A predictive model of early mortality in trauma patients

Abstract Background Rapid thrombelastography (rTEG) is a real-time whole-blood viscoelastic coagulation assay. We hypothesized that admission rTEG and clinical data are independent predictors of trauma-related mortality. Methods Prospective observational data (patient demographics, admission vital s...

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Veröffentlicht in:The American journal of surgery 2014-05, Vol.207 (5), p.642-647
Hauptverfasser: Hampton, David A., M.D., M.Eng, Lee, Tim H., M.D, Diggs, Brian S., Ph.D, McCully, Sean P., M.D, Schreiber, Martin A., M.D., F.A.C.S
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container_end_page 647
container_issue 5
container_start_page 642
container_title The American journal of surgery
container_volume 207
creator Hampton, David A., M.D., M.Eng
Lee, Tim H., M.D
Diggs, Brian S., Ph.D
McCully, Sean P., M.D
Schreiber, Martin A., M.D., F.A.C.S
description Abstract Background Rapid thrombelastography (rTEG) is a real-time whole-blood viscoelastic coagulation assay. We hypothesized that admission rTEG and clinical data are independent predictors of trauma-related mortality. Methods Prospective observational data (patient demographics, admission vital signs, laboratory studies, and injury characteristics) from trauma patients enrolled within 6 hours of injury were collected. Mann–Whitney U test and analysis of variance test assessed significance ( P ≤ .05). Logistic regression analyses determined the association of the studied variables with 24-hour mortality. Results Seven hundred ninety-five trauma patients were enrolled, of which 55 died within 24 hours of admission. Admission variables which independently predicted 24-hour mortality were as follows: Glasgow Coma Scale ≤8, hemoglobin 1.5, Ly30 >8%, and penetrating injury ( P < .05). This 5-variable model's area under the receiver operator characteristic curve was .88. The Hosmer–Lemeshow goodness-of-fit test was .90. Conclusions This 5-variable model provides a rapid prediction of 24-hour mortality. The inclusion of rTEG Ly30 demonstrates the association of fibrinolysis with outcome and may support the early use of antifibrinolytic therapies.
doi_str_mv 10.1016/j.amjsurg.2013.12.009
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We hypothesized that admission rTEG and clinical data are independent predictors of trauma-related mortality. Methods Prospective observational data (patient demographics, admission vital signs, laboratory studies, and injury characteristics) from trauma patients enrolled within 6 hours of injury were collected. Mann–Whitney U test and analysis of variance test assessed significance ( P ≤ .05). Logistic regression analyses determined the association of the studied variables with 24-hour mortality. Results Seven hundred ninety-five trauma patients were enrolled, of which 55 died within 24 hours of admission. Admission variables which independently predicted 24-hour mortality were as follows: Glasgow Coma Scale ≤8, hemoglobin &lt;11 g/dL, international normalized ratio &gt;1.5, Ly30 &gt;8%, and penetrating injury ( P &lt; .05). This 5-variable model's area under the receiver operator characteristic curve was .88. The Hosmer–Lemeshow goodness-of-fit test was .90. Conclusions This 5-variable model provides a rapid prediction of 24-hour mortality. The inclusion of rTEG Ly30 demonstrates the association of fibrinolysis with outcome and may support the early use of antifibrinolytic therapies.</description><identifier>ISSN: 0002-9610</identifier><identifier>EISSN: 1879-1883</identifier><identifier>DOI: 10.1016/j.amjsurg.2013.12.009</identifier><identifier>PMID: 24630907</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Age ; Blood pressure ; Coma ; Confidence intervals ; Decision Support Techniques ; Emergency medical care ; Heart rate ; Humans ; Injuries ; Logistic Models ; Logistics ; Middle Aged ; Mortality ; Patients ; Prognosis ; Prospective Studies ; Risk Assessment ; ROC Curve ; Surgery ; Thrombelastography ; Trauma ; Variables ; Wounds and Injuries - blood ; Wounds and Injuries - mortality</subject><ispartof>The American journal of surgery, 2014-05, Vol.207 (5), p.642-647</ispartof><rights>Elsevier Inc.</rights><rights>2014 Elsevier Inc.</rights><rights>Copyright © 2014 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited May 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c448t-79c96a5d006979ed04e85979a8d8a9db511adbd7350f0c2f59401b515a3ca4123</citedby><cites>FETCH-LOGICAL-c448t-79c96a5d006979ed04e85979a8d8a9db511adbd7350f0c2f59401b515a3ca4123</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S000296101400066X$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24630907$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hampton, David A., M.D., M.Eng</creatorcontrib><creatorcontrib>Lee, Tim H., M.D</creatorcontrib><creatorcontrib>Diggs, Brian S., Ph.D</creatorcontrib><creatorcontrib>McCully, Sean P., M.D</creatorcontrib><creatorcontrib>Schreiber, Martin A., M.D., F.A.C.S</creatorcontrib><title>A predictive model of early mortality in trauma patients</title><title>The American journal of surgery</title><addtitle>Am J Surg</addtitle><description>Abstract Background Rapid thrombelastography (rTEG) is a real-time whole-blood viscoelastic coagulation assay. We hypothesized that admission rTEG and clinical data are independent predictors of trauma-related mortality. Methods Prospective observational data (patient demographics, admission vital signs, laboratory studies, and injury characteristics) from trauma patients enrolled within 6 hours of injury were collected. Mann–Whitney U test and analysis of variance test assessed significance ( P ≤ .05). Logistic regression analyses determined the association of the studied variables with 24-hour mortality. Results Seven hundred ninety-five trauma patients were enrolled, of which 55 died within 24 hours of admission. Admission variables which independently predicted 24-hour mortality were as follows: Glasgow Coma Scale ≤8, hemoglobin &lt;11 g/dL, international normalized ratio &gt;1.5, Ly30 &gt;8%, and penetrating injury ( P &lt; .05). This 5-variable model's area under the receiver operator characteristic curve was .88. The Hosmer–Lemeshow goodness-of-fit test was .90. 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The inclusion of rTEG Ly30 demonstrates the association of fibrinolysis with outcome and may support the early use of antifibrinolytic therapies.</description><subject>Adult</subject><subject>Age</subject><subject>Blood pressure</subject><subject>Coma</subject><subject>Confidence intervals</subject><subject>Decision Support Techniques</subject><subject>Emergency medical care</subject><subject>Heart rate</subject><subject>Humans</subject><subject>Injuries</subject><subject>Logistic Models</subject><subject>Logistics</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Patients</subject><subject>Prognosis</subject><subject>Prospective Studies</subject><subject>Risk Assessment</subject><subject>ROC Curve</subject><subject>Surgery</subject><subject>Thrombelastography</subject><subject>Trauma</subject><subject>Variables</subject><subject>Wounds and Injuries - blood</subject><subject>Wounds and Injuries - mortality</subject><issn>0002-9610</issn><issn>1879-1883</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkUuLFDEQgIMo7rj6E5QGL166rUrSj1yUZdFVWPCggreQSaolbT_GJL0w_940M7qwF3NJVfiqknzF2EuECgGbt0NlpiGu4WfFAUWFvAJQj9gOu1aV2HXiMdsBAC9Vg3DBnsU45BRRiqfsgstGgIJ2x7qr4hDIeZv8HRXT4mgslr4gE8ZjTkMyo0_Hws9FCmadTHEwydOc4nP2pDdjpBfn_ZJ9__jh2_Wn8vbLzefrq9vSStmlslVWNaZ2AI1qFTmQ1NU5Mp3rjHL7GtG4vWtFDT1Y3tdKAubT2ghrJHJxyd6c-h7C8nulmPTko6VxNDMta9RYcxRcgVQZff0AHZY1zPl1GwXYNnllqj5RNiwxBur1IfjJhKNG0JtaPeizWr2p1ch1VpvrXp27r_uJ3L-qvy4z8P4EUNZx5ynoaLMqm-0Gskm7xf_3incPOtjRz96a8RcdKd7_RsdcoL9u893GizJHTfND_AH_gZ-u</recordid><startdate>20140501</startdate><enddate>20140501</enddate><creator>Hampton, David A., M.D., M.Eng</creator><creator>Lee, Tim H., M.D</creator><creator>Diggs, Brian S., Ph.D</creator><creator>McCully, Sean P., M.D</creator><creator>Schreiber, Martin A., M.D., F.A.C.S</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20140501</creationdate><title>A predictive model of early mortality in trauma patients</title><author>Hampton, David A., M.D., M.Eng ; Lee, Tim H., M.D ; Diggs, Brian S., Ph.D ; McCully, Sean P., M.D ; Schreiber, Martin A., M.D., F.A.C.S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c448t-79c96a5d006979ed04e85979a8d8a9db511adbd7350f0c2f59401b515a3ca4123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Adult</topic><topic>Age</topic><topic>Blood pressure</topic><topic>Coma</topic><topic>Confidence intervals</topic><topic>Decision Support Techniques</topic><topic>Emergency medical care</topic><topic>Heart rate</topic><topic>Humans</topic><topic>Injuries</topic><topic>Logistic Models</topic><topic>Logistics</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Patients</topic><topic>Prognosis</topic><topic>Prospective Studies</topic><topic>Risk Assessment</topic><topic>ROC Curve</topic><topic>Surgery</topic><topic>Thrombelastography</topic><topic>Trauma</topic><topic>Variables</topic><topic>Wounds and Injuries - blood</topic><topic>Wounds and Injuries - mortality</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hampton, David A., M.D., M.Eng</creatorcontrib><creatorcontrib>Lee, Tim H., M.D</creatorcontrib><creatorcontrib>Diggs, Brian S., Ph.D</creatorcontrib><creatorcontrib>McCully, Sean P., M.D</creatorcontrib><creatorcontrib>Schreiber, Martin A., M.D., F.A.C.S</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Health &amp; 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We hypothesized that admission rTEG and clinical data are independent predictors of trauma-related mortality. Methods Prospective observational data (patient demographics, admission vital signs, laboratory studies, and injury characteristics) from trauma patients enrolled within 6 hours of injury were collected. Mann–Whitney U test and analysis of variance test assessed significance ( P ≤ .05). Logistic regression analyses determined the association of the studied variables with 24-hour mortality. Results Seven hundred ninety-five trauma patients were enrolled, of which 55 died within 24 hours of admission. Admission variables which independently predicted 24-hour mortality were as follows: Glasgow Coma Scale ≤8, hemoglobin &lt;11 g/dL, international normalized ratio &gt;1.5, Ly30 &gt;8%, and penetrating injury ( P &lt; .05). This 5-variable model's area under the receiver operator characteristic curve was .88. The Hosmer–Lemeshow goodness-of-fit test was .90. Conclusions This 5-variable model provides a rapid prediction of 24-hour mortality. The inclusion of rTEG Ly30 demonstrates the association of fibrinolysis with outcome and may support the early use of antifibrinolytic therapies.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>24630907</pmid><doi>10.1016/j.amjsurg.2013.12.009</doi><tpages>6</tpages></addata></record>
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subjects Adult
Age
Blood pressure
Coma
Confidence intervals
Decision Support Techniques
Emergency medical care
Heart rate
Humans
Injuries
Logistic Models
Logistics
Middle Aged
Mortality
Patients
Prognosis
Prospective Studies
Risk Assessment
ROC Curve
Surgery
Thrombelastography
Trauma
Variables
Wounds and Injuries - blood
Wounds and Injuries - mortality
title A predictive model of early mortality in trauma patients
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