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Best leads in the standard electrocardiogram for the emergency detection of acute coronary syndrome.

Green, Michael LU ; Ohlsson, Mattias LU ; Lundager Hansen, Jakob LU ; Björk, Jonas LU ; Edenbrandt, Lars LU and Ekelund, Ulf LU (2007) In Journal of Electrocardiology 40(3). p.251-256
Abstract
Background and Purpose: The purpose of this study was to determine which leads in the standard 12-lead electrocardiogram (ECG) are the best for detecting acute coronary syndrome (ACS) among chest pain patients in the emergency department. Methods: Neural network classifiers were used to determine the predictive capability of individual leads and combinations of leads from 862 ECCs from chest pain patients in the emergency department at Lund University Hospital. Results: The best individual lead was aVL, with an area under the receiver operating characteristic curve of 75.5%. The best 3-lead combination was III, aVL, and V-2, with a receiver operating characteristic area of 82.0%, compared with the 12-lead ECG performance of 80.5%.... (More)
Background and Purpose: The purpose of this study was to determine which leads in the standard 12-lead electrocardiogram (ECG) are the best for detecting acute coronary syndrome (ACS) among chest pain patients in the emergency department. Methods: Neural network classifiers were used to determine the predictive capability of individual leads and combinations of leads from 862 ECCs from chest pain patients in the emergency department at Lund University Hospital. Results: The best individual lead was aVL, with an area under the receiver operating characteristic curve of 75.5%. The best 3-lead combination was III, aVL, and V-2, with a receiver operating characteristic area of 82.0%, compared with the 12-lead ECG performance of 80.5%. Conclusions: Our results indicate that leads III, aVL, and V2 are sufficient for computerized prediction of ACS. The present results are likely important in situations where the 12-lead ECG is impractical and for the creation of clinical decision support systems for ECG prediction of ACS. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
acute coronary syndrome, artificial neural networks, myocardial infarction, electrocardiography
in
Journal of Electrocardiology
volume
40
issue
3
pages
251 - 256
publisher
Elsevier
external identifiers
  • wos:000246541000008
  • scopus:34247521885
ISSN
1532-8430
DOI
10.1016/j.jelectrocard.2006.12.011
language
English
LU publication?
yes
id
62561451-1b4c-4a05-968a-2aec3171ac59 (old id 165777)
date added to LUP
2007-07-09 15:28:35
date last changed
2017-10-22 03:47:09
@article{62561451-1b4c-4a05-968a-2aec3171ac59,
  abstract     = {Background and Purpose: The purpose of this study was to determine which leads in the standard 12-lead electrocardiogram (ECG) are the best for detecting acute coronary syndrome (ACS) among chest pain patients in the emergency department. Methods: Neural network classifiers were used to determine the predictive capability of individual leads and combinations of leads from 862 ECCs from chest pain patients in the emergency department at Lund University Hospital. Results: The best individual lead was aVL, with an area under the receiver operating characteristic curve of 75.5%. The best 3-lead combination was III, aVL, and V-2, with a receiver operating characteristic area of 82.0%, compared with the 12-lead ECG performance of 80.5%. Conclusions: Our results indicate that leads III, aVL, and V2 are sufficient for computerized prediction of ACS. The present results are likely important in situations where the 12-lead ECG is impractical and for the creation of clinical decision support systems for ECG prediction of ACS.},
  author       = {Green, Michael and Ohlsson, Mattias and Lundager Hansen, Jakob and Björk, Jonas and Edenbrandt, Lars and Ekelund, Ulf},
  issn         = {1532-8430},
  keyword      = {acute coronary syndrome,artificial neural networks,myocardial infarction,electrocardiography},
  language     = {eng},
  number       = {3},
  pages        = {251--256},
  publisher    = {Elsevier},
  series       = {Journal of Electrocardiology},
  title        = {Best leads in the standard electrocardiogram for the emergency detection of acute coronary syndrome.},
  url          = {http://dx.doi.org/10.1016/j.jelectrocard.2006.12.011},
  volume       = {40},
  year         = {2007},
}