Elizabeth W Covington, Jihyun L Chae, Sarah Grace Gunter
{"title":"万古霉素贝叶斯模型在预稳态和稳态浓度下的回顾性研究。","authors":"Elizabeth W Covington, Jihyun L Chae, Sarah Grace Gunter","doi":"10.1177/87551225251362731","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> Bayesian modeling of vancomycin can estimate 24-hour area under the curve (AUC<sub>24</sub>) using pre-steady-state concentrations. Limited literature exists comparing Bayesian AUC<sub>24</sub> calculations derived from steady-state versus pre-steady-state concentrations. <b>Objective:</b> To assess the agreement between vancomycin AUC<sub>24</sub> calculations using pre-steady-state versus steady-state concentrations, employing Bayesian modeling. <b>Methods:</b> This retrospective within-subjects cohort study included patients with at least 1 pre-steady-state and 1 steady-state vancomycin concentration. Patients with age >100 years, weight <40 kg, height <60 inches, or renal dysfunction were excluded. The steady-state AUC<sub>24</sub> from dosing software was documented with and without hiding steady-state levels from calculations. The primary outcome was agreement between AUC<sub>24</sub> without levels hidden compared with AUC<sub>24</sub> with steady-state levels hidden from analysis. Secondary outcomes included the agreement between AUC<sub>24</sub> with pre-steady-state levels hidden and the percentage of patients with matching AUC<sub>24</sub> categories. The AUC<sub>24</sub> agreement was evaluated via Bland-Altman plot and bias via linear regression. Statistical tests were performed using SPSS statistics software (IBM Corp). <b>Results:</b> A total of 93 patients were included. The mean difference in AUC<sub>24</sub> compared to AUC<sub>24</sub> with steady-state levels hidden was 8.8 mg*h/L, and with pre-steady-state levels hidden, it was -3.7 mg*h/L. Linear regression analysis indicated a proportional bias when steady-state levels were hidden (β = 0.22; <i>P</i> = 0.038) but not when pre-steady-state levels were hidden. Category mismatch occurred more often when steady-state levels were hidden vs when pre-steady-state levels were hidden (26% vs 8%; <i>P</i> < 0.001). <b>Conclusion and Relevance:</b> The study demonstrated overall agreement between AUC<sub>24</sub> compared to AUC<sub>24</sub> with steady-state levels hidden. The mean differences in AUC<sub>24</sub> estimates were small, no matter which level was hidden, although tighter limits of agreement were observed when steady-state levels were utilized in Bayesian calculations. Further research with larger sample sizes is necessary.</p>","PeriodicalId":16796,"journal":{"name":"Journal of Pharmacy Technology","volume":" ","pages":"87551225251362731"},"PeriodicalIF":1.3000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370660/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Retrospective Within-Subjects Analysis of Vancomycin Bayesian Modeling With Pre-steady-State vs Steady-State Concentrations.\",\"authors\":\"Elizabeth W Covington, Jihyun L Chae, Sarah Grace Gunter\",\"doi\":\"10.1177/87551225251362731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Background:</b> Bayesian modeling of vancomycin can estimate 24-hour area under the curve (AUC<sub>24</sub>) using pre-steady-state concentrations. Limited literature exists comparing Bayesian AUC<sub>24</sub> calculations derived from steady-state versus pre-steady-state concentrations. <b>Objective:</b> To assess the agreement between vancomycin AUC<sub>24</sub> calculations using pre-steady-state versus steady-state concentrations, employing Bayesian modeling. <b>Methods:</b> This retrospective within-subjects cohort study included patients with at least 1 pre-steady-state and 1 steady-state vancomycin concentration. Patients with age >100 years, weight <40 kg, height <60 inches, or renal dysfunction were excluded. The steady-state AUC<sub>24</sub> from dosing software was documented with and without hiding steady-state levels from calculations. The primary outcome was agreement between AUC<sub>24</sub> without levels hidden compared with AUC<sub>24</sub> with steady-state levels hidden from analysis. Secondary outcomes included the agreement between AUC<sub>24</sub> with pre-steady-state levels hidden and the percentage of patients with matching AUC<sub>24</sub> categories. The AUC<sub>24</sub> agreement was evaluated via Bland-Altman plot and bias via linear regression. Statistical tests were performed using SPSS statistics software (IBM Corp). <b>Results:</b> A total of 93 patients were included. The mean difference in AUC<sub>24</sub> compared to AUC<sub>24</sub> with steady-state levels hidden was 8.8 mg*h/L, and with pre-steady-state levels hidden, it was -3.7 mg*h/L. Linear regression analysis indicated a proportional bias when steady-state levels were hidden (β = 0.22; <i>P</i> = 0.038) but not when pre-steady-state levels were hidden. Category mismatch occurred more often when steady-state levels were hidden vs when pre-steady-state levels were hidden (26% vs 8%; <i>P</i> < 0.001). <b>Conclusion and Relevance:</b> The study demonstrated overall agreement between AUC<sub>24</sub> compared to AUC<sub>24</sub> with steady-state levels hidden. The mean differences in AUC<sub>24</sub> estimates were small, no matter which level was hidden, although tighter limits of agreement were observed when steady-state levels were utilized in Bayesian calculations. Further research with larger sample sizes is necessary.</p>\",\"PeriodicalId\":16796,\"journal\":{\"name\":\"Journal of Pharmacy Technology\",\"volume\":\" \",\"pages\":\"87551225251362731\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12370660/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Pharmacy Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/87551225251362731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Pharmacy Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/87551225251362731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
A Retrospective Within-Subjects Analysis of Vancomycin Bayesian Modeling With Pre-steady-State vs Steady-State Concentrations.
Background: Bayesian modeling of vancomycin can estimate 24-hour area under the curve (AUC24) using pre-steady-state concentrations. Limited literature exists comparing Bayesian AUC24 calculations derived from steady-state versus pre-steady-state concentrations. Objective: To assess the agreement between vancomycin AUC24 calculations using pre-steady-state versus steady-state concentrations, employing Bayesian modeling. Methods: This retrospective within-subjects cohort study included patients with at least 1 pre-steady-state and 1 steady-state vancomycin concentration. Patients with age >100 years, weight <40 kg, height <60 inches, or renal dysfunction were excluded. The steady-state AUC24 from dosing software was documented with and without hiding steady-state levels from calculations. The primary outcome was agreement between AUC24 without levels hidden compared with AUC24 with steady-state levels hidden from analysis. Secondary outcomes included the agreement between AUC24 with pre-steady-state levels hidden and the percentage of patients with matching AUC24 categories. The AUC24 agreement was evaluated via Bland-Altman plot and bias via linear regression. Statistical tests were performed using SPSS statistics software (IBM Corp). Results: A total of 93 patients were included. The mean difference in AUC24 compared to AUC24 with steady-state levels hidden was 8.8 mg*h/L, and with pre-steady-state levels hidden, it was -3.7 mg*h/L. Linear regression analysis indicated a proportional bias when steady-state levels were hidden (β = 0.22; P = 0.038) but not when pre-steady-state levels were hidden. Category mismatch occurred more often when steady-state levels were hidden vs when pre-steady-state levels were hidden (26% vs 8%; P < 0.001). Conclusion and Relevance: The study demonstrated overall agreement between AUC24 compared to AUC24 with steady-state levels hidden. The mean differences in AUC24 estimates were small, no matter which level was hidden, although tighter limits of agreement were observed when steady-state levels were utilized in Bayesian calculations. Further research with larger sample sizes is necessary.
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