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.

Abstract Background Acute Myocardial Infarction (AMI) represents a significant clinical challenge with diverse outcomes. Predicting patient-oriented composite endpoints (POCE) (all-cause death, any stroke, any AMI, or any revascularization) can significantly enhance post-AMI care. Incorporating clinical data with neuroendocrine biomarkers may offer improved prognostic capabilities. Objective To develop and validate a machine learning model to predict POCE in AMI patients, utilizing clinical parameters and neuroendocrine biomarkers. Methods There was prospective, observational, single-center study. Three approaches have been used to obtain the predictions for POCE event. First, as the dataset was imbalanced, an adaptive synthetic (ADASYN) sampling approach was used to generate synthetic instances, particularly focusing on those that are difficult-to-learn by using a weighted distribution. Then, random forest classifier (RF) was used to build a machine learning model to predict POCE. The model was tuned via a grid-search algorithm for optimal hyperparameters and validated using a 10-fold stratified cross-validation. Finally, the feature importance was determined by Shapley Additives, which measure the average marginal contribution of a feature value across all potential feature combinations. For the comparative purpose, the Gini index, which also shows the feature importance but in terms of mean decrease in impurity, was calculated. Results The study incorporated data from 315 patients, examining 47 variables and identifying 72 instances of POCE. After applying the ADASYN algorithm, the class distribution within the dataset was effectively equalized, facilitating the training of a robust RF model. Upon training with 252 instances, the model distinguished POCE with an accuracy of 83.8%, demonstrating a sensitivity of 80% and a specificity of 86%. During 10-fold cross-validation, the model's accuracy slightly dipped to 75%, with a sensitivity of 56% and specificity of 82%, indicating a balance between generalizability and overfitting. Testing mirrored these results, underscoring the model’s consistent performance. Notably, SHAP value analysis highlighted C-Reactive Protein (CRP) and alanine transaminase (ALT) as the most influential features, underscoring their significance in the context of AMI (Figure 1-2). The predictive power of each feature was further demonstrated by the mean decrease in Gini index (Figure 1-2). Conclusion Our study highlights the feasibility of employing machine learning to predict POCE post-AMI using an integrative dataset of clinical and neuroendocrine markers. The predictive model has the potential to revolutionize post-AMI care by allowing clinicians to identify high-risk patients early, tailor interventions, and allocate resources efficiently. Future research could explore the integration of this model into clinical workflows and its impact on patient outcomes.

Background and Objectives: The combination of aortic valve stenosis (AS) and ischemic heart disease (IHD) is quite common and is associated with myocardial fibrosis (MF). The purpose of this study was to evaluate the association between the histologically verified left ventricular (LV) MF and its geometry and function in isolated AS and AS within IHD groups. Materials and Methods: In a single-center, prospective trial, 116 patients underwent aortic valve replacement (AVR) with/without concomitant surgery. The study population was divided into groups of isolated AS with/without IHD. Echocardiography was used, and LV measurements and aortic valve parameters were obtained from all patients. Myocardial tissue was procured from all study patients undergoing elective surgery. Results: There were no statistical differences between isolated AS and AS+IHD groups in LV parameters or systolic and diastolic functions during the study periods. The collagen volume fraction was significantly different between the isolated AS and AS+IHD groups and was 7.3 ± 5.6 and 8.3 ± 6.4, respectively. Correlations between MF and left ventricular end-diastolic diameter (LVEDD) (r = 0.59, p = < 0.001), left ventricular mass (LVM) (r = 0.42, p = 0.011), left ventricular ejection fraction (LVEF) (r = −0.67, p < 0.001) and an efficient orifice area (EOA) (r = 0.371, p = 0.028) were detected in isolated AS during the preoperative period; the same was observed for LVEDD (r = 0.45, p = 0.002), LVM (r = 0.36, p = 0.026), LVEF (r = −0.35, p = 0.026) and aortic annulus (r = 0.43, p = 0.018) in the early postoperative period; and LVEDD (r = 0.35, p ≤ 0.05), LVM (r = 0.43, p = 0.007) and EOA (r = 0.496, p = 0.003) in the follow-up period. In the group of AS and IHD, correlations were found only with LV posterior wall thickness (r = 0.322, p = 0.022) in the follow-up period. Conclusions: Histological MF in AS was correlated with LVM and LVEDD in all study periods. No correlations between MF and LV parameters were found in aortic stenosis in the ischemic heart disease group across all study periods.

BACKGROUND:The dry-pericardium Vienna transcatheter aortic valve system is repositionable and retrievable, already premounted on the delivery system, eliminating the need for assembly and crimping of the device before valve implantation. METHODS:The VIVA first-in-human feasibility study, a prospective, nonrandomized, single-center trial, evaluated the Vienna aortic valve in 10 patients with severe symptomatic aortic stenosis, who were at intermediate or high surgical risk. This study, registered at ClinicalTrials.gov (NCT04861805), focused on the safety, feasibility, clinical and hemodynamic performance of the Vienna system up to 1-year follow-up. RESULTS:The mean patient age was 79 ± 5 years, 60% male. Valve sizes used: 26 mm (10%), 29 mm (30%), 31 mm (60%). Key hemodynamic improvements were significant: mean aortic valve pressure gradient (mmHg) decreased from 48.7 to 8.1, aortic valve area (cm2) increased from 0.75 to 1.91, and maximum jet velocity through the aortic valve (m/s) decreased from 4.41 to 1.95 (p < 0.0001). No moderate/severe paravalvular leakage was observed, and computed tomography scans revealed no evidence of hypo-attenuated leaflet thickening. The study recorded one life-threatening bleeding event, two cases requiring postprocedural pacemaker implantation, and three ischemic events, with only one causing lasting neurological impairment. Importantly, there were no cases of cardiovascular mortality and only one noncardiovascular death, which was confirmed as unrelated to the device. CONCLUSIONS:The study indicates the Vienna valve as a potential option for severe symptomatic aortic stenosis, designed to streamline the procedure and potentially lower healthcare costs by reducing resource and equipment needs, also procedural errors. Further research is essential to thoroughly evaluate its safety and efficacy.

Background: The NR3C2 gene encodes the mineralocorticoid receptor, which is present on cardiomyocytes. Prior studies reported an association between the presence of NR3C2 single-nucleotide polymorphisms (SNPs) and an increased cortisol production during a stress response such as acute myocardial infarction (AMI), which may lead to adverse cardiac remodeling. Objective: To study the impact of the NR3C2 rs2070950, rs4635799 and rs5522 gene polymorphisms on left ventricular (LV) remodeling, rhythm and conduction disorders in AMI patients. Methods: A cohort of 301 AMI patients who underwent revascularization was included. SNPs of the NR3C2 gene (rs2070950, rs4635799 and rs5522) were evaluated. A total of 127 AMI patients underwent transthoracic echocardiography follow-up after 72 h and 6 months. Results: The rs2070950 GG genotype and rs4635799 TT genotype were most common in patients who had LV end-diastolic volume increase < 20% and the same or increased LV ejection fraction, indicating a possible protective effect of these SNPs. The rs5522 TT genotype was associated with a higher frequency of arrhythmias, while the presence of at least one rs5522 C allele was associated with a lower risk of arrhythmias. Conclusion: SNPs of the NR3C2 gene appear to correlate with better ventricular remodeling and a reduced rate of arrhythmias post-AMI, possibly by limiting the deleterious effects of cortisol on cardiomyocytes.

Background:The novel Vienna TAVI system is repositionable and retrievable, already pre-mounted on the delivery system, eliminating the need for assembly and crimping of the device prior to valve implantation.Aims:The purpose of this first-in-human feasibility study was to determine the safety, feasibility, clinical and hemodynamic performance of the Vienna TAVI system at 6-month follow-up. (ClinicalTrials.gov identifier NCT04861805).Methods:This is a prospective, non-randomized, single-arm, single-center, first-stage FIH feasibility study, which is followed by a second-stage pivotal, multicenter, multinational study in symptomatic patients with severe aortic stenosis (SAS). The first-stage FIH study evaluated the safety and feasibility, clinical and hemodynamic performance of the device in 10 patients with SAS based on recommendations by the VARC-2.Results:All patients were alive at 3-month follow-up. 1 non-cardiovascular mortality was reported 5 months after implantation. There were no new cerebrovascular events, life-threatening bleeding or conduction disturbances observed at 6-month follow-up. The mean AV gradient significantly decreased from 48.7 ± 10.8 to 7.32 ± 2.0 mmHg and mean AVA increased from 0.75 ± 0.18 to 2.16 ± 0.42 cm2 (p < 0.00001). There was no incidence of moderate or severe total AR observed. In the QoL questionnaires, the patients reported a significant improvement from the baseline 12-KCCQ mean score 58 ± 15 to 76 ± 20. NYHA functional class improved in two patients, remained unchanged in one patient. There was an increase in mean 6-min-walk distance from baseline 285 ± 97 to 347 ± 57 m.Conclusions:This study demonstrates that using Vienna TAVI system has favourable and sustained 6-month safety and performance outcomes in patients with symptomatic severe aortic stenosis.

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients with acute myocardial infarction (AMI) suffer from distress that causes a rise in cortisol (stress hormone) which acts through glucocorticoid receptors (GR) and mineralocorticoid receptors (MR). Both receptors are present in cardiomyocyte nuclei (1-4). The animal model study in 2017 showed that activated MR increases cardiomyocyte oxidative stress leading to adverse electrophysiological remodelling that causes arrhythmias. 1.4% of tachyarrhythmias which is the main cause of cardiac death occur within the first month in AMI patients. MR are encoded by the human gene NR3C2 (nuclear receptor subfamily 3 group C member (5-6). Thus, we hypothesized that NR3C2 rs2070950, rs4635799 and rs5522 gene polymorphisms might have an extensive impact on rhythm disorders that occur in a cohort of AMI patients. Aim The aim is to evaluate the impact of the NR3C2 rs2070950, rs4635799 and rs5522 genes polymorphism in patients that developed rhythm and conduction disorders after suffering AMI. Methods The study included 301 patients treated at our hospital after suffering from AMI; all study subjects underwent primary percutaneous coronary intervention (PCI) and guideline-directed medical treatment (1). Patients' blood samples that were collected upon arrival had cortisol and troponin I levels checked and SNPs of the NR3C2 gene (rs2070950, rs4635799 and rs5522) assessed. To avoid inaccuracies all patients with a previous history of coronary syndrome or PCI were excluded. Rhythm conduction disorders and NR3C2 gene polymorphism were analyzed using the exact Fisher’s test. All the statistical analyses were performed with SPSS 27.0 software. The value of p < 0.05 was considered statistically significant. Results Patients with ventricular and atrial events in the early phase of AMI had higher levels of serum cortisol than the patients that did not have rhythm disorders (p=0.001) (Table 1). Rhythm disorders such as ventricular tachycardia (VT), ventricular flutter (VF) and atrial flutter or atrial fibrillation (AF/AFL) that occurred during hospitalization for AMI were notably associated with rs5522 gene polymorphism. During a hospital stay for AMI higher rs5522 TT genotype frequency was noticed in patients with AF/AFL than in patients without. C allele recurrence was 19.6%. Moreover, the protective effect was detected for AF/AFL there is also a protective effect in VA. (Table 2). Despite this, the gene polymorphism and high-grade atrioventricular block (HAVB) were unrelated. Genes rs2070950 and rs4635799 were not found significant to rhythm and conduction disorders. Conclusions Patients with the rs5522 TT allele are more prone to experience a higher frequency of arrhythmias. However, if at least one rs5522 C is found it associates with a smaller risk of arrhythmias post-AMI, meaning that this gene possibly limits damaging effects on cardiomyocytes that are caused by cortisol.

Abstract Funding Acknowledgements Type of funding sources: None. Background The neutrophil-to-lymphocyte ratio (NLR) is associated with inflammation. The theory of Endobiogeny is a complex systems theory of physiology that evaluates the relationship between biomarkers and endocrine management of adaptation response. NLR is referred to in this system as the "Genito-thyroid index" (GTI) due to the roles of estrogen and thyroid hormones in immune response. Basophils correlate with worse outcomes in critical illness and are stimulated by ACTH when there is delayed cortisol excretion from the adrenal cortex. These biomarkers are routinely obtained after acute myocardial infarction (AMI), but their relationship to AMI and left ventricular ejection fraction (LVEF) have not been established. Purpose The aim of this study was to assess the relationship between the GTI and %Basophils to LVEF in first time AMI. Methods This prospective study included 52 consecutive patients diagnosed with AMI, admitted to the intensive care unit of our university hospital from April 2017 to November 2017. Percent neutrophils, lymphocytes and basophils were determined on admission (GTI1, Basophil1) and before discharge (GTI2, Basophil2). Diagnostic coronary angiography and percutaneous coronary intervention (PCI) was performed for all patients. All patients underwent transthoracic echocardiography within hospitalization period (LVEF1) and after 6 months (LVEF2) during follow up period. Echocardiography was performed using a Philips machine. LV function was assessed by the measurement of EF using the biplane Simpson’s disc summation method through QLAB ultrasound cardiac analysis on apical two- and four-chamber views. Statistical analyses were performed using the SPSS 20.0 software. Spearman’s rank correlation coefficient was used to examine the relationship between different variables. A p-value <0.05 was considered statistically significant. Results Study population mean age was 63.9 ± 11.6 years. Mean GTI1 was 4.5 ± 2.8 (1.5-2.5). Mean GTI2 was 2.8 ± 1.4. Δ GTI1-2 significantly and positively correlated with Δ LVEF1-2 (r = 0.380, p = 0.019). Mean Basophils1 was 0.3 ± 0.2% (<0.2%). Mean Basophil2 was 0.4 ± 0.3%. Δ Basophil1-2 positively correlated with Δ LVEF 1-2 (r = 0.435, p = 0.015). No significant correlation was found between GTI1 and Δ LVEF1-2 (r = 0.137, p = 0.332), or Basophil1 and Δ LVEF1-2 (r = -0.186, p = 0.196). Conclusion Admission values of GTI and basophils, while both elevated did not correlate with LVEF1-2. However, Δ GTI1-2 and Δ basophils1-2 did. From this we conclude that relative recovery of the systemic response to AMI is more significative than initial response and affects myocardial recovery. Monitoring GTI and basophils is commonly performed and inexpensive. It reflects a role of the endocrine system not before investigated in myocardial recovery post-AMI. It may be useful for identifying patients at risk of poor LVEF post-AMI.

Background and Objectives: Serum cortisol has been extensively studied for its role during acute myocardial infarction (AMI). Reports have been inconsistent, with high and low serum cortisol associated with various clinical outcomes. Several publications claim to have developed methods to evaluate cortisol activity by using elements of complete blood count with its differential. This study aims to compare the prognostic value of the cortisol index of Endobiogeny with serum cortisol in AMI patients, and to identify if the risk of mortality in AMI patients can be more precisely assessed by using both troponin I and cortisol index than troponin I alone. Materials and methods: This prospective study included 123 consecutive patients diagnosed with AMI. Diagnostic coronary angiography and revascularization was performed for all patients. Cortisol index was measured on admission, on discharge, and after 6 months. Two year follow-up for all patients was obtained. Results: Our study shows cortisol index peaks at 7–12 h after the onset of AMI, while serum cortisol peaked within 3 h from the onset of AMI. The cortisol index is elevated at admission, then significantly decreases at discharge; furthermore, the decline to its bottom most at 6 months is observed with mean values being constantly elevated. The cortisol index on admission correlated with 24-month mortality. We established combined cut-off values of cortisol index on admission > 100 and troponin I > 1.56 μg/las a prognosticator of poor outcomes for the 24-month period. Conclusions: The cortisol index derived from the global living systems theory of Endobiogeny is more predictive of mortality than serum cortisol. Moreover, a combined assessment of cortisol index and Troponin I during AMI offers more accurate risk stratification of mortality risk than troponin alone.

Ionizing radiation management is among the most important safety issues in interventional cardiology. Multiple radiation protection measures allow the minimization of x-ray exposure during interventional procedures. Our purpose was to assess the utilization and effectiveness of radiation protection and optimization techniques among interventional cardiologists in Lithuania. Interventional cardiologists of five cardiac centres were interviewed by anonymized questionnaire, addressing personal use of protective garments, shielding, table/detector positioning, frame rate (FR), resolution, field of view adjustment and collimation. Effective patient doses were compared between operators who work with and without x-ray optimization. Thirty one (68.9%) out of 45 Lithuanian interventional cardiologists participated in the survey. Protective aprons were universally used, but not the thyroid collars; 35.5% (n  =  11) operators use protective eyewear and 12.9% (n  =  4) wear radio-protective caps; 83.9% (n  =  26) use overhanging shields, 58.1% (n  =  18)—portable barriers; 12.9% (n  =  4)—abdominal patient’s shielding; 35.5% (n  =  11) work at a high table position; 87.1% (n  =  27) keep an image intensifier/receiver close to the patient; 58.1% (n  =  18) reduce the fluoroscopy FR; 6.5% (n  =  2) reduce the fluoro image detail resolution; 83.9% (n  =  26) use a ‘store fluoro’ option; 41.9% (N  =  13) reduce magnification for catheter transit; 51.6% (n  =  16) limit image magnification; and 35.5% (n  =  11) use image collimation. Median effective patient doses were significantly lower with x-ray optimization techniques in both diagnostic and therapeutic interventions. Many of the ionizing radiation exposure reduction tools and techniques are underused by a considerable proportion of interventional cardiology operators. The application of basic radiation protection tools and techniques effectively reduces ionizing radiation exposure and should be routinely used in practice.