Hypotension in ICU Patients Receiving Vasopressor Therapy
Abstract Vasopressor 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. Retrospect...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2017-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-017-08137-0 |
| _version_ | 1818405784440012800 |
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| author | Bryce Yapps Sungtae Shin Ramin Bighamian Jill Thorsen Colleen Arsenault Sadeq A. Quraishi Jin-Oh Hahn Andrew T. Reisner |
| author_facet | Bryce Yapps Sungtae Shin Ramin Bighamian Jill Thorsen Colleen Arsenault Sadeq A. Quraishi Jin-Oh Hahn Andrew T. Reisner |
| author_sort | Bryce Yapps |
| collection | DOAJ |
| description | Abstract Vasopressor 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. |
| first_indexed | 2024-12-14T09:01:33Z |
| format | Article |
| id | doaj.art-bc974ca9cee54447b17d51c39558d6d0 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-14T09:01:33Z |
| publishDate | 2017-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-bc974ca9cee54447b17d51c39558d6d02022-12-21T23:08:48ZengNature PortfolioScientific Reports2045-23222017-08-017111010.1038/s41598-017-08137-0Hypotension in ICU Patients Receiving Vasopressor TherapyBryce Yapps0Sungtae Shin1Ramin Bighamian2Jill Thorsen3Colleen Arsenault4Sadeq A. Quraishi5Jin-Oh Hahn6Andrew T. Reisner7Department of Mechanical Engineering, University of MarylandDepartment of Mechanical Engineering, University of MarylandDepartment of Mechanical Engineering, University of MarylandDepartment of Emergency Medicine, Massachusetts General HospitalDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, and Harvard Medical SchoolDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, and Harvard Medical SchoolDepartment of Mechanical Engineering, University of MarylandDepartment of Emergency Medicine, Massachusetts General HospitalAbstract Vasopressor 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.https://doi.org/10.1038/s41598-017-08137-0 |
| spellingShingle | Bryce Yapps Sungtae Shin Ramin Bighamian Jill Thorsen Colleen Arsenault Sadeq A. Quraishi Jin-Oh Hahn Andrew T. Reisner Hypotension in ICU Patients Receiving Vasopressor Therapy Scientific Reports |
| title | Hypotension in ICU Patients Receiving Vasopressor Therapy |
| title_full | Hypotension in ICU Patients Receiving Vasopressor Therapy |
| title_fullStr | Hypotension in ICU Patients Receiving Vasopressor Therapy |
| title_full_unstemmed | Hypotension in ICU Patients Receiving Vasopressor Therapy |
| title_short | Hypotension in ICU Patients Receiving Vasopressor Therapy |
| title_sort | hypotension in icu patients receiving vasopressor therapy |
| url | https://doi.org/10.1038/s41598-017-08137-0 |
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