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Abstract Background Catheter ablation for atrial fibrillation (AF) improves quality of life and lowers cardiovascular adverse events. However, AF recurrence rates remain high - thus the need for better or improved predictors of AF recurrence. The role of left atrial (LA) stiffness remains unclear, as prior findings were controversial. Purpose To explore the relationship between a noninvasive LA stiffness index (LAstiffn) and AF recurrence after catheter ablation. Methods We analyzed a prospectively recruited cohort of patients who underwent catheter ablation for AF, were in sinus rhythm at 3 months post-ablation, had no significant (< moderate) valvular disease, and had LA volumes and LA diastolic function prospectively measured. LAStiffn was calculated as (E/e’)/LA emptying fraction (LAEF) ratio (abnormal defined as >15/45≈0.3). Outcome endpoint was the first documented AF/atrial flutter episode, lasting >30s, beyond 3 months post ablation (end of blanking period). Results A total of 589 patients were studied (mean age 60±10 years; 75% men; 50% with persistent AF; Table 1). At 3 months post-ablation, mean LAVI(Left atrial volume index) was 36±10 mL/m2 and LAstiffn 0.32±0.22. LAstiffn tended to be higher in older patients, in females, and patients with persistent AF and comorbidities (hypertension, congestive heart failure, coronary artery disease, CHA2DS2-VASc score ≥2, etc). At multivariable regression analysis, LAstiffn correlated with LV size and mass, degree of mitral/tricuspid regurgitation, and right ventricular systolic pressure. At 1 year, 3 years, and 8 years follow up, AF recurred in 118, 191, and 347 patients, respectively. At univariate Cox proportional hazards regression analysis, LAstiffn index >0.3 was significantly associated with AF recurrence at 1 year (log-rank P=.0005), 3 years (P=.0002), and 8 years follow up (P<.0001; Figure). In multivariate analysis including all clinical and laboratory factors with P<.10 in univariate analysis, LAstiffn >0.3 remained an independent factor for AF recurrence only at 3-years (adjusted HR 1.40 [1.03-1.91], P=.03) and 8 years follow up (adjusted HR 1.65 [1.29-2.13], P<.0001) after adjustment for age, sex, type of AF (persistent/paroxysmal), LA volume index (LAVi), obstructive sleep apnea, and prior pacemaker/ICD implantation (best independent factors); P=.14 at 1 year follow up. In ROC analysis, LAstiffn (AUC 0.61, P=.001) performed slightly better than LA deformation LAEF (AUC 0.59, P=.002) or E/e’ (AUC 0.58, P=.03), though with modest sensitivity/specificity (58%/62%). Conclusions LAstiffn may reflect LA myopathy that is likely due to the cumulative effects of comorbidities, diastolic dysfunction, and intrinsic LA tissue remodeling. LA stiffening may be a substrate facilitating redevelopment of AF, thus patients with increased LAstiffn may need more frequent monitoring to prevent/treat AF recurrence earlier.

Abstract Background AI-enhanced electrocardiogram (AI-ECG) is a cost-effective tool for left ventricular dysfunction screening. However, its cost-effectiveness for other forms of structural heart disease (SHD) is unknown. While AI-ECG is inexpensive, the relatively low positive predictive value (PPV) of many models can lead to high costs from unnecessary follow-up tests like transthoracic echocardiography (TTE). Therefore, strategies to improve the yield of AI-ECG-based screening are needed. Purpose To evaluate the cost savings of a stepwise approach to SHD screening using AI-ECG followed by point-of-care ultrasound (POCUS) compared to AI-ECG alone. Methods 286 adult outpatients undergoing AI-ECG were randomly selected to undergo same-day POCUS. All participants were required to have a recent TTE, our gold standard for SHD diagnosis, for comparison purposes. We evaluated four SHDs: aortic stenosis, cardiac amyloidosis, hypertrophic cardiomyopathy, and left ventricular dysfunction (defined as left ventricular ejection fraction <50%). The costs of AI-ECG ($75/test) and TTE ($1,305/test) were sourced from Healthcare Bluebook, while the cost of POCUS ($100/test) was independently estimated. We compared the costs of screening with AI-ECG alone to stepwise screening with AI-ECG followed by POCUS. Costs were analyzed for two paradigms: screening for all forms of SHD in parallel and screening for each SHD individually. Results AI-ECG alone identified potential SHD in 125 out of 286 patients. When compared to TTE, only 39 out of 125 were true positives (31% PPV). Among the AI-ECG-positive patients, POCUS demonstrated findings of SHD in 52 out of 125 cases. When compared to TTE, this stepwise approach yielded 32 true positives and 20 false positives (62% PPV). In the parallel screening paradigm, the cost per patient diagnosed with SHD was $4,733 with AI-ECG alone, which decreased to $3,182 with stepwise screening (33% cost savings). For the individual SHD screening paradigm, cost reductions were as follows: aortic stenosis ($18,724 to $6,315, 66% savings), cardiac amyloidosis ($21,023 to $12,230, 42% savings), hypertrophic cardiomyopathy ($9,883 to $6,175, 38% savings), and left ventricular dysfunction ($4,019 to $3,582, 11% savings). Conclusions Stepwise SDH screening with AI-ECG followed by POCUS markedly reduces costs compared to AI-ECG alone. The greatest cost savings for individual SHD screening were observed for aortic stenosis and cardiac amyloidosis, conditions where AI-ECG models have lower PPVs. Parallel screening for multiple SHDs is also less costly than screening for any individual SHD alone. Therefore, a parallel screening approach may maximize SHD detection while minimizing screening costs. Stepwise Screening Approach for SHD SDH Screening Costs

Abstract Background The left ventricular (LV) hypercontractile phenotype (HP) plays a critical role in hypertrophic cardiomyopathy (HCM) and is usually identified with the left ventricular outflow tract gradient (LVOTG). Purpose To assess the systemic and coronary hemodynamic profile associated with HP identified with increased LV elastance (also known as force) at rest in patients with HCM. Methods We enrolled 1248 HCM patients (age 50 ± 15 years, 798 males, 64%) with ejection fraction (EF) ≥50%, referred for rest transthoracic echocardiography (TTE) in 14 quality-controlled sites from 7 countries TTE assessment included LVOTG, EF, and LV force (systolic blood pressure + LVOTG/LV end-systolic volume, mmHg/mL). Volumetric echocardiography with Simpson’s method was used to measure EF from end-diastolic volume (EDV) and end-systolic volume (ESV), stroke volume (SV), arterial elastance (AE) and ventricular-arterial coupling (VAC). We also assessed resting peak diastolic coronary flow velocity (D-CFV) in the mid-distal left anterior descending artery in a subset of 275 patients. Results EF equaled 68 ± 7%, force = 6.8 ± 5.3 mmHg/ml and LVOTG = 22 ± 28 mmHg. HP was identified as the highest quartile of force (> 7.85 mmHg/ml, mean value= 13.3 ± 7.0). HP showed the lowest SV (46 ± 18 ml) and EDV (61 ± 20 ml), with the highest AE (3.19 ± 1.35 mmHg/ml) and VAC (3.46 ± 1.59) compared to other quartiles (p<0.001) ( see Picture) . D-CFV was not higher in patients with HP (n = 65) compared to those (n = 210) without HP (41± 11 vs 38 ± 14 cm/s, p=ns, but higher in comparison to joint first and second Force quartile (n=122) vs 37 ±14 p =0.0472). Table displays the demografic, clinical and TTE parameters related to HP (Table). In multivariate logistic analysis 4 independent predictors of HP were identified: SBP >130 mmHg with OR 2.5, female sex with OR 5.4, LV EF >70% with OR 6.1 and LVOTG >30 mmHg with the highest OR = 6.3. Conclusion: HCM patients with HP exhibit a distinctive systemic hemodynamic and coronary physiology profile, characterized by low SV, high VAC, and supranormal baseline D-CFV compared to non-HP patients. These findings suggest reduced cardiovascular efficiency and increased myocardial oxygen demand, possibly detrimental over time.

Abstract Aims Pulmonary regurgitation (PR) after reparative intervention for congenital heart disease has been studied extensively. However, the burden, distribution of causes, and outcome of PR in adults is unknown. The study aimed to evaluate the prevalence, types, and outcomes of moderate/severe PR in adults in the community setting. Methods and results A total of 398 adult residents of Olmsted County who had clinically indicated echocardiography 2004–2023 at Mayo Clinic, Rochester, and had moderate or severe PR were identified retrospectively. The median age was 77 years, 48% were females, and 61 (51%) had severe PR. The age- and sex-adjusted US prevalence was 0.11% (vs. 0.67% for ≥moderate tricuspid regurgitation). Moderate/severe PR was due to pulmonary hypertension in 77%, congenital/iatrogenic in 11%, primary pulmonary valve disease in 2% (88% due to carcinoid), and idiopathic isolated in 10%. In contrast, severe PR was due to congenital/iatrogenic disease in 52%, pulmonary hypertension in 39%, primary PR in 5%, and isolated idiopathic in 3%. The all-cause mortality rate per 100 person-year was 73 in primary (mostly carcinoid) PR, 16 in pulmonary hypertension–related PR (not different vs. propensity-matched patients without PR), and 6 in isolated idiopathic PR (not different vs. matched patients without PR). Conclusion Moderate or severe PR had a lower prevalence vs. TR. The most frequent cause was pulmonary hypertension for ≥moderate PR and congenital/iatrogenic for severe PR. Mortality in patients with acquired ≥moderate PR appeared to be related to the underlying cause, with no excess mortality compared with matched patients without PR. Whether specifically severe PR confers excess mortality requires future investigation.

Background: AI-ECG is a cost-effective tool for left ventricular dysfunction (LVD) screening. However, its cost-effectiveness for other forms of structural heart disease (SHD) is unknown. While AI-ECG is inexpensive, a drawback is low positive predictive value (PPV), which leads to high costs from unnecessary follow-up tests. Therefore, strategies to improve the yield of AI-ECG-based screening are needed. Aim: To evaluate the cost savings of a stepwise approach to SHD screening with AI-ECG followed by POCUS compared to AI-ECG alone. Methods: 286 adult outpatients undergoing AI-ECG were selected at random. Participants received same-day POCUS and had a recent TTE (our gold standard for SHD). We evaluated four SHDs: aortic stenosis (AS), cardiac amyloidosis (CA), HCM, and LVD. The costs of AI-ECG ($75) and TTE ($1,305) were obtained from Healthcare Bluebook. The cost of POCUS ($100) was estimated independently. Cost savings were analyzed for simultaneous screening for all forms of SHD and screening for individual SHDs. Results: AI-ECG identified potential SHD in 125 patients, but only 39 were true positives by TTE (31% PPV). In AI-ECG positive patients, POCUS demonstrated findings of SHD in 52/125. Compared to TTE, this stepwise approach yielded 32 true positives and 20 false positives (62% PPV). The cost per patient diagnosed with SHD was $4,733 with AI-ECG alone but decreased to $3,182 with stepwise screening (33% cost savings). Screening for individual SHDs resulted in cost reduction from $18,724 to $6,315 (66% savings) for AS, $21,023 to $12,230 (42% savings) for CA, $9,883 to $6,175 (38% savings) for HCM, and $4,019 to $3,582 (11% savings) for LVD. Conclusions: Stepwise screening for SHD with AI-ECG followed by POCUS significantly reduces costs compared to AI-ECG alone. We also suggest a model for parallel screening for multiple SHDs, which is likely more cost-effective than screening for individual SHDs.

Background: Patients with normal resting left ventricular ejection fraction (LVEF) without either coronary artery disease (CAD) or a hypertensive response can paradoxically develop reduced LVEF during exercise stress echocardiography (ESE). The clinical phenotype and outcomes of these patients is unknown. Hypothesis: Patients who paradoxically develop reduced LVEF during exercise may represent a sub-phenotype of heart failure with preserved LVEF (HFpEF). Aims: To describe the baseline characteristics and clinical outcomes of this unique patient population. Methods: Among all ESE performed between January 2003 and December 2022, patients without a hypertensive response to exercise and without CAD by angiogram within 90 days of ESE, who had a resting LVEF ≥50% with a ≥5% LVEF decrease during ESE were identified. All-cause mortality, HF hospitalization, and atrial fibrillation (AF) outcomes were assessed. Kaplan-Meier and Cox regression methods were used to analyze time-to-event outcomes. Results: Among 213,643 stress echocardiograms performed, 134 patients met eligibility criteria (Table 1). The mean age of the population was 66±10 years, 76% were women, and 16% had AF at baseline. Mean LVEF was 58±4% at rest and 43±4% at peak stress. Stress electrocardiogram met criteria for ischemia in 14%. The 10-year all-cause mortality risk was 12.9% (95% CI 5.5-20.3) with 10 (37%) of 27 deaths due to cancer (Figure 1, Panel A). The 10-year estimated risk of HF hospitalization was 17.6% (95% CI 9.0-26.2) (Figure 1, Panel B). Among 112 patients without AF at baseline, the 10-year risk of developing AF was 23.4% (95% CI 13.4-33.4). Conclusions: Patients with exercise-induced reduced LVEF in the absence of obstructive CAD have a high incidence of HF hospitalizations and AF. Given the preponderance of women, risk for AF, HF hospitalizations, and cancer-related deaths, the possibility that this condition is an early sub-phenotype of HFpEF should be investigated.

Background: Atrial functional mitral regurgitation (AFMR) constitutes ~25% of ≥moderate MR and has been associated with a high prevalence and incidence of HFpEF. Transcatheter edge-to-edge repair (TEER) has shown effectiveness in improving symptoms in AFMR, but its impact on mortality and HF hospitalizations is unknown. Objective: Evaluate rates of mortality and HF hospitalizations in patients with ≥moderate AFMR treated with TEER and compare them to conservative management. Methods: Consecutive adults with ≥moderate AFMR (functional MR with left atrial enlargement, ejection fraction≥50%, and absent >mild left ventricular enlargement) were identified retrospectively. Ecxlusion criteria were previous cardiac surgery, ≥moderate aortic regurgitation/stenosis, infiltrative/hypertrophic cardiomyopathy, regional wall motion abnormalities or malignancy. Propensity score matching was performed (1:1 ratio) between patients treated with TEER and patients treated conservatively based on age, sex, EuroScore II, effective regurgitant orifice area, and the integrative MR severity. To ensure similar technique in evaluation in the 2 groups, variables were obtained from the closest transthoracic echocardiogram before TEER in the TEER group [median 65 (IQR 29-111) days]. Results: Overall, 46 patients with ≥moderate AFMR treated by TEER and 46 treated conservatively were included, Table 1 . Patients undergoing TEER had more frequent atrial fibrillation and NYHA class ≥III. MR improved to ≤moderate in 93% of patients undergoing TEER on procedural transesophageal echocardiography, Figure 1 . On 1–3-month post-TEER follow-up, 64% had NYHA class I/II (vs 33% pre-TEER), Figure 1 . Over median 2.2 (IQR 1.2-3.1) years, 32 patients died (rate 13%/year in each group, log-rank p=0.85), Figure 2 . When adjusted for baseline NYHA, rates of HF hospitalizations were not different between the groups (Wald-test p-value=0.48). Residual ≥moderate AFMR in the TEER group was not associated with mortality (log-rank p=0.83), but ≥1 class improvement of NYHA in patients with baseline NYHA >1 was associated with decreased mortality, Figure 2 . Conclusion: MR severity and NYHA class improved with TEER for AFMR, and improved NYHA class was associated with decreased mortality. However, the association of TEER with decreased risk of mortality or HF hospitalization remains unproven, and larger randomized studies are needed to evaluate the potential role of TEER on these outcomes in AFMR.

Background: Electrocardiography-based artificial intelligence (AI-ECG) validated models that detect cardiac disease are increasingly being applied in clinical practice. The utility of such tools to detect insidious cardiac disease in patients with normal baseline left ventricular ejection fraction (LVEF) who paradoxically develop reduced LVEF during exercise stress echocardiography (ESE), and do not have coronary artery disease (CAD) or hypertension, is unknown. Hypothesis: AI-ECG is useful to diagnose insidious cardiac disease and predict clinical outcomes in patients with exercise-induced cardiomyopathy. Aims: To assess the utility of AI ECG in patients with exercise-induced cardiomyopathy. Methods: Among all ESE performed between January 2003 and December 2022, patients without a hypertensive response to exercise and without CAD (confirmed by coronary angiography within 90 days after ESE), with resting LVEF ≥50% and a paradoxical ≥5% LVEF decrease during ESE were identified. A previously validated AI-ECG algorithm that predicts atrial fibrillation (AF), reduced LVEF, and cardiac amyloidosis (CA) was applied to the baseline ECG closest to the time of ESE. The predicted probability of AF, reduced LVEF, and CA if above the published thresholds, was determined. Results: There were 134 patients with exercise-induced cardiomyopathy who were identified. The mean age of this cohort was 66±10 years, 76% were women and 16% had AF at baseline. Mean LVEF was 58±4% at rest and 43±4% at peak stress. The median follow-up period was 6.8 years (IQR 3.0-12.2). Among patients without a baseline history of AF (n=112), AI-ECG identified 29% with a significant probability of AF, which was associated with a subsequent AF diagnosis at univariable analysis (HR 2.505, 95%CI 1.016-6.177, p=0.046). There were 10 patients with an AI-ECG prediction of reduced LVEF among whom 3 were subsequently hospitalized with HF. AI-ECG was positive for CA in 8 and 3 amongst these had subsequent HF hospitalizations (Table). Conclusions: Baseline AI-ECG may help predict subsequent AF and diagnose preclinical amyloid cardiomyopathy in patients who by resting echocardiography do not seem to have cardiac disease but with exercise develop reduced LVEF.

Background: Carcinoid heart disease (CaHD) typically affects tricuspid and pulmonary valves and is associated with poor survival. To date, the role of right ventricular (RV) and atrial (RA) strain has not been evaluated in such cohort. Research Questions: To evaluate RV and RA strain patterns and assess their impact on survival and congestive heart failure (CHF) development. Methods: Retrospective study of CaHD patients (ICD 9/10 diagnosis of neuroendocrine tumor and echocardiographic evidence of CaHD prior to any surgical intervention; 2004-2019). Longitudinal strain was evaluated using speckle-tracking, RV/RA-focused view was used. RV strain was averaged from 3 and 6 segments for free wall (FWS) and global strain (GS), respectively. Auto-tracking with manual adjustment was done to ensure optimal tracking. The tracing of RV/RA endocardium was done with 15 points using the tricuspid valve annulus as a reference. The impact of strain parameters on mortality and CHF was evaluated with the Kaplan Meier and Cox proportional hazard analyses. Results: A total of 138 patients were included (mean age was 63 ± 10 years; 47% females). Median follow-up was 5.0 years (3.7-8.2). Significant RA and RV enlargement (72 and 79%, respectively) was more common than RV dysfunction (10%). The most common valvular disease > moderate was tricuspid regurgitation (TR; 97%) followed by pulmonary regurgitation (PR; 70%). RV GS mean was -21 + 6%, with FWS of -23 + 7%. The mean RA strain analysis revealed (93% sinus rhythm): a reservoir of 26 + 11%, a conduit of 14 + 8%, and an atrial contraction of 12 + 8%. Strain parameters were not associated with overall mortality. As opposed to PR/TR severity and RV/RA enlargement/dysfunction, patients with low RA reservoir strain (<23%) were more likely to develop CHF (adjusted-HR=1.80, p=0.04, 95% CI 1.04 - 3.134). Conclusions: Our findings suggests that CaHD patients have RV/RA dysfunction with overall reduced strain parameters. Patients with low RA reservoir had higher risk of CHF, but none of the RV/RA strain parameters were associated with excess mortality. This shows how strain analysis could complement other echocardiographic parameters in CaHD morbidity assessment.

Background: Aortic regurgitation (AR) is a prevalent valve disease with a long latent period to symptoms. Recent data has suggested the role of novel markers of myocardial overload in assessing onset of decompensation. Method: We sought to evaluate the role of unsupervised cluster analyses in identifying different clinical clusters, including clinical status, and a large number of echocardiographic variables including left ventricular (LV) volumes, and their association with mortality. Patients with ≥moderate-severe chronic AR identified using echocardiography at Mayo Clinic, Rochester were retrospectively analyzed. Primary outcome was all-cause mortality censored at aortic valve surgery/last follow-up. Uniform Manifold Approximation and Projection (UMAP) with K -means algorithm was used to cluster patients using clinical and, echocardiographic variables at the time of presentation. Missing data were imputed with the Multiple Imputation by Chained Equations (MICE) method. A supervised approach trained on the training set was used to find cluster membership in a hold-out validation set. Log-rank tests were used to assess differences in mortality rates between the clusters, both in the training and validation sets. Results: Three distinct clusters were identified among 1100 patients (log-rank P for survival <0.001). Cluster 1 (n=337), which included younger males with severe AR but fewer symptoms, showed the best survival, 75.6% (69.5, 82.3). Cluster 2 (n=235), older and more females with elevated filling pressures, showed intermediate survival of 64.2 % (56.8, 72.5). Cluster 3 (n=253), characterized by severe symptomatic AR, demonstrated the lowest survival of 45.3 % (34.4, 59.8) at 5 years. Similar clusters were formed in the internal validation cohort. Conclusion: Distinct clusters with variable echocardiographic features and mortality differences exist within patients with chronic ≥moderate-severe AR. Recognizing these clusters can refine individual risk stratification and clinical decision-making after verification in future prospective studies.