Automated discrimination of proximal right coronary artery occlusion from middle-to-distal right coronary artery occlusion and left circumflex occlusion in ST-elevation myocardial infarction.
Background: Classifying the location of an occlusion in the culprit artery during ST-elevation myocardial infarction (STEMI) is important for risk stratification to optimize treatment. We developed a new logistic regression (LR) algorithm for 3-group classification of occlusion location as proximal...
| Publicado en: | Journal of Electrocardiology Vol. 45; no. 4; pp. 343 - 350 |
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| Autores principales: | , , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
W B Saunders
Jul/Aug2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104498464&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104498464 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00220736 1276 jtl: Journal of Electrocardiology issn: 00220736 maglogo: N pubinfo: dt: Jul/Aug2012 vid: 45 iid: 4 pid: 1351 pub: W B Saunders place: Philadelphia, Pennsylvania artinfo: ui: 104498464 77282099 2011660411 10.1016/j.jelectrocard.2012.03.008 NLM22912955 104498464 ppf: 343 ppct: 7 formats: tig: atl: Automated discrimination of proximal right coronary artery occlusion from middle-to-distal right coronary artery occlusion and left circumflex occlusion in ST-elevation myocardial infarction. aug: au: Gregg RE Fiol-Sala M Nikus KC Startt-Selvester R Zhou SH Carrillo A Barbara V Chien CH Lindauer JM Gregg, Richard E Fiol-Sala, Miquel Nikus, Kjell C Startt-Selvester, Ronald Zhou, Sophia H Carrillo, Andrés Barbara, Victoria Chien, Cheng-hao Simon Lindauer, James M affil: Advanced Algorithm Research Center, Philips Healthcare, Thousand Oaks, CA, USA sug: subj: Coronary Disease Diagnosis Electrocardiography Myocardial Infarction Diagnosis Adult Aged Aged, 80 and Over Algorithms Coronary Angiography Coronary Disease Complications Coronary Disease Pathology Coronary Disease Radiography Female Human Logistic Regression Male Middle Age Myocardial Infarction Complications Myocardial Infarction Radiography Predictive Value of Tests Sensitivity and Specificity Adult: 19-44 years Aged: 65+ years Aged, 80 & over Middle Aged: 45-64 years Female Male ab: Background: Classifying the location of an occlusion in the culprit artery during ST-elevation myocardial infarction (STEMI) is important for risk stratification to optimize treatment. We developed a new logistic regression (LR) algorithm for 3-group classification of occlusion location as proximal right coronary artery (RCA), middle-to-distal RCA or left circumflex (LCx) coronary artery with inferior myocardial infarction. We compared the performance of the new LR algorithm with the recently introduced decision tree classifier of Fiol et al (Ann Noninvasive Electrocardiol. 2004;4:383-388) in the classification of the same 3 categories.Methods: The new algorithm was developed on a set of electrocardiograms from an emergency department setting (n = 64) and tested on a different set from a prehospital setting (n = 68). All patients met the current STEMI criteria with angiographic confirmation of culprit artery and occlusion location. Using LR, 4 ST-segment deviation features were chosen by forward stepwise selection. Final LR coefficients were obtained by averaging more than 200 bootstrap iterations on the training set. In addition, a separate 4-feature classifier was designed adding ST features of V4R and V8, only available in the training set.Results: The LR algorithm classified proximal RCA occlusion vs combined LCx occlusion and middle-to-distal RCA occlusion, with a sensitivity of 76% and specificity of 81% as compared with 71% and 62% for the Fiol classifier. The difference in specificity was statistically significant. The LR classifier trained with additional ST features of V4R and V8, but still limited to 4, improved the overall agreement in the training set from 65% to 70%.Conclusion: Discrimination of proximal RCA lesion location from LCx or middle-to-distal RCA using the new LR classifier shows improvement over decision tree–type classification criteria. Automated identification of proximal RCA occlusion could speed up the risk stratification of patients with STEMI. The addition of leads V4R and V8 should further improve the automated classification of the occlusion site in RCA and LCx. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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