OBJECTIVES:Mitral regurgitation (MR) evolution after transcatheter aortic valve replacement (TAVR) in low-flow aortic stenosis (LFAS) is poorly characterized. The authors evaluated MR trajectories across LFAS phenotypes, predictors of MR worsening, and associations with clinical outcomes. METHODS:The authors retrospectively studied 614 patients with LFAS undergoing TAVR: 153 with low-flow high-gradient (LFHG) (24.9%), 155 with classical low-flow low-gradient (cLFLG) (25.2%), and 306 with paradoxical low-flow low-gradient (pLFLG) (49.8%). MR severity was abstracted from clinical echocardiography reports using a 6-level ordinal scale. MR worsening was defined as a grade increase of at least 1 from baseline MR at approximately 30 days or 1 year. Multivariable logistic models identified predictors of MR worsening. Kaplan-Meier and Cox models evaluated associations of MR trajectory and LFAS subtype with all-cause death, heart failure hospitalization, and their composite. RESULTS:Among 614 LFAS patients, 443 had 30-day and 290 had 1-year echocardiographic follow-up. At 30 days, MR trajectory differed significantly across LFAS phenotypes, with the highest rate of worsening in cLFLG and the lowest in LFHG. At 1 year, unadjusted MR trajectory distributions did not differ significantly across phenotypes. In adjusted logistic models, cLFLG remained independently associated with MR worsening at both timepoints. MR worsening was associated with worse unadjusted outcomes at 30 days but was not independently associated with the composite endpoint after multivariable adjustment. LFAS phenotype, particularly cLFLG, remained the dominant predictor of adverse clinical outcomes. CONCLUSIONS:MR evolution after TAVR is phenotype-specific; patients with cLFLG have the highest risk of MR worsening and lowest event-free survival, supporting phenotype-informed post-TAVR surveillance.
Large language models (LLMs) have rapidly emerged as a transformative class of artificial intelligence systems capable of understanding and generating human-like text from vast corpora of clinical and scientific literature. While their use in general cardiology has been extensively reviewed, their specific role in interventional cardiology and within the catheterization laboratory (cath lab) environment remains less well characterized. This narrative review synthesizes the current evidence on LLM applications across the interventional cardiology workflow, including coronary revascularization decision-making, multidisciplinary Heart Team support, structural heart intervention planning, periprocedural communication, and acute cath lab decision support. Recent studies suggest that contemporary LLMs such as ChatGPT-4 (OpenAI), Claude (Anthropic), and Gemini (Alphabet, Inc.) can achieve clinically meaningful concordance with expert Heart Team recommendations for percutaneous coronary intervention vs coronary artery bypass grafting, and that their outputs may approach or even match those of early-career interventional cardiologists in simulated emergency scenarios. However, important limitations persist, including variable accuracy across prompt formats, susceptibility to hallucinations, lack of multimodal integration with angiographic and intravascular imaging, opacity of training sources, and unresolved medicolegal issues. The authors discuss the current evidence base, highlight promising avenues such as multimodal LLMs and retrieval-augmented generation tools that leverage current guidelines, and outline regulatory and ethical considerations that must accompany clinical adoption. LLMs are unlikely to replace interventional cardiologists in the foreseeable future, but they may meaningfully support decision-making, education, and patient communication in a domain where speed, complexity, and risk converge.
OBJECTIVES:Chronic total occlusion (CTO) percutaneous coronary intervention (PCI) can lead to positive vascular remodeling after revascularization, potentially resulting in late stent malapposition. Self-expanding drug-eluting stents (SE-DES) may adapt better to dynamic vessel diameters than balloon-expandable drug-eluting stents (BE-DES), potentially reducing strut malapposition after CTO-PCI. The authors compared stent malapposition at 6 months between SE-DES and BE-DES in CTO-PCI using optical coherence tomography (OCT). METHODS:In this single-center, prospective, randomized controlled trial, 23 patients with CTO were allocated 1:1 to SE-DES (STENTYS Xposition S [STENTYS S.A]) or BE-DES following successful lesion crossing and balloon predilatation. The primary endpoint was the percentage of malapposed stent struts on 6-month OCT. Secondary endpoints included neointimal hyperplasia, late lumen loss, in-stent restenosis (ISR), and clinical outcomes. RESULTS:At 6 months, OCT showed significantly lower malapposition in the SE-DES group compared with BE-DES (0.0% [0.0-0.0] vs 0.8% [0.0-2.4]; P = .01). SE-DES was associated with greater neointimal thickness (0.3 mm vs 0.1 mm; P < .001) and late lumen loss (0.7 mm vs 0.1 mm; P = .003). ISR occurred more frequently in the SE-DES group (4 vs 1 patients), without reaching statistical significance. No major clinical events were reported in either group. CONCLUSIONS:SE-DES were associated with a statistically significant reduction in strut malapposition compared with BE-DES. However, the absolute malapposition burden was very low in both groups, making the clinical relevance of this imaging finding uncertain. These findings emphasize the importance of individualized stent selection and systematic intracoronary imaging in complex PCI.
OBJECTIVES:Intravascular imaging (IVI) with percutaneous coronary intervention (PCI) in the United States has historically been low, but there have been recent increases. However, how IVI use has changed at an operator level and the characteristics of operators who adopted IVI vs those who did not are unknown. METHODS:Using Medicare Provider Utilization and Payment data, the authors identified PCI operators in 2019 and 2023 who performed at least 30 PCI annually. IVI use was categorized as low/none (IVI to PCI ratio [IPR]: 0.0-0.30), intermediate (IPR: 0.31-0.70), and high (IPR: ≥0.71). Regression models identified provider characteristics associated with IVI adoption. RESULTS:In 2019, 3385 operators performed at least 30 PCI. IVI use in 2019 was low/none among 77.8% operators, intermediate in 15.7%, and high in 6.4%. In 2023, 2289 operators performed at least 30 PCI. IVI use in 2023 was low/none among 48.8% operators, intermediate in 21.8%, and high in 29.3%. Among 1671 operators active in both years, 30.9% of prior low/none users adopted IVI. Only 12.2% of intermediate or high IVI users had a reduction in IVI use. Newer high-volume operators showed high IVI use (51.1%). Non-adoption of IVI was associated with earlier graduation year, smaller hospitals, Southern region, and higher procedural volume, while gender, practice focus, teaching status of affiliated hospital, and hospital affiliation changes were not significant. CONCLUSIONS:IVI use has increased nationally but adoption remains uneven, with structural and generational factors driving persistent disparities and highlighting the need for targeted implementation strategies.
OBJECTIVES:Coronary artery disease affects nearly half of patients undergoing transcatheter aortic valve implantation (TAVI), but the accuracy of angiography-derived, wire-free coronary physiology in severe aortic stenosis remains uncertain. The authors evaluated its diagnostic performance for detecting fractional flow reserve (FFR)-defined significant stenoses in TAVI candidates and assessed whether accuracy differed when invasive FFR was measured before vs after TAVI. METHODS:A diagnostic accuracy meta-analysis was performed including studies reporting lesion-level comparisons between angiography-derived physiology (threshold ≤0.80) and invasive FFR (≤0.80) in patients undergoing TAVI evaluation. All included studies evaluated quantitative flow ratio (QFR) or Murray-law-based QFR; no eligible studies using FFRangio or vFFR were identified. Pooled sensitivity and specificity were calculated using random-effects models. Diagnostic odds ratios (DOR), likelihood ratios, and post-test probabilities were derived. Meta-regression evaluated the impact of FFR timing (CRD420261332222). RESULTS:Five studies met inclusion criteria. Four studies (422 lesions) contributed to the primary analysis and 3 studies (250 lesions) to the secondary analysis. In the primary analysis, pooled sensitivity was 0.79 (95% CI, 0.68-0.87) and specificity 0.88 (95% CI, 0.80-0.93) (DOR 28). In the secondary analysis, sensitivity was 0.71 (95% CI, 0.57-0.82) and specificity 0.95 (95% CI, 0.90-0.98) (DOR 46.5), with comparable global discrimination (Youden index 0.66 vs 0.67). Meta-regression showed no significant interaction by reference timing (P = .39). CONCLUSIONS:Angiography-derived coronary physiology demonstrates good diagnostic performance in patients undergoing TAVI evaluation, with comparable overall discrimination when referenced to both pre- and post-TAVI FFR, although interpretation is limited by the absence of a stable reference standard across hemodynamic states.
OBJECTIVES:Sex-specific differences in left ventricular (LV) remodeling after transcatheter aortic valve replacement (TAVR) in low-flow aortic stenosis (LFAS) remain incompletely defined, and the influence of LFAS subtype on remodeling by sex is uncertain. The authors sought to characterize post-TAVR remodeling in LFAS by sex and subtype and identify predictors of remodeling. METHODS:This retrospective cohort study included 488 patients with LFAS (303 men, 185 women) who underwent TAVR. Smoothed conditional mean curves assessed longitudinal changes in LV mass index (LVMi), relative wall thickness (RWT), and LV ejection fraction (LVEF) through 18 months. Linear mixed models identified predictors of remodeling. RESULTS:Women more often had paradoxical low-flow low-gradient (pLFLG) AS (58.4% vs 43.6%, P = .001), whereas men more often had classical low-flow low-gradient AS (31.4% vs 13.5%, P < .001). At 1 year, both sexes showed significant improvement in LVMi, RWT, and LVEF. Men demonstrated sustained improvement in LVEF and LVMi during follow-up, whereas women showed earlier improvement followed by decline beginning around 12 months. Predictors also differed: lower LVMi after TAVR was associated with White race and less severe baseline mitral regurgitation in men, and with pLFLG subtype in women. CONCLUSIONS:Reverse remodeling after TAVR occurred in both sexes, but trajectories and predictors were sex-specific.
Coronary computed tomography angiography (CCTA) can be used beyond diagnostic purposes to support the preprocedural planning of percutaneous coronary intervention (PCI). Advances in scanner technology, software platforms, and physiology- and plaque-based visualization tools have expanded the role of CCTA-guided PCI. CCTA provides detailed assessment of coronary anatomy, plaque and calcium morphology, lesion length, vessel size, and noninvasive physiology, offering opportunities to anticipate procedural complexity, optimize resource utilization, and individualize PCI strategy. Emerging data, including randomized studies in chronic total occlusions and ongoing multicenter trials, support the feasibility and potential clinical value of this approach. In April 2024, the first CCTA-guided PCI summit in the United States convened interventional cardiologists and cardiac imagers, as well as industry stakeholders, to discuss the evidence, technical considerations, clinical applications, and unmet needs related to CCTA-guided PCI. This manuscript summarizes the key discussions and conclusions specific to this meeting, with a focus on the transition of CCTA from a diagnostic to a therapeutic planning tool, emerging artificial intelligence applications, its complementary role with intravascular imaging, and opportunities to enhance procedural planning and decision-making. While early experience is promising, broader adoption will require broader educational efforts, access to purpose-built visualization software tools designed for interventional cardiologists, multidisciplinary collaboration, and additional randomized and real-world studies to define its impact on clinical outcomes and procedural efficiency.
