Simple Risk Algorithm to Predict Serious Bleeding in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: RISK-PCI Bleeding Score
Background: Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention (PPCI). It occurs most frequently within the first 30 days following the intervention. The aim of this study was to generate a simple and accurate risk model for the prediction of bleedin...
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| Veröffentlicht in: | Circulation Journal 2013, Vol.77(7), pp.1719-1727 |
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| creator | Mrdovic, Igor Savic, Lidija Krljanac, Gordana Asanin, Milika Lasica, Ratko Djuricic, Nemanja Brdar, Natasa Marinkovic, Jelena Kocev, Nikola Perunicic, Jovan |
| description | Background: Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention (PPCI). It occurs most frequently within the first 30 days following the intervention. The aim of this study was to generate a simple and accurate risk model for the prediction of bleeding after PPCI. Methods and Results: The training set included 2,096 patients enrolled in the RISK-PCI trial. The model was validated using a database of 961 patients enrolled in the ART-PCI trial. Bleeding was defined as type ≥3a bleeding according to the Bleeding Academic Research Consortium definition. Multivariate logistic regression was used to evaluate the predictors of outcome. A sum of weighted points for specific predictors was calculated to determine the final score. The model included 5 independent predictors of 30-day bleeding: gender (female); history of peptic ulcer; creatinine clearance at admission ( |
| doi_str_mv | 10.1253/circj.CJ-12-1177 |
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| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1372697611</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1372697611</sourcerecordid><originalsourceid>FETCH-LOGICAL-c381t-b78065528bf8a3e44cde25b73d2c198995a61e695c7e17d27fa4998e2ff3aa263</originalsourceid><addsrcrecordid>eNpFkU1v3CAYhFHVqknT3HuqOPbixIBtzDG1knajVF11E-WIWPzaYWvDBthI-T39o8HrbXLhY3hmAA1CX0h-RmjJzrXxenPWXGeEZoRw_g4dE1bwrKhp_n6_rjJRF-wIfQphk-dU5KX4iI4oq3KW9GP0b2XG7QD4jwl_8cXQO2_iw4ijw0sPrdERr8Abtwv4-wBJsD02Fi9VNGBjwPeJxqvbbAX9mAR8OcBTOnMW_3p2WvnWqAEvbKe83qt3tgXfuylm6c2o_DNegte7qCxMlzTOOzupCxvBP6XI5PqMPnRqCHB6mE_Q3dXlbfMzu_n9Y9Fc3GSa1SRma17nVVnSet3VikFR6BZoueaspZqIWohSVQQqUWoOhLeUd6oQogbadUwpWrET9G3O3Xr3uIMQ5WiChmGYHycJ47QSvCIkofmMau9C8NDJ7fwdSXI5VSP31cjmOu3kVE2yfD2k79YjtK-G_10k4GoGNiGqHl4B5aPRAxwSOZd8Gt6S34AH5SVY9gL7kqgg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1372697611</pqid></control><display><type>article</type><title>Simple Risk Algorithm to Predict Serious Bleeding in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: RISK-PCI Bleeding Score</title><source>J-STAGE Free</source><source>MEDLINE</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Mrdovic, Igor ; Savic, Lidija ; Krljanac, Gordana ; Asanin, Milika ; Lasica, Ratko ; Djuricic, Nemanja ; Brdar, Natasa ; Marinkovic, Jelena ; Kocev, Nikola ; Perunicic, Jovan</creator><creatorcontrib>Mrdovic, Igor ; Savic, Lidija ; Krljanac, Gordana ; Asanin, Milika ; Lasica, Ratko ; Djuricic, Nemanja ; Brdar, Natasa ; Marinkovic, Jelena ; Kocev, Nikola ; Perunicic, Jovan</creatorcontrib><description>Background: Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention (PPCI). It occurs most frequently within the first 30 days following the intervention. The aim of this study was to generate a simple and accurate risk model for the prediction of bleeding after PPCI. Methods and Results: The training set included 2,096 patients enrolled in the RISK-PCI trial. The model was validated using a database of 961 patients enrolled in the ART-PCI trial. Bleeding was defined as type ≥3a bleeding according to the Bleeding Academic Research Consortium definition. Multivariate logistic regression was used to evaluate the predictors of outcome. A sum of weighted points for specific predictors was calculated to determine the final score. The model included 5 independent predictors of 30-day bleeding: gender (female); history of peptic ulcer; creatinine clearance at admission (<60ml/min); hemoglobin at presentation (<125g/dl); and Killip class >1 heart failure at admission. The model showed good discrimination and calibration for the prediction of bleeding in the derivation set (C-statistic, 0.79; goodness of fit, P=0.12) and in the validation set (C-statistic, 0.76; goodness of fit, P=0.37). Patients were classified into 3 risk classes and the observed incidence of 30-day bleeding of 1.0%, 3.5% and 10.7% corresponded to the low-, intermediate- and high-risk classes, respectively. Conclusions: A simple risk model was developed that has a reasonably good capacity for the prediction of 30-day bleeding after PPCI. (Circ J 2013; 77: 1719–1727)</description><identifier>ISSN: 1346-9843</identifier><identifier>EISSN: 1347-4820</identifier><identifier>DOI: 10.1253/circj.CJ-12-1177</identifier><identifier>PMID: 23603843</identifier><language>eng</language><publisher>Japan: The Japanese Circulation Society</publisher><subject>Aged ; Algorithms ; Female ; Follow-Up Studies ; Humans ; Incidence ; Male ; Middle Aged ; Models, Cardiovascular ; Myocardial Infarction - epidemiology ; Myocardial Infarction - physiopathology ; Myocardial Infarction - therapy ; Percutaneous Coronary Intervention - adverse effects ; Postoperative Hemorrhage - epidemiology ; Postoperative Hemorrhage - etiology ; Postoperative Hemorrhage - physiopathology ; Predictive Value of Tests ; Primary percutaneous coronary intervention ; Risk Assessment - methods ; Risk Factors ; Risk score ; Serious bleeding ; Sex Factors ; Time Factors</subject><ispartof>Circulation Journal, 2013, Vol.77(7), pp.1719-1727</ispartof><rights>2013 THE JAPANESE CIRCULATION SOCIETY</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,1883,4024,27923,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23603843$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mrdovic, Igor</creatorcontrib><creatorcontrib>Savic, Lidija</creatorcontrib><creatorcontrib>Krljanac, Gordana</creatorcontrib><creatorcontrib>Asanin, Milika</creatorcontrib><creatorcontrib>Lasica, Ratko</creatorcontrib><creatorcontrib>Djuricic, Nemanja</creatorcontrib><creatorcontrib>Brdar, Natasa</creatorcontrib><creatorcontrib>Marinkovic, Jelena</creatorcontrib><creatorcontrib>Kocev, Nikola</creatorcontrib><creatorcontrib>Perunicic, Jovan</creatorcontrib><title>Simple Risk Algorithm to Predict Serious Bleeding in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: RISK-PCI Bleeding Score</title><title>Circulation Journal</title><addtitle>Circ J</addtitle><description>Background: Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention (PPCI). It occurs most frequently within the first 30 days following the intervention. The aim of this study was to generate a simple and accurate risk model for the prediction of bleeding after PPCI. Methods and Results: The training set included 2,096 patients enrolled in the RISK-PCI trial. The model was validated using a database of 961 patients enrolled in the ART-PCI trial. Bleeding was defined as type ≥3a bleeding according to the Bleeding Academic Research Consortium definition. Multivariate logistic regression was used to evaluate the predictors of outcome. A sum of weighted points for specific predictors was calculated to determine the final score. The model included 5 independent predictors of 30-day bleeding: gender (female); history of peptic ulcer; creatinine clearance at admission (<60ml/min); hemoglobin at presentation (<125g/dl); and Killip class >1 heart failure at admission. The model showed good discrimination and calibration for the prediction of bleeding in the derivation set (C-statistic, 0.79; goodness of fit, P=0.12) and in the validation set (C-statistic, 0.76; goodness of fit, P=0.37). Patients were classified into 3 risk classes and the observed incidence of 30-day bleeding of 1.0%, 3.5% and 10.7% corresponded to the low-, intermediate- and high-risk classes, respectively. Conclusions: A simple risk model was developed that has a reasonably good capacity for the prediction of 30-day bleeding after PPCI. (Circ J 2013; 77: 1719–1727)</description><subject>Aged</subject><subject>Algorithms</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Humans</subject><subject>Incidence</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Cardiovascular</subject><subject>Myocardial Infarction - epidemiology</subject><subject>Myocardial Infarction - physiopathology</subject><subject>Myocardial Infarction - therapy</subject><subject>Percutaneous Coronary Intervention - adverse effects</subject><subject>Postoperative Hemorrhage - epidemiology</subject><subject>Postoperative Hemorrhage - etiology</subject><subject>Postoperative Hemorrhage - physiopathology</subject><subject>Predictive Value of Tests</subject><subject>Primary percutaneous coronary intervention</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Risk score</subject><subject>Serious bleeding</subject><subject>Sex Factors</subject><subject>Time Factors</subject><issn>1346-9843</issn><issn>1347-4820</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpFkU1v3CAYhFHVqknT3HuqOPbixIBtzDG1knajVF11E-WIWPzaYWvDBthI-T39o8HrbXLhY3hmAA1CX0h-RmjJzrXxenPWXGeEZoRw_g4dE1bwrKhp_n6_rjJRF-wIfQphk-dU5KX4iI4oq3KW9GP0b2XG7QD4jwl_8cXQO2_iw4ijw0sPrdERr8Abtwv4-wBJsD02Fi9VNGBjwPeJxqvbbAX9mAR8OcBTOnMW_3p2WvnWqAEvbKe83qt3tgXfuylm6c2o_DNegte7qCxMlzTOOzupCxvBP6XI5PqMPnRqCHB6mE_Q3dXlbfMzu_n9Y9Fc3GSa1SRma17nVVnSet3VikFR6BZoueaspZqIWohSVQQqUWoOhLeUd6oQogbadUwpWrET9G3O3Xr3uIMQ5WiChmGYHycJ47QSvCIkofmMau9C8NDJ7fwdSXI5VSP31cjmOu3kVE2yfD2k79YjtK-G_10k4GoGNiGqHl4B5aPRAxwSOZd8Gt6S34AH5SVY9gL7kqgg</recordid><startdate>2013</startdate><enddate>2013</enddate><creator>Mrdovic, Igor</creator><creator>Savic, Lidija</creator><creator>Krljanac, Gordana</creator><creator>Asanin, Milika</creator><creator>Lasica, Ratko</creator><creator>Djuricic, Nemanja</creator><creator>Brdar, Natasa</creator><creator>Marinkovic, Jelena</creator><creator>Kocev, Nikola</creator><creator>Perunicic, Jovan</creator><general>The Japanese Circulation Society</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></search><sort><creationdate>2013</creationdate><title>Simple Risk Algorithm to Predict Serious Bleeding in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention</title><author>Mrdovic, Igor ; Savic, Lidija ; Krljanac, Gordana ; Asanin, Milika ; Lasica, Ratko ; Djuricic, Nemanja ; Brdar, Natasa ; Marinkovic, Jelena ; Kocev, Nikola ; Perunicic, Jovan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c381t-b78065528bf8a3e44cde25b73d2c198995a61e695c7e17d27fa4998e2ff3aa263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Aged</topic><topic>Algorithms</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Humans</topic><topic>Incidence</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Cardiovascular</topic><topic>Myocardial Infarction - epidemiology</topic><topic>Myocardial Infarction - physiopathology</topic><topic>Myocardial Infarction - therapy</topic><topic>Percutaneous Coronary Intervention - adverse effects</topic><topic>Postoperative Hemorrhage - epidemiology</topic><topic>Postoperative Hemorrhage - etiology</topic><topic>Postoperative Hemorrhage - physiopathology</topic><topic>Predictive Value of Tests</topic><topic>Primary percutaneous coronary intervention</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>Risk score</topic><topic>Serious bleeding</topic><topic>Sex Factors</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mrdovic, Igor</creatorcontrib><creatorcontrib>Savic, Lidija</creatorcontrib><creatorcontrib>Krljanac, Gordana</creatorcontrib><creatorcontrib>Asanin, Milika</creatorcontrib><creatorcontrib>Lasica, Ratko</creatorcontrib><creatorcontrib>Djuricic, Nemanja</creatorcontrib><creatorcontrib>Brdar, Natasa</creatorcontrib><creatorcontrib>Marinkovic, Jelena</creatorcontrib><creatorcontrib>Kocev, Nikola</creatorcontrib><creatorcontrib>Perunicic, Jovan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Circulation Journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mrdovic, Igor</au><au>Savic, Lidija</au><au>Krljanac, Gordana</au><au>Asanin, Milika</au><au>Lasica, Ratko</au><au>Djuricic, Nemanja</au><au>Brdar, Natasa</au><au>Marinkovic, Jelena</au><au>Kocev, Nikola</au><au>Perunicic, Jovan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simple Risk Algorithm to Predict Serious Bleeding in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: RISK-PCI Bleeding Score</atitle><jtitle>Circulation Journal</jtitle><addtitle>Circ J</addtitle><date>2013</date><risdate>2013</risdate><volume>77</volume><issue>7</issue><spage>1719</spage><epage>1727</epage><pages>1719-1727</pages><issn>1346-9843</issn><eissn>1347-4820</eissn><abstract>Background: Bleeding is a potentially catastrophic complication after primary percutaneous coronary intervention (PPCI). It occurs most frequently within the first 30 days following the intervention. The aim of this study was to generate a simple and accurate risk model for the prediction of bleeding after PPCI. Methods and Results: The training set included 2,096 patients enrolled in the RISK-PCI trial. The model was validated using a database of 961 patients enrolled in the ART-PCI trial. Bleeding was defined as type ≥3a bleeding according to the Bleeding Academic Research Consortium definition. Multivariate logistic regression was used to evaluate the predictors of outcome. A sum of weighted points for specific predictors was calculated to determine the final score. The model included 5 independent predictors of 30-day bleeding: gender (female); history of peptic ulcer; creatinine clearance at admission (<60ml/min); hemoglobin at presentation (<125g/dl); and Killip class >1 heart failure at admission. The model showed good discrimination and calibration for the prediction of bleeding in the derivation set (C-statistic, 0.79; goodness of fit, P=0.12) and in the validation set (C-statistic, 0.76; goodness of fit, P=0.37). Patients were classified into 3 risk classes and the observed incidence of 30-day bleeding of 1.0%, 3.5% and 10.7% corresponded to the low-, intermediate- and high-risk classes, respectively. Conclusions: A simple risk model was developed that has a reasonably good capacity for the prediction of 30-day bleeding after PPCI. (Circ J 2013; 77: 1719–1727)</abstract><cop>Japan</cop><pub>The Japanese Circulation Society</pub><pmid>23603843</pmid><doi>10.1253/circj.CJ-12-1177</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Circulation Journal, 2013, Vol.77(7), pp.1719-1727 |
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| subjects | Aged Algorithms Female Follow-Up Studies Humans Incidence Male Middle Aged Models, Cardiovascular Myocardial Infarction - epidemiology Myocardial Infarction - physiopathology Myocardial Infarction - therapy Percutaneous Coronary Intervention - adverse effects Postoperative Hemorrhage - epidemiology Postoperative Hemorrhage - etiology Postoperative Hemorrhage - physiopathology Predictive Value of Tests Primary percutaneous coronary intervention Risk Assessment - methods Risk Factors Risk score Serious bleeding Sex Factors Time Factors |
| title | Simple Risk Algorithm to Predict Serious Bleeding in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention: RISK-PCI Bleeding Score |
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