Key result
Prior ECGs in machine learning models fail to improve 30-day MACE prediction for ED chest pain.
Why the study?
Machine learning models can assist ED physicians in predicting MACE, but whether model performance can be improved by incorporating prior ECGs remains unknown.
Does including a prior ECG improve machine learning predictions of MACE within 30 days in ED chest pain patients?
Cohort (n=19,499)
Yes
Does including a prior ECG improve machine learning predictions of MACE within 30 days in ED chest pain patients?
Including prior ECGs does not improve machine learning model performance for predicting 30-day MACE in ED patients with chest pain, suggesting simpler models with fewer inputs are sufficient.
Does not support adding prior ECGs to ML models for ED chest pain risk stratification; leaves open whether alternative temporal features improve performance.
At the emergency department (ED), it is important to quickly and accurately determine which patients are likely to have a major adverse cardiac event (MACE). Machine learning (ML) models can be used to aid physicians in detecting MACE, and improving the performance of such models is an active area of research. In this study, we sought to determine if ML models can be improved by including a prior electrocardiogram (ECG) from each patient. To that end, we trained several models to predict MACE within 30 days, both with and without prior ECGs, using data collected from 19,499 consecutive patients with chest pain, from five EDs in southern Sweden, between the years 2017 and 2018. Our results indicate no improvement in AUC from prior ECGs. This was consistent across models, both with and without additional clinical input variables, for different patient subgroups, and for different subsets of the outcome. While contradicting current best practices for manual ECG analysis, the results are positive in the sense that ML models with fewer inputs are more easily and widely applicable in practice.
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Nyström et al. (2023) conducted a cohort in Chest pain (n=19,499). Machine learning models including prior ECGs vs. Machine learning models without prior ECGs was evaluated on Major adverse cardiac event (MACE) within 30 days. Including prior electrocardiograms in machine learning models did not improve the AUC for predicting 30-day major adverse cardiac events among 19,499 emergency department patients with chest pain.
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