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Derivation and Validation of a Prognostic Model for Pulmonary Embolism
An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment. To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other advers...
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Published in: | American journal of respiratory and critical care medicine 2005-10, Vol.172 (8), p.1041-1046 |
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container_title | American journal of respiratory and critical care medicine |
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creator | Aujesky, Drahomir Obrosky, D. Scott Stone, Roslyn A Auble, Thomas E Perrier, Arnaud Cornuz, Jacques Roy, Pierre-Marie Fine, Michael J |
description | An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment.
To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes.
We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France.
We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples.
The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were |
doi_str_mv | 10.1164/rccm.200506-862OC |
format | article |
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To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes.
We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France.
We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples.
The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were <or= 1.1% among patients in class I and <or= 1.9% among patients in class II.
Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.</description><identifier>ISSN: 1073-449X</identifier><identifier>EISSN: 1535-4970</identifier><identifier>DOI: 10.1164/rccm.200506-862OC</identifier><identifier>PMID: 16020800</identifier><language>eng</language><publisher>New York, NY: Am Thoracic Soc</publisher><subject>Acute Disease ; Aged ; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy ; Biological and medical sciences ; Cause of Death ; Comorbidity ; Decision Support Techniques ; Discriminant Analysis ; Female ; France - epidemiology ; Hospitals ; Hospitals, University ; Humans ; Intensive care medicine ; J. Pulmonary Vascular Disease ; Laboratories ; Logistic Models ; Male ; Medical sciences ; Metabolic diseases ; Mortality ; Obesity ; Patients ; Pennsylvania - epidemiology ; Pneumology ; Predictive Value of Tests ; Prognosis ; Pulmonary Embolism - classification ; Pulmonary Embolism - complications ; Pulmonary Embolism - diagnosis ; Pulmonary Embolism - mortality ; Pulmonary Embolism - therapy ; Pulmonary embolisms ; Pulmonary hypertension. Acute cor pulmonale. Pulmonary embolism. Pulmonary vascular diseases ; Regression analysis ; Risk Assessment - organization & administration ; Risk Factors ; ROC Curve ; Severity of Illness Index ; Switzerland - epidemiology ; Tomography</subject><ispartof>American journal of respiratory and critical care medicine, 2005-10, Vol.172 (8), p.1041-1046</ispartof><rights>2005 INIST-CNRS</rights><rights>Copyright American Thoracic Society Oct 15, 2005</rights><rights>Copyright © 2005, American Thoracic Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c555t-93228fb513648c2b930742f0ce602f1aa51073999368df238671921957a0e15b3</citedby><cites>FETCH-LOGICAL-c555t-93228fb513648c2b930742f0ce602f1aa51073999368df238671921957a0e15b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17205477$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16020800$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Aujesky, Drahomir</creatorcontrib><creatorcontrib>Obrosky, D. Scott</creatorcontrib><creatorcontrib>Stone, Roslyn A</creatorcontrib><creatorcontrib>Auble, Thomas E</creatorcontrib><creatorcontrib>Perrier, Arnaud</creatorcontrib><creatorcontrib>Cornuz, Jacques</creatorcontrib><creatorcontrib>Roy, Pierre-Marie</creatorcontrib><creatorcontrib>Fine, Michael J</creatorcontrib><title>Derivation and Validation of a Prognostic Model for Pulmonary Embolism</title><title>American journal of respiratory and critical care medicine</title><addtitle>Am J Respir Crit Care Med</addtitle><description>An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment.
To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes.
We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France.
We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples.
The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were <or= 1.1% among patients in class I and <or= 1.9% among patients in class II.
Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.</description><subject>Acute Disease</subject><subject>Aged</subject><subject>Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy</subject><subject>Biological and medical sciences</subject><subject>Cause of Death</subject><subject>Comorbidity</subject><subject>Decision Support Techniques</subject><subject>Discriminant Analysis</subject><subject>Female</subject><subject>France - epidemiology</subject><subject>Hospitals</subject><subject>Hospitals, University</subject><subject>Humans</subject><subject>Intensive care medicine</subject><subject>J. Pulmonary Vascular Disease</subject><subject>Laboratories</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Metabolic diseases</subject><subject>Mortality</subject><subject>Obesity</subject><subject>Patients</subject><subject>Pennsylvania - epidemiology</subject><subject>Pneumology</subject><subject>Predictive Value of Tests</subject><subject>Prognosis</subject><subject>Pulmonary Embolism - classification</subject><subject>Pulmonary Embolism - complications</subject><subject>Pulmonary Embolism - diagnosis</subject><subject>Pulmonary Embolism - mortality</subject><subject>Pulmonary Embolism - therapy</subject><subject>Pulmonary embolisms</subject><subject>Pulmonary hypertension. Acute cor pulmonale. Pulmonary embolism. Pulmonary vascular diseases</subject><subject>Regression analysis</subject><subject>Risk Assessment - organization & administration</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><subject>Severity of Illness Index</subject><subject>Switzerland - epidemiology</subject><subject>Tomography</subject><issn>1073-449X</issn><issn>1535-4970</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNpdkU9v1DAQxSMEoqXwAbigCAkOSCkz_pPYFyS0bQGpqD0A4mY5jrPrlRMXO2nFt8chKwqcbGt-8-aNX1E8RzhFrNnbaMxwSgA41JWoydXmQXGMnPKKyQYe5js0tGJMfj8qnqS0B0AiEB4XR1gDAQFwXFyc2ehu9eTCWOqxK79p77r1GfpSl9cxbMeQJmfKz6GzvuxDLK9nP4RRx5_l-dAG79LwtHjUa5_ss8N5Uny9OP-y-VhdXn34tHl_WRnO-VRJSojoW460ZsKQVlJoGOnB2GyoR635YllKSWvR9YSKukFJUPJGg0Xe0pPi3ap7M7eD7Ywdp6i9uoluyHZU0E79WxndTm3DrSINCoaQBV4fBGL4Mds0qcElY73Xow1zUnUeKYhYwJf_gfswxzEvp1DKmtL8fRnCFTIxpBRt_8cJgloiUktEao1I_Y4o97z4e4X7jkMmGXh1AHQy2vdRj8ale64hwFnTZO7Nyu3cdnfnolVp0N5nWVR6vwzOqBLZCkP6C4oap3s</recordid><startdate>20051015</startdate><enddate>20051015</enddate><creator>Aujesky, Drahomir</creator><creator>Obrosky, D. 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Pulmonary Vascular Disease</topic><topic>Laboratories</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Metabolic diseases</topic><topic>Mortality</topic><topic>Obesity</topic><topic>Patients</topic><topic>Pennsylvania - epidemiology</topic><topic>Pneumology</topic><topic>Predictive Value of Tests</topic><topic>Prognosis</topic><topic>Pulmonary Embolism - classification</topic><topic>Pulmonary Embolism - complications</topic><topic>Pulmonary Embolism - diagnosis</topic><topic>Pulmonary Embolism - mortality</topic><topic>Pulmonary Embolism - therapy</topic><topic>Pulmonary embolisms</topic><topic>Pulmonary hypertension. Acute cor pulmonale. Pulmonary embolism. 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Scott</au><au>Stone, Roslyn A</au><au>Auble, Thomas E</au><au>Perrier, Arnaud</au><au>Cornuz, Jacques</au><au>Roy, Pierre-Marie</au><au>Fine, Michael J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Derivation and Validation of a Prognostic Model for Pulmonary Embolism</atitle><jtitle>American journal of respiratory and critical care medicine</jtitle><addtitle>Am J Respir Crit Care Med</addtitle><date>2005-10-15</date><risdate>2005</risdate><volume>172</volume><issue>8</issue><spage>1041</spage><epage>1046</epage><pages>1041-1046</pages><issn>1073-449X</issn><eissn>1535-4970</eissn><abstract>An objective and simple prognostic model for patients with pulmonary embolism could be helpful in guiding initial intensity of treatment.
To develop a clinical prediction rule that accurately classifies patients with pulmonary embolism into categories of increasing risk of mortality and other adverse medical outcomes.
We randomly allocated 15,531 inpatient discharges with pulmonary embolism from 186 Pennsylvania hospitals to derivation (67%) and internal validation (33%) samples. We derived our prediction rule using logistic regression with 30-day mortality as the primary outcome, and patient demographic and clinical data routinely available at presentation as potential predictor variables. We externally validated the rule in 221 inpatients with pulmonary embolism from Switzerland and France.
We compared mortality and nonfatal adverse medical outcomes across the derivation and two validation samples.
The prediction rule is based on 11 simple patient characteristics that were independently associated with mortality and stratifies patients with pulmonary embolism into five severity classes, with 30-day mortality rates of 0-1.6% in class I, 1.7-3.5% in class II, 3.2-7.1% in class III, 4.0-11.4% in class IV, and 10.0-24.5% in class V across the derivation and validation samples. Inpatient death and nonfatal complications were <or= 1.1% among patients in class I and <or= 1.9% among patients in class II.
Our rule accurately classifies patients with pulmonary embolism into classes of increasing risk of mortality and other adverse medical outcomes. Further validation of the rule is important before its implementation as a decision aid to guide the initial management of patients with pulmonary embolism.</abstract><cop>New York, NY</cop><pub>Am Thoracic Soc</pub><pmid>16020800</pmid><doi>10.1164/rccm.200506-862OC</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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source | Freely Accessible Science Journals - check A-Z of ejournals; Free E-Journal (出版社公開部分のみ) |
subjects | Acute Disease Aged Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy Biological and medical sciences Cause of Death Comorbidity Decision Support Techniques Discriminant Analysis Female France - epidemiology Hospitals Hospitals, University Humans Intensive care medicine J. Pulmonary Vascular Disease Laboratories Logistic Models Male Medical sciences Metabolic diseases Mortality Obesity Patients Pennsylvania - epidemiology Pneumology Predictive Value of Tests Prognosis Pulmonary Embolism - classification Pulmonary Embolism - complications Pulmonary Embolism - diagnosis Pulmonary Embolism - mortality Pulmonary Embolism - therapy Pulmonary embolisms Pulmonary hypertension. Acute cor pulmonale. Pulmonary embolism. Pulmonary vascular diseases Regression analysis Risk Assessment - organization & administration Risk Factors ROC Curve Severity of Illness Index Switzerland - epidemiology Tomography |
title | Derivation and Validation of a Prognostic Model for Pulmonary Embolism |
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