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Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED)
The primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 3...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388874/ https://www.ncbi.nlm.nih.gov/pubmed/28401961 http://dx.doi.org/10.1038/srep46474 |
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author | Ha, Duc T. Dang, Tam Q. Tran, Ngoc V. Pham, Thao N. T. Nguyen, Nguyen D. Nguyen, Tuan V. |
author_facet | Ha, Duc T. Dang, Tam Q. Tran, Ngoc V. Pham, Thao N. T. Nguyen, Nguyen D. Nguyen, Tuan V. |
author_sort | Ha, Duc T. |
collection | PubMed |
description | The primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 30 days after admission. Potential risk factors included clinical characteristics, vital signs, and routine haematological and biochemistry tests. The Bayesian Model Averaging method within the Cox’s regression model was used to identify independent risk factors for mortality. In the development cohort, the incidence of 30-day mortality was 9.8%, and the following factors were associated with a greater risk of mortality: male gender, increased respiratory rate and serum urea, decreased peripheral oxygen saturation and serum albumin, lower Glasgow Coma Score, and admission to intensive care unit. The area under the receiver operating characteristic curve for the model with the listed factors was 0.871 (95% CI, 0.844–0.898) in the development cohort and 0.783 (95% CI, 0.743–0.823) in the validation cohort. Calibration analysis found a close agreement between predicted and observed mortality risk. We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests. |
format | Online Article Text |
id | pubmed-5388874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53888742017-04-14 Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) Ha, Duc T. Dang, Tam Q. Tran, Ngoc V. Pham, Thao N. T. Nguyen, Nguyen D. Nguyen, Tuan V. Sci Rep Article The primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 30 days after admission. Potential risk factors included clinical characteristics, vital signs, and routine haematological and biochemistry tests. The Bayesian Model Averaging method within the Cox’s regression model was used to identify independent risk factors for mortality. In the development cohort, the incidence of 30-day mortality was 9.8%, and the following factors were associated with a greater risk of mortality: male gender, increased respiratory rate and serum urea, decreased peripheral oxygen saturation and serum albumin, lower Glasgow Coma Score, and admission to intensive care unit. The area under the receiver operating characteristic curve for the model with the listed factors was 0.871 (95% CI, 0.844–0.898) in the development cohort and 0.783 (95% CI, 0.743–0.823) in the validation cohort. Calibration analysis found a close agreement between predicted and observed mortality risk. We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests. Nature Publishing Group 2017-04-12 /pmc/articles/PMC5388874/ /pubmed/28401961 http://dx.doi.org/10.1038/srep46474 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ha, Duc T. Dang, Tam Q. Tran, Ngoc V. Pham, Thao N. T. Nguyen, Nguyen D. Nguyen, Tuan V. Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) |
title | Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) |
title_full | Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) |
title_fullStr | Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) |
title_full_unstemmed | Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) |
title_short | Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED) |
title_sort | development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ed) |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388874/ https://www.ncbi.nlm.nih.gov/pubmed/28401961 http://dx.doi.org/10.1038/srep46474 |
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