학술논문
Derivation and Validation of a New Equation for Estimating Free Valproate Concentration in Critically Ill Adult Patients.
Document Type
Academic Journal
Author
Liu JT; Department of Pharmacy, Beth Israel Deaconess Medical Center, Boston, MA.; Brown CS; Department of Pharmacy, Mayo Clinic, Rochester, MN.; Mara KC; Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN.; Riker RR; Department of Critical Care Services, Maine Medical Center, Portland, ME.; Tufts University School of Medicine, Boston, MA.; Rabinstein AA; Division of Neurology, Mayo Clinic, Rochester, MN.; Fraser GL; Tufts University School of Medicine, Boston, MA.; May TL; Department of Critical Care Services, Maine Medical Center, Portland, ME.; Tufts University School of Medicine, Boston, MA.; Maine Medical Center Research Institute, Portland, ME.; Armstrong KJ; Department of Critical Care Services, Maine Medical Center, Portland, ME.; Department of Pharmacy, Maine Medical Center, Portland, ME.; Seder DB; Department of Critical Care Services, Maine Medical Center, Portland, ME.; Tufts University School of Medicine, Boston, MA.; Maine Medical Center Research Institute, Portland, ME.; Gagnon DJ; Department of Critical Care Services, Maine Medical Center, Portland, ME.; Maine Medical Center Research Institute, Portland, ME.; Department of Pharmacy, Maine Medical Center, Portland, ME.
Source
Publisher: Wolters Kluwer Health Country of Publication: United States NLM ID: 101746347 Publication Model: eCollection Cited Medium: Internet ISSN: 2639-8028 (Electronic) Linking ISSN: 26398028 NLM ISO Abbreviation: Crit Care Explor Subsets: PubMed not MEDLINE
Subject
Language
English
Abstract
Importance: Protein binding of valproate varies among ICU patients, altering the biologically active free valproate concentration (VPAC). Free VPAC is measured at few laboratories and is often discordant with total VPAC. Existing equations to predict free VPAC are either not validated or are inaccurate in ICU patients.
Objectives: We designed this study to derive and validate a novel equation to predict free VPAC using data from ICU patients and to compare its performance to published equations.
Design: Retrospective cohort study.
Setting: Two academic medical centers.
Participants: Patients older than 18 years old with concomitant free and total VPACs measured in the ICU were included in the derivation cohort if admitted from 2014 to 2018, and the validation cohort if admitted from 2019 to 2022.
Main Outcomes and Measures: Multivariable linear regression was used to derive an equation to predict free VPAC. Modified Bland-Altman plots and the rate of therapeutic concordance between the measured and predicted free VPAC were compared.
Results: Demographics, median free and total VPACs, and valproate free fractions were similar among 115 patients in the derivation cohort and 147 patients in the validation cohort. The Bland-Altman plots showed the new equation performed better (bias, 0.3 [95% limits of agreement, -13.6 to 14.2]) than the Nasreddine (-9.2 [-26.5 to 8.2]), Kodama (-9.7 [-30.0 to 10.7]), Conde Giner (-7.9 [-24.9 to 9.1]), and Parent (-9.9 [-30.7 to 11.0]) equations, and similar to Doré (-2.0 [-16.0 to 11.9]). The Doré and new equations had the highest therapeutic concordance rate (73%).
Conclusions and Relevance: For patients at risk of altered protein binding such as ICU patients, existing equations to predict free VPAC are discordant with measured free VPAC. A new equation had low bias but was imprecise. External validation should be performed to improve its precision and generalizability. Until then, monitoring free valproate is recommended during critical illness.
(Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)
Objectives: We designed this study to derive and validate a novel equation to predict free VPAC using data from ICU patients and to compare its performance to published equations.
Design: Retrospective cohort study.
Setting: Two academic medical centers.
Participants: Patients older than 18 years old with concomitant free and total VPACs measured in the ICU were included in the derivation cohort if admitted from 2014 to 2018, and the validation cohort if admitted from 2019 to 2022.
Main Outcomes and Measures: Multivariable linear regression was used to derive an equation to predict free VPAC. Modified Bland-Altman plots and the rate of therapeutic concordance between the measured and predicted free VPAC were compared.
Results: Demographics, median free and total VPACs, and valproate free fractions were similar among 115 patients in the derivation cohort and 147 patients in the validation cohort. The Bland-Altman plots showed the new equation performed better (bias, 0.3 [95% limits of agreement, -13.6 to 14.2]) than the Nasreddine (-9.2 [-26.5 to 8.2]), Kodama (-9.7 [-30.0 to 10.7]), Conde Giner (-7.9 [-24.9 to 9.1]), and Parent (-9.9 [-30.7 to 11.0]) equations, and similar to Doré (-2.0 [-16.0 to 11.9]). The Doré and new equations had the highest therapeutic concordance rate (73%).
Conclusions and Relevance: For patients at risk of altered protein binding such as ICU patients, existing equations to predict free VPAC are discordant with measured free VPAC. A new equation had low bias but was imprecise. External validation should be performed to improve its precision and generalizability. Until then, monitoring free valproate is recommended during critical illness.
(Copyright © 2023 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)