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Modelling physiological deterioration in post-operative patient vital-sign data

Patients who undergo upper-gastrointestinal surgery have a high incidence of post-operative complications, often requiring admission to the intensive care unit several days after surgery. A dataset comprising observational vital-sign data from 171 post-operative patients taking part in a two-phase c...

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Autores principales: Pimentel, Marco A. F., Clifton, David A., Clifton, Lei, Watkinson, Peter J., Tarassenko, Lionel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3709086/
https://www.ncbi.nlm.nih.gov/pubmed/23516077
http://dx.doi.org/10.1007/s11517-013-1059-0
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author Pimentel, Marco A. F.
Clifton, David A.
Clifton, Lei
Watkinson, Peter J.
Tarassenko, Lionel
author_facet Pimentel, Marco A. F.
Clifton, David A.
Clifton, Lei
Watkinson, Peter J.
Tarassenko, Lionel
author_sort Pimentel, Marco A. F.
collection PubMed
description Patients who undergo upper-gastrointestinal surgery have a high incidence of post-operative complications, often requiring admission to the intensive care unit several days after surgery. A dataset comprising observational vital-sign data from 171 post-operative patients taking part in a two-phase clinical trial at the Oxford Cancer Centre, was used to explore the trajectory of patients’ vital-sign changes during their stay in the post-operative ward using both univariate and multivariate analyses. A model of normality based vital-sign data from patients who had a “normal” recovery was constructed using a kernel density estimate, and tested with “abnormal” data from patients who deteriorated sufficiently to be re-admitted to the intensive care unit. The vital-sign distributions from “normal” patients were found to vary over time from admission to the post-operative ward to their discharge home, but no significant changes in their distributions were observed from halfway through their stay on the ward to the time of discharge. The model of normality identified patient deterioration when tested with unseen “abnormal” data, suggesting that such techniques may be used to provide early warning of adverse physiological events.
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spelling pubmed-37090862013-07-15 Modelling physiological deterioration in post-operative patient vital-sign data Pimentel, Marco A. F. Clifton, David A. Clifton, Lei Watkinson, Peter J. Tarassenko, Lionel Med Biol Eng Comput Original Article Patients who undergo upper-gastrointestinal surgery have a high incidence of post-operative complications, often requiring admission to the intensive care unit several days after surgery. A dataset comprising observational vital-sign data from 171 post-operative patients taking part in a two-phase clinical trial at the Oxford Cancer Centre, was used to explore the trajectory of patients’ vital-sign changes during their stay in the post-operative ward using both univariate and multivariate analyses. A model of normality based vital-sign data from patients who had a “normal” recovery was constructed using a kernel density estimate, and tested with “abnormal” data from patients who deteriorated sufficiently to be re-admitted to the intensive care unit. The vital-sign distributions from “normal” patients were found to vary over time from admission to the post-operative ward to their discharge home, but no significant changes in their distributions were observed from halfway through their stay on the ward to the time of discharge. The model of normality identified patient deterioration when tested with unseen “abnormal” data, suggesting that such techniques may be used to provide early warning of adverse physiological events. Springer Berlin Heidelberg 2013-03-21 2013 /pmc/articles/PMC3709086/ /pubmed/23516077 http://dx.doi.org/10.1007/s11517-013-1059-0 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Original Article
Pimentel, Marco A. F.
Clifton, David A.
Clifton, Lei
Watkinson, Peter J.
Tarassenko, Lionel
Modelling physiological deterioration in post-operative patient vital-sign data
title Modelling physiological deterioration in post-operative patient vital-sign data
title_full Modelling physiological deterioration in post-operative patient vital-sign data
title_fullStr Modelling physiological deterioration in post-operative patient vital-sign data
title_full_unstemmed Modelling physiological deterioration in post-operative patient vital-sign data
title_short Modelling physiological deterioration in post-operative patient vital-sign data
title_sort modelling physiological deterioration in post-operative patient vital-sign data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3709086/
https://www.ncbi.nlm.nih.gov/pubmed/23516077
http://dx.doi.org/10.1007/s11517-013-1059-0
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