Yapps, BryceShin, SungtaeBighamian, RaminThorsen, JillArsenault, ColleenQuraishi, SadeqHahn, Jin-OhReisner, Andrew2017-11-212017Yapps, Bryce, Sungtae Shin, Ramin Bighamian, Jill Thorsen, Colleen Arsenault, Sadeq A. Quraishi, Jin-Oh Hahn, and Andrew T. Reisner. 2017. “Hypotension in ICU Patients Receiving Vasopressor Therapy.” Scientific Reports 7 (1): 8551. doi:10.1038/s41598-017-08137-0. http://dx.doi.org/10.1038/s41598-017-08137-0.http://nrs.harvard.edu/urn-3:HUL.InstRepos:34375249Vasopressor infusion (VPI) is used to treat hypotension in an ICU. We studied compliance with blood pressure (BP) goals during VPI and whether a statistical model might be efficacious for advance warning of impending hypotension, compared with a basic hypotension threshold alert. Retrospective data were obtained from a public database. Studying adult ICU patients receiving VPI at submaximal dosages, we analyzed characteristics of sustained hypotension episodes (>15 min) and then developed a logistic regression model to predict hypotension episodes using input features related to BP trends. The model was then validated with prospective data. In the retrospective dataset, 102-of-215 ICU stays experienced >1 hypotension episode (median of 2.5 episodes per day in this subgroup). When trained with 75% of retrospective dataset, testing with the remaining 25% of the dataset showed that the model and the threshold alert detected 99.6% and 100% of the episodes, respectively, with median advance forecast times (AFT) of 12 and 0 min. In a second, prospective dataset, the model detected 100% of 26 episodes with a median AFT of 22 min. In conclusion, episodes of hypotension were common during VPI in the ICU. A logistic regression model using BP temporal trend features predicted the episodes before their onset.en-USJournal Article2017-11-2110.1038/s41598-017-08137-0