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The impact of delirium on the prediction of in-hospital mortality in intensive care patients
INTRODUCTION: Predictive models, such as acute physiology and chronic health evaluation II (APACHE-II), are widely used in intensive care units (ICUs) to estimate mortality. Although the presence of delirium is associated with a higher mortality in ICU patients, delirium is not part of the APACHE-II...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945129/ https://www.ncbi.nlm.nih.gov/pubmed/20682037 http://dx.doi.org/10.1186/cc9214 |
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author | van den Boogaard, Mark Peters, Sanne AE van der Hoeven, Johannes G Dagnelie, Pieter C Leffers, Pieter Pickkers, Peter Schoonhoven, Lisette |
author_facet | van den Boogaard, Mark Peters, Sanne AE van der Hoeven, Johannes G Dagnelie, Pieter C Leffers, Pieter Pickkers, Peter Schoonhoven, Lisette |
author_sort | van den Boogaard, Mark |
collection | PubMed |
description | INTRODUCTION: Predictive models, such as acute physiology and chronic health evaluation II (APACHE-II), are widely used in intensive care units (ICUs) to estimate mortality. Although the presence of delirium is associated with a higher mortality in ICU patients, delirium is not part of the APACHE-II model. The aim of the current study was to evaluate whether delirium, present within 24 hours after ICU admission, improves the predictive value of the APACHE-II score. METHODS: In a prospective cohort study 2116 adult patients admitted between February 2008 and February 2009 were screened for delirium with the confusion assessment method-ICU (CAM-ICU). Exclusion criteria were sustained coma and unable to understand Dutch. Logistic regression analysis was used to estimate the predicted probabilities in the model with and without delirium. Calibration plots and the Hosmer-Lemeshow test (HL-test) were used to assess calibration. The discriminatory power of the models was analyzed by the area under the receiver operating characteristics curve (AUC) and AUCs were compared using the Z-test. RESULTS: 1740 patients met the inclusion criteria, of which 332 (19%) were delirious at the time of ICU admission or within 24 hours after admission. Delirium was associated with in-hospital mortality in unadjusted models, odds ratio (OR): 3.22 (95% confidence interval [CI]: 2.23 - 4.66). The OR between the APACHE-II and in-hospital mortality was 1.15 (95% CI 1.12 - 1.19) per point. The predictive accuracy of the APACHE-II did not improve after adding delirium, both in the total group as well as in the subgroup without cardiac surgery patients. The AUC of the APACHE model without delirium was 0.77 (0.73 - 0.81) and 0.78 (0.74 - 0.82) when delirium was added to the model. The z-value was 0.92 indicating no improvement in discriminative power, and the HL-test and calibration plots indicated no improvement in calibration. CONCLUSIONS: Although delirium is a significant predictor of mortality in ICU patients, adding delirium as an additional variable to the APACHE-II model does not result in an improvement in its predictive estimates. |
format | Text |
id | pubmed-2945129 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29451292010-09-25 The impact of delirium on the prediction of in-hospital mortality in intensive care patients van den Boogaard, Mark Peters, Sanne AE van der Hoeven, Johannes G Dagnelie, Pieter C Leffers, Pieter Pickkers, Peter Schoonhoven, Lisette Crit Care Research INTRODUCTION: Predictive models, such as acute physiology and chronic health evaluation II (APACHE-II), are widely used in intensive care units (ICUs) to estimate mortality. Although the presence of delirium is associated with a higher mortality in ICU patients, delirium is not part of the APACHE-II model. The aim of the current study was to evaluate whether delirium, present within 24 hours after ICU admission, improves the predictive value of the APACHE-II score. METHODS: In a prospective cohort study 2116 adult patients admitted between February 2008 and February 2009 were screened for delirium with the confusion assessment method-ICU (CAM-ICU). Exclusion criteria were sustained coma and unable to understand Dutch. Logistic regression analysis was used to estimate the predicted probabilities in the model with and without delirium. Calibration plots and the Hosmer-Lemeshow test (HL-test) were used to assess calibration. The discriminatory power of the models was analyzed by the area under the receiver operating characteristics curve (AUC) and AUCs were compared using the Z-test. RESULTS: 1740 patients met the inclusion criteria, of which 332 (19%) were delirious at the time of ICU admission or within 24 hours after admission. Delirium was associated with in-hospital mortality in unadjusted models, odds ratio (OR): 3.22 (95% confidence interval [CI]: 2.23 - 4.66). The OR between the APACHE-II and in-hospital mortality was 1.15 (95% CI 1.12 - 1.19) per point. The predictive accuracy of the APACHE-II did not improve after adding delirium, both in the total group as well as in the subgroup without cardiac surgery patients. The AUC of the APACHE model without delirium was 0.77 (0.73 - 0.81) and 0.78 (0.74 - 0.82) when delirium was added to the model. The z-value was 0.92 indicating no improvement in discriminative power, and the HL-test and calibration plots indicated no improvement in calibration. CONCLUSIONS: Although delirium is a significant predictor of mortality in ICU patients, adding delirium as an additional variable to the APACHE-II model does not result in an improvement in its predictive estimates. BioMed Central 2010 2010-08-03 /pmc/articles/PMC2945129/ /pubmed/20682037 http://dx.doi.org/10.1186/cc9214 Text en Copyright ©2010 van den Boogaard et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research van den Boogaard, Mark Peters, Sanne AE van der Hoeven, Johannes G Dagnelie, Pieter C Leffers, Pieter Pickkers, Peter Schoonhoven, Lisette The impact of delirium on the prediction of in-hospital mortality in intensive care patients |
title | The impact of delirium on the prediction of in-hospital mortality in intensive care patients |
title_full | The impact of delirium on the prediction of in-hospital mortality in intensive care patients |
title_fullStr | The impact of delirium on the prediction of in-hospital mortality in intensive care patients |
title_full_unstemmed | The impact of delirium on the prediction of in-hospital mortality in intensive care patients |
title_short | The impact of delirium on the prediction of in-hospital mortality in intensive care patients |
title_sort | impact of delirium on the prediction of in-hospital mortality in intensive care patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945129/ https://www.ncbi.nlm.nih.gov/pubmed/20682037 http://dx.doi.org/10.1186/cc9214 |
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