ArticleJMIR formative research2022
A Free Open-Source Bayesian Vancomycin Dosing App for Adults: Design and Evaluation Study.
Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Comparing the Effectiveness of a Clinical Decision Support Tool in Reducing Pediatric Opioid Dose Calculation Errors: PediPain App vs. Traditional Calculators - A Simulation-Based Randomised Controlled Study.Journal of medical systems · 2024Trial
- Observed Trough-Based Vancomycin Dosing Decisions Versus Model-Predicted Bayesian AUC-Guided Recommendations.Healthcare (Basel, Switzerland) · 2026Article
- Therapeutic Monitoring of Vancomycin and Factors Affecting Survival in ICU Patients with Infections.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Pharmacokinetics and Customized Dosing of Vancomycin in Adult Patients With Hematological Malignancies: Status, Challenges, and Opportunities.Pharmacology research & perspectives · 2026Review
- No Impact of Vancomycin MIC, AUC, or AUC/MIC in Enterococcus faecium Bacteremia.Fundamental & clinical pharmacology · 2025Article
- A Deep Learning-Based Approach for Prediction of Vancomycin Treatment Monitoring: Retrospective Study Among Patients With Critical Illness.JMIR formative research · 2024Article
- Implementing Vancomycin Population Pharmacokinetic Models: An App for Individualized Antibiotic Therapy in Critically Ill Patients.Antibiotics (Basel, Switzerland) · 2023Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIt has been suggested that Bayesian dosing apps can assist in the therapeutic drug monitoring of patients receiving vancomycin. Unfortunately, Bayesian dosing tools are often unaffordable to resource-limited hospitals. Our aim was to improve vancomycin dosing in adults. We created a free and open-source dose adjustment app, VancoCalc, which uses Bayesian inference to aid clinicians in dosing and monitoring of vancomycin.
objectiveThe aim of this paper is to describe the design, development, usability, and evaluation of a free open-source Bayesian vancomycin dosing app, VancoCalc.
methodsThe app build and model fitting process were described. Previously published pharmacokinetic models were used as priors. The ability of the app to predict vancomycin concentrations was performed using a small data set comprising of 52 patients, aged 18 years and over, who received at least 1 dose of intravenous vancomycin and had at least 2 vancomycin concentrations drawn between July 2018 and January 2021 at Lakeridge Health Corporation Ontario, Canada. With these estimated and actual concentrations, median prediction error (bias), median absolute error (accuracy), and root mean square error (precision) were calculated to evaluate the accuracy of the Bayesian estimated pharmacokinetic parameters.
resultsA total of 52 unique patients' initial vancomycin concentrations were used to predict subsequent concentration; 104 total vancomycin concentrations were assessed. The median prediction error was -0.600 ug/mL (IQR -3.06, 2.95), the median absolute error was 3.05 ug/mL (IQR 1.44, 4.50), and the root mean square error was 5.34.
conclusionsWe described a free, open-source Bayesian vancomycin dosing calculator based on revisions of currently available calculators. Based on this small retrospective preliminary sample of patients, the app offers reasonable accuracy and bias, which may be used in everyday practice. By offering this free, open-source app, further prospective validation could be implemented in the near future.
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