| Title: | Neural networks applied to 12-lead electrocardiograms predict body mass index, visceral adiposity and concurrent cardiometabolic ill-health |
| Journal: | Cardiovascular Digital Health Journal |
| Published: | 13 Oct 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34957430/ |
| DOI: | https://doi.org/10.1016/j.cvdhj.2021.10.003 |
| URL: | http://www.cvdigitalhealthjournal.com/article/S2666693621001195/pdf |
Publication 15048
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Abstract
BACKGROUND: Obesity is associated with electrophysiological remodeling, which manifests as detectable changes on the surface electrocardiogram (ECG).</p>
OBJECTIVE: To develop neural networks (NN) to predict body mass index (BMI) from ECGs and test the hypothesis that discrepancies between NN-predicted BMI and measured BMI are indicative of underlying adiposity and/or concurrent cardiometabolic ill-health.</p>
METHODS: NN models were developed using 36,856 12-lead resting ECGs from the UK Biobank. Two architectures were developed for continuous and categorical BMI estimation (normal weight [BMI <25 kg/m2] vs overweight/obese [BMI ≥25 kg/m2]). Models for male and female participants were trained and tested separately. For each sex, data were randomly divided into 4 folds, and models were evaluated in a leave-1-fold-out manner.</p>
RESULTS: ECGs were available for 17,807 male and 19,049 female participants (mean ages: 61 ± 7 and 63 ± 8 years; mean BMI 26 ± 5 kg/m2 and 27 ± 4 kg/m2, respectively). NN models detected overweight/obese individuals with average accuracies of 75% and 73% for male and female subjects, respectively. The magnitudes of difference between NN-predicted BMI and actual BMI were significantly correlated with visceral adipose tissue volumes. Concurrent hypertension, diabetes, dyslipidemia, and/or coronary heart disease explained false-positive classifications (ie, calculated BMI <25 kg/m2 misclassified as ≥25 kg/m2 by NN model, P < .001).</p>
CONCLUSION: NN models applied to 12-lead ECGs predict BMI with a reasonable degree of accuracy. Discrepancies between NN-predicted and calculated BMI may be indicative of underlying visceral adiposity and concomitant cardiometabolic perturbation, which could be used to identify individuals at risk of cardiometabolic disease.</p>
5 Authors
- Xinyang Li
- Kiran Haresh Kumar Patel
- Lin Sun
- Nicholas S. Peters
- Fu Siong Ng
1 Application
| Application ID | Title |
|---|---|
| 48666 | Electrophysiological remodelling in patients at elevated risk of ventricular arrhythmia and sudden cardiac death |
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