Document Detail


Discrimination between demand and supply ischemia episodes in Holter recordings.
MedLine Citation:
PMID:  18002522     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
ST segment changes provide a sensitive marker in the diagnosis of myocardial ischemia in Holter recordings. However not only the mechanisms of ischemia result in ST segment deviation but also heart rate related events. The very similar signature of ST modifications in ischemia and heart rate related events have driven us to look for other ECG indexes allowing to discriminate between them. Heart rate-based indexes, correlation between the absolute ST segment deviation and heart rate series, the interval between T apex and T end and changes in the upward/downward slopes of the QRS complex have been shown as significant discriminant parameters, getting a sensitivity for the ischemic events SE = 82.2%, specificity SP = 88.4%, positive predictivity value + PV = 87.6% and negative predictivity value - PV = 83.2% in ST events of the Long Term ST database.
Authors:
Ana Mincholé; Franc Jager; Pablo Laguna
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference     Volume:  2007     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2007  
Date Detail:
Created Date:  2007-11-16     Completed Date:  2008-05-05     Revised Date:  2014-08-21    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2579-82     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Databases, Factual
Diagnosis, Computer-Assisted
Electrocardiography, Ambulatory
Heart Rate*
Humans
Myocardial Ischemia / diagnosis*,  physiopathology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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