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The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA

The AUC(0–24) is the most accurate way to track the vancomycin level while the C(min) is not an accurate surrogate. Most hospitals in Saudi Arabia are under-practicing the AUC-guided vancomycin dosing and monitoring. No previous work has been conducted to evaluate such practice in the whole kingdom....

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Autores principales: Alzahrani, Abdullah M., Naeem, Anjum, Alzhrani, Rami M., Harbi, Manar A., Alghamdi, Sarah A., Karim, Shahid, Ali, Ahmed S., Alsenaini, Ghusun, Hasan, Hani, Alkatheeri, Ayed A., Basudan, Samah S., Alzahrani, Yahya A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914540/
https://www.ncbi.nlm.nih.gov/pubmed/36766937
http://dx.doi.org/10.3390/healthcare11030362
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author Alzahrani, Abdullah M.
Naeem, Anjum
Alzhrani, Rami M.
Harbi, Manar A.
Alghamdi, Sarah A.
Karim, Shahid
Ali, Ahmed S.
Alsenaini, Ghusun
Hasan, Hani
Alkatheeri, Ayed A.
Basudan, Samah S.
Alzahrani, Yahya A.
author_facet Alzahrani, Abdullah M.
Naeem, Anjum
Alzhrani, Rami M.
Harbi, Manar A.
Alghamdi, Sarah A.
Karim, Shahid
Ali, Ahmed S.
Alsenaini, Ghusun
Hasan, Hani
Alkatheeri, Ayed A.
Basudan, Samah S.
Alzahrani, Yahya A.
author_sort Alzahrani, Abdullah M.
collection PubMed
description The AUC(0–24) is the most accurate way to track the vancomycin level while the C(min) is not an accurate surrogate. Most hospitals in Saudi Arabia are under-practicing the AUC-guided vancomycin dosing and monitoring. No previous work has been conducted to evaluate such practice in the whole kingdom. The current study objective is to calculate the AUC(0–24) using the Bayesian dosing software (PrecisePK), identify the probability of patients who receive the optimum dose of vancomycin, and evaluate the accuracy and precision of the Bayesian platform. This retrospective study was conducted at King Abdulaziz medical city, Jeddah. All adult patients treated with vancomycin were included. Pediatric patients, critically ill patients requiring ICU admission, patients with acute renal failure or undergoing dialysis, and febrile neutropenic patients were excluded. The AUC(0–24) was predicted using the PrecisePK platform based on the Bayesian principle. The two-compartmental model by Rodvold et al. in this platform and patients’ dose data were utilized to calculate the AUC(0–24) and trough level. Among 342 patients included in the present study, the mean of the estimated vancomycin AUC(0–24) by the posterior model of PrecisePK was 573 ± 199.6 mg, and the model had a bias of 16.8%, whereas the precision was 2.85 mg/L. The target AUC(0–24) (400 to 600 mg·h/L) and measured trough (10 to 20 mg/L) were documented in 127 (37.1%) and 185 (54%), respectively. Furthermore, the result demonstrated an increase in odds of AUC(0–24) > 600 mg·h/L among trough level 15–20 mg/L group (OR = 13.2, p < 0.05) as compared with trough level 10–14.9 mg/L group. In conclusion, the discordance in the AUC(0–24) ratio and measured trough concentration may jeopardize patient safety, and implantation of the Bayesian approach as a workable alternative to the traditional trough method should be considered.
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spelling pubmed-99145402023-02-11 The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA Alzahrani, Abdullah M. Naeem, Anjum Alzhrani, Rami M. Harbi, Manar A. Alghamdi, Sarah A. Karim, Shahid Ali, Ahmed S. Alsenaini, Ghusun Hasan, Hani Alkatheeri, Ayed A. Basudan, Samah S. Alzahrani, Yahya A. Healthcare (Basel) Article The AUC(0–24) is the most accurate way to track the vancomycin level while the C(min) is not an accurate surrogate. Most hospitals in Saudi Arabia are under-practicing the AUC-guided vancomycin dosing and monitoring. No previous work has been conducted to evaluate such practice in the whole kingdom. The current study objective is to calculate the AUC(0–24) using the Bayesian dosing software (PrecisePK), identify the probability of patients who receive the optimum dose of vancomycin, and evaluate the accuracy and precision of the Bayesian platform. This retrospective study was conducted at King Abdulaziz medical city, Jeddah. All adult patients treated with vancomycin were included. Pediatric patients, critically ill patients requiring ICU admission, patients with acute renal failure or undergoing dialysis, and febrile neutropenic patients were excluded. The AUC(0–24) was predicted using the PrecisePK platform based on the Bayesian principle. The two-compartmental model by Rodvold et al. in this platform and patients’ dose data were utilized to calculate the AUC(0–24) and trough level. Among 342 patients included in the present study, the mean of the estimated vancomycin AUC(0–24) by the posterior model of PrecisePK was 573 ± 199.6 mg, and the model had a bias of 16.8%, whereas the precision was 2.85 mg/L. The target AUC(0–24) (400 to 600 mg·h/L) and measured trough (10 to 20 mg/L) were documented in 127 (37.1%) and 185 (54%), respectively. Furthermore, the result demonstrated an increase in odds of AUC(0–24) > 600 mg·h/L among trough level 15–20 mg/L group (OR = 13.2, p < 0.05) as compared with trough level 10–14.9 mg/L group. In conclusion, the discordance in the AUC(0–24) ratio and measured trough concentration may jeopardize patient safety, and implantation of the Bayesian approach as a workable alternative to the traditional trough method should be considered. MDPI 2023-01-27 /pmc/articles/PMC9914540/ /pubmed/36766937 http://dx.doi.org/10.3390/healthcare11030362 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alzahrani, Abdullah M.
Naeem, Anjum
Alzhrani, Rami M.
Harbi, Manar A.
Alghamdi, Sarah A.
Karim, Shahid
Ali, Ahmed S.
Alsenaini, Ghusun
Hasan, Hani
Alkatheeri, Ayed A.
Basudan, Samah S.
Alzahrani, Yahya A.
The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA
title The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA
title_full The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA
title_fullStr The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA
title_full_unstemmed The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA
title_short The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA
title_sort bayesian-based area under the curve of vancomycin by using a single trough level: an evaluation of accuracy and discordance at tertiary care hospital in ksa
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9914540/
https://www.ncbi.nlm.nih.gov/pubmed/36766937
http://dx.doi.org/10.3390/healthcare11030362
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