Search Results (9)

Background: In elderly, multimorbid patients, renal function changes are frequent following transcatheter aortic valve implantation. However, the early renal recovery following the relief of aortic stenosis is not sufficiently characterized. Methods: This retrospective single-center study comprised 410 consecutive patients who underwent TAVI. Serum creatinine and estimated glomerular filtration rate (eGFR) were measured prior to and within 72 h of TAVI to evaluate renal function. Primary outcomes were defined as absolute alterations (Δcreatinine and ΔeGFR). Spearman’s correlation and multivariable regression were implemented to assess associations. Results: The mean age was 82.0 ± 8.7 years, and 46.9% of the participants were female. The eGFR demonstrated modest improvement (mean ΔeGFR +3.83 mL/min/1.73 m²), while creatinine showed minimal change (mean Δ −0.015 mg/dL). Renal function exhibited bidirectional alterations. Baseline creatinine was inversely associated with Δcreatinine (ρ = −0.127, p = 0.010), which was consistent with regression to the mean. Conversely, baseline eGFR was not associated with ΔeGFR (ρ = 0.004, p = 0.934). There were no significant correlations between renal changes and BMI (ρ = −0.041 and ρ = 0.047; both p > 0.30). In multivariable analysis, baseline creatinine remained independently associated with Δcreatinine (β = −0.279, p < 0.001), whereas ejection fraction exhibited a modest association (β = 0.012, p = 0.020). Acute kidney injury was observed in 13.9% of the population (57/410) and was not independently correlated with baseline variables. Conclusions: Early renal alterations following TAVI are frequent and frequently favorable; however, they are primarily indicative of baseline renal function, with limited independent predictive value of other variables. The results should be regarded as hypothesis-generating. Full article

Introduction: Artificial intelligence (AI) tools have emerged in cardiovascular clinical practice. Regarding transcatheter aortic valve replacement/implantation (TAVR/TAVI) procedures, their utilization optimizes procedural planning, aids physicians with decision making, and predicts possible post-procedural complications. Moreover, machine-learning (ML) models, compared with traditional mortality risk scores, show promising results considering predicted mortality in TAVI patients. However, further validation is required. As the implementation of cardiovascular procedures can be challenging, AI technology broadens the armamentarium of tools that a clinician is able to use for a more comprehensive evaluation of patients, minimizing complications and resulting in optimum clinical outcomes. Methods: A comprehensive literature search was conducted through the PubMed and Google Scholar databases from inception to 20 September 2025, to identify relevant studies. The search strategy included the following keywords: [“TAVI” OR “TAVR”] AND [“AI”, Artificial Intelligence]. Results: According to our database research, 7177 articles were initially screened, and 2145 duplicate articles were excluded. Eventually, 189 articles were evaluated by our reviewers and 51 articles of studies published between 2014 and 2025 were included in our review. Conclusions: AI algorithms could revolutionize the Heart Team decision making process, being not only a tool for patient evaluation but an active member of the team with applications to analyze and optimize all stages of the TAVI procedure, guide decision making and predict outcomes, and, with the contribution and evaluation of information from all human members of the team, enhance even more the patient-mediated medicine/interventions. Full article

The rapid expansion of structural heart interventions over the past decade has created unprecedented challenges in procedural planning and complication prediction. While traditional imaging provides essential anatomical information, translating two-dimensional images into a comprehensive three-dimensional understanding of complex cardiac structures remains challenging. This review encompasses finite element analysis (FEA), computational fluid dynamics (CFD), and fluid–structure interaction (FSI) technologies across major structural heart procedures, including transcatheter aortic valve implantation (TAVI), transcatheter mitral valve interventions, and left atrial appendage occlusion (LAAO). We evaluated the technical foundations, clinical validation studies, and practical applications of various simulation platforms. Advanced computer simulation has demonstrated feasibility and clinical utility across multiple structural heart procedures. Computer simulation for structural heart interventions has evolved from a proof of concept to clinical implementation, with growing evidence of procedural planning benefits in TAVI and LAAO. While feasibility has been established across multiple intervention types, this field requires larger validation studies to demonstrate accuracy and clinical outcome improvements. Future directions include integration of machine learning, real-time simulation capabilities, and expanding applications to complex anatomies and redo procedures. This technology represents an emerging paradigm that may facilitate precision medicine in structural heart interventions, with potential for significant improvements in procedural success and patient safety. Full article

Background: Aortic stenosis (AS) is the most common valvular heart disease, associated with poor outcomes if left untreated. Current guidelines recommend that transcatheter aortic valve implantation (TAVI) procedures be performed in hospitals with an on-site cardiac surgery unit due to potential complications requiring surgical intervention. Objective: Based on our experience, we evaluated the feasibility and outcomes of implementing a TAVI program in a cardiology department without an on-site cardiac surgery unit, in collaboration with a remote hospital for surgical backup. Methods: The TAVI program involved pre- and post-procedural evaluations conducted at Meir Medical Center (Kfar Saba, Israel) with a remote surgical team available. The study population included 149 consecutive patients with severe aortic stenosis treated at the Meir valve clinic between November 2019 and December 2023. Procedures were performed by the center’s interventional cardiology team. Results: The mean age of the 149 patients was 80 ± 6 years, and 75 (50%) were female. The average STS score was 4.3, and the EuroSCORE II was 3.1. Among the patients, 68 (45%) were classified as New York Heart Association (NYHA) class III-IV. The valve types used included ACURATE neo2 (57 patients, 38%), Edwards SAPIEN 3 (43 patients, 28%), Evolut-PRO (41 patients, 27%), and Navitor (7 patients, 4%). There were no cases of moderate to severe paravalvular leak and no elevated post-implantation gradients, and there was no need for urgent cardiac surgery. One case of valve embolization was successfully managed percutaneously during the procedure. In-hospital follow-up revealed no deaths and only one major vascular complication. At one-year follow-up, six patients had died, with only one death attributed to cardiac causes. Conclusions: Our findings support the safe and effective performance of transfemoral TAVI in cardiology departments without on-site cardiac surgery, in collaboration with a remote surgical team. Further prospective, multicenter studies are warranted to confirm these results and guide broader clinical implementation of this practice. Full article

Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical implantation and its implementation is progressively increasing worldwide. We routinely perform pre-procedural aortic angiography CT to assess aortic dimensions and vascular anatomy. This study aims to evaluate the image quality of CTA for TAVI planning using dual-layer spectral CT, with virtual monoenergetic image reconstructions at 40 keV. Thirty-one patients underwent a CTA protocol with the injection of 20 mL of contrast media. Image quality was assessed by measuring the mean density in Hounsfield Units (HU), the signal-to-noise ratio, and the contrast-to-noise ratio in VMI reconstructions. Additionally, a blinded subjective analysis was conducted by two observers. The results showed significant enhancement at all sampled vascular levels with a gradual decrease in HU from proximal to distal regions. Favourable subjective ratings were given for all parameters, with greater variability in the evaluation of iliac axes. A significant negative correlation (p < 0.05) was observed between BMI and CA at all vascular levels, indicating reduced contrast enhancement with increasing BMI. Spectral CT, along with reducing iodine load, allows for obtaining high-quality images without a significant increase in noise. The reduction in iodine load can have positive implications in clinical practice, improving patient safety and resource efficiency. Full article

Transcatheter aortic valve implantation (TAVI) is a procedure to treat severe aortic stenosis. There are several clinical concerns related to potential complications after the procedure, which demand the analysis of computerized tomography (CT) scans after TAVI to assess the implant’s result. This work introduces a novel, fully automatic method for the analysis of post-TAVI 4D-CT scans to characterize the prosthesis and its relationship with the patient’s anatomy. The method enables measurement extraction, including prosthesis volume, center of mass, cross-sectional area (CSA) along the prosthesis axis, and CSA difference between the aortic root and prosthesis, all the variables studied throughout the cardiac cycle. The method has been implemented and evaluated with a cohort of 13 patients with five different prosthesis models, successfully extracting all the measurements from each patient in an automatic way. For Allegra patients, the mean of the obtained inner volume values ranged from 10,798.20 mm³ to 18,172.35 mm³, and CSA in the maximum diameter plane varied from 396.35 mm² to 485.34 mm². The implantation of this new method could provide information of the important clinical value that would contribute to the improvement of TAVI, significantly reducing the time and effort invested by clinicians in the image interpretation process. Full article

Quality of life is an important factor influencing mood. In any group of elderly people undergoing valve implementation or surgical aortic valve replacement, one in three will have depressive symptoms. The aims of this study were as follows: 1. to evaluate the impact of health-related quality of life on depressive symptoms in elderly patients undergoing TAVI, and 2. to analyze beliefs about TAVI. Methods: A total of 131 elderly people (mean age: 82.1 ± 6.1 years) scheduled to receive TAVI completed the Geriatric Depression Scale, EQ-5D-3L, and Mini Mental State Examination. A total of 43 patients completed the questionnaires after the treatment. The narrative interview analyses were performed based on 20 randomly selected patients after TAVI. Results: The mean level of general depression before TAVI was 4.19 ± 2.83, and after it was 3.12 ± 2.52 (p = 0.02), and the frequency decreased from 20% to 3%. An increase in the level of activity and number of interests and a decrease in life satisfaction were identified. The higher the general quality of life was, the lower the levels of depressiveness before and after TAVI were (r = 0.26 vs. r = 0.48; p < 0.05). Conclusions: Patients differed in their depressive symptoms, as well as their intensity and frequency, before and after TAVI. These results underscore the importance of screening for depression at baseline and reassessing changes in depressiveness during follow-up. Full article

The transcatheter aortic valve implantation (TAVI) treatment pathway is complex, leading to procedure-related delays. Dedicated TAVI coordinators can improve pathway efficiency. COORDINATE was a pilot observational prospective registry at three German centers that enrolled consecutive elective patients with severe aortic stenosis undergoing TAVI to investigate the impact a TAVI coordinator program. Pathway parameters and clinical outcomes were assessed before (control group) and after TAVI coordinator program implementation (intervention phase). The number of repeated diagnostics remained unchanged after implementation. Patients with separate hospitalizations for screening and TAVI had long delays, which increased after implementation (65 days pre- vs. 103 days post-implementation); hospitalizations combining these were more efficient. The mean time between TAVI and hospital discharge remained constant. Nurse (p = 0.001) and medical technician (p = 0.008) working hours decreased. Patient satisfaction increased, and more consistent/intensive contact between patients and staff was reported. TAVI coordinators provided more post-TAVI support, including discharge management. No adverse effects on post-procedure or 30-day outcomes were seen. This pilot suggests that TAVI coordinator programs may improve aspects of the TAVI pathway, including post-TAVI care and patient satisfaction, without compromising safety. These findings will be further investigated in the BENCHMARK registry. Full article

The launch of ‘Rapid Recommendations’ by the Grading of Recommendations Assessment, Development and Evaluation (GRADE) group, in collaboration with Making GRADE the Irresistible Choice (MAGIC) and the British Medical Journal (BMJ), is a very interesting recent development in e-healthcare. Designed to respond quickly to developments that have created new decision situations, their first project resulted from the arrival of minimally invasive Transcatheter Aortic Valve Implantation (TAVI) as an alternative to Surgical Aortic Valve Replacement (SAVR), for patients with symptomatic severe aortic stenosis. The interactive MAGIC decision aid that accompanies a Rapid Recommendation and is the main route to its clinical implementation, represents a major advance in e-health, for a cardiovascular decision in this case. However, it needs to go further in order to facilitate fully person-centred care, where the weighted preferences of the individual person are elicited at the point of decision, and transparently integrated with the best (most personalised) estimates of option performances, to produce personalised, preference-sensitive option evaluations. This can be achieved by inputting the collated GRADE evidence on the criteria relevant in the TAVI/SAVR choice into a Multi-Criteria Decision Analysis-based decision support tool, generating a personalised, preference-sensitive opinion. A demonstration version of this add-on to the MAGIC aid, divested of recommendations, is available online as proof of method. Full article