An ECG biomarker for sudden cardiac death discovered with deep learning

Study cohort and outcomes: Sweden We obtained all 441,614 ECGs done from 2010 to 2016 in Region Halland, a public regional health system in Sweden. (Twelve patients in the region opted out of participation in research, so we did not include their ECGs.) We linked these to death certificates and patient electronic health records, which capture all interactions between patients and the national health-care system that oversees all care in Sweden 51 . ECGs were sampled at 500 Hz and retrieved in XML format from a Philips IntelliSpace system. This research was approved by the ethical review board of Lund University (protocol 2016/517 and amendment 2024-02316-02). Before performing any analysis, we created strict random splits in our dataset to safeguard against overfitting (see Supplementary Information section VII.A for a CONSORT-style diagram). We first created a data lockbox by randomly sampling 40% of patients and all of their ECGs. The lockbox remained untouched from model development through peer review, until provisional acceptance of the manuscript. The remaining 60% was split in half at the patient level, one half for training and the other half for validation, and used for initial submission and the usual peer-review process. …