Predicting Blood Pressure After Nitroglycerin Infusion Dose Titration in Critical Care Units

Abstract

Critical care nurses use physiological indicators, such as blood pressure, to guide their decision-making regarding the titration of nitroglycerin infusions. A retrospective study was conducted to determine the accuracy of systolic blood pressure predictions during nitroglycerin infusions. Data were extracted from the publicly accessible eICU program database. The accuracy of a linear model, least absolute shrinkage and selection operator, ridge regression, and a stacked ensemble model trained using the AutoGluon-Tabular framework were investigated. A persistence model, where the future value in a time series is predicted as equal to its preceding value, was used as the baseline comparison for model accuracy. Internal-external validation was used to examine if heterogeneity among hospitals could contribute to model performance. The sample consisted of 827 patients and 2541 nitroglycerin dose titrations with corresponding systolic blood pressure measurements. The root-mean-square error on the test set for the stacked ensemble model developed using the AutoGluon-Tabular framework was the lowest of all models at 15.3 mm Hg, equating to a 22% improvement against the baseline. Internal-external validation revealed consistent accuracy across hospitals. Further studies are needed to determine the impact of using systolic blood pressure predictions to inform nurses' clinical decision-making regarding nitroglycerin infusion titration in critical care.