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Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study

BACKGROUND: Medical emergency teams (METs) have been implemented to reduce hospital mortality by the early recognition and treatment of potentially life-threatening conditions. The objective of this study was to establish a clinically useful association between clinical variables and mortality risk,...

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Autores principales: Adielsson, Anna, Danielsson, Christian, Forkman, Pontus, Karlsson, Thomas, Pettersson, Linda, Herlitz, Johan, Lundin, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733206/
https://www.ncbi.nlm.nih.gov/pubmed/36494620
http://dx.doi.org/10.1186/s12873-022-00739-w
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author Adielsson, Anna
Danielsson, Christian
Forkman, Pontus
Karlsson, Thomas
Pettersson, Linda
Herlitz, Johan
Lundin, Stefan
author_facet Adielsson, Anna
Danielsson, Christian
Forkman, Pontus
Karlsson, Thomas
Pettersson, Linda
Herlitz, Johan
Lundin, Stefan
author_sort Adielsson, Anna
collection PubMed
description BACKGROUND: Medical emergency teams (METs) have been implemented to reduce hospital mortality by the early recognition and treatment of potentially life-threatening conditions. The objective of this study was to establish a clinically useful association between clinical variables and mortality risk, among patients assessed by the MET, and further to design an easy-to-use risk score for the prediction of death within 30 days. METHODS: Observational retrospective register study in a tertiary university hospital in Sweden, comprising 2,601 patients, assessed by the MET from 2010 to 2015. Patient registry data at the time of MET assessment was analysed from an epidemiological perspective, using univariable and multivariable analyses with death within 30 days as the outcome variable. Predictors of outcome were defined from age, gender, type of ward for admittance, previous medical history, acute medical condition, vital parameters and laboratory biomarkers. Identified factors independently associated with mortality were then used to develop a prognostic risk score for mortality. RESULTS: The overall 30-day mortality was high (29.0%). We identified thirteen factors independently associated with 30-day mortality concerning; age, type of ward for admittance, vital parameters, laboratory biomarkers, previous medical history and acute medical condition. A MET risk score for mortality based on the impact of these individual thirteen factors in the model yielded a median (range) AUC of 0.780 (0.774–0.785) with good calibration. When corrected for optimism by internal validation, the score yielded a median (range) AUC of 0.768 (0.762–0.773). CONCLUSIONS: Among clinical variables available at the time of MET assessment, thirteen factors were found to be independently associated with 30-day mortality. By applying a simple risk scoring system based on these individual factors, patients at higher risk of dying within 30 days after the MET assessment may be identified and treated earlier in the process. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12873-022-00739-w.
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spelling pubmed-97332062022-12-10 Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study Adielsson, Anna Danielsson, Christian Forkman, Pontus Karlsson, Thomas Pettersson, Linda Herlitz, Johan Lundin, Stefan BMC Emerg Med Research Article BACKGROUND: Medical emergency teams (METs) have been implemented to reduce hospital mortality by the early recognition and treatment of potentially life-threatening conditions. The objective of this study was to establish a clinically useful association between clinical variables and mortality risk, among patients assessed by the MET, and further to design an easy-to-use risk score for the prediction of death within 30 days. METHODS: Observational retrospective register study in a tertiary university hospital in Sweden, comprising 2,601 patients, assessed by the MET from 2010 to 2015. Patient registry data at the time of MET assessment was analysed from an epidemiological perspective, using univariable and multivariable analyses with death within 30 days as the outcome variable. Predictors of outcome were defined from age, gender, type of ward for admittance, previous medical history, acute medical condition, vital parameters and laboratory biomarkers. Identified factors independently associated with mortality were then used to develop a prognostic risk score for mortality. RESULTS: The overall 30-day mortality was high (29.0%). We identified thirteen factors independently associated with 30-day mortality concerning; age, type of ward for admittance, vital parameters, laboratory biomarkers, previous medical history and acute medical condition. A MET risk score for mortality based on the impact of these individual thirteen factors in the model yielded a median (range) AUC of 0.780 (0.774–0.785) with good calibration. When corrected for optimism by internal validation, the score yielded a median (range) AUC of 0.768 (0.762–0.773). CONCLUSIONS: Among clinical variables available at the time of MET assessment, thirteen factors were found to be independently associated with 30-day mortality. By applying a simple risk scoring system based on these individual factors, patients at higher risk of dying within 30 days after the MET assessment may be identified and treated earlier in the process. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12873-022-00739-w. BioMed Central 2022-12-09 /pmc/articles/PMC9733206/ /pubmed/36494620 http://dx.doi.org/10.1186/s12873-022-00739-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Adielsson, Anna
Danielsson, Christian
Forkman, Pontus
Karlsson, Thomas
Pettersson, Linda
Herlitz, Johan
Lundin, Stefan
Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
title Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
title_full Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
title_fullStr Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
title_full_unstemmed Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
title_short Outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
title_sort outcome prediction for patients assessed by the medical emergency team: a retrospective cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733206/
https://www.ncbi.nlm.nih.gov/pubmed/36494620
http://dx.doi.org/10.1186/s12873-022-00739-w
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