Document Detail


Computerized classification of proximal occlusion in the left anterior descending coronary artery.
MedLine Citation:
PMID:  21069903     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
Proximal occlusion within the left anterior descending (LAD) coronary artery in patients with acute myocardial infarction leads to higher mortality than does nonproximal occlusion. We evaluated an automated program to detect proximal LAD occlusion. All patients with suspected acute coronary syndrome (n = 7,710) presenting consecutively to the emergency department of a local hospital with a coronary angiogram–confirmed flow-limiting lesion and notation of occlusion site were included in the study (n = 711). Electrocardiograms (ECGs) that met ST-segment elevation myocardial infarction (STEMI) criteria were included in the training set (n = 183). Paired angiographic location of proximal LAD and ECGs with ST elevation in the anterolateral region were used for the computer program development (n = 36). The test set was based on ECG criteria for anterolateral STEMI only without angiographic reports (n = 162). Tested against 2 expert cardiologists' agreed reading of proximal LAD occlusion, the algorithm has a sensitivity of 95% and a specificity of 82%. The algorithm is designed to have high sensitivity rather than high specificity for the purpose of not missing any proximal LAD in the STEMI population. Our preliminary evaluation suggests that the algorithm can detect proximal LAD occlusion as an additional interpretation to STEMI detection with similar accuracy as cardiologist readers.
Authors:
Richard E Gregg; Kjell C Nikus; Sophia H Zhou; Ronald H Startt Selvester; Victoria Barbara
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of electrocardiology     Volume:  43     ISSN:  1532-8430     ISO Abbreviation:  J Electrocardiol     Publication Date:    2010 Nov-Dec
Date Detail:
Created Date:  2010-11-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0153605     Medline TA:  J Electrocardiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  634-9     Citation Subset:  IM    
Affiliation:
Advanced Algorithm Research Center, Philips Healthcare, Thousand Oaks, CA, USA. rich.gregg@philips.com
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