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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...

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Autores principales: Hutchinson, Ann, Pickering, Alastair, Williams, Paul, Johnson, Miriam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
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.
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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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