Background: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic stenosis are critical for patient prognosis. Accurate prediction of adverse events can enhance patient management and improve outcomes. Aim: This study aimed to develop a machine learning model to predict early safety outcomes in patients with severe aortic stenosis undergoing TAVI. Methods: We conducted a retrospective single-centre study involving 224 patients with severe aortic stenosis who underwent TAVI. Seventy-seven clinical and biochemical variables were collected for analysis. To handle unbalanced classification problems, an adaptive synthetic (ADASYN) sampling approach was used. A fined-tuned random forest (RF) machine learning model was developed to predict early safety outcomes, defined as all-cause mortality, stroke, life-threatening bleeding, acute kidney injury (stage 2 or 3), coronary artery obstruction requiring intervention, major vascular complications, and valve-related dysfunction requiring repeat procedures. Shapley Additive Explanations (SHAPs) were used to explain the output of the machine learning model by attributing each variable’s contribution to the final prediction of early safety outcomes. Results: The random forest model identified left femoral artery diameter and aortic valve calcification volume as the most influential predictors of early safety outcomes. SHAPs analysis demonstrated that smaller left femoral artery diameter and higher aortic valve calcification volume were associated with poorer early safety prognoses. Conclusions: The machine learning model highlights of early safety outcomes after TAVI. These findings suggest that incorporating these variables into pre-procedural assessments may improve risk stratification and inform clinical decision-making to enhance patient care.

Introduction: Patient-prosthesis mismatch (PPM) has been associated with numerous short- and long-term adverse events. This study aimed to evaluate the effect of PPM on early postoperative results after aortic valve replacement (AVR) in daily practice. Methods: In this single-centre retrospective study, 150 non-consecutive patients from March 2019 to January 2020 with clinically indicated AVR with/without concomitant surgery were analysed. The study protocol included operative mortality, complication rate, and pre- and postoperative echocardiographic data. PPM was considered severe with indexed effective orifice area at 0.85 cm²/m². Results: Moderate PPM was observed in 16 patients (10.6%). No patient had severe PPM. PPM was not related to early mortality ( r = 0.40, p = 0.630), intra- ( r = −0.076, p = 0.352) and postoperative ( r = −0.0134, p = 0.102) events. Conclusion: In this study, moderate PPM was a frequent finding after AVR, whereas severe PPM was not observed. PPM did not affect the early results after AVR. A long-term follow-up study in a large patient population is required to assess the actual influence of residual PPM.

Background: Transcatheter aortic valve implantation (TAVI) has emerged as a pivotal intervention for managing severe aortic stenosis in high-risk surgical patients. Objective: This study aimed to evaluate the impacts of procedural factors and patient characteristics on TAVI outcomes, with a focus on survival rates, cardiac mortality, and associated complications. Methods: A retrospective, single-center study involving 224 patients who underwent TAVI at the Lithuanian University of Health Sciences from September 2021 to April 2023 was conducted. Data encompassing demographic characteristics, medical history, procedural specifics, and follow-up outcomes were analyzed. Survival and adverse events were assessed at 30 days, 6 months, and 12 months post-TAVI. Results: The study included 224 patients. The mean age in the non-death group was 80 ± 6.17 years (range, 49–91), while that in the cardiac death group was 81.5 ± 6.14 years (range, 70–94; p = 0.079). Males accounted for 37.7% of the non-death group and 50% of the cardiac death group (p = 0.304). Statistical analyses identified factors significantly associated with mortality and complications. The overall survival rate was 88.8%, with cardiac-related mortality observed in 8% of patients. Increased fluoroscopy time (p < 0.001), a higher contrast volume (p = 0.005), and less improvement in aortic valve velocity post-TAVI (p = 0.031) were significantly associated with cardiac mortality. Advanced age and a reduced left ventricular ejection fraction (<50%) were prominent predictors of adverse outcomes. Patients with non-coronary cusp calcification exhibited lower cardiac mortality (p = 0.005), while mitral valve regurgitation was linked to poorer outcomes (p = 0.015). Logistic regression analysis underscored the incremental risks posed by procedural complexities and comorbidities. Conclusions: Procedural factors such as fluoroscopy duration and contrast volume, along with patient-specific attributes including age, left ventricular function, and valve calcification patterns, critically influence TAVI outcomes. These findings emphasize the need for tailored procedural strategies and patient management protocols to mitigate risks and enhance the efficacy of TAVI interventions.

Introduction: The use of cardioplegia not only achieves cardiac arrest but also minimizes ischemic/reperfusion (I/R) injury, potentially improving short- or long-term outcomes. The aim of this study was to evaluate the impact of different cardioplegic solutions – del Nido, Custodiol HTK and St. Thomas on genes expression and cytokines response in an immature rat heart model of I/R using the Langendorff preparation. Expression of genes which are involved in cell cycle, proliferation, apoptosis resistance and response to hypoxia were determined in cardiac tissue, as well as levels pro/anti-inflammatory cytokines were measured. Methods: A total of 39 male Wistar albino rats were utilized in this study. Experimental animals were divided into 3 groups, four animals in each following groups: St. Thomas (ST), Custodiol HTK (HTK) and del Nido (DN) group. Moreover, each of these groups was divided into 3 groups according to ischemia’s time: 1h ischemia with 20 min reperfusion time, 2h ischemia with 40 min reperfusion time, 4h ischemia with 80 min reperfusion and control groups (K-PRF) with 30 minutes of perfusion was performed in the K-PRF (n = 3). The heart was removed from the chest and immediately frozen at –81°C. Results: All cardioplegic solutions effectively modulate the expression of HIF1A, FOS, and BNIP2 genes. The results indicated that DN actively induces HIF1A within the first hour. Compared to the ST, and HTK groups, the expression of the HIF1A gene was on average 2 times higher (P < 0.01). Similar results were observed in the 2-hour group. After 4 hours, the effect of cardioplegic solutions continued to maintain the dynamics, but the differences were not statistically significant. The expression of the FOS gene after 2 and 4 hours of incubation with the DN solution remained significantly higher compared to ST (P < 0.05) and HTK (P < 0.05). A comparative analysis with the perfusion group showed that BNIP2 gene expression in the ST and HTK solution groups was significantly lower than in perfused tissue (P < 0.05). Pro-inflammatory cytokines: TNF-alpha, IL-6 and anti-inflammatory cytokines: IL-4 and IL-10 were evaluated. The results showed that there was no statistically significant difference between the groups (P > 0.05). Conclusion: In our experiment, statistically significant differences were not observed in cytokines. Although statistically significant differences were observed only in gene expression, and only in the rat model, the overall results suggest that del Nido cardioplegic solution may provide better cellular protection. It is also worth mentioning that gene expression and cytokines change are not direct markers of cardioprotection. Further research is needed to confirm these results in human tissues and broader clinical settings.

Background and objectives: The aims of this study were to investigate changes in the hemodynamics associated with different types of aortic prostheses and to evaluate patient-prosthesis mismatch (PPM) at rest and after exercise. Materials and Methods: We retrospectively analyzed 150 patients who presented with indications for aortic valve replacement (AVR) with/without concomitant surgery from March 2019 to January 2020. The study population included 90 (60%) men and 60 (40%) women (mean age, 67.33 ± 10.22 years; range, 37–88 years). Echocardiography data such as peak and mean transprosthetic pressure gradients (Gmax, Gmean), velocity (V), effective orifice area (EOA), and indexed EOA (iEOA) were derived at rest and after exercise at baseline and before discharge. The study patients performed the six-minute walk test (6MWT) on the 5th–7th postoperative day. Results: Stented tissue valves showed excellent performance at rest and after exercise in comparison with mechanical valves, which showed favorable hemodynamics at rest only. At the time of discharge, moderate PPM was observed in 7/74 patients (9.5%) at rest and 5/98 (3.3%) patients after exercise. None of the patients showed severe PPM. EOA and iEOA were not significantly different between the groups. However, the stented group showed more pronounced changes in EOA and iEOA after exercise, whereas the changes in the mechanical valve group did not reach significance. Conclusions: In the early postoperative period, mechanical valves and stented valves showed favorable resting hemodynamics. The PPM rate measured after exercise was lower than that at rest.