Background:The development of symptoms or left ventricular dysfunction in severe aortic stenosis (AS) is associated with high morbidity and mortality. While elective transcatheter aortic valve replacement (TAVR) is supported by robust randomized evidence, data on TAVR performed in non-elective settings (urgent, emergent, or salvage) remain limited and heterogeneous. In these settings, outcomes may be influenced more by baseline clinical severity than by procedural factors. This study aimed to systematically evaluate the safety and effectiveness of non-elective TAVR and to compare the associated outcomes with those of elective TAVR.Methods:This systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and registered with PROSPERO. The PubMed, Embase, and Scopus databases were searched for studies published after 2002 evaluating urgent, emergent, or salvage TAVR in adult patients with severe AS. Eligible studies were required to include elective TAVR as a comparator. Outcomes included mortality and major procedural complications. Prespecified era-based analyses and sensitivity analyses excluding studies at critical risk of bias were performed. Risk of bias was assessed using the ROBINS-I tool.Results:A total of 17 observational studies published between 2015 and 2025 were included, comprising 215,141 patients. Compared with elective patients, those undergoing non-elective TAVR had more advanced heart failure, higher NYHA class, greater comorbidity burden, and higher surgical risk scores, whereas baseline echocardiographic severity of AS was similar. Pooled outcomes for non-elective TAVR showed in-hospital, 30-day, and 1-year mortality rates of 5.1%, 12.4%, and 26.7%, respectively. Non-elective TAVR was associated with higher mortality at all time points compared with elective procedures; meanwhile, rates of stroke, vascular complications, and permanent pacemaker implantation were similar, while major bleeding and acute kidney injury were more frequent. Era-based analyses showed a stable relative mortality risk over time.Conclusions:Although non-elective TAVR is associated with worse outcomes than elective procedures, these differences appear to be largely driven by baseline clinical severity rather than by the transcatheter intervention. In unstable patients with severe AS, non-elective TAVR remains the most effective definitive treatment option compared with balloon aortic valvuloplasty or conservative management.The PROSPERO Registration:CRD420251239620, https://www.crd.york.ac.uk/PROSPERO/view/CRD420251239620.
Ticagrelor vs. clopidogrel in elderly patients following acute myocardial infarction: a multicenter international analysis
Prognostication Following Transcatheter Edge-to-Edge Mitral Valve Repair Using Combined Echocardiography-Derived Velocity Time Integral Ratio and Artificial Intelligence Applied to Electrocardiogram
Introduction: Mitral valve transcatheter edge-to-edge repair (M-TEER) has emerged as a minimally invasive option for high-risk surgical candidates with severe and symptomatic mitral regurgitation (MR), but post-procedure residual mitral valve (MV) dysfunction remains a significant concern. This study evaluates the clinical utility of combining artificial intelligence applied to electrocardiograms (ECG-AI) for diastolic dysfunction (DD) grading and the echocardiography-derived velocity time integral of the MV and left ventricular outflow tract ratio (VTIMV/LVOT) in predicting prognosis in patients post-M-TEER. Methods: A retrospective analysis of patients who underwent M-TEER between 2014 and 2021 was conducted. Patients were categorized based on VTIMV/LVOT and ECG-AI scores into three groups: both normal parameters, either abnormal parameter, or both abnormal parameters to compare outcomes (mortality, major adverse cardiovascular events [MACE], and the need for subsequent MV reintervention) using Kaplan–Meier analysis, multivariable Cox regression models, and net reclassification improvement. Results: Overall, 250 patients were included; the median age was 79.5 (IQR: 73.1, 84.6) and 66.4% were male. The combined abnormal VTIMV/LVOT (≥2.5) and ECG-AI score for DD (>1) was associated with higher risk of one-year mortality (adjusted HR: 4.56 [1.04–19.89], p = 0.044) and MACE (adjusted HR: 3.72 [1.09–12.72], p = 0.037) compared to patients with both normal parameters. Conclusions: This study highlights the potential additive value of integrating VTIMV/LVOT and ECG-AI scores as a prognostic tool for a personalized approach to the post-operative evaluation and risk stratification in M-TEER patients.
Ticagrelor and sleep apnea: an international retrospective cohort study
Abstract Aims Lipoprotein(a) [Lp(a)] has demonstrated its association with atherosclerosis and myocardial infarction. However, its role in the development of in-stent restenosis (ISR) after percutaneous coronary intervention (PCI) is not clearly established. The aim of this study is to investigate the association between Lp(a) and ISR. Methods and results A retrospective study of adult patients who underwent successful PCI between January 2006 and December 2017 at the three Mayo Clinic sites and had a preprocedural Lp(a) measurement was conducted. Patients were divided into two groups according to the serum Lp(a) concentration [high Lp(a) ≥ 50 mg/dL and low Lp(a) < 50 mg/dL]. Univariable and multivariable analyses were performed to compare risk of ISR between patients with high Lp(a) vs. those with low Lp(a). A total of 1209 patients were included, with mean age 65.9 ± 11.7 years and 71.8% were male. Median follow-up after baseline PCI was 8.8 [interquartile range (IQR) 7.4] years. Restenosis was observed in 162 (13.4%) patients. Median serum levels of Lp(a) were significantly higher in patients affected by ISR vs. non-affected cases: 27 (IQR 73.8) vs. 20 (IQR 57.5) mg/dL, P = 0.008. The rate of ISR was significantly higher among patients with high Lp(a) vs. patients with low Lp(a) values (17.0% vs. 11.6%, P = 0.010). High Lp(a) values were independently associated with ISR events (hazard ratio 1.67, 95% confidence interval 1.18–2.37, P = 0.004), and this association was more prominent after the first year following the PCI. Conclusion Lipoprotein(a) is an independent predictor for long-term ISR and should be considered in the evaluation of patients undergoing PCI.
Disproportionately high aortic valve calcium scores in atrial fibrillation: implications for transcatheter aortic valve replacement
Abstract Aims Doppler mean gradient (MG) can underestimate aortic stenosis (AS) severity in patients with atrial fibrillation (AF) compared with patients with sinus rhythm (SR), potentially delaying intervention in AF. This study compared outcomes in patients with AF and SR following transcatheter aortic valve replacement (TAVR) and investigated delay in TAVR based on computed tomography aortic valve calcium score (AVCS). Methods and results Patients who underwent TAVR from 2013 to 2017 for native valve severe AS were identified from an institutional database. Baseline characteristics and overall survival were compared between those with SR and AF. There were 820 patients (mean age 81 years; 41.6% females) included in this study. AF was present in 356 patients. Patients with AF were older (82.2 vs. 80.5, P = 0.003) and had a lower MG compared with patients with SR (42.0 vs. 44.9, P = 0.002) with similar indexed aortic valve area (0.4 vs. 0.4, P = 0.17). Median AVCS was higher in AF (males: AF 2850.0 vs. SR 2561.0, P = 0.044; females: AF 1942.0 vs. SR 1610.5, P = 0.025). Projected AVCS, assuming the same age of diagnosis, was similar between AF and SR. Median survival post-TAVR was worse in AF compared with SR (3.2 vs. 5.4 years, log rank P < 0.001). AF, lower MG, higher right ventricular systolic pressure, dialysis, diabetes, and significant tricuspid regurgitation were associated with higher mortality (P < 0.05 for all). Conclusion Older age and higher AVCS in patients with AF compared with those with SR suggest that AS was both underestimated and more advanced at TAVR referral.
Trends and Disparities in Valvular Heart Disease Mortality in the United States From 1999 to 2020
Background Percutaneous heart valve procedures have been increasingly performed over the past decade, yet real‐world mortality data on valvular heart disease (VHD) in the United States remain limited. Methods and Results We queried the Centers for Disease Control and Prevention's Wide‐Ranging Online Data for Epidemiologic Research database among patients ≥15 years old from 1999 to 2020. VHD and its subtypes were listed as the underlying cause of death. We calculated age‐adjusted mortality rate (AAMR) per 100 000 individuals and determined overall trends by estimating the average annual percent change using the Joinpoint regression program. Subgroup analyses were performed based on demographic and geographic factors. In the 22‐year study, there were 446 096 VHD deaths, accounting for 0.80% of all‐cause mortality (56 014 102 people) and 2.38% of the total cardiovascular mortality (18 759 451 people). Aortic stenosis recorded the highest mortality of VHD‐related death in both male (109 529, 61.74%) and female (166 930, 62.13%) populations. The AAMR of VHD has declined from 8.4 (95% CI, 8.2–8.5) to 6.6 (95% CI, 6.5–6.7) per 100 000 population. Similar decreasing AAMR trends were also seen for the VHD subtypes. Men recorded higher AAMR for aortic stenosis and aortic regurgitation, whereas women had higher AAMR for mitral stenosis and mitral regurgitation. Mitral regurgitation had the highest change in average annual percent change in AAMR. Conclusions The mortality rate of VHD among the US population has declined over the past 2 decades. This highlights the likely efficacy of increasing surveillance and advancement in the management of VHD, resulting in improved outcomes.
The prognostic value of artificial intelligence to predict cardiac amyloidosis in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement
Abstract Aims Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01–1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01–1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13–2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.
Abstract 14695: Artificial Intelligence Applied to the Electrocardiogram Predicts Outcomes in Patients With Severe Aortic Stenosis and Potential Cardiac Amyloidosis Undergoing Transcatheter Aortic Valve Replacement
Introduction: Cardiac amyloidosis (CA) has been suggested to be common (up to 16%) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). CA has poorer outcomes and its assessment in all TAVR patients may be costly and challenging. Hypothesis: CA may be screened for with an artificial intelligence (AI) clinical predictive model applied to pre-TAVR ECGs, and high probability (>50%) for CA may be associated with worse clinical outcomes. Methods: In this retrospective analysis of the Mayo institutional National Cardiovascular Disease Registry (NCDR)-TAVR, patients undergoing a TAVR between Jan-2012 and Dec-2017 were included. Pre-TAVR ECGs were analyzed by the AI predictive model for CA embedded in the EMR. EMRs were reviewed to assess for a clinical diagnosis of CA in those identified as high probability (>50%) by the AI tool. Clinical outcomes on 1 year follow-up were extracted from the NCDR-TAVR database and Kaplan-Meier curves were created to compare patients with high CA probability (≥50%) versus those with low probability (<50%). Results: Of 1070 patients who underwent TAVR (mean age 81.1± 8.5 years, 58.2% male), 263 (24.6%) had ≥50% probability for CA on pre-procedure ECG. Only 18 (1.7%) of these had clinical diagnosis of CA. In the survival analysis, high probability of CA by AI tool was associated with higher all-cause mortality (HR 1.60, 95%CI 1.09-2.34, p=0.01) and greater HF admissions (HR 1.59, 95%CI 1.08-2.35, p<0.01). Neither TIA/stroke nor myocardial infarction were statistically significant. MACE (TIA/stroke, myocardial infarction, heart failure admissions) was higher in the ≥50% CA probability group (HR 1.68, 95%CI 1.17-2.40, p<0.01), (Figure) . Conclusion: CA is clinically underdiagnosed in patients undergoing TAVR. AI applied to pre-TAVR ECGs suggesting higher probability for CA identifies a subgroup at higher risk of clinical events, who may benefit from further diagnostic evaluation for CA.
The role of serum lipoprotein(a) levels in bioprosthetic aortic valve degeneration
Abstract Introduction Lipoprotein(a) [Lp(a)] is associated with an increased incidence of aortic stenosis. Bioprosthetic aortic valve degeneration and native aortic stenosis share similar pathological mechanisms. Evidence regarding the role of serum Lp(a) concentrations in bioprosthetic aortic valve degeneration is lacking. Purpose To evaluate the association between serum Lp(a) concentrations and bioprosthetic aortic valve degeneration. Methods In this retrospective multicenter study, consecutive patients who underwent a bioprosthetic aortic valve replacement between Jan-2010 and Dec-2020 and had a preoperatory serum Lp(a) measurement were included. A baseline transthoracic echocardiography (TTE) was performed following the aortic valve replacement and a follow-up TTE was performed at least 24 months after the baseline study to determine the presence of bioprosthetic valve degeneration. Significant degeneration was defined as: (a) an increase >10 mmHg in mean bioprosthetic aortic valve gradient from baseline status + a decrease in effective orifice area + a decrease in Doppler velocity index + exclusion of clinically thrombotic leaflet thickening, OR (b) new moderate or severe prosthetic aortic regurgitation (if the main component was periprosthetic, then it was not considered). Lp(a) concentrations were compared between patients with and without degeneration and regression analysis was conducted to investigate the association between bioprosthetic valve degeneration and Lp(a) levels. Results In total, 211 cases were included (mean age 74.1 ±9.4 years, 72.0% males, 29.9% transcatheter aortic valve replacements) (Figure 1). Median time between baseline and follow-up TTE was 5.0 (IQR 3.7) years. Bioprostheses degeneration was observed in 33 (15.6%) patients at follow-up. Median serum levels of Lp(a) were significantly higher in the patients affected by degeneration versus non-affected cases (50.0 vs 15.7 mg/dl, p=0.003). In the regression analysis, high Lp(a) levels (≥30 mg/dl) were associated with degeneration both in a univariate analysis (OR 4.8, 95%CI 2.2-10.9, p<0.001) and multivariate analysis adjusted by other risk factors for bioprostheses degeneration (age, sex, hypertension, smoking, patient prosthesis mismatch, creatinine levels, and body surface area) (OR 5.2, 95%CI 2.1-12.8, p<0.001). Conclusion Serum Lp(a) concentrations seem to be a risk factor for bioprosthetic aortic valve degeneration (Figure 2). There is an increasing need to accurately predict bioprosthetic aortic valve degeneration and to develop novel methods and treatments to increase their durability. Prospective studies are needed to confirm these findings and to investigate whether lowering Lp(a) could slow bioprostheses degradation.Population characteristicsLp(a) and bioprostheses degeneration