Prediction of Bleeding After Cardiac Surgery: Comparison of Model Performances: A Prospective Observational Study

Objectives Primary aims were to (1) perform external validation of the Papworth Bleeding Risk Score, and (2) compare the usefulness of the Dyke et al universal definition of perioperative bleeding with that used in the Papworth Bleeding Risk Score. A secondary aim was to use a locally developed logi...

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Veröffentlicht in:Journal of cardiothoracic and vascular anesthesia 2015-04, Vol.29 (2), p.311-319
Hauptverfasser: Greiff, Guri, MD, Pleym, Hilde, MD, PhD, Stenseth, Roar, MD, PhD, Berg, Kristin S., MD, Wahba, Alexander, MD, PhD, Videm, Vibeke, MD, PhD
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container_end_page 319
container_issue 2
container_start_page 311
container_title Journal of cardiothoracic and vascular anesthesia
container_volume 29
creator Greiff, Guri, MD
Pleym, Hilde, MD, PhD
Stenseth, Roar, MD, PhD
Berg, Kristin S., MD
Wahba, Alexander, MD, PhD
Videm, Vibeke, MD, PhD
description Objectives Primary aims were to (1) perform external validation of the Papworth Bleeding Risk Score, and (2) compare the usefulness of the Dyke et al universal definition of perioperative bleeding with that used in the Papworth Bleeding Risk Score. A secondary aim was to use a locally developed logistic prediction model for severe postoperative bleeding to investigate whether prediction could be improved with inclusion of the variable “surgeon” or selected intraoperative variables. Design Single-center prospective observational study. Setting University hospital. Participants 7,030 adults undergoing cardiac surgery. Interventions None. Measurements and Main Results Papworth Bleeding Risk Score could identify the group of patients with low risk of postoperative bleeding, with negative predictive value of 0.98, when applying the Papworth Score on this population. The positive predictive value was low; only 15% of the patients who were rated high risk actually suffered from increased postoperative bleeding when using the Papworth Score on this population. Using the universal definition of perioperative bleeding proposed by Dyke et al, 28% of patients in the Papworth high-risk group exceeded the threshold of excessive bleeding in this population. The local models showed low ability for discrimination (area under the receiver operating characteristics curve
doi_str_mv 10.1053/j.jvca.2014.08.002
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A secondary aim was to use a locally developed logistic prediction model for severe postoperative bleeding to investigate whether prediction could be improved with inclusion of the variable “surgeon” or selected intraoperative variables. Design Single-center prospective observational study. Setting University hospital. Participants 7,030 adults undergoing cardiac surgery. Interventions None. Measurements and Main Results Papworth Bleeding Risk Score could identify the group of patients with low risk of postoperative bleeding, with negative predictive value of 0.98, when applying the Papworth Score on this population. The positive predictive value was low; only 15% of the patients who were rated high risk actually suffered from increased postoperative bleeding when using the Papworth Score on this population. Using the universal definition of perioperative bleeding proposed by Dyke et al, 28% of patients in the Papworth high-risk group exceeded the threshold of excessive bleeding in this population. The local models showed low ability for discrimination (area under the receiver operating characteristics curve&lt;0.75). Addition of the factor “surgeon” or selected intraoperative variables did not substantially improve the models. Conclusion Prediction of risk for excessive bleeding after cardiac surgery was not possible using clinical variables only, independent of endpoint definition and inclusion of the variable “surgeon” or of selected intraoperative variables. These findings may be due to incomplete understanding of the causative factors underlying excessive bleeding.</description><identifier>ISSN: 1053-0770</identifier><identifier>EISSN: 1532-8422</identifier><identifier>DOI: 10.1053/j.jvca.2014.08.002</identifier><identifier>PMID: 25529438</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; Anesthesia &amp; Perioperative Care ; bleeding endpoint ; cardiac surgery ; Cardiac Surgical Procedures - adverse effects ; Critical Care ; Female ; hemorrhage ; Humans ; Male ; Models, Theoretical ; Postoperative Hemorrhage - diagnosis ; Postoperative Hemorrhage - etiology ; Prospective Studies ; Reproducibility of Results ; Risk Factors ; risk prediction ; risk score ; ROC Curve</subject><ispartof>Journal of cardiothoracic and vascular anesthesia, 2015-04, Vol.29 (2), p.311-319</ispartof><rights>Elsevier Inc.</rights><rights>2015 Elsevier Inc.</rights><rights>Copyright © 2015 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c481t-ee0d6daaf57a9b8a24f495d3b566b87142257ee64f4b852df113a90fd02e0733</citedby><cites>FETCH-LOGICAL-c481t-ee0d6daaf57a9b8a24f495d3b566b87142257ee64f4b852df113a90fd02e0733</cites><orcidid>0000-0002-8528-5644 ; 0000-0002-4548-0293</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1053/j.jvca.2014.08.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,27929,27930,46000</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25529438$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Greiff, Guri, MD</creatorcontrib><creatorcontrib>Pleym, Hilde, MD, PhD</creatorcontrib><creatorcontrib>Stenseth, Roar, MD, PhD</creatorcontrib><creatorcontrib>Berg, Kristin S., MD</creatorcontrib><creatorcontrib>Wahba, Alexander, MD, PhD</creatorcontrib><creatorcontrib>Videm, Vibeke, MD, PhD</creatorcontrib><title>Prediction of Bleeding After Cardiac Surgery: Comparison of Model Performances: A Prospective Observational Study</title><title>Journal of cardiothoracic and vascular anesthesia</title><addtitle>J Cardiothorac Vasc Anesth</addtitle><description>Objectives Primary aims were to (1) perform external validation of the Papworth Bleeding Risk Score, and (2) compare the usefulness of the Dyke et al universal definition of perioperative bleeding with that used in the Papworth Bleeding Risk Score. A secondary aim was to use a locally developed logistic prediction model for severe postoperative bleeding to investigate whether prediction could be improved with inclusion of the variable “surgeon” or selected intraoperative variables. Design Single-center prospective observational study. Setting University hospital. Participants 7,030 adults undergoing cardiac surgery. Interventions None. Measurements and Main Results Papworth Bleeding Risk Score could identify the group of patients with low risk of postoperative bleeding, with negative predictive value of 0.98, when applying the Papworth Score on this population. The positive predictive value was low; only 15% of the patients who were rated high risk actually suffered from increased postoperative bleeding when using the Papworth Score on this population. Using the universal definition of perioperative bleeding proposed by Dyke et al, 28% of patients in the Papworth high-risk group exceeded the threshold of excessive bleeding in this population. The local models showed low ability for discrimination (area under the receiver operating characteristics curve&lt;0.75). Addition of the factor “surgeon” or selected intraoperative variables did not substantially improve the models. Conclusion Prediction of risk for excessive bleeding after cardiac surgery was not possible using clinical variables only, independent of endpoint definition and inclusion of the variable “surgeon” or of selected intraoperative variables. These findings may be due to incomplete understanding of the causative factors underlying excessive bleeding.</description><subject>Aged</subject><subject>Anesthesia &amp; Perioperative Care</subject><subject>bleeding endpoint</subject><subject>cardiac surgery</subject><subject>Cardiac Surgical Procedures - adverse effects</subject><subject>Critical Care</subject><subject>Female</subject><subject>hemorrhage</subject><subject>Humans</subject><subject>Male</subject><subject>Models, Theoretical</subject><subject>Postoperative Hemorrhage - diagnosis</subject><subject>Postoperative Hemorrhage - etiology</subject><subject>Prospective Studies</subject><subject>Reproducibility of Results</subject><subject>Risk Factors</subject><subject>risk prediction</subject><subject>risk score</subject><subject>ROC Curve</subject><issn>1053-0770</issn><issn>1532-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc1u1DAUhS0EoqXwAiyQl2wSru04PxVCGka0IBV1pOnecuybyiGJp3Yy0rw9jqawYMHKP_rukc9nQt4zyBlI8anP-6PROQdW5FDnAPwFuWRS8KwuOH-Z9onKoKrggryJsQdgTMrqNbngUvKmEPUledoFtM7Mzk_Ud_TrgOk4PdJNN2OgWx2s04bul_CI4XRNt3486ODimf7pLQ50h6HzYdSTwXhNN3QXfDxgijwivW8jhqNe4_VA9_NiT2_Jq04PEd89r1fk4ebbw_Z7dnd_-2O7uctMUbM5QwRbWq07WemmrTUvuqKRVrSyLNu6YqmhrBDLdN3WktuOMaEb6CxwhEqIK_LxHHsI_mnBOKvRRYPDoCf0S1SsLCXjwEuZUH5GTXp5DNipQ3CjDifFQK0OVa9W02o1raBWyXQa-vCcv7Qj2r8jf9Qm4PMZwFTy6DCoaBwmSdaFZEdZ7_6f_-WfcTO4yRk9_MITxt4vISlNPVTkCtR-zVm_mhUAQjYgfgN9x6TK</recordid><startdate>20150401</startdate><enddate>20150401</enddate><creator>Greiff, Guri, MD</creator><creator>Pleym, Hilde, MD, PhD</creator><creator>Stenseth, Roar, MD, PhD</creator><creator>Berg, Kristin S., MD</creator><creator>Wahba, Alexander, MD, PhD</creator><creator>Videm, Vibeke, MD, PhD</creator><general>Elsevier Inc</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>7X8</scope><orcidid>https://orcid.org/0000-0002-8528-5644</orcidid><orcidid>https://orcid.org/0000-0002-4548-0293</orcidid></search><sort><creationdate>20150401</creationdate><title>Prediction of Bleeding After Cardiac Surgery: Comparison of Model Performances: A Prospective Observational Study</title><author>Greiff, Guri, MD ; 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A secondary aim was to use a locally developed logistic prediction model for severe postoperative bleeding to investigate whether prediction could be improved with inclusion of the variable “surgeon” or selected intraoperative variables. Design Single-center prospective observational study. Setting University hospital. Participants 7,030 adults undergoing cardiac surgery. Interventions None. Measurements and Main Results Papworth Bleeding Risk Score could identify the group of patients with low risk of postoperative bleeding, with negative predictive value of 0.98, when applying the Papworth Score on this population. The positive predictive value was low; only 15% of the patients who were rated high risk actually suffered from increased postoperative bleeding when using the Papworth Score on this population. Using the universal definition of perioperative bleeding proposed by Dyke et al, 28% of patients in the Papworth high-risk group exceeded the threshold of excessive bleeding in this population. The local models showed low ability for discrimination (area under the receiver operating characteristics curve&lt;0.75). Addition of the factor “surgeon” or selected intraoperative variables did not substantially improve the models. Conclusion Prediction of risk for excessive bleeding after cardiac surgery was not possible using clinical variables only, independent of endpoint definition and inclusion of the variable “surgeon” or of selected intraoperative variables. 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subjects Aged
Anesthesia & Perioperative Care
bleeding endpoint
cardiac surgery
Cardiac Surgical Procedures - adverse effects
Critical Care
Female
hemorrhage
Humans
Male
Models, Theoretical
Postoperative Hemorrhage - diagnosis
Postoperative Hemorrhage - etiology
Prospective Studies
Reproducibility of Results
Risk Factors
risk prediction
risk score
ROC Curve
title Prediction of Bleeding After Cardiac Surgery: Comparison of Model Performances: A Prospective Observational Study
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