Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease
Abstract Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac i...
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| creator | Min, James K., MD Dunning, Allison, MS Gransar, Heidi, MS Achenbach, Stephan, MD Lin, Fay Y., MD Al-Mallah, Mouaz, MD Budoff, Matthew J., MD Callister, Tracy Q., MD Chang, Hyuk-Jae, MD Cademartiri, Filippo, MD Maffei, Erica, MD Chinnaiyan, Kavitha, MD Chow, Benjamin J.W., MD D'Agostino, Ralph, PhD DeLago, Augustin, MD Friedman, John, MD Hadamitzky, Martin, MD Hausleiter, Joerg, MD Hayes, Sean W., MD Kaufmann, Philipp, MD Raff, Gilbert L., MD Shaw, Leslee J., PhD Thomson, Louise, MD Villines, Todd, MD Cury, Ricardo C., MD Feuchtner, Gudrun, MD Kim, Yong-Jin, MD Leipsic, Jonathon, MD Marques, Hugo, MD Berman, Daniel S., MD Pencina, Michael, PhD |
| description | Abstract Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease. |
| doi_str_mv | 10.1016/j.amjmed.2014.10.031 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4516558</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>1_s2_0_S0002934314009735</els_id><sourcerecordid>3789171701</sourcerecordid><originalsourceid>FETCH-LOGICAL-c546t-dde76f818109ad280867d8b7d14ef2e95a9f9776360d1928e03b00349aa222903</originalsourceid><addsrcrecordid>eNqFUsFu1DAQjRCIbgt_gJAlLlyy2E7sxBek1RYoUhEVC2fLG09ap0m89TiL-vd1tKWFXjiNPPPm-c28ybI3jC4ZZfJDtzRDN4BdcsrKlFrSgj3LFkwIkVdM8ufZglLKc1WUxVF2jNilJ1VCvsyOuKilULxYZPtvYF1jenLmMPpwS1ofyEXwl6PH6Bryw-E1WSEC4gBjJGa05NSZueyQ-JZsotn2QC5MdKmO5LeLV2Qz4Q6aCJasffCjSbyrECGFU4dgEF5lL1rTI7y-jyfZr8-ffq7P8vPvX76uV-d5I0oZc2uhkm3NakaVsbymtaxsva0sK6HloIRRraoqWUhqmeI10GJLaVEqYzjnihYn2ccD727apl01SWIwvd4FNyRR2hun_62M7kpf-r0uBZNC1Ing_T1B8DcTYNSDwwb63ozgJ9RMKlUqWgmeoO-eQDs_hTGNp1mVEElgOaPKA6oJHjFA-yCGUT0bqzt9MFbPxs7ZZGxqe_v3IA9Nf5x8nBTSOvcOgsYmOdIke0OyQlvv_vfDU4Kmd-N8G9dwC_g4i0auqd7MxzXfFivTVVWFKO4A9o_L1Q</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1707519242</pqid></control><display><type>article</type><title>Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><creator>Min, James K., MD ; Dunning, Allison, MS ; Gransar, Heidi, MS ; Achenbach, Stephan, MD ; Lin, Fay Y., MD ; Al-Mallah, Mouaz, MD ; Budoff, Matthew J., MD ; Callister, Tracy Q., MD ; Chang, Hyuk-Jae, MD ; Cademartiri, Filippo, MD ; Maffei, Erica, MD ; Chinnaiyan, Kavitha, MD ; Chow, Benjamin J.W., MD ; D'Agostino, Ralph, PhD ; DeLago, Augustin, MD ; Friedman, John, MD ; Hadamitzky, Martin, MD ; Hausleiter, Joerg, MD ; Hayes, Sean W., MD ; Kaufmann, Philipp, MD ; Raff, Gilbert L., MD ; Shaw, Leslee J., PhD ; Thomson, Louise, MD ; Villines, Todd, MD ; Cury, Ricardo C., MD ; Feuchtner, Gudrun, MD ; Kim, Yong-Jin, MD ; Leipsic, Jonathon, MD ; Marques, Hugo, MD ; Berman, Daniel S., MD ; Pencina, Michael, PhD</creator><creatorcontrib>Min, James K., MD ; Dunning, Allison, MS ; Gransar, Heidi, MS ; Achenbach, Stephan, MD ; Lin, Fay Y., MD ; Al-Mallah, Mouaz, MD ; Budoff, Matthew J., MD ; Callister, Tracy Q., MD ; Chang, Hyuk-Jae, MD ; Cademartiri, Filippo, MD ; Maffei, Erica, MD ; Chinnaiyan, Kavitha, MD ; Chow, Benjamin J.W., MD ; D'Agostino, Ralph, PhD ; DeLago, Augustin, MD ; Friedman, John, MD ; Hadamitzky, Martin, MD ; Hausleiter, Joerg, MD ; Hayes, Sean W., MD ; Kaufmann, Philipp, MD ; Raff, Gilbert L., MD ; Shaw, Leslee J., PhD ; Thomson, Louise, MD ; Villines, Todd, MD ; Cury, Ricardo C., MD ; Feuchtner, Gudrun, MD ; Kim, Yong-Jin, MD ; Leipsic, Jonathon, MD ; Marques, Hugo, MD ; Berman, Daniel S., MD ; Pencina, Michael, PhD</creatorcontrib><description>Abstract Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.</description><identifier>ISSN: 0002-9343</identifier><identifier>EISSN: 1555-7162</identifier><identifier>DOI: 10.1016/j.amjmed.2014.10.031</identifier><identifier>PMID: 25865923</identifier><identifier>CODEN: AJMEAZ</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adolescent ; Adult ; Adults ; Algorithms ; Cardiovascular disease ; Coronary Angiography ; Coronary artery disease ; Coronary Artery Disease - complications ; Coronary Artery Disease - diagnosis ; Diagnosis ; Female ; Humans ; Internal Medicine ; Male ; Medical History Taking ; Medical imaging ; Middle Aged ; Mortality ; Myocardial Infarction - diagnosis ; Myocardial Infarction - mortality ; Prognosis ; Proportional Hazards Models ; Reproducibility of Results ; Risk Assessment - methods ; Risk Factors ; Tomography, X-Ray Computed ; Young Adult</subject><ispartof>The American journal of medicine, 2015-08, Vol.128 (8), p.871-878</ispartof><rights>Elsevier Inc.</rights><rights>2015 Elsevier Inc.</rights><rights>Copyright © 2015 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Aug 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c546t-dde76f818109ad280867d8b7d14ef2e95a9f9776360d1928e03b00349aa222903</citedby><cites>FETCH-LOGICAL-c546t-dde76f818109ad280867d8b7d14ef2e95a9f9776360d1928e03b00349aa222903</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0002934314009735$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25865923$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Min, James K., MD</creatorcontrib><creatorcontrib>Dunning, Allison, MS</creatorcontrib><creatorcontrib>Gransar, Heidi, MS</creatorcontrib><creatorcontrib>Achenbach, Stephan, MD</creatorcontrib><creatorcontrib>Lin, Fay Y., MD</creatorcontrib><creatorcontrib>Al-Mallah, Mouaz, MD</creatorcontrib><creatorcontrib>Budoff, Matthew J., MD</creatorcontrib><creatorcontrib>Callister, Tracy Q., MD</creatorcontrib><creatorcontrib>Chang, Hyuk-Jae, MD</creatorcontrib><creatorcontrib>Cademartiri, Filippo, MD</creatorcontrib><creatorcontrib>Maffei, Erica, MD</creatorcontrib><creatorcontrib>Chinnaiyan, Kavitha, MD</creatorcontrib><creatorcontrib>Chow, Benjamin J.W., MD</creatorcontrib><creatorcontrib>D'Agostino, Ralph, PhD</creatorcontrib><creatorcontrib>DeLago, Augustin, MD</creatorcontrib><creatorcontrib>Friedman, John, MD</creatorcontrib><creatorcontrib>Hadamitzky, Martin, MD</creatorcontrib><creatorcontrib>Hausleiter, Joerg, MD</creatorcontrib><creatorcontrib>Hayes, Sean W., MD</creatorcontrib><creatorcontrib>Kaufmann, Philipp, MD</creatorcontrib><creatorcontrib>Raff, Gilbert L., MD</creatorcontrib><creatorcontrib>Shaw, Leslee J., PhD</creatorcontrib><creatorcontrib>Thomson, Louise, MD</creatorcontrib><creatorcontrib>Villines, Todd, MD</creatorcontrib><creatorcontrib>Cury, Ricardo C., MD</creatorcontrib><creatorcontrib>Feuchtner, Gudrun, MD</creatorcontrib><creatorcontrib>Kim, Yong-Jin, MD</creatorcontrib><creatorcontrib>Leipsic, Jonathon, MD</creatorcontrib><creatorcontrib>Marques, Hugo, MD</creatorcontrib><creatorcontrib>Berman, Daniel S., MD</creatorcontrib><creatorcontrib>Pencina, Michael, PhD</creatorcontrib><title>Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease</title><title>The American journal of medicine</title><addtitle>Am J Med</addtitle><description>Abstract Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Adults</subject><subject>Algorithms</subject><subject>Cardiovascular disease</subject><subject>Coronary Angiography</subject><subject>Coronary artery disease</subject><subject>Coronary Artery Disease - complications</subject><subject>Coronary Artery Disease - diagnosis</subject><subject>Diagnosis</subject><subject>Female</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Male</subject><subject>Medical History Taking</subject><subject>Medical imaging</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Myocardial Infarction - diagnosis</subject><subject>Myocardial Infarction - mortality</subject><subject>Prognosis</subject><subject>Proportional Hazards Models</subject><subject>Reproducibility of Results</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Tomography, X-Ray Computed</subject><subject>Young Adult</subject><issn>0002-9343</issn><issn>1555-7162</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUsFu1DAQjRCIbgt_gJAlLlyy2E7sxBek1RYoUhEVC2fLG09ap0m89TiL-vd1tKWFXjiNPPPm-c28ybI3jC4ZZfJDtzRDN4BdcsrKlFrSgj3LFkwIkVdM8ufZglLKc1WUxVF2jNilJ1VCvsyOuKilULxYZPtvYF1jenLmMPpwS1ofyEXwl6PH6Bryw-E1WSEC4gBjJGa05NSZueyQ-JZsotn2QC5MdKmO5LeLV2Qz4Q6aCJasffCjSbyrECGFU4dgEF5lL1rTI7y-jyfZr8-ffq7P8vPvX76uV-d5I0oZc2uhkm3NakaVsbymtaxsva0sK6HloIRRraoqWUhqmeI10GJLaVEqYzjnihYn2ccD727apl01SWIwvd4FNyRR2hun_62M7kpf-r0uBZNC1Ing_T1B8DcTYNSDwwb63ozgJ9RMKlUqWgmeoO-eQDs_hTGNp1mVEElgOaPKA6oJHjFA-yCGUT0bqzt9MFbPxs7ZZGxqe_v3IA9Nf5x8nBTSOvcOgsYmOdIke0OyQlvv_vfDU4Kmd-N8G9dwC_g4i0auqd7MxzXfFivTVVWFKO4A9o_L1Q</recordid><startdate>20150801</startdate><enddate>20150801</enddate><creator>Min, James K., MD</creator><creator>Dunning, Allison, MS</creator><creator>Gransar, Heidi, MS</creator><creator>Achenbach, Stephan, MD</creator><creator>Lin, Fay Y., MD</creator><creator>Al-Mallah, Mouaz, MD</creator><creator>Budoff, Matthew J., MD</creator><creator>Callister, Tracy Q., MD</creator><creator>Chang, Hyuk-Jae, MD</creator><creator>Cademartiri, Filippo, MD</creator><creator>Maffei, Erica, MD</creator><creator>Chinnaiyan, Kavitha, MD</creator><creator>Chow, Benjamin J.W., MD</creator><creator>D'Agostino, Ralph, PhD</creator><creator>DeLago, Augustin, MD</creator><creator>Friedman, John, MD</creator><creator>Hadamitzky, Martin, MD</creator><creator>Hausleiter, Joerg, MD</creator><creator>Hayes, Sean W., MD</creator><creator>Kaufmann, Philipp, MD</creator><creator>Raff, Gilbert L., MD</creator><creator>Shaw, Leslee J., PhD</creator><creator>Thomson, Louise, MD</creator><creator>Villines, Todd, MD</creator><creator>Cury, Ricardo C., MD</creator><creator>Feuchtner, Gudrun, MD</creator><creator>Kim, Yong-Jin, MD</creator><creator>Leipsic, Jonathon, MD</creator><creator>Marques, Hugo, MD</creator><creator>Berman, Daniel S., MD</creator><creator>Pencina, Michael, PhD</creator><general>Elsevier Inc</general><general>Elsevier Sequoia S.A</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>7T5</scope><scope>7TK</scope><scope>7TO</scope><scope>7TS</scope><scope>7U9</scope><scope>H94</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20150801</creationdate><title>Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease</title><author>Min, James K., MD ; Dunning, Allison, MS ; Gransar, Heidi, MS ; Achenbach, Stephan, MD ; Lin, Fay Y., MD ; Al-Mallah, Mouaz, MD ; Budoff, Matthew J., MD ; Callister, Tracy Q., MD ; Chang, Hyuk-Jae, MD ; Cademartiri, Filippo, MD ; Maffei, Erica, MD ; Chinnaiyan, Kavitha, MD ; Chow, Benjamin J.W., MD ; D'Agostino, Ralph, PhD ; DeLago, Augustin, MD ; Friedman, John, MD ; Hadamitzky, Martin, MD ; Hausleiter, Joerg, MD ; Hayes, Sean W., MD ; Kaufmann, Philipp, MD ; Raff, Gilbert L., MD ; Shaw, Leslee J., PhD ; Thomson, Louise, MD ; Villines, Todd, MD ; Cury, Ricardo C., MD ; Feuchtner, Gudrun, MD ; Kim, Yong-Jin, MD ; Leipsic, Jonathon, MD ; Marques, Hugo, MD ; Berman, Daniel S., MD ; Pencina, Michael, PhD</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c546t-dde76f818109ad280867d8b7d14ef2e95a9f9776360d1928e03b00349aa222903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Adults</topic><topic>Algorithms</topic><topic>Cardiovascular disease</topic><topic>Coronary Angiography</topic><topic>Coronary artery disease</topic><topic>Coronary Artery Disease - complications</topic><topic>Coronary Artery Disease - diagnosis</topic><topic>Diagnosis</topic><topic>Female</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Male</topic><topic>Medical History Taking</topic><topic>Medical imaging</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Myocardial Infarction - diagnosis</topic><topic>Myocardial Infarction - mortality</topic><topic>Prognosis</topic><topic>Proportional Hazards Models</topic><topic>Reproducibility of Results</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>Tomography, X-Ray Computed</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Min, James K., MD</creatorcontrib><creatorcontrib>Dunning, Allison, MS</creatorcontrib><creatorcontrib>Gransar, Heidi, MS</creatorcontrib><creatorcontrib>Achenbach, Stephan, MD</creatorcontrib><creatorcontrib>Lin, Fay Y., MD</creatorcontrib><creatorcontrib>Al-Mallah, Mouaz, MD</creatorcontrib><creatorcontrib>Budoff, Matthew J., MD</creatorcontrib><creatorcontrib>Callister, Tracy Q., MD</creatorcontrib><creatorcontrib>Chang, Hyuk-Jae, MD</creatorcontrib><creatorcontrib>Cademartiri, Filippo, MD</creatorcontrib><creatorcontrib>Maffei, Erica, MD</creatorcontrib><creatorcontrib>Chinnaiyan, Kavitha, MD</creatorcontrib><creatorcontrib>Chow, Benjamin J.W., MD</creatorcontrib><creatorcontrib>D'Agostino, Ralph, PhD</creatorcontrib><creatorcontrib>DeLago, Augustin, MD</creatorcontrib><creatorcontrib>Friedman, John, MD</creatorcontrib><creatorcontrib>Hadamitzky, Martin, MD</creatorcontrib><creatorcontrib>Hausleiter, Joerg, MD</creatorcontrib><creatorcontrib>Hayes, Sean W., MD</creatorcontrib><creatorcontrib>Kaufmann, Philipp, MD</creatorcontrib><creatorcontrib>Raff, Gilbert L., MD</creatorcontrib><creatorcontrib>Shaw, Leslee J., PhD</creatorcontrib><creatorcontrib>Thomson, Louise, MD</creatorcontrib><creatorcontrib>Villines, Todd, MD</creatorcontrib><creatorcontrib>Cury, Ricardo C., MD</creatorcontrib><creatorcontrib>Feuchtner, Gudrun, MD</creatorcontrib><creatorcontrib>Kim, Yong-Jin, MD</creatorcontrib><creatorcontrib>Leipsic, Jonathon, MD</creatorcontrib><creatorcontrib>Marques, Hugo, MD</creatorcontrib><creatorcontrib>Berman, Daniel S., MD</creatorcontrib><creatorcontrib>Pencina, Michael, PhD</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Physical Education Index</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The American journal of medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Min, James K., MD</au><au>Dunning, Allison, MS</au><au>Gransar, Heidi, MS</au><au>Achenbach, Stephan, MD</au><au>Lin, Fay Y., MD</au><au>Al-Mallah, Mouaz, MD</au><au>Budoff, Matthew J., MD</au><au>Callister, Tracy Q., MD</au><au>Chang, Hyuk-Jae, MD</au><au>Cademartiri, Filippo, MD</au><au>Maffei, Erica, MD</au><au>Chinnaiyan, Kavitha, MD</au><au>Chow, Benjamin J.W., MD</au><au>D'Agostino, Ralph, PhD</au><au>DeLago, Augustin, MD</au><au>Friedman, John, MD</au><au>Hadamitzky, Martin, MD</au><au>Hausleiter, Joerg, MD</au><au>Hayes, Sean W., MD</au><au>Kaufmann, Philipp, MD</au><au>Raff, Gilbert L., MD</au><au>Shaw, Leslee J., PhD</au><au>Thomson, Louise, MD</au><au>Villines, Todd, MD</au><au>Cury, Ricardo C., MD</au><au>Feuchtner, Gudrun, MD</au><au>Kim, Yong-Jin, MD</au><au>Leipsic, Jonathon, MD</au><au>Marques, Hugo, MD</au><au>Berman, Daniel S., MD</au><au>Pencina, Michael, PhD</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease</atitle><jtitle>The American journal of medicine</jtitle><addtitle>Am J Med</addtitle><date>2015-08-01</date><risdate>2015</risdate><volume>128</volume><issue>8</issue><spage>871</spage><epage>878</epage><pages>871-878</pages><issn>0002-9343</issn><eissn>1555-7162</eissn><coden>AJMEAZ</coden><abstract>Abstract Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>25865923</pmid><doi>10.1016/j.amjmed.2014.10.031</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0002-9343 |
| ispartof | The American journal of medicine, 2015-08, Vol.128 (8), p.871-878 |
| issn | 0002-9343 1555-7162 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4516558 |
| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Adolescent Adult Adults Algorithms Cardiovascular disease Coronary Angiography Coronary artery disease Coronary Artery Disease - complications Coronary Artery Disease - diagnosis Diagnosis Female Humans Internal Medicine Male Medical History Taking Medical imaging Middle Aged Mortality Myocardial Infarction - diagnosis Myocardial Infarction - mortality Prognosis Proportional Hazards Models Reproducibility of Results Risk Assessment - methods Risk Factors Tomography, X-Ray Computed Young Adult |
| title | Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease |
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