BACKGROUND: Vasoactive drug infusion rates are titrated to achieve a desired effect, e.g., mean arterial blood pressure (MAP), rather than using infusion rates based on body weight. The purpose of this study is to evaluate a method to automatically identify a patient's sensitivity to sodium-nitroprusside, dobutamine or dopamine and to evaluate, whether an advisory system that predicts MAP 5 min in the future enhances a clinician's ability to titrate sodium-nitroprusside infusions. METHODS: We used published models implemented in MATLAB to simulate the response of 100 individual patients to infusions of sodium-nitroprusside, dopamine and dobutamine. The simulated patient's sensitivity to the three drugs was identified using an adaptive filter approach, where MAP was altered in a binary stepwise fashion. Next, 9 nurses were asked to control the MAP of 6 of the simulated patients. For half of the patients, we used the identified sensitivity to predict and display MAP 5 min into the future. RESULTS: Identifying each individual patient's sensitivity improved the accuracy of the MAP prediction by 75% for sodium-nitroprusside, 82% for dopamine and 52% for dobutamine over the MAP prediction based on an "average" patient's sensitivity. The advisory system shortened the median time to reach the desired MAP from 10.2 to 4.1 min, decreased the median number of infusion rate changes from 6 to 4, and resulted in a significant reduction of mental workload and effort. DISCUSSION: Patient-specific drug sensitivity identifi- cation significantly improved the prediction of future MAP. By predicting and displaying the expected MAP 5 min in the future, the advisory system helped nurses titrate faster, reduced their perceived workload and might improve patient safety.
BACKGROUND: Vasoactive drug infusion rates are titrated to achieve a desired effect, e.g., mean arterial blood pressure (MAP), rather than using infusion rates based on body weight. The purpose of this study is to evaluate a method to automatically identify a patient's sensitivity to sodium-nitroprusside, dobutamine or dopamine and to evaluate, whether an advisory system that predicts MAP 5 min in the future enhances a clinician's ability to titrate sodium-nitroprusside infusions. METHODS: We used published models implemented in MATLAB to simulate the response of 100 individual patients to infusions of sodium-nitroprusside, dopamine and dobutamine. The simulated patient's sensitivity to the three drugs was identified using an adaptive filter approach, where MAP was altered in a binary stepwise fashion. Next, 9 nurses were asked to control the MAP of 6 of the simulated patients. For half of the patients, we used the identified sensitivity to predict and display MAP 5 min into the future. RESULTS: Identifying each individual patient's sensitivity improved the accuracy of the MAP prediction by 75% for sodium-nitroprusside, 82% for dopamine and 52% for dobutamine over the MAP prediction based on an "average" patient's sensitivity. The advisory system shortened the median time to reach the desired MAP from 10.2 to 4.1 min, decreased the median number of infusion rate changes from 6 to 4, and resulted in a significant reduction of mental workload and effort. DISCUSSION: Patient-specific drug sensitivity identifi- cation significantly improved the prediction of future MAP. By predicting and displaying the expected MAP 5 min in the future, the advisory system helped nurses titrate faster, reduced their perceived workload and might improve patient safety.