Abstrakti
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%.
Alkuperäiskieli | Englanti |
---|---|
Sivut | 355-361 |
Sivumäärä | 7 |
Julkaisu | Annals of Noninvasive Electrocardiology |
Vuosikerta | 20 |
Numero | 4 |
DOI - pysyväislinkit | |
Tila | Julkaistu - 1 heinäk. 2015 |
OKM-julkaisutyyppi | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä |