Correlation of Non-Invasive Transthoracic Doppler Echocardiography with Invasive Doppler Wire-Derived Coronary Flow Reserve and Their Impact on Infarct Size in Patients with ST-Segment Elevation Myocardial Infarction Treated with Primary Percutaneous Coronary Intervention.

Background: Coronary microvascular dysfunction is associated with adverse prognosis after ST-segment elevation myocardial infarction (STEMI). We aimed to compare the invasive, Doppler wire-based coronary flow reserve (CFR) with the non-invasive transthoracic Doppler echocardiography (TTDE)-derived CFR, and their ability to predict infarct size. Methods: We included 36 patients with invasive Doppler wire assessment on days 3-7 after STEMI treated with primary percutaneous coronary intervention (PCI), of which TTDE-derived CFR was measured in 47 vessels (29 patients) within 6 h of the invasive Doppler. Infarct size was assessed by cardiac magnetic resonance at a median of 8 months. Results: The correlation between invasive and non-invasive CFR was modest in the overall cohort (rho 0.400, p = 0.005). It improved when only measurements in the LAD artery were considered (rho 0.554, p = 0.002), with no significant correlation in the RCA artery (rho -0.190, p = 0.435). Both invasive (AUC 0.888) and non-invasive (AUC 0.868) CFR, measured in the recanalized culprit artery, showed a good ability to predict infarct sizes ≥18% of the left ventricular mass, with the optimal cut off values of 1.85 and 1.80, respectively. Conclusions: In patients with STEMI, TTDE- and Doppler wire-derived CFR exhibit significant correlation, when measured in the LAD artery, and both have a similarly strong association with the final infarct size.

Prognostic Value of Mitral Regurgitation in Patients with Primary Hypertrophic Cardiomyopathy.

Background and Objectives: Mitral valve pathology and mitral regurgitation (MR) are very common in patients with hypertrophic cardiomyopathy (HCM), and the evaluation of mitral valve anatomy and degree of MR is important in patients with HCM. The aim of our study was to examine the potential influence of moderate or moderately severe MR on the prognosis, clinical presentation, and structural characteristics of HCM patients. Materials and Methods: A prospective study examined 176 patients diagnosed with primary asymmetric HCM. According to the severity of the MR, the patients were divided into two groups: Group 1 (n = 116) with no/trace or mild MR and Group 2 (n = 60) with moderate or moderately severe MR. All patients had clinical and echocardiographic examinations, as well as a 24 h Holter ECG. Results: Group 2 had significantly more often the presence of the obstructive type of HCM (p < 0.001), syncope (p = 0.030), NYHA II class (p < 0.001), and atrial fibrillation (p = 0.023). Also, Group 2 had an enlarged left atrial dimension (p < 0.001), left atrial volume index (p < 0.001), and indirectly measured systolic pressure in the right ventricle (p < 0.001). Patients with a higher grade of MR had a significantly higher E/e' (p < 0.001) and, as a result, higher values of Nt pro BNP values (p < 0.001) compared to Group 1. Kaplan-Meier analysis demonstrated that the event-free survival rate during a median follow-up of 88 (IQR 40-112) months was significantly higher in Group 1 compared to Group 2 (84% vs. 45% at 8 years; log-rank 20.4, p < 0.001). After adjustment for relevant confounders, the presence of moderate or moderately severe MR remained as an independent predictor of adverse outcomes (HR 2.788; 95% CI 1.221-6.364, p = 0.015). Conclusions: The presence of moderate or moderately severe MR was associated with unfavorable long-term outcomes in HCM patients.

Multi-Swarm Algorithm for Extreme Learning Machine Optimization.

There are many machine learning approaches available and commonly used today, however, the extreme learning machine is appraised as one of the fastest and, additionally, relatively efficient models. Its main benefit is that it is very fast, which makes it suitable for integration within products that require models taking rapid decisions. Nevertheless, despite their large potential, they have not yet been exploited enough, according to the recent literature. Extreme learning machines still face several challenges that need to be addressed. The most significant downside is that the performance of the model heavily depends on the allocated weights and biases within the hidden layer. Finding its appropriate values for practical tasks represents an NP-hard continuous optimization challenge. Research proposed in this study focuses on determining optimal or near optimal weights and biases in the hidden layer for specific tasks. To address this task, a multi-swarm hybrid optimization approach has been proposed, based on three swarm intelligence meta-heuristics, namely the artificial bee colony, the firefly algorithm and the sine-cosine algorithm. The proposed method has been thoroughly validated on seven well-known classification benchmark datasets, and obtained results are compared to other already existing similar cutting-edge approaches from the recent literature. The simulation results point out that the suggested multi-swarm technique is capable to obtain better generalization performance than the rest of the approaches included in the comparative analysis in terms of accuracy, precision, recall, and f1-score indicators. Moreover, to prove that combining two algorithms is not as effective as joining three approaches, additional hybrids generated by pairing, each, two methods employed in the proposed multi-swarm approach, were also implemented and validated against four challenging datasets. The findings from these experiments also prove superior performance of the proposed multi-swarm algorithm. Sample code from devised ELM tuning framework is available on the GitHub.

Prognostic impact of non-culprit chronic total occlusion over time in patients with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention.

AIMS: Previous studies indicated that a chronic total occlusion (CTO) in a non-infarct-related artery is linked to higher mortality mainly in the acute setting in patients with ST-elevation myocardial infarction (STEMI). Our aim was to assess the temporal distribution of mortality risk associated with non-culprit CTO over years after STEMI. METHODS AND RESULTS: The study included 8679 STEMI patients treated with primary percutaneous coronary intervention (PCI). Kaplan-Meier cumulative mortality curves for non-culprit CTO vs. no CTO were compared with log-rank test, with landmarks set at 30 days and 1 year. Adjusted Cox regression models were constructed to assess the impact of non-culprit CTO on mortality over different time intervals. Tests for interaction were pre-specified between non-culprit CTO and acute heart failure and left ventricular ejection fraction. The primary outcome variable was all-cause mortality, and the median follow-up was 5 years. Non-culprit CTO was present in 11.6% of patients (n = 1010). Presence of a CTO was associated with increased early [30-day adjusted hazard ratio (HR) 1.91, 95% confidence interval (CI) 1.54-2.36; P < 0.001] and late mortality (5-year adjusted HR 1.66, 95% CI 1.42-1.95; P < 0.001). Landmark analyses revealed an annual two-fold increase in mortality in patients with vs. without a CTO after the first year of follow-up. The observed pattern of mortality increase over time was independent of acute or chronic LV impairment. CONCLUSIONS: Non-culprit CTO is independently associated with mortality over 5 years after primary PCI for STEMI, with a constant annual two-fold increase in the risk of death beyond the first year of follow-up.