Determining steady-state trough range in vancomycin drug dosing using machine learning.
J Crit Care
; 82: 154784, 2024 Aug.
Article
in En
| MEDLINE
| ID: mdl-38503008
ABSTRACT
BACKGROUND:
Vancomycin is a renally eliminated, nephrotoxic, glycopeptide antibiotic with a narrow therapeutic window, widely used in intensive care units (ICU). We aimed to predict the risk of inappropriate vancomycin trough levels and appropriate dosing for each ICU patient.METHODS:
Observed vancomycin trough levels were categorized into sub-therapeutic, therapeutic, and supra-therapeutic levels to train and compare different classification models. We included adult ICU patients (≥ 18 years) with at least one vancomycin concentration measurement during hospitalization at Mayo Clinic, Rochester, MN, from January 2007 to December 2017.RESULT:
The final cohort consisted of 5337 vancomycin courses. The XGBoost models outperformed other machine learning models with the AUC-ROC of 0.85 and 0.83, specificity of 53% and 47%, and sensitivity of 94% and 94% for sub- and supra-therapeutic categories, respectively. Kinetic estimated glomerular filtration rate and other creatinine-based measurements, vancomycin regimen (dose and interval), comorbidities, body mass index, age, sex, and blood pressure were among the most important variables in the models.CONCLUSION:
We developed models to assess the risk of sub- and supra-therapeutic vancomycin trough levels to improve the accuracy of drug dosing in critically ill patients.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Vancomycin
/
Machine Learning
/
Intensive Care Units
/
Anti-Bacterial Agents
Limits:
Adult
/
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Language:
En
Journal:
J Crit Care
Journal subject:
TERAPIA INTENSIVA
Year:
2024
Document type:
Article
Country of publication:
United States