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Using the LACE index to predict hospital readmissions in congestive heart failure patients
BACKGROUND: The LACE index has been used to predict the risk of unplanned readmission within 30 days after hospital discharge in both medical and surgical patients. The aim of this study is to validate the accuracy of using the LACE index in CHF patients. METHODS: This was a retrospective study. The...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4128541/ https://www.ncbi.nlm.nih.gov/pubmed/25099997 http://dx.doi.org/10.1186/1471-2261-14-97 |
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author | Wang, Hao Robinson, Richard D Johnson, Carlos Zenarosa, Nestor R Jayswal, Rani D Keithley, Joshua Delaney, Kathleen A |
author_facet | Wang, Hao Robinson, Richard D Johnson, Carlos Zenarosa, Nestor R Jayswal, Rani D Keithley, Joshua Delaney, Kathleen A |
author_sort | Wang, Hao |
collection | PubMed |
description | BACKGROUND: The LACE index has been used to predict the risk of unplanned readmission within 30 days after hospital discharge in both medical and surgical patients. The aim of this study is to validate the accuracy of using the LACE index in CHF patients. METHODS: This was a retrospective study. The LACE index score was calculated on each patient who was admitted to hospital due to an acute CHF exacerbation. Operational and clinical variables were collected from patients including basic clinical characteristics, length of hospitalization, comorbidities, number of previous ED visits in the past 6 months before the index admission, and the number of post discharge ED revisits at 30, 60, and 90 days. All variables were analyzed by multivariate logistic regression to determine the association between clinical variables and the hospital unplanned readmissions. C-statistic was used to discriminate those patients with high risk of readmissions. RESULTS: Of the 253 patients included in the study, 24.50% (62/253) experienced unplanned readmission to hospital within 30 days after discharge. The LACE index was slightly higher in patients readmitted versus patients not readmitted (12.17 ± 2.22 versus 11.80 ± 1.92, p = 0.199). Adjusted odds ratios based on logistic regression of all clinical variables showed only the number of previous ED visits (OR 1.79, 95% CI 1.30-2.47, p < 0.001), history of myocardial infarction (OR 2.51, 95% CI 1.02-6.21, p = 0.045), and history of peripheral vascular disease (OR 10.75, 95% CI 1.52-75.73, p = 0.017) increased the risk of unplanned readmission within 30 days of hospital discharge. However, patients with high LACE scores (≥10) had a significantly higher rate of ED revisits (15.04% vs 0%) within 30 days from the index discharge than those with low LACE scores (p = 0.030). CONCLUSION: The LACE index may not accurately predict unplanned readmissions within 30 days from hospital discharge in CHF patients. The LACE high risk index may have utility as a screening tool to predict high risk ED revisits after hospital discharge. |
format | Online Article Text |
id | pubmed-4128541 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41285412014-08-12 Using the LACE index to predict hospital readmissions in congestive heart failure patients Wang, Hao Robinson, Richard D Johnson, Carlos Zenarosa, Nestor R Jayswal, Rani D Keithley, Joshua Delaney, Kathleen A BMC Cardiovasc Disord Research Article BACKGROUND: The LACE index has been used to predict the risk of unplanned readmission within 30 days after hospital discharge in both medical and surgical patients. The aim of this study is to validate the accuracy of using the LACE index in CHF patients. METHODS: This was a retrospective study. The LACE index score was calculated on each patient who was admitted to hospital due to an acute CHF exacerbation. Operational and clinical variables were collected from patients including basic clinical characteristics, length of hospitalization, comorbidities, number of previous ED visits in the past 6 months before the index admission, and the number of post discharge ED revisits at 30, 60, and 90 days. All variables were analyzed by multivariate logistic regression to determine the association between clinical variables and the hospital unplanned readmissions. C-statistic was used to discriminate those patients with high risk of readmissions. RESULTS: Of the 253 patients included in the study, 24.50% (62/253) experienced unplanned readmission to hospital within 30 days after discharge. The LACE index was slightly higher in patients readmitted versus patients not readmitted (12.17 ± 2.22 versus 11.80 ± 1.92, p = 0.199). Adjusted odds ratios based on logistic regression of all clinical variables showed only the number of previous ED visits (OR 1.79, 95% CI 1.30-2.47, p < 0.001), history of myocardial infarction (OR 2.51, 95% CI 1.02-6.21, p = 0.045), and history of peripheral vascular disease (OR 10.75, 95% CI 1.52-75.73, p = 0.017) increased the risk of unplanned readmission within 30 days of hospital discharge. However, patients with high LACE scores (≥10) had a significantly higher rate of ED revisits (15.04% vs 0%) within 30 days from the index discharge than those with low LACE scores (p = 0.030). CONCLUSION: The LACE index may not accurately predict unplanned readmissions within 30 days from hospital discharge in CHF patients. The LACE high risk index may have utility as a screening tool to predict high risk ED revisits after hospital discharge. BioMed Central 2014-08-07 /pmc/articles/PMC4128541/ /pubmed/25099997 http://dx.doi.org/10.1186/1471-2261-14-97 Text en Copyright © 2014 Wang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Wang, Hao Robinson, Richard D Johnson, Carlos Zenarosa, Nestor R Jayswal, Rani D Keithley, Joshua Delaney, Kathleen A Using the LACE index to predict hospital readmissions in congestive heart failure patients |
title | Using the LACE index to predict hospital readmissions in congestive heart failure patients |
title_full | Using the LACE index to predict hospital readmissions in congestive heart failure patients |
title_fullStr | Using the LACE index to predict hospital readmissions in congestive heart failure patients |
title_full_unstemmed | Using the LACE index to predict hospital readmissions in congestive heart failure patients |
title_short | Using the LACE index to predict hospital readmissions in congestive heart failure patients |
title_sort | using the lace index to predict hospital readmissions in congestive heart failure patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4128541/ https://www.ncbi.nlm.nih.gov/pubmed/25099997 http://dx.doi.org/10.1186/1471-2261-14-97 |
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