Caseous calcification of the mitral annulus; scary image during robotic surgery.

Caseous calcification of the mitral annulus (CCMA) is a very rare form of mitral annular calcification (MAC). CCMA accounts for 0.63% of all cases and 0.06-0.07% of the total population and usually seen in elderly and female patients. It mostly affects the posterior leaflet of the mitral valve. The pathogenesis of CCMA remains unclear. Hypercholesterolemia and the dissolution of lipid-laden macrophages may be implicated in liquefaction necrosis. CCMA is composed of a mixture of calcium, fatty acid, and cholesterol. The name "caseous" comes from the cheese-like or toothpaste-like consistency of the mass. Cardiac magnetic resonance imaging may help in differentiating MAC from CCMA and should perform. The first treatment option should be conservative treatment because of surgical complications of the procedure. We presented a case report which is about CCMA with preoperative and intraoperative robotic images.

Evaluation of the Transcatheter Aortic Valve Replacement Results in Patients with Borderline Aortic Annulus and the Impact of Under- or Oversizing the Valve.

BACKGROUND: Optimal valve sizing provides improved results in transcatheter aortic valve replacement. Operators hesitate about the valve size when the annulus measurements fall into borderline area. Our purpose was to compare the results of borderline versus non-borderline annulus and to understand the impact of valve type and under or oversizing. METHODS: Data from 338 consecutive transcatheter aortic valve replacement procedures were analyzed. The study population was divided into 2 groups as 'borderline annulus' and 'non-borderline annulus.' Balloon expandable valves already have a grey zone definition. Similar to balloon expandable valves, annulus sizes that are within 15% above or below the upper or lower limit of a particular self-expandable valve size are defined as the 'borderline annulus' for self-expandable valves. The borderline annulus group was also divided into 2 subgroups according to the smaller or larger valve selection as 'undersizing' and 'oversizing.' Comparisons were made regarding the paravalvular leakage and residual transvalvular gradient. RESULTS: Of these 338 patients, 102 (30.1%) had a borderline and 226 (69.9%) had a non-borderline annulus. Both the transvalvular gradient (17.81 ± 7.15 vs. 14.44 ± 6.27) and the frequency of paravalvular leakage (for mild, mild to moderate, and moderate, 40.2%, 11.8%, and 2.9% vs., 18.8%, 6.7%, and 0.4%, respectively) were significantly higher in the borderline annulus than the non-borderline annulus group (P <.001). There were no significant differences between the groups balloon expandable versus self-expandable valves and oversizing versus undersizing regarding the transvalvular gradient and paravalvular leakage in patients with borderline annulus (P >.05). CONCLUSION: Regardless of the valve type and oversizing or undersizing, borderline annulus is related to significantly higher transvalvular gradient and paravalvular leakage when compared to the non-borderline annulus in transcatheter aortic valve replacement.

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF. Various machine learning and deep learning (DL) techniques have been developed for the automated detection of AF. In this review, we focused on the automated AF detection models developed using DL techniques. Twenty-four relevant articles published in international journals were reviewed. DL models based on deep neural network, convolutional neural network (CNN), recurrent neural network, long short-term memory, and hybrid structures were discussed. Our analysis showed that the majority of the studies used CNN models, which yielded the highest detection performance using ECG and heart rate variability signals. Details of the ECG databases used in the studies, performance metrics of the various models deployed, associated advantages and limitations, as well as proposed future work were summarized and discussed. This review paper serves as a useful resource for the researchers interested in developing innovative computer-assisted ECG-based DL approaches for AF detection.

Relationship between Cardiovascular Disease Risk and Neck Circumference Shown in the Systematic Coronary Risk Estimation (SCORE) Risk Model.

INTRODUCTION: The most important way to reduce CVD-related mortality is to apply appropriate treatment according to the risk status of the patients. For this purpose, the SCORE risk model is used in Europe. In addition to these risk models, some anthropometric measurements are known to be associated with CVD risk and risk factors. OBJECTIVES: This study aimed to investigate the association of these anthropometric measurements, especially neck circumference (NC), with the SCORE risk chart. METHODS: This was planned as a cross-sectional study. The study population were classified according to their SCORE risk values. The relationship of NC and other anthropometric measurements with the total cardiovascular risk indicated by the SCORE risk was investigated. RESULTS: A total of 232 patients were included in the study. The patients participating in the study were analysed in four groups according to the SCORE ten-year total cardiovascular mortality risk. As a result, the NC was statistically significantly lower among the SCORE low and moderate risk group than all other SCORE risk groups (low-high and very high 36(3)-38(4) (IQR) p: 0.026, 36(3)-39(4) (IQR) p < 0.001, 36(3)-40(4) (IQR) p < 0.001), (moderate-high and very high 38(4) vs. 39(4) (IQR) p: 0.02, 38(4) vs. 40(4) (IQR) p < 0.001, 39(4) vs. 40(4) (IQR) p > 0.05). NC was found to have the strongest correlation with SCORE than the other anthropometric measurements. CONCLUSIONS: Neck circumference correlates strongly with the SCORE risk model which shows the ten-year cardiovascular mortality risk and can be used in clinical practice to predict CVD risk.