Search

Background: Identifying individuals with severe aortic stenosis (AS) at high risk of mortality remains challenging using current clinical imaging methods., Objectives: The purpose of this study was to evaluate an artificial intelligence decision support algorithm (AI-DSA) to augment the detection of severe AS within a well-resourced health care setting., Methods: Agnostic to clinical information, an AI-DSA trained to identify echocardiographic phenotype associated with an aortic valve area (AVA)<1 cm 2 using minimal input data (excluding left ventricular outflow tract measures) was applied to routine transthoracic echocardiograms (TTE) reports from 31,141 U.S. Medicare beneficiaries at an academic medical center (2003-2017)., Results: Performance of AI-DSA to detect the phenotype associated with an AVA<1 cm 2 was excellent (sensitivity 82.2%, specificity 98.1%, negative predictive value 9.2%, c-statistic = 0.986). In addition to identifying clinical severe AS cases, AI-DSA identified an additional 1,034 (3.3%) individuals with guideline-defined moderate AS but with a similar clinical and TTE phenotype to those with severe AS with low rates of aortic valve replacement (6.6%). Five-year mortality was 75.9% in those with known severe AS, 73.5% in those with a similar phenotype to severe AS, and 44.6% in those without severe AS. The AI-DSA continued to perform well to identify severe AS among those with a depressed left ventricular ejection fraction. Overall rates of aortic valve replacement remained low, even in those with an AVA<1 cm 2 (21.9%)., Conclusions: Without relying on left ventricular outflow tract measurements, an AI-DSA used echocardiographic reports to reliably identify the phenotype of severe AS. These results suggest possible utility for this AI-DSA to enhance detection of severe AS individuals at risk for adverse outcomes., Competing Interests: This work was supported by Echo IQ Pty Ltd. Dr Stewart is supported by the 10.13039/501100000925National Health and Medical Research Council of Australia (GNT1135894). Dr Strom is supported by the 10.13039/100000002National Institutes of Health (1K23HL144907, R01AG063937), 10.13039/100006520Edwards Lifesciences, Ultromics, HeartSciences, Anumana, and EchoIQ. Unrelated to this work, Dr Strom has served on the Scientific Advisory Board for Edwards Lifesciences and EchoIQ and has received consulting fees from Bracco Diagnostics, General Electric Healthcare, and Lantheus Medical Imaging. Prof Strange has received consulting fees from Edwards, Medtronic, and Echo IQ and has received speaker fees from Edwards, Medtronic, Abbott, and Echo IQ. Prof Playford has received consulting fees from Edwards, Medtronic, and Echo IQ. Prof Stewart has received consulting fees from Echo IQ., (© 2024 The Authors.)

Background: Peak tricuspid regurgitant velocity (TRV) on transthoracic echocardiography (TTE) is a commonly obtained parameter and robust predictor of subsequent adverse clinical outcomes., Objectives: The purpose of this study was to determine the predictors and clinical significance of TRV progression., Methods: We retrospectively linked consecutive outpatient TTE reports from our institution to 2005 to 2017 Medicare claims. Individuals with prior tricuspid surgery, endocarditis, tricuspid stenosis, missing TRV values, TTEs performed during inpatient hospitalization, or <2 TTEs were excluded., Results: A total of 4,572 patients (mean age 67.8 ± 11.9 years, 50.4% female) received 13,273 TTEs over a median follow-up of 7.4 (IQR: 4.5-6.9) years. TRV increased by a mean of 0.23 (95% CI: 0.22 to 0.23 m/s/y, P < 0.001) (range, 0.01-0.80 m/s/y). Older age, depressed left ventricular ejection fraction, diabetes, hypertension, hyperlipidemia, atrial fibrillation, heart failure, and chronic kidney disease were associated with faster progression (all P < 0.05). Accounting for 23 demographic, clinical, and TTE variables, faster TRV progression was associated with a stepwise increased risk of all-cause mortality (TRV progression quartile 4 vs 1; adjusted HR: 2.17; 95% CI: 1.74-2.71; P < 0.001). Those with regression of TRV (n = 384 [8.4%]) had a lower mortality risk (adjusted HR: 0.40; 95% CI: 0.28-0.57; P < 0.001)., Conclusions: In this large, multidecade study of Medicare beneficiaries with serial TTEs performed in the outpatient setting, the mean rate of TRV progression was 0.23 m/s/y. Older age, left heart disease, and adverse metabolic features were associated with faster progression. Faster progression was associated with a graded risk for all-cause mortality.

We report a case of a 70-year-old woman who presented for a cavotricuspid isthmus atrial flutter ablation that was aborted prematurely. On subsequent imaging, she was discovered to have a right atrial diverticulum, which was present on prior imaging but not reported, likely due to unfamiliarity with the entity. ( Level of Difficulty: Intermediate. )., Competing Interests: Dr Waks has received grant support from Anumana. Dr Strom has received funding from the National Institutes of Health/National Heart, Lung, and Blood Institute (1K23HL144907); has received grant support from Edwards Lifesciences, Ultromics, HeartSciences, and Anumana; has received consulting fees from Bracco Diagnostics and General Electric Healthcare; and has served on the advisory boards for Edwards Lifesciences, Ultromics, and EchoIQ. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© 2023 The Authors.)