**Authors and Affiliations**
Eunjung Lee, PhD
Assistant Professor of Medicine
Mayo Clinc, Cardiovascular medicine

**Background**
Left ventricular diastolic function and filling pressure (FP) can be assessed by echocardiography and cardiac catheterization. Recently, a novel artificial intelligence (AI)-enabled ECG has proven to be effective in identifying increased FP determined by echocardiographic assessment of diastolic function. We aimed to compare a prognostic value of AI-ECG determination of FP compared to echocardiography and catheterization.

**Methods**
This study included 4,213 patients who had a transthoracic echocardiogram and ECG within 30 days before hemodynamic cardiac catheterization. Increased FP was defined as pulmonary artery wedge pressure >15 mmHg by catheterization and grade 2 or 3 diastolic dysfunction by echocardiography based on diastolic function guidelines. Increased FP by ECG was identified using previously developed AI-ECG. AI-ECG performance was evaluated using the area under the curve (AUC) of the receiver operating curve. We assessed the risk of all-cause mortality using Kaplan-Meier estimate and multivariable Cox proportional-hazards models.

**Results**
AI-ECG had AUCs of 0.8 and 0.7 for predicting increased FP determined by echocardiography and catheterization, respectively. Death was observed in 2,776 (34%) patients over a median follow-up of 7.7 years (IQR 7.1, 8.3). Survival of patients with normal and increased FP by AI-ECG, Echocardiography, and catheterization are shown in Figure 1a . Concordant diagnoses of normal and increased FP by AI-ECG and catheterization or echocardiography had the highest and lowest survival rates, respectively. When FP by AI-ECG was discordant, survival was better predicted by AI-ECG compared to echocardiography and catheterization (Figure 1b ).
(Figure: https://www.dropbox.com/scl/fi/5c602g4l4vatb7dazerlt/figure1.jpg?rlkey=mk4v7vx5qagxpexwvefvsw93c&dl=0 )

**Conclusion**
AI-ECG for assessing filling pressure has the potential to serve as a valuable daily screening tool, offering an initial assessment of increased filling pressure and guiding the need for additional diagnostic evaluations, such as echocardiography or catheterization. Further clinical investigations are needed to establish the role of AI-ECG in determining diastolic filling pressure in clinical practice.



**Authors and Affiliations**
Eunjung Lee, PhD
[Assistant Professor of Medicine](https://quarterly.mayo.edu/directory/photolisting/default.htm?academic_rank=Assistant+Professor+of+Medicine&displaymode=)
Mayo Clinc, Cardiovascular medicine

**Background**
Left ventricular diastolic function and filling pressure (FP) can be assessed by echocardiography and cardiac catheterization. Recently, a novel artificial intelligence (AI)-enabled ECG has proven to be effective in identifying increased FP determined by echocardiographic assessment of diastolic function. We aimed to compare a prognostic value of AI-ECG determination of FP compared to echocardiography and catheterization.

**Methods**
This study included 4,213 patients who had a transthoracic echocardiogram and ECG within 30 days before hemodynamic cardiac catheterization. Increased FP was defined as pulmonary artery wedge pressure >15 mmHg by catheterization and grade 2 or 3 diastolic dysfunction by echocardiography based on diastolic function guidelines. Increased FP by ECG was identified using previously developed AI-ECG. AI-ECG performance was evaluated using the area under the curve (AUC) of the receiver operating curve. We assessed the risk of all-cause mortality using Kaplan-Meier estimate and multivariable Cox proportional-hazards models.

**Results**
AI-ECG had AUCs of 0.8 and 0.7 for predicting increased FP determined by echocardiography and catheterization, respectively. Death was observed in 2,776 (34%) patients over a median follow-up of 7.7 years (IQR 7.1, 8.3). Survival of patients with normal and increased FP by AI-ECG, Echocardiography, and catheterization are shown in [Figure 1a](https://www.dropbox.com/scl/fi/5c602g4l4vatb7dazerlt/figure1.jpg?rlkey=mk4v7vx5qagxpexwvefvsw93c&dl=0) . Concordant diagnoses of normal and increased FP by AI-ECG and catheterization or echocardiography had the highest and lowest survival rates, respectively. When FP by AI-ECG was discordant, survival was better predicted by AI-ECG compared to echocardiography and catheterization ([Figure 1b](https://www.dropbox.com/scl/fi/5c602g4l4vatb7dazerlt/figure1.jpg?rlkey=mk4v7vx5qagxpexwvefvsw93c&dl=0) ).
(Figure: [https://www.dropbox.com/scl/fi/5c602g4l4vatb7dazerlt/figure1.jpg?rlkey=mk4v7vx5qagxpexwvefvsw93c&dl=0](https://www.dropbox.com/scl/fi/5c602g4l4vatb7dazerlt/figure1.jpg?rlkey=mk4v7vx5qagxpexwvefvsw93c&dl=0) )

**Conclusion**
AI-ECG for assessing filling pressure has the potential to serve as a valuable daily screening tool, offering an initial assessment of increased filling pressure and guiding the need for additional diagnostic evaluations, such as echocardiography or catheterization. Further clinical investigations are needed to establish the role of AI-ECG in determining diastolic filling pressure in clinical practice.



Prognostic Value of Artificial Intelligence-Enabled ECG Determination of Increased Left Ventricular Diastolic Filling Pressure