Kane, Garvan C.

Abstract Background Chronotropic incompetence (CI) is a biomarker of cardiac autonomic dysfunction. Aim To assess the risk stratification value of CI during physical or pharmacological stress echocardiography in patients with chronic coronary syndromes. Methods In a prospective, multicenter, international, observational study design, we enrolled 13,445 patients with known or suspected chronic coronary syndromes who underwent stress echo in 19 sites from 10 countries using either exercise (n=2,594), dobutamine (n=2,440), or dipyridamole (n=8,411). Heart rate was automatically measured from the 1-lead ECG in the echo monitor. We considered CI as failure to reach 85% of the maximal predicted (220-age) heart rate for exercise and dobutamine, and heart rate reserve (peak/rest heart rate) <1.22 (<1.17 in permanent atrial fibrillation) for dipyridamole. All-cause death was the outcome measure. Results Heart rate reserve was available in all patients; there was no extra imaging or analysis time, and no intra- and inter-observer variability. CI was observed in 5,045 patients (38%); abnormal regional wall motion abnormality in 1,648 (13%). Over a median follow-up time of 3.5 years, there were 2,426 (18%) deaths. The 10-year mortality was 39% in patients with and 21% in patients without CI (p<0.0001). CI was associated with a significant (p<0.0001) increase in 10-year mortality in all age groups ranging from <54 years to >75 years. In addition, it was associated with increased mortality (p<0.0001) irrespective of β-blocker use (Figure). Cox multivariable analysis revealed that CI was a significant predictor of mortality (HR 1.60, 95% confidence interval 1.47-1.74; p<0.0001) together with age, male sex, diabetes mellitus, ejection fraction, and resting heart rate. Conclusion In patients with chronic coronary syndromes, CI during physical or pharmacological stress is a simple, inexpensive, quantitative, and objective predictor of survival.

Abstract Background Inducible ST-segment depression during stress echocardiography (SE) is associated with a higher risk in patients with inducible regional wall motion abnormality (RWMA). Objective To assess ST segment elevation's prevalence and functional correlates during SE. Methods ECG response was analyzed in 1712 patients (age 63±12 years; 1011 men, 59%) undergoing SE for chronic coronary syndromes (CCS) prospectively recruited at 39 laboratories. Among the patients analyzed, 1286 (75%) performed SE with exercise, 306 (18%) with dobutamine and 120 (7%) with a vasodilator. ECG response was considered abnormal in case of ST-segment shift >1.0 mm from baseline at 80 ms from the J point developed in ≥2 contiguous leads during SE. The stress to rest (∆) change in the wall motion score index (WMSI) was assessed in all patients. Coronary angiography was available in 765 patients. Major adverse cardiac events (MACE) were the outcome measure in 746 patients with follow-up information. Results No significant ST segment shift was observed in 1000 patients (58%, Group 1), ST-segment depression occurred in 609 patients (35.5%, Group 2), and ST-segment elevation in 103 patients (6%, Group 3). ST-segment elevation occurred in 66/1286 patients (5.2%) with exercise, 30/306 with dobutamine (10%), and 7/120 with vasodilators (6%, p = ns vs. exercise and p<0.01 vs. dobutamine). The prevalence of stress-induced RMWA was higher in Group 2 (38.1%) compared to Group 3 (33%) and Group 1 (11.9%. P< 0.001 vs. Groups 2 and 3); however, the ΔWMSI was more pronounced in Group 3 compared to Group 2 and Group 1 (p = ns vs. Group 2 and p<0.001 vs. Group 1). (Figure, left panel). Non-significant CAD (defined as coronary stenosis <50% on coronary angiography) was more prevalent in Group 1 (36%) and 3 (40%) compared to Group 2 (17.5%, p<0.01 vs. Group 1 and 3). . During a median follow-up of 387 days (IQ range 314-603 days), 150 events occurred in 112 patients: 14 all-cause deaths, 39 acute myocardial infarctions, 19 atrial fibrillations, 34 late coronary revascularizations, and 44 acute heart failure hospitalizations. The exposure-adjusted event rate was the lowest in Group 1 compared to Groups 2 and 3 (Figure, right panel). Conclusion In all-comers with CCS, the electrocardiographic pattern of ST-segment elevation is not rare, more frequent with dobutamine, associated with more stress-to-rest change in RWMA and more events despite less extensive underlying anatomic CAD. The paradox of more ischemia with less coronary stenosis is consistent with a coronary vasospastic origin as an important yet frequently overlooked cause of stress-induced ST segment elevation.Figure

Abstract Background Left ventricular diastolic function (LVDF) and left bundle branch block (LBBB) are both linked with increased risk of LV systolic dysfunction, heart failure, and mortality. Assessing LVDF, which is typically done through echocardiography, becomes challenging in the presence of LBBB due to the intraventricular conduction delay that disrupts the reliability of tissue Doppler imaging. Recently, we validated an artificial intelligence-enabled electrocardiogram (AI-ECG) model to assess LVDF and filling pressures. Methods We performed a retrospective study among patients with ECG-confirmed LBBB who also underwent comprehensive echocardiography within 14 days of the index ECG between September 2001 and June 2022. Using multivariable survival models, we assessed the risk of all-cause mortality across AI-ECG-derived LVDF grades. Results Of 2,554 patients with LBBB (mean age 72.0+12.6, 54.6% women), 252 (9.8%), 656 (25.7%), and 1,436 (56.2%), and 210 (8.2%) had normal LVDF, G1 LVDF, G2 LVDF, and G3 LVDF, respectively. The median LV ejection fraction (LVEF) was 54% and 49.3% of the patients had heart failure. Worse LVDF was associated with older age, lower LVEF, and higher rates of diabetes, hypertension, chronic pulmonary disease, renal failure, cardiovascular disease, and heart failure (p-of-trend<0.001 for all). During a median follow-up of 2.6 years (interquartile range 0.5-4.0 years), 847 (33.2%) patients died. In multivariable survival analysis, adjusted to multiple risk factors including baseline LVEF and heart failure, worse LVDF was independently associated with a higher risk of death [G1 LVDF: adjusted hazard ratio (aHR) 2.15 (95% confidence interval (95%CI) 0.75-1.77), G2 LVDF: aHR 2.25 (95%CI 1.50-3.38) G3 LVDF: aHR 2.96 (95%CI 1.88-4.65); p<0.001 for both)]. These findings were consistent also in a subgroup of patients with baseline LVEF > 50%. Conclusion Among patients with LBBB, worse LVDF, as derived by a dedicated AI-ECG algorithm is independently associated with all-cause mortality beyond baseline LVEF and clinical heart failure.survival across AI-ECG LVDF grades

Abstract Background Ischemic mitral regurgitation (IMR) is a common complication of coronary artery disease (CAD), often occurring after myocardial infarction (MI). Even when moderate in severity, IMR is associated with adverse outcomes, including a twofold increase in mortality rates. Aim To assess the functional correlates of resting IMR during stress echocardiography (SE) in patients with CAD. Methods This prospective multicenter study included 192 patients with CAD (143 males; mean age 65 ± 10 years) from eight cardiology institutions. Exclusion criteria included a history of coronary artery bypass surgery, more than moderate IMR, and other significant valvular diseases. Patients were divided into two groups based on semiquantitative- quantitative assessment at rest based on EACVI-ASE criteria: Group 1: Patients with moderate IMR, Group 2: Patients without IMR or with trivial IMR. All patients underwent stress echocardiography (SE) using the ABCE protocol. Patients underwent exercise tests, if execise echocardiography was not possible, dobutamine stress tests were performed. At rest and peak SE, we assessed: Left atrial volume index (LAVi), Left ventricular end-diastolic (LV EDV) and end-systolic volumes (LV ESV), ejection fraction (EF), wall motion score index (WMSI), global longitudinal strain (GLS), B-lines (4-site simplified scan), tricuspid annular plane systolic excursion (TAPSE), systolic pulmonary artery pressure (SPAP), LV contractile reserve (LVCR) and heart rate reserve (HRR). Results Despite similar EF at rest, Group 1 patients showed more pronounced functional impairment at rest, which increased during stress. Stress-induced functional worsening affected indices of MR (more frequently becoming severe), ischemic burden (WMSI), diastolic function (LAVI and LVEDV dilation), LV systolic function (LVCR), pulmonary congestion (B-lines), cardiac sympathetic reserve (reduced HRR) and right ventricular/pulmonary artery coupling (reduced TAPSE/SPAP): table 1. Conclusion Compared to CAD patients with absent-to-trivial resting IMR, patients with moderate IMR at rest show a constellation of functional vulnerabilities during SE involving more frequent exercise-induced worsening of MR, blunted LV diastolic and systolic reserve, more pulmonary congestion, impaired cardiac autonomic reserve, and worse right ventricular-pulmonary artery coupling. The individual patient's functional response heterogeneity can be identified with comprehensive exercise SE, possibly a roadmap to personalized and targeted therapeutic interventions.

Abstract Background Right ventricular (RV) systolic function is an independent predictor of outcome, but a robust automated method of quantitation is lacking. Purpose To develop and validate a deep learning model for quantifying RV systolic function from 2D echo clips and assess its prognostic value in various loading states and left-heart disease. Methods A deep learning convolutional neural network (CNN) was developed to quantitate RV systolic function using all available apical 4 chamber (A4C) views from 13,039 patients (61,187 A4C video clips) in a US institution. Videos were converted to frames of 256x256 grayscale pixels, with graphics, including the ECG, removed. The model used the S3D architecture, a 3D-CNN with many of the spatial and temporal convolutions separated. RV free wall longitudinal strain (RVFWLS) was used to define RV function: normal (≤-25%); mild (-20% to –24%); moderate (-15% to –19%) and severe RV dysfunction (0% to –14%). The AI-estimate was the average of multiple 32-frame segments for each clip identified as an A4C, including both standard and RV-focused variations. The model was validated in four distinct clinical cohorts from independent data sources: 1) 1365 patients referred to an external diagnostic echocardiography lab in a different US state; 2) 569 patients recruited prospectively with known or suspected pulmonary hypertension (PH); 3) 416 patients with moderate or greater tricuspid valve regurgitation (TR); 4) 872 patients imaged at an Eastern European University with left-sided cardiac diseases (valvular disease, cardiomyopathies, etc.), athletes, or healthy volunteers. Results Model output was strongly correlated with the presence of RV dysfunction by manual measurement [AUC 0.907 (95% CI: 0.888-0.926)] in the internal validation set. Results were similar in an external validation US cohort [N=1365; AUC 0.919 (95% CI: 0.899-0.939)]. When the model was applied to 569 patients with known or suspected PH, presence and severity of the AI measures of RV dysfunction were strongly associated with functional class, 6 min walk distance, NT-proBNP levels and right heart failure (p<0.001). The presence and severity of RV dysfunction (as categorized by the AI model) was strongly associated with all-cause mortality in patients with PH (Figure 1A) and in patients with significant TR (Figure 1B). The European cohort was a geographically and institutionally distinct cohort with a low prevalence of >mild TR (10.8%) or PH (6.4%). In this cohort the AI model predicted a reduced RVEF (< 45%) with an AUC of 0.864 (95% CI: 0.831-0.898) and associated with both all-cause mortality (Figure 2A) and a composite endpoint of heart failure hospitalization or death (Figure 2B). Conclusions A fully automated, AI-based assessment of RV systolic function, using 2D apical 4 chamber echo views alone, is highly feasible and can accurately categorize disease severity and predict outcome across a wide spectrum of cardiovascular conditions.Figure 1 Figure 2

Background Artificial intelligence (AI)–enabled electrocardiography has emerged as a tool for detecting cardiac dysfunction. The prognostic relevance of AI‐enabled electrocardiography–derived diastolic dysfunction (DD) in patients undergoing transcatheter aortic valve replacement had not been assessed. Methods We analyzed 3197 patients undergoing transcatheter aortic valve replacement for severe aortic stenosis between 2010 and 2023 with baseline 12‐lead ECGs processed by a validated AI model to classify diastolic function (grades 0–3). Multivariable Cox models and nested model comparisons assessed associations with all‐cause mortality, including a prespecified analysis in patients with indeterminate echocardiographic grading. Trajectories were defined by change in AI‐enabled electrocardiography DD grade (<2 versus ≥2) from baseline to 30‐day or 1‐year follow‐up. Results At baseline, 21% had grade 3, 57% had grade 2, 8% had grade 1, and 14% had grade 0 AI‐enabled electrocardiography DD. Higher grades were associated with adverse cardiac remodeling and comorbidities. Over a median follow‐up of 3.4 years, grade 3 AI‐enabled electrocardiography DD independently predicted mortality (hazard ratio [HR], 1.80 [95% CI, 1.47–2.20]; P <0.001). AI‐enabled electrocardiography DD improved prognostic discrimination beyond clinical and echocardiographic measures (ΔHarrell concordance statistic, 0.016; Δ χ 2 =57; P <0.001). Among 1259 patients with indeterminate echocardiographic grading, AI‐enabled electrocardiography added prognostic value (ΔHarrell concordance statistic, 0.02; Δ χ 2 =13; P =0.006). Worsening or persistently high‐risk trajectories were associated with increased mortality (HRs, 1.45–1.80; all P <0.05). Conclusions AI‐enabled electrocardiography–derived DD independently predicts mortality after transcatheter aortic valve replacement, adds value beyond echocardiographic grading, and enables dynamic risk stratification through longitudinal tracking.

BACKGROUND: Chronic aortic regurgitation (AR) is associated with significant cardiac remodeling, but the prevalence and prognostic impact of extravalvular cardiac damage remain unexplored. METHODS: Adults with moderate or greater chronic AR identified on echocardiogram between January 2008 and July 2024 were included. Exclusion criteria were acute AR, hypertrophic and infiltrative cardiomyopathies, prior cardiac surgery, and valve stenosis. Cardiac damage was classified into hierarchical stages: no cardiac damage (stage 0), left ventricular damage (stage 1), moderate or greater mitral regurgitation or left atrial enlargement or atrial fibrillation (stage 2), pulmonary hypertension or moderate or greater tricuspid regurgitation (stage 3), and significant right ventricular dysfunction (stage 4). The primary outcome was the association between cardiac damage stages and all-cause mortality under medical surveillance. RESULTS: Of 4026 patients (median age, 72 [61–80] years), 78% had moderate AR, 11% had moderate-severe, and 11% had severe AR. Cardiac damage was present in 87% of patients: 14% in stage 1, 53% in stage 2, 18% in stage 3, and 2% in stage 4. In a multivariable model, including age, sex, AR severity, and Charlson Comorbidity Index, cardiac damage stages were associated with mortality. Adjusted hazard ratios were 1.42 (95% CI, 1.04–1.96) for stage 1, 1.58 (95% CI, 1.21–2.06) for stage 2, 2.78 (95% CI, 2.10–3.67) for stage 3, and 5.34 (95% CI, 3.67–7.76) for stage 4. Adding cardiac damage staging to multivariable models improved predictive accuracy for mortality, increasing the concordance statistics from 0.73 (95% CI, 0.71–0.75) to 0.76 (95% CI, 0.74–0.77). CONCLUSIONS: Cardiac damage is present in nearly 90% of patients with moderate or greater AR and is associated with increased mortality, highlighting the need for a more comprehensive evaluation of cardiac structure and function beyond the aortic valve and left ventricle.

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous entity including patients with different phenotypes of near normal, normal, and supernormal left ventricular (LV) function. Objectives To assess the value of resting LV elastance (also known as force) with transthoracic echocardiography (TTE) to identify HFpEF phenotypes. Methods In a prospective, observational, multicenter study, 2380 HFpEF patients were recruited from July 2016 to May 2024. Systolic blood pressure (SBP) was measured. We assessed LV end-diastolic volume (EDV), end-systolic volume (ESV), EF, force (SBP/ESV), stroke volume (SV), arterial elastance (AE), ventricular-arterial coupling (VAC), and left atrial volume index (LAVI). Global longitudinal strain (GLS) was available in 1164 (48.9%) patients. 680 patients finished follow-up with a composite end-point of major adverse cardiac events (MACEs). Patients were divided into three groups: low force (&lt; 25th percentile, Group 1, &lt; 3.24 mmHg/ml), intermediate force (≥ 25th percentile and ≤ 75 thpercentile, Group 2, 3.24-5.48 mmHg/ml), and high force (&gt; 75 th percentile, Group 3, &gt;5.48 mmHg/ml). Results The 3 groups showed a gradient with descending values (Group 3&gt;2&gt;1) for SBP, EF, GLS, AE, and VAC, with the opposite gradient (Group 1&gt; 2&gt; 3) for EDV, ESV, SV, and LAVI values (all P&lt;0.01). After a median follow-up of 16 months, 205 MACEs occurred in 138 patients. Cumulative MACEs rate was lowest in group 2 (14.7% person-year), higher in group 1 (16.1% person-year) and 3 (22.9% person-year, log rank p = 0.036). Conclusions HFpEF patients present with different LV contractile phenotypes, easily identified with resting LV force and volumetric TTE. The dominant hemodynamic feature of hypocontractile phenotype is a preload recruitment with larger LV EDV and normal SV, while the hypercontractile phenotype is characterized by a small LV with reduced SV. The hypercontractile and hypocontractile phenotypes are associated with a higher risk of subsequent events.

Abstract Backgrounds Transthoracic echocardiography (TTE) identifies a peculiar hypercontractile phenotype (HP) in patients with heart failure and preserved ejection fraction (HFpEF) with high resting left ventricular (LV) elastance (also called force). Objectives To assess the functional response and its prognosis associated with HP in HFpEF by stress echocardiography (SE). Methods In a prospective, observational, multicenter study, 1213 patients with HFpEF were divided into two groups based on the highest quartile of rest force: non-hypercontractile phenotype group (non-HP, &lt; 5.64 mmHg/mL, Group 1, n= 910), and HP group (≥5.64 mmHg/mL, Group 2, n= 303). All patients underwent SE with at least 4 of the following stress parameters assessed: wall motion score index (WMSI), B-lines (4-site score), force-based LV contractile reserve, coronary flow velocity reserve (CFVR), and heart rate reserve (HRR). The employed stress was exercise (n=687), dobutamine (n=195), or vasodilators (n=331). SE score ranged from 0 (all steps normal) to 1-5, according to the number of abnormal steps. Follow-up was completed in a subset of 260 patients. Results The 2 groups showed similar values of peak stress WMSI but the global functional burden was higher in Group 2 patients: see table. In a subset of 260 patients who finished follow-up, there were 212 non-HP patients and 48 HP patients. During a median follow-up of 15 months (interquartile range: 10-20), 26 deaths, 20 heart failure (HF) rehospitalizations, and 64 major adverse cardiovascular events (MACEs) occurred. The cumulative HF rehospitalization rate and MACEs rate were higher in HP group (log-rank p&lt;0.01): see figure. Rest force (HR, 1.17; 95% CI: 1.06-1.29; P: 0.040), rest SPAP (HR, 1.08; 95% CI: 1.02-1.14; P: 0.007) and ABCDE score (HR, 1.15; 95% CI: 1.01-1.66; P: 0.032) were independently associated with MACEs. Conclusions HFpEF patients with HP are functionally weaker with multiple vulnerabilities during stress and at higher risk of subsequent events compared to non-HP patients.Relation between resting values of force

Abstract Background Elevated left ventricular filling pressure (LVFP) is associated with an increased risk of heart failure and mortality. Pulmonary artery wedge pressure (PAWP) is considered the gold standard for assessing LVFP. Recently, we validated an artificial intelligence-enabled electrocardiogram (AI-ECG) to assess LV diastolic function (LVDF) and LVFP. Herein, we compare AI-ECG with PAWP in predicting long-term mortality. Methods We included adults who had comprehensive echocardiography with available ECG within 14-days and right-heart-catheterization (RHC) within 30-days of echocardiography. Elevated-LVFP was defined as PAWP&gt;15 mmHg by RHC, grades 2-3 LVDF by echocardiography, or as adjudicated by the AI-ECG algorithm. Prognosis by AI-ECG was compared to that by echocardiography and PAWP. Results Among 4,168 patients (median age 64 years, 47.7% female), 1,841 had normal-LVFP, and 2,327 had elevated-LVFP by RHC. Echocardiography classified 1,502 patients as normal-LVFP, 1,643 as elevated-LVFP, and 1,023 as indeterminate-LVFP. AI-ECG demonstrated an area-under-the-curve of 0.879 (95%-confidence-interval 0.867-0.891) for predicting elevated-LVFP as determined by echocardiography and 0.742 (95%-confidence-interval 0.724-0.759) for predicting elevated-LVFP as determined by RHC. Over a median follow-up of 7.7 years, 2,735 (34.4%) patients died. In multivariable models, elevated-LVFP by any modality was associated with an increased risk of death (AI-ECG: adjusted-hazard-ratio 1.80, 95% confidence-interval 1.55-2.09; echocardiography: adjusted-hazard-ratio 1.74, 95% confidence-interval 1.51-2.02; PAWP: adjusted-hazard-ratio 1.26, 95% confidence-interval 1.11-1.43). AI-ECG-derived LVFP provided incremental prognostic discrimination compared to echocardiography- or RHC-derived LVFP. Conclusions AI-ECG-derived LVFP offers an accessible, affordable, and noninvasive alternative for detecting elevated LVFP, with potential independent prognostic value beyond traditional echocardiographic and invasive assessments.Survival across LVFP concordance