Computer-aided systematized approach to pediatric ECG analysis.
BACKGROUND
In pediatric electrocardiography (ECG), the correct classification of segments in the medical record is subjected to various components. A conventional analysis based either on the cardiologist's skills or a quick reference to a standard normality table may lead to mistakes and to an incorrect final medical diagnosis. In this study, the evaluation of 12 specific ECG segments (ES) is defined as segmental analysis (SA). We hypothesized that a computer-aided SA can provide better results for a correct classification of pediatric ECGs, compared to the conventional analysis. This study aims to evaluate the accuracy of a computer-aided SA ECG diagnosis of pediatric patients by cardiologists.


METHODS
To validate the software, we selected four normal and one altered ECG as references, all with concordant reports given by two cardiologists using manual planimetry. Nineteen cardiology experts independently examined each of the five standard pediatric ECGs twice. First, the ECG was analyzed in the conventional form. Subsequently, the participants evaluated ECGs with our proposed computer-aided AS, by measuring the 12 specific ES in the grid paper and having their values entered into a custom-made software, in order to compare them with normality standards.


RESULTS
The computer-aided SA reduced ECG misreading or ECG misinterpretation errors by 83%. It also showed a more uniform, high-quality analysis of all ES (minimum of 92% correctly reviewed segments from normal pediatric ECGs) by all the participant cardiologists.


CONCLUSIONS
We consider the computer-aided SA for ECG evaluation in pediatric cardiology an efficient and safe complementary method.
Molina
Marcos S
MS
Heart Institute (InCor) of the University of São Paulo Medical School, São Paulo, Brazil.
Benjo
Alexandre M
AM
Molina
Alessandra I
AI
Favarato
Desiderio
D
Tobias
Nancy
N
Garcia
Euler de Vilhena
Ede V
Ramires
José A F
JA
Pastore
Carlos Alberto
CA
D000293:Adolescent; D002309:Cardiology / Q000379:methods*; D002648:Child; D002675:Child, Preschool; D002983:Clinical Competence; D003936:Diagnosis, Computer-Assisted; D004562:Electrocardiography; D005260:Female; D006801:Humans; D007223:Infant; D008297:Male; D010372:Pediatrics / Q000379:methods*; D012984:Software; D011795:Surveys and Questionnaires