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Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression
BACKGROUND: Breathlessness due to medical conditions commonly causes emergency department presentations and unplanned admissions. Acute-on-chronic breathlessness is a reason for 20% of emergency presentations by ambulance with 69% of these being admitted. The emergency department may be inappropriat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10426999/ https://www.ncbi.nlm.nih.gov/pubmed/37582083 http://dx.doi.org/10.1371/journal.pone.0289263 |
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author | Hutchinson, Ann Pickering, Alastair Williams, Paul Johnson, Miriam |
author_facet | Hutchinson, Ann Pickering, Alastair Williams, Paul Johnson, Miriam |
author_sort | Hutchinson, Ann |
collection | PubMed |
description | BACKGROUND: Breathlessness due to medical conditions commonly causes emergency department presentations and unplanned admissions. Acute-on-chronic breathlessness is a reason for 20% of emergency presentations by ambulance with 69% of these being admitted. The emergency department may be inappropriate for many presenting with acute-on-chronic breathlessness. AIM: To examine predictors of emergency department departure status in people with acute-on-chronic breathlessness. DESIGN, SETTING AND METHOD: Secondary analysis of patient-report survey and clinical record data from consecutive eligible attendees by ambulance. Variables associated with emergency department departure status (unifactorial analyses; p<0.05) were included in a binary logistic regression model. The study was conducted in a single tertiary hospital. Consecutive survey participants presenting in May 2015 with capacity were eligible. 1,212/1,345 surveys were completed. 245/1,212 presented with acute-on-chronic breathlessness, 171 of whom consented to clinical record review and were included in this analysis. RESULTS: In the final model, the odds of admission were increased with every extra year of age [OR 1.041 (95% CI: 1.016 to 1.066)], having talked to a specialist doctor about breathlessness [9.262 (1.066 to 80.491)] and having a known history of a heart condition [4.177 (1.680 to 10.386)]. Odds of admission were decreased with every percentage increase in oxygen saturation [0.826 (0.701 to 0.974)]. CONCLUSION: Older age, lower oxygen saturation, having talked to a specialist, and having history of a cardiac condition predict hospital admission in people presenting to the emergency department with acute-on-chronic breathlessness. These clinical factors could be assessed in the community and may inform the decision regarding conveyance. |
format | Online Article Text |
id | pubmed-10426999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-104269992023-08-16 Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression Hutchinson, Ann Pickering, Alastair Williams, Paul Johnson, Miriam PLoS One Research Article BACKGROUND: Breathlessness due to medical conditions commonly causes emergency department presentations and unplanned admissions. Acute-on-chronic breathlessness is a reason for 20% of emergency presentations by ambulance with 69% of these being admitted. The emergency department may be inappropriate for many presenting with acute-on-chronic breathlessness. AIM: To examine predictors of emergency department departure status in people with acute-on-chronic breathlessness. DESIGN, SETTING AND METHOD: Secondary analysis of patient-report survey and clinical record data from consecutive eligible attendees by ambulance. Variables associated with emergency department departure status (unifactorial analyses; p<0.05) were included in a binary logistic regression model. The study was conducted in a single tertiary hospital. Consecutive survey participants presenting in May 2015 with capacity were eligible. 1,212/1,345 surveys were completed. 245/1,212 presented with acute-on-chronic breathlessness, 171 of whom consented to clinical record review and were included in this analysis. RESULTS: In the final model, the odds of admission were increased with every extra year of age [OR 1.041 (95% CI: 1.016 to 1.066)], having talked to a specialist doctor about breathlessness [9.262 (1.066 to 80.491)] and having a known history of a heart condition [4.177 (1.680 to 10.386)]. Odds of admission were decreased with every percentage increase in oxygen saturation [0.826 (0.701 to 0.974)]. CONCLUSION: Older age, lower oxygen saturation, having talked to a specialist, and having history of a cardiac condition predict hospital admission in people presenting to the emergency department with acute-on-chronic breathlessness. These clinical factors could be assessed in the community and may inform the decision regarding conveyance. Public Library of Science 2023-08-15 /pmc/articles/PMC10426999/ /pubmed/37582083 http://dx.doi.org/10.1371/journal.pone.0289263 Text en © 2023 Hutchinson et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hutchinson, Ann Pickering, Alastair Williams, Paul Johnson, Miriam Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression |
title | Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression |
title_full | Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression |
title_fullStr | Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression |
title_full_unstemmed | Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression |
title_short | Predictors of hospital admission when presenting with acute-on-chronic breathlessness: Binary logistic regression |
title_sort | predictors of hospital admission when presenting with acute-on-chronic breathlessness: binary logistic regression |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10426999/ https://www.ncbi.nlm.nih.gov/pubmed/37582083 http://dx.doi.org/10.1371/journal.pone.0289263 |
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