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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Autores principales:	Bryce Yapps, Sungtae Shin, Ramin Bighamian, Jill Thorsen, Colleen Arsenault, Sadeq A. Quraishi, Jin-Oh Hahn, Andrew T. Reisner
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bc974ca9cee54447b17d51c39558d6d0
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spelling	oai:doaj.org-article:bc974ca9cee54447b17d51c39558d6d02021-12-02T12:31:54ZHypotension in ICU Patients Receiving Vasopressor Therapy10.1038/s41598-017-08137-02045-2322https://doaj.org/article/bc974ca9cee54447b17d51c39558d6d02017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08137-0https://doaj.org/toc/2045-2322Abstract 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.Bryce YappsSungtae ShinRamin BighamianJill ThorsenColleen ArsenaultSadeq A. QuraishiJin-Oh HahnAndrew T. ReisnerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q 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
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.
format	article
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
title	Hypotension in ICU Patients Receiving Vasopressor Therapy
title_short	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_sort	hypotension in icu patients receiving vasopressor therapy
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/bc974ca9cee54447b17d51c39558d6d0
work_keys_str_mv	AT bryceyapps hypotensioninicupatientsreceivingvasopressortherapy AT sungtaeshin hypotensioninicupatientsreceivingvasopressortherapy AT raminbighamian hypotensioninicupatientsreceivingvasopressortherapy AT jillthorsen hypotensioninicupatientsreceivingvasopressortherapy AT colleenarsenault hypotensioninicupatientsreceivingvasopressortherapy AT sadeqaquraishi hypotensioninicupatientsreceivingvasopressortherapy AT jinohhahn hypotensioninicupatientsreceivingvasopressortherapy AT andrewtreisner hypotensioninicupatientsreceivingvasopressortherapy
_version_	1718394239480496128

Hypotension in ICU Patients Receiving Vasopressor Therapy

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