Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)

<h4>Objective</h4> Develop and validate a prognostic model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. <h4>Methods</h4> We used prospective registry data from six emergency departments. The primary composi...

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Autores principales:	Anthony J. Weekes, Jaron D. Raper, Kathryn Lupez, Alyssa M. Thomas, Carly A. Cox, Dasia Esener, Jeremy S. Boyd, Jason T. Nomura, Jillian Davison, Patrick M. Ockerse, Stephen Leech, Jakea Johnson, Eric Abrams, Kathleen Murphy, Christopher Kelly, H. James Norton
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/fab60701f37a4dd3a7c8f0c557a41428
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spelling	oai:doaj.org-article:fab60701f37a4dd3a7c8f0c557a414282021-11-25T06:19:35ZDevelopment and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)1932-6203https://doaj.org/article/fab60701f37a4dd3a7c8f0c557a414282021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8601564/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Objective</h4> Develop and validate a prognostic model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. <h4>Methods</h4> We used prospective registry data from six emergency departments. The primary composite outcome was death or deterioration (respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension, and rescue reperfusion intervention) within 5 days. Candidate predictors included laboratory and imaging right ventricle (RV) assessments. The prognostic model was developed from 935 PE patients. Univariable analysis of 138 candidate variables was followed by penalized and standard logistic regression on 26 retained variables, and then tested with a validation database (N = 801). <h4>Results</h4> Logistic regression yielded a nine-variable model, then simplified to a nine-point tool (PE-SCORE): one point each for abnormal RV by echocardiography, abnormal RV by computed tomography, systolic blood pressure < 100 mmHg, dysrhythmia, suspected/confirmed systemic infection, syncope, medico-social admission reason, abnormal heart rate, and two points for creatinine greater than 2.0 mg/dL. In the development database, 22.4% had the primary outcome. Prognostic accuracy of logistic regression model versus PE-SCORE model: 0.83 (0.80, 0.86) vs. 0.78 (0.75, 0.82) using area under the curve (AUC) and 0.61 (0.57, 0.64) vs. 0.50 (0.39, 0.60) using precision-recall curve (AUCpr). In the validation database, 26.6% had the primary outcome. PE-SCORE had AUC 0.77 (0.73, 0.81) and AUCpr 0.63 (0.43, 0.81). As points increased, outcome proportions increased: a score of zero had 2% outcome, whereas scores of six and above had ≥ 69.6% outcomes. In the validation dataset, PE-SCORE zero had 8% outcome [no deaths], whereas all patients with PE-SCORE of six and above had the primary outcome. <h4>Conclusions</h4> PE-SCORE model identifies PE patients at low- and high-risk for deterioration and may help guide decisions about early outpatient management versus need for hospital-based monitoring.Anthony J. WeekesJaron D. RaperKathryn LupezAlyssa M. ThomasCarly A. CoxDasia EsenerJeremy S. BoydJason T. NomuraJillian DavisonPatrick M. OckerseStephen LeechJakea JohnsonEric AbramsKathleen MurphyChristopher KellyH. James NortonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Anthony J. Weekes Jaron D. Raper Kathryn Lupez Alyssa M. Thomas Carly A. Cox Dasia Esener Jeremy S. Boyd Jason T. Nomura Jillian Davison Patrick M. Ockerse Stephen Leech Jakea Johnson Eric Abrams Kathleen Murphy Christopher Kelly H. James Norton Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)
description	<h4>Objective</h4> Develop and validate a prognostic model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. <h4>Methods</h4> We used prospective registry data from six emergency departments. The primary composite outcome was death or deterioration (respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension, and rescue reperfusion intervention) within 5 days. Candidate predictors included laboratory and imaging right ventricle (RV) assessments. The prognostic model was developed from 935 PE patients. Univariable analysis of 138 candidate variables was followed by penalized and standard logistic regression on 26 retained variables, and then tested with a validation database (N = 801). <h4>Results</h4> Logistic regression yielded a nine-variable model, then simplified to a nine-point tool (PE-SCORE): one point each for abnormal RV by echocardiography, abnormal RV by computed tomography, systolic blood pressure < 100 mmHg, dysrhythmia, suspected/confirmed systemic infection, syncope, medico-social admission reason, abnormal heart rate, and two points for creatinine greater than 2.0 mg/dL. In the development database, 22.4% had the primary outcome. Prognostic accuracy of logistic regression model versus PE-SCORE model: 0.83 (0.80, 0.86) vs. 0.78 (0.75, 0.82) using area under the curve (AUC) and 0.61 (0.57, 0.64) vs. 0.50 (0.39, 0.60) using precision-recall curve (AUCpr). In the validation database, 26.6% had the primary outcome. PE-SCORE had AUC 0.77 (0.73, 0.81) and AUCpr 0.63 (0.43, 0.81). As points increased, outcome proportions increased: a score of zero had 2% outcome, whereas scores of six and above had ≥ 69.6% outcomes. In the validation dataset, PE-SCORE zero had 8% outcome [no deaths], whereas all patients with PE-SCORE of six and above had the primary outcome. <h4>Conclusions</h4> PE-SCORE model identifies PE patients at low- and high-risk for deterioration and may help guide decisions about early outpatient management versus need for hospital-based monitoring.
format	article
author	Anthony J. Weekes Jaron D. Raper Kathryn Lupez Alyssa M. Thomas Carly A. Cox Dasia Esener Jeremy S. Boyd Jason T. Nomura Jillian Davison Patrick M. Ockerse Stephen Leech Jakea Johnson Eric Abrams Kathleen Murphy Christopher Kelly H. James Norton
author_facet	Anthony J. Weekes Jaron D. Raper Kathryn Lupez Alyssa M. Thomas Carly A. Cox Dasia Esener Jeremy S. Boyd Jason T. Nomura Jillian Davison Patrick M. Ockerse Stephen Leech Jakea Johnson Eric Abrams Kathleen Murphy Christopher Kelly H. James Norton
author_sort	Anthony J. Weekes
title	Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)
title_short	Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)
title_full	Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)
title_fullStr	Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)
title_full_unstemmed	Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)
title_sort	development and validation of a prognostic tool: pulmonary embolism short-term clinical outcomes risk estimation (pe-score)
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/fab60701f37a4dd3a7c8f0c557a41428
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Development and validation of a prognostic tool: Pulmonary embolism short-term clinical outcomes risk estimation (PE-SCORE)

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