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Development and Validation of a Risk Score for Predicting Death after Pneumonectomy
Pneumonectomy is associated with significant postoperative mortality. This study was undertaken to develop and validate a risk model of mortality following pneumonectomy. We reviewed our prospective database and identified 774 pneumonectomies from a total of 7792 consecutive anatomical lung resectio...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391778/ https://www.ncbi.nlm.nih.gov/pubmed/25856315 http://dx.doi.org/10.1371/journal.pone.0121295 |
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author | Safi, Seyer Benner, Axel Walloschek, Janos Renner, Maria op den Winkel, Jan Muley, Thomas Storz, Konstantina Dienemann, Hendrik Hoffmann, Hans Schneider, Thomas |
author_facet | Safi, Seyer Benner, Axel Walloschek, Janos Renner, Maria op den Winkel, Jan Muley, Thomas Storz, Konstantina Dienemann, Hendrik Hoffmann, Hans Schneider, Thomas |
author_sort | Safi, Seyer |
collection | PubMed |
description | Pneumonectomy is associated with significant postoperative mortality. This study was undertaken to develop and validate a risk model of mortality following pneumonectomy. We reviewed our prospective database and identified 774 pneumonectomies from a total of 7792 consecutive anatomical lung resections in the years 2003 to 2010 (rate of pneumonectomy: 9.9%). Based on data from 542 pneumonectomies between 2003 and 2007 (i.e., the "discovery set"), a penalized multivariable logistic regression analysis was performed to identify preoperative risk factors. A risk model was developed and validated in an independent data set of 232 pneumonectomies that were performed between 2008 and 2010 (i.e., the "validation set"). Of the 542 patients in the discovery set (DS), 35 patients (6.5%) died after pneumonectomy during the same admission. We developed a risk prediction model for in-hospital mortality following pneumonectomy; that model included age, current alcohol use, coronary artery disease, preoperative leukocyte count and palliative indication as possible risk factors. The risk model was subsequently successfully validated in an independent data set (n = 232) in which 18 patients (7.8%) died following pneumonectomy. For the validation set, the sensitivity of the model was 53.3% (DS: 54.3%), the specificity was 88.0% (DS: 87.4%), the positive predictive value was 26.7% (DS: 22.9%) and the negative predictive value was 95.8% (DS: 96.5%). The Brier score was 0.062 (DS: 0.054). The prediction model is statistically valid and clinically relevant. |
format | Online Article Text |
id | pubmed-4391778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-43917782015-04-21 Development and Validation of a Risk Score for Predicting Death after Pneumonectomy Safi, Seyer Benner, Axel Walloschek, Janos Renner, Maria op den Winkel, Jan Muley, Thomas Storz, Konstantina Dienemann, Hendrik Hoffmann, Hans Schneider, Thomas PLoS One Research Article Pneumonectomy is associated with significant postoperative mortality. This study was undertaken to develop and validate a risk model of mortality following pneumonectomy. We reviewed our prospective database and identified 774 pneumonectomies from a total of 7792 consecutive anatomical lung resections in the years 2003 to 2010 (rate of pneumonectomy: 9.9%). Based on data from 542 pneumonectomies between 2003 and 2007 (i.e., the "discovery set"), a penalized multivariable logistic regression analysis was performed to identify preoperative risk factors. A risk model was developed and validated in an independent data set of 232 pneumonectomies that were performed between 2008 and 2010 (i.e., the "validation set"). Of the 542 patients in the discovery set (DS), 35 patients (6.5%) died after pneumonectomy during the same admission. We developed a risk prediction model for in-hospital mortality following pneumonectomy; that model included age, current alcohol use, coronary artery disease, preoperative leukocyte count and palliative indication as possible risk factors. The risk model was subsequently successfully validated in an independent data set (n = 232) in which 18 patients (7.8%) died following pneumonectomy. For the validation set, the sensitivity of the model was 53.3% (DS: 54.3%), the specificity was 88.0% (DS: 87.4%), the positive predictive value was 26.7% (DS: 22.9%) and the negative predictive value was 95.8% (DS: 96.5%). The Brier score was 0.062 (DS: 0.054). The prediction model is statistically valid and clinically relevant. Public Library of Science 2015-04-09 /pmc/articles/PMC4391778/ /pubmed/25856315 http://dx.doi.org/10.1371/journal.pone.0121295 Text en © 2015 Safi et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Safi, Seyer Benner, Axel Walloschek, Janos Renner, Maria op den Winkel, Jan Muley, Thomas Storz, Konstantina Dienemann, Hendrik Hoffmann, Hans Schneider, Thomas Development and Validation of a Risk Score for Predicting Death after Pneumonectomy |
title | Development and Validation of a Risk Score for Predicting Death after Pneumonectomy |
title_full | Development and Validation of a Risk Score for Predicting Death after Pneumonectomy |
title_fullStr | Development and Validation of a Risk Score for Predicting Death after Pneumonectomy |
title_full_unstemmed | Development and Validation of a Risk Score for Predicting Death after Pneumonectomy |
title_short | Development and Validation of a Risk Score for Predicting Death after Pneumonectomy |
title_sort | development and validation of a risk score for predicting death after pneumonectomy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4391778/ https://www.ncbi.nlm.nih.gov/pubmed/25856315 http://dx.doi.org/10.1371/journal.pone.0121295 |
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