B Vadher1, D L Patterson, M Leaning. 1. Clinical and Academic Department of Cardiovascular Medicine, Whittington Hospital, London, N19 5NF, UK.
Abstract
AIMS: A pharmacokinetic/pharmacodynamic model, with Bayesian parameter estimation, was used to retrospectively predict the daily International Normalized Ratios (INRs) and the maintenance doses during the initiation of warfarin therapy in 74 inpatients. METHODS: INRs and maintenance doses predicted by the model were compared with the actual INRs and the eventual maintenance dose. Cases with drugs or medical conditions interacting with warfarin or receiving concurrent heparin therapy were not excluded. As the study was retrospective, model predictions of the maintenance dose were not those that were administered. Mean prediction error (MPE) and percentage absolute prediction errors (PAPE) were used to assess the model predictions. RESULTS: INR MPE ranged from -0.07 to 0.06 and median PAPE from 10% to 20%. Dose MPE ranged from -0.7 to 0.17 mg and median PAPE from 16.7% to 37.5%. Accurate and precise dose predictions were obtained after 3 or more INR feedback's. CONCLUSIONS: This study shows that the model can accurately predict daily INRs and the maintenance dose in this sample of cases. The model can be incorporated into computer decision-support systems for warfarin therapy and may lead to improvement in the initiation of warfarin therapy.
AIMS: A pharmacokinetic/pharmacodynamic model, with Bayesian parameter estimation, was used to retrospectively predict the daily International Normalized Ratios (INRs) and the maintenance doses during the initiation of warfarin therapy in 74 inpatients. METHODS: INRs and maintenance doses predicted by the model were compared with the actual INRs and the eventual maintenance dose. Cases with drugs or medical conditions interacting with warfarin or receiving concurrent heparin therapy were not excluded. As the study was retrospective, model predictions of the maintenance dose were not those that were administered. Mean prediction error (MPE) and percentage absolute prediction errors (PAPE) were used to assess the model predictions. RESULTS: INR MPE ranged from -0.07 to 0.06 and median PAPE from 10% to 20%. Dose MPE ranged from -0.7 to 0.17 mg and median PAPE from 16.7% to 37.5%. Accurate and precise dose predictions were obtained after 3 or more INR feedback's. CONCLUSIONS: This study shows that the model can accurately predict daily INRs and the maintenance dose in this sample of cases. The model can be incorporated into computer decision-support systems for warfarin therapy and may lead to improvement in the initiation of warfarin therapy.