denoted as AUCeGFR/0.789, AUCeGFR, AUCeCCr, and AUCeCCr (SCr + 0.2) respectively. The reference AUC (AUCREF) was calculated by applying VCM’s peak and trough steady-state concentrations to first-order pharmacokinetic equations. The medians (range) of AUCeGFR/0.789/AUCREF, AUCeGFR/AUCREF, AUCeCCr/AUCREF, and AUCeCCr (SCr + 0.2)/AUCREF were 0.88 (0.74–0.93), 0.90 (0.79–1.04), 0.92 (0.81–1.07), and 1.00 (0.88–1.11), respectively. Moreover, the percentage of patients within 10% of the AUCREF, defined as |Bayesian-estimated AUC − AUCREF| < AUCREF × 0.1, was the highest (86%) in AUCeCCr (SCr + 0.2). These results suggest that the Bayesian approach using eCCr (SCr + 0.2) has the highest prediction accuracy for the AUCREF in bedridden elderly patients. Although further studies are required with more accurate determination methods of the CCr and AUC, our findings highlight the potential of eCCr (SCr + 0.2) for estimating VCM’s AUC by the Bayesian approach in such patients.