Open AccessSensitivity and Specificity of Automated Detection of Early Repolarization in Standard 12‐Lead Electrocardiography
Author(s) -
Kenttä Tuomas,
Porthan Kimmo,
Tikkanen Jani T.,
Väänänen Heikki,
Oikarinen Lasse,
Viitasalo Matti,
Karanko Hannu,
Laaksonen Maarit,
Huikuri Heikki V.
Publication year - 2015
Publication title -
annals of noninvasive electrocardiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.494
H-Index - 48
eISSN - 1542-474X
pISSN - 1082-720X
DOI - 10.1111/anec.12226
Subject(s) - medicine , benign early repolarization , notching , qrs complex , electrocardiography , repolarization , diagnostic accuracy , cardiology , sensitivity (control systems) , gold standard (test) , algorithm , st segment , computer science , myocardial infarction , electrophysiology , materials science , electronic engineering , engineering , metallurgy
Background Early repolarization (ER) is defined as an elevation of the QRS‐ST junction in at least two inferior or lateral leads of the standard 12‐lead electrocardiogram (ECG). Our purpose was to create an algorithm for the automated detection and classification of ER. Methods A total of 6,047 electrocardiograms were manually graded for ER by two experienced readers. The automated detection of ER was based on quantification of the characteristic slurring or notching in ER‐positive leads. The ER detection algorithm was tested and its results were compared with manual grading, which served as the reference. Results Readers graded 183 ECGs (3.0%) as ER positive, of which the algorithm detected 176 recordings, resulting in sensitivity of 96.2%. Of the 5,864 ER‐negative recordings, the algorithm classified 5,281 as negative, resulting in 90.1% specificity. Positive and negative predictive values for the algorithm were 23.2% and 99.9%, respectively, and its accuracy was 90.2%. Inferior ER was correctly detected in 84.6% and lateral ER in 98.6% of the cases. Conclusions As the automatic algorithm has high sensitivity, it could be used as a prescreening tool for ER; only the electrocardiograms graded positive by the algorithm would be reviewed manually. This would reduce the need for manual labor by 90%.