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Comparison of area under the curve for vancomycin from one- and two-compartment models using sparse data.

Nyein Hsu MaungJanthima MethaneethornThitima WattanavijitkulTatta Sriboonruang
Published in: European journal of hospital pharmacy : science and practice (2021)
Regardless of statistically significant differences between AUCs from one- and two-compartment models, the level of difference was acceptable from the clinical perspective, being <17% in models from peak-trough data. Therefore, both one- and two-compartment models with sparse data having at least a pair of peak-trough data per patient could be reliable for predicting AUC. Furthermore, AUCs of the one-compartment model from trough-only data did not show a significant difference from the AUCref. Hence, one-compartment models developed from trough-only data could be useful for predicting AUC when models with rich data are not available for the intended population. However, it is suggested that the use of the two-compartment model built from trough-only data should be avoided.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • methicillin resistant staphylococcus aureus