Physiol Meas. 2023 Jun 27. doi: 10.1088/1361-6579/ace241. Online ahead of print.
ABSTRACT
Acute myocardial ischemia in the setting of acute coronary syndrome (ACS) may lead to myocardial infarction. Therefore, timely decisions, already in the pre-hospital phase, are crucial to preserving cardiac function as much as possible. Serial electrocardiography, a comparison of the acute electrocardiogram (AECG) with a previously recorded (reference) ECG (RECG) of the same patient, aids in identifying ischemia-induced electrocardiographic changes by correcting for interindividual ECG variability. Recently, the combination of deep learning and serial electrocardiography provided promising results in detecting emerging cardiac diseases; thus, the aim of our current study is the application of our novel Advanced Repeated Structuring & Learning Procedure (AdvRS&LP), specifically designed for acute myocardial ischemia detection in the pre-hospital phase by using serial ECG features. Data belong to the SUBTRACT study, which includes 1425 ECG pairs, 194 (14%) ACS patients, and 1035 (73%) controls. Each ECG pair was characterized by 28 serial features that, with sex and age, constituted the inputs of the Advanced Repeated Structuring & Learning Procedure (AdvRS&LP), an automatic constructive procedure for creating supervised neural networks (NN). We created 100 NNs to compensate for statistical fluctuations due to random data divisions of a limited dataset. We compared the performance of the obtained NNs to a logistic regression (LR) procedure and the Glasgow program (Uni-G) in terms of area-under-the-curve (AUC) of the receiver-operating-characteristic (ROC) curve, sensitivity (SE), and specificity (SP). NNs (median AUC=83%, median SE=77%, and median SP=89%) presented statistically (P value lower than 0.05) higher testing performance than those presented by LR (median AUC=80%, median SE=67%, and median SP=81%) and by Uni-G algorithm (median SE=72% and median SP=82%). In conclusion, the positive results underscore the value of serial comparison of ECG in ischemia detection and, NNs created by AdvRS&LP seems to be considered as realible tools in terms of generalization and clinical applicability.
PMID:37376978 | DOI:10.1088/1361-6579/ace241
