Heart failure & cardiomyopathies
Deep Learning–Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes
Authors' conclusion
Deep learning echocardiographic interpretation accurately quantified standard measures of left heart structure and function, which in turn were associated with future clinical outcomes.
Study context
- Population
- Ambulatory cardiology and primary care patients with echocardiograms64,028 echocardiograms (training)
- Participants
- 27,135 participants
- Outcome
- Deep learning view classification and left heart quantification; association with incident outcomes
Methodological detailsmulti-institutional, external validation
- Multi-institutional
- External validation
Main finding
As reported in the abstract
View discrimination (PLAX, apical 4- and 2-chamber) vs human expert annotation, AUC
>0.97
Standard left heart measures vs study report values, R2 range
0.53 to 0.91
1-SD lower model-LVEF and HF, HR
1.43
95% CI 1.23–1.66
1-SD lower model-LVEF and death, HR
1.17
95% CI 1.06–1.30
Observational data: associations, not effects.
Further findings
Other model-derived left heart measures
- Model-derived measures predicted incident HF, AF, MI and death; similar results for other measures
Original publication
Deep Learning–Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes. J Am Coll Cardiol. Published 14 November 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →