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Establishment of a new initial dose plan for vancomycin using the generalized linear mixed model.
Kourogi, Yasuyuki; Ogata, Kenji; Takamura, Norito; Tokunaga, Jin; Setoguchi, Nao; Kai, Mitsuhiro; Tanaka, Emi; Chiyotanda, Susumu.
Afiliación
  • Kourogi Y; Chiyoda Hospital, Social Medial Corporation Senwakai, Hyuga, Japan.
  • Ogata K; School of Pharmaceutical Sciences, Kyushu University of Health and Welfare, Nobeoka, Japan.
  • Takamura N; School of Pharmaceutical Sciences, Kyushu University of Health and Welfare, Nobeoka, Japan.
  • Tokunaga J; School of Pharmaceutical Sciences, Kyushu University of Health and Welfare, Nobeoka, Japan. noritotaka@phoenix.ac.jp.
  • Setoguchi N; Second Department of Clinical Pharmacy, Graduate School of Clinical Pharmacy, Kyushu University of Health and Welfare, 1714-1 Yoshino, Nobeoka, Miyazaki, 882-8508, Japan. noritotaka@phoenix.ac.jp.
  • Kai M; School of Pharmaceutical Sciences, Kyushu University of Health and Welfare, Nobeoka, Japan.
  • Tanaka E; School of Pharmaceutical Sciences, Kyushu University of Health and Welfare, Nobeoka, Japan.
  • Chiyotanda S; Chiyoda Hospital, Social Medial Corporation Senwakai, Hyuga, Japan.
Theor Biol Med Model ; 14(1): 8, 2017 04 08.
Article en En | MEDLINE | ID: mdl-28388921
BACKGROUND: When administering vancomycin hydrochloride (VCM), the initial dose is adjusted to ensure that the steady-state trough value (Css-trough) remains within the effective concentration range. However, the Css-trough (population mean method predicted value [PMMPV]) calculated using the population mean method (PMM) often deviate from the effective concentration range. In this study, we used the generalized linear mixed model (GLMM) for initial dose planning to create a model that accurately predicts Css-trough, and subsequently assessed its prediction accuracy. METHODS: The study included 46 subjects whose trough values were measured after receiving VCM. We calculated the Css-trough (Bayesian estimate predicted value [BEPV]) from the Bayesian estimates of trough values. Using the patients' medical data, we created models that predict the BEPV and selected the model with minimum information criterion (GLMM best model). We then calculated the Css-trough (GLMMPV) from the GLMM best model and compared the BEPV correlation with GLMMPV and with PMMPV. RESULTS: The GLMM best model was {[0.977 + (males: 0.029 or females: -0.081)] × PMMPV + 0.101 × BUN/adjusted SCr - 12.899 × SCr adjusted amount}. The coefficients of determination for BEPV/GLMMPV and BEPV/PMMPV were 0.623 and 0.513, respectively. CONCLUSION: We demonstrated that the GLMM best model was more accurate in predicting the Css-trough than the PMM.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Vancomicina / Modelos Lineales / Antibacterianos / Modelos Biológicos Tipo de estudio: Prognostic_studies Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Theor Biol Med Model Asunto de la revista: BIOLOGIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Vancomicina / Modelos Lineales / Antibacterianos / Modelos Biológicos Tipo de estudio: Prognostic_studies Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Theor Biol Med Model Asunto de la revista: BIOLOGIA / MEDICINA Año: 2017 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido