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ID 60376
JaLCDOI
フルテキストURL
74_4_365.pdf 1.94 MB
著者
Chuma, Masayuki Clinical Research Center for Developmental Therapeutics, Tokushima University Hospital
Kondo, Masateru Department of Pharmacy, Tokushima University Hospital
Zamami, Yoshito Department of Pharmacy, Tokushima University Hospital
Takechi, Kenshi Clinical Research Center for Developmental Therapeutics, Tokushima University Hospital
Goda, Mitsuhiro Department of Pharmacy, Tokushima University Hospital
Okada, Naoto Department of Pharmacy, Tokushima University Hospital
Shibata, Akitomo Department of Pharmacy, Saiseikai Kumamoto Hospital
Asada, Mizuho Department of Pharmacy, Medical Hospital, Tokyo Medical and Dental University
Oto, Jun Department of Emergency and Critical Care Medicine, Tokushima University Graduate School of Biomedical Sciences
Yanagawa, Hiroaki Clinical Research Center for Developmental Therapeutics, Tokushima University Hospital
Ishizawa, Keisuke Department of Pharmacy, Tokushima University Hospital
抄録
Cystatin C-guided vancomycin (VCM) dosing is useful in critically ill patients. Its usefulness in septic patients with bacterial meningitis remains unknown, as there are no published reports. In this study, we sought to clarify its benefit. Cystatin C was used to guide VCM dosing in a septic bacterial meningitis patient with normal kidney function, according to therapeutic drug monitoring (TDM). Using cystatin C, the Bayesian method-based TDM made optimal VCM dosing possible, and decreased the predicted error (4.85 mg/L) compared to serum creatinine (16.83 mg/L). We concluded TDM of VCM using cystatin C can be considered in sepsis patients with bacterial meningitis with normal kidney function.
キーワード
vancomycin,
therapeutic drug monitoring
cystatin C
bacterial meningitis
sepsis
Amo Type
Case Report
出版物タイトル
Acta Medica Okayama
発行日
2020-08
74巻
4号
出版者
Okayama University Medical School
開始ページ
365
終了ページ
370
ISSN
0386-300X
NCID
AA00508441
資料タイプ
学術雑誌論文
言語
英語
著作権者
CopyrightⒸ 2020 by Okayama University Medical School
論文のバージョン
publisher
査読
有り
PubMed ID
Web of Science KeyUT
NAID