Predicting troponin biomarker elevation from electrocardiograms using a deep neural network.

ABSTRACT:

Background

Elevated troponin levels are a sensitive biomarker for cardiac injury. The quick and reliable prediction of troponin elevation for patients with chest pain from readily available ECGs may pose a valuable time-saving diagnostic tool during decision-making concerning this patient population.

Methods and results

The data used included 15 856 ECGs from patients presenting to the emergency rooms with chest pain or dyspnoea at two centres in Sweden from 2015 to June 2023. All patients had high-sensitivity troponin test results within 6 hours after 12-lead ECG. Both troponin I (TnI) and TnT were used, with biomarker-specific cut-offs and sex-specific cut-offs for TnI. On this dataset, a residual convolutional neural network (ResNet) was trained 10 times, each on a unique

SUBMITTER: Hilgendorf L 

PROVIDER: S-EPMC11529765 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature