Unicommissural unicuspid aortic valve (UAV) presenting as ascending aortic aneurysm with aortic dissection.

We herein present an exceptionally rare instance of a unicommissural unicuspid aortic valve (UAV) manifesting with an aneurysmal ascending aorta complicated by a type A aortic dissection .

Transcatheter Mitral Valve Therapies in Patients with Mitral Annular Calcification.

Mitral annular calcification is a chronic process involving degeneration and calcium deposition within the fibrous skeleton of the mitral valve annulus, which can lead to mitral valve dysfunction. It can be asymptomatic, or it can have pathologic sequelae leading to cardiovascular morbidity and mortality. Mitral annular calcification is increasingly recognized with the advancement of diagnostic imaging modalities, especially in an era with a growing elderly population. Its presence poses considerable challenges in terms of surgical and transcatheter management. Multiple surgical and transcatheter techniques have been developed to overcome these challenges. New transcatheter technologies are under investigation to tackle this problem.

Management of prosthetic valve thrombosis with unfractionated heparin.

BACKGROUND: Prosthetic valve thrombosis (PVT) is a severe and life-threatening complication. Surgery and thrombolytic therapy (TT) carry a high risk, and in several circumstances, optimal anticoagulation with unfractionated heparin (UFH) infusion may be an alternative treatment. This study aimed to assess the results of UFH in patients diagnosed with both obstructive and non-obstructive PVT. METHODS: This observational retrospective study enrolled patients who had contraindications for TT and surgery underwent UFH therapy. RESULTS: A total of 136 patients were enrolled [male: 55 (40.4%), mean age: 50.3 ± 14.6 years] in the study. In the successful group, 66 patients (48,5%) showed >75% regression in the thrombus burden without facing death or major non-fatal complications.In the unsuccessful group, 56 had less than a 50% reduction in thrombus load and 14 (10.3%) suffered major complications. The presence of obstruction (27.1% vs. 12.1%; p = 0.028), thrombus area 1.1 cm2 vs. 0.8 cm2; p = 0.005] and the duration of UFH treatment (15.1 vs. 11.8 (days); p = 0.005) were significantly higher in the unsuccessful UFH group.In multivariate regression analyses the presence of obstruction (RR: 3.088, p = 0.020), increased thrombus area (RR: 2.400; p = 0.015), and increased duration of UFH therapy (RR: 1.073 95%, p = 0.012) were identified as independent predictive parameters for a failed UFH therapy. CONCLUSIONS: This study suggests that UFH therapy may be considered a relatively beneficial treatment strategy for some patients with PVT. The most significant factors affecting success are the obstructive nature and area of the thrombus.

The future of valvular heart disease assessment and therapy.

Valvular heart disease (VHD) is becoming more prevalent in an ageing population, leading to challenges in diagnosis and management. This two-part Series offers a comprehensive review of changing concepts in VHD, covering diagnosis, intervention timing, novel management strategies, and the current state of research. The first paper highlights the remarkable progress made in imaging and transcatheter techniques, effectively addressing the treatment paradox wherein populations at the highest risk of VHD often receive the least treatment. These advances have attracted the attention of clinicians, researchers, engineers, device manufacturers, and investors, leading to the exploration and proposal of treatment approaches grounded in pathophysiology and multidisciplinary strategies for VHD management. This Series paper focuses on innovations involving computational, pharmacological, and bioengineering approaches that are transforming the diagnosis and management of patients with VHD. Artificial intelligence and digital methods are enhancing screening, diagnosis, and planning procedures, and the integration of imaging and clinical data is improving the classification of VHD severity. The emergence of artificial intelligence techniques, including so-called digital twins-eg, computer-generated replicas of the heart-is aiding the development of new strategies for enhanced risk stratification, prognostication, and individualised therapeutic targeting. Various new molecular targets and novel pharmacological strategies are being developed, including multiomics-ie, analytical methods used to integrate complex biological big data to find novel pathways to halt the progression of VHD. In addition, efforts have been undertaken to engineer heart valve tissue and provide a living valve conduit capable of growth and biological integration. Overall, these advances emphasise the importance of early detection, personalised management, and cutting-edge interventions to optimise outcomes amid the evolving landscape of VHD. Although several challenges must be overcome, these breakthroughs represent opportunities to advance patient-centred investigations.

Valvular Heart Disease.

Valvular heart disease is a common abnormality seen in the primary care setting. There are many causes of valvular heart disease including congenital, degenerative, infectious, traumatic, and many more. There is a wide variety of types of valvular heart disease with each valve having the ability to develop both regurgitation and stenosis by multiple mechanisms. All these complexities make diagnosis and management of valvular heart disease complicated, especially in the context of comorbidities. For this reason, it is important for primary care physicians to have a thorough understanding of how these diseases present and when interventions are indicated.

Guidelines for the Evaluation of Prosthetic Valve Function With Cardiovascular Imaging: A Report From the American Society of Echocardiography Developed in Collaboration With the Society for Cardiovascular Magnetic Resonance and the Society of Cardiovascular Computed Tomography.

In patients with significant cardiac valvular disease, intervention with either valve repair or valve replacement may be inevitable. Although valve repair is frequently performed, especially for mitral and tricuspid regurgitation, valve replacement remains common, particularly in adults. Diagnostic methods are often needed to assess the function of the prosthesis. Echocardiography is the first-line method for noninvasive evaluation of prosthetic valve function. The transthoracic approach is complemented with two-dimensional and three-dimensional transesophageal echocardiography for further refinement of valve morphology and function when needed. More recently, advances in computed tomography and cardiac magnetic resonance have enhanced their roles in evaluating valvular heart disease. This document offers a review of the echocardiographic techniques used and provides recommendations and general guidelines for evaluation of prosthetic valve function on the basis of the scientific literature and consensus of a panel of experts. This guideline discusses the role of advanced imaging with transesophageal echocardiography, cardiac computed tomography, and cardiac magnetic resonance in evaluating prosthetic valve structure, function, and regurgitation. It replaces the 2009 American Society of Echocardiography guideline on prosthetic valves and complements the 2019 guideline on the evaluation of valvular regurgitation after percutaneous valve repair or replacement.

Functionally unicuspid aortic valve in an adult: Case report and literature review.

Aortic stenosis is one of the most prevalent cardiac valvular diseases throughout the world and has a significant impact on quality of life. While there are several etiologies, we will be discussing the case of a male in his mid-thirties of southeast Asian descent with a bicuspid aortic valve which was found to be functionally unicuspid and complicated by aortic dilation. Following a comprehensive review of literature, it appears this subset of aortic stenosis is not commonly encountered. In addition to presenting this fascinating case, we will review the epidemiology, classification and management of aortic stenosis. Furthermore, we will examine the latest evidence-based literature on bicuspid aortic valve and unicuspid aortic valve and discuss interventions and diagnostic tools that may improve clinical prognosis.

Transformer-Based Spatio-Temporal Analysis for Classification of Aortic Stenosis Severity From Echocardiography Cine Series.

Aortic stenosis (AS) is characterized by restricted motion and calcification of the aortic valve and is the deadliest valvular cardiac disease. Assessment of AS severity is typically done by expert cardiologists using Doppler measurements of valvular flow from echocardiography. However, this limits the assessment of AS to hospitals staffed with experts to provide comprehensive echocardiography service. As accurate Doppler acquisition requires significant clinical training, in this paper, we present a deep learning framework to determine the feasibility of AS detection and severity classification based only on two-dimensional echocardiographic data. We demonstrate that our proposed spatio-temporal architecture effectively and efficiently combines both anatomical features and motion of the aortic valve for AS severity classification. Our model can process cardiac echo cine series of varying length and can identify, without explicit supervision, the frames that are most informative towards the AS diagnosis. We present an empirical study on how the model learns phases of the heart cycle without any supervision and frame-level annotations. Our architecture outperforms state-of-the-art results on a private and a public dataset, achieving 95.2% and 91.5% in AS detection, and 78.1% and 83.8% in AS severity classification on the private and public datasets, respectively. Notably, due to the lack of a large public video dataset for AS, we made slight adjustments to our architecture for the public dataset. Furthermore, our method addresses common problems in training deep networks with clinical ultrasound data, such as a low signal-to-noise ratio and frequently uninformative frames. Our source code is available at: https://github.com/neda77aa/FTC.git.

Meta-Analysis of the Performance of AI-Driven ECG Interpretation in the Diagnosis of Valvular Heart Diseases.

Valvular heart diseases (VHDs) significantly impact morbidity and mortality rates worldwide. Early diagnosis improves patient outcomes. Artificial intelligence (AI) applied to electrocardiogram (ECG) interpretation presents a promising approach for early VHD detection. We conducted a meta-analysis on the efficacy of AI models in this context. We reviewed databases including PubMed, MEDLINE, Embase, Scopus, and Cochrane until August 20, 2023, focusing on AI for ECG-based VHD detection. The outcomes included pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value. The pooled proportions were derived using a random-effects model with 95% confidence intervals (CIs). Study heterogeneity was evaluated with the I-squared statistic. Our analysis included 10 studies, involving ECG data from 713,537 patients. The AI algorithms mainly screened for aortic stenosis (n = 6), mitral regurgitation (n = 4), aortic regurgitation (n = 3), mitral stenosis (n = 1), mitral valve prolapse (n = 2), and tricuspid regurgitation (n = 1). A total of 9 studies used convolution neural network models, whereas 1 study combined the strengths of support vector machine logistic regression and multilayer perceptron for ECG interpretation. The collective AI models demonstrated a pooled accuracy of 81% (95% CI 73 to 89, I² = 92%), sensitivity was 83% (95% CI 77 to 88, I² = 86%), specificity was 72% (95% CI 68 to 75, I² = 52%), PPV was 13% (95% CI 7 to 19, I² = 90%), and negative predictive value was 99% (95% CI 97 to 99, I² = 50%). The subgroup analyses for aortic stenosis and mitral regurgitation detection yielded analogous outcomes. In conclusion, AI-driven ECG offers high accuracy in VHD screening. However, its low PPV indicates the need for a combined approach with clinical judgment, especially in primary care settings.

Valvular heart disease and cardiomyopathy: reappraisal of their interplay.

Cardiomyopathies and valvular heart diseases are typically considered distinct diagnostic categories with dedicated guidelines for their management. However, the interplay between these conditions is increasingly being recognized and they frequently coexist, as in the paradigmatic examples of dilated cardiomyopathy and hypertrophic cardiomyopathy, which are often complicated by the occurrence of mitral regurgitation. Moreover, cardiomyopathies and valvular heart diseases can have a shared aetiology because several genetic or acquired diseases can affect both the cardiac valves and the myocardium. In addition, the association between cardiomyopathies and valvular heart diseases has important prognostic and therapeutic implications. Therefore, a better understanding of their shared pathophysiological mechanisms, as well as of the prevalence and predisposing factors to their association, might lead to a different approach in the risk stratification and management of these diseases. In this Review, we discuss the different scenarios in which valvular heart diseases and cardiomyopathies coexist, highlighting the need for an improved classification and clustering of these diseases with potential repercussions in the clinical management and, particularly, personalized therapeutic approaches.

Diagnosis and Management of Aortic Diseases.

This JAMA Clinical Guidelines Synopsis summarizes the 2022 American College of Cardiology/American Heart Association guidelines for diagnosis and management of aortic disease.

Advances in diagnosis and treatment of mechanical hemolysis following percutaneous interventional for valvular heart diseases. / å¿ƒè„ç“£è†œç— ä»‹å ¥æ²»ç–—æœ¯åŽæœºæ¢°æ€§æº¶è¡€è¯Šç–—è¿›å±•.

Valvular heart disease is one of the common heart diseases in clinical practice, characterized by valve stenosis and/or incomplete closure. At present, drug therapy, surgery, and emerging percutaneous intervention therapy are the main treating methods for heart valve disease. Although the research and development of percutaneous intervention therapy devices is relatively mature, there are still problems such as postoperative mechanical hemolysis. The occurrence of mechanical hemolysis is associated with factors such as excessive shear stress experienced by red blood cells, direct interaction between red blood cells and the heart and valve surfaces, and thrombus formation. Furthermore, the presence of postoperative infection and other hemolytic diseases can also affect the occurrence of mechanical hemolysis. Although most patients are asymptomatic when hemolysis occurs, there are still critical cases. This type of hemolysis can accelerate the deterioration of the condition, and even endanger life in severe cases. Therefore, elucidating the background, pathogenesis, epidemiology, and related clinical research progress of mechanical hemolysis after percutaneous intervention therapy for valvular heart disease is of great significance for guiding the standardized diagnosis and treatment of the disease.

[Detection method of early heart valve diseases based on heart sound features].

Heart valve disease (HVD) is one of the common cardiovascular diseases. Heart sound is an important physiological signal for diagnosing HVDs. This paper proposed a model based on combination of basic component features and envelope autocorrelation features to detect early HVDs. Initially, heart sound signals lasting 5 minutes were denoised by empirical mode decomposition (EMD) algorithm and segmented. Then the basic component features and envelope autocorrelation features of heart sound segments were extracted to construct heart sound feature set. Then the max-relevance and min-redundancy (MRMR) algorithm was utilized to select the optimal mixed feature subset. Finally, decision tree, support vector machine (SVM) and k-nearest neighbor (KNN) classifiers were trained to detect the early HVDs from the normal heart sounds and obtained the best accuracy of 99.9% in clinical database. Normal valve, abnormal semilunar valve and abnormal atrioventricular valve heart sounds were classified and the best accuracy was 99.8%. Moreover, normal valve, single-valve abnormal and multi-valve abnormal heart sounds were classified and the best accuracy was 98.2%. In public database, this method also obtained the good overall accuracy. The result demonstrated this proposed method had important value for the clinical diagnosis of early HVDs.

[Surgical concepts for atrial fibrillation in patients with concomitant mitral valve disease]. / Sravnitel'nyi analiz dvukh kontseptsii khirurgicheskogo lecheniya fibrillyatsii predserdii u patsientov s soputstvuyushchim porazheniem mitral'nogo klapana.

OBJECTIVE: To analyze in-hospital results after «Cox-maze III¼ and «Cox-maze IV¼ procedures with concomitant mitral valve surgery. MATERIAL AND METHODS: This study included patients who underwent «Cox-maze III¼ and «Cox-maze IV¼ procedures between January 2015 and February 2022. We distinguished 2 groups using propensity score matching: «Cox-maze III¼ group (n=15), «Cox-maze IV¼ group (n=14). All patients had preoperative atrial fibrillation: paroxysmal (3 (10.3%) patients), persistent (5 (17.2%)) and long-standing persistent (21 (72.4%) patients). Mean duration of AF before surgery was 11 [9-60] months in both groups. We used standard statistical methods using the IBM SPSS Statistics 26.0 software package (USA). RESULTS: Aortic cross-clamping time was significantly less in the «Cox-maze IV¼ group (p<0.001). There was no in-hospital mortality in both groups. Mean duration of mechanical ventilation was significantly less in the «Cox-maze IV¼ group (5 [3.5-9] vs. 14 [12-18] hours, respectively, p<0.001). Drainage output in the first postoperative day was significantly less in the «Cox-maze IV¼ group (295 [220-370] vs. 400 [325-500] ml, respectively, p=0.02). Temporary pacemaker was required in 73.3% and 42.8% of cases, respectively (p=0.03). CONCLUSION: We should emphasize high efficiency of sinus rhythm recovery after both procedures without significant difference (p=0.16). However, time of aortic cross-clamping, mechanical ventilation and volume of postoperative bleeding were significantly less in the «Cox-maze IV¼ group.

Improving outcomes in carcinoid heart disease - learning from a single centre.

INTRODUCTION: A significant proportion of patients with carcinoid syndrome develop carcinoid heart disease (CHD). Valve degeneration can lead to right heart failure, and worsening prognosis. Replacement of affected valves is an effective therapy. We reviewed patients treated with valve replacement to assess prognostic factors. METHODS: CHD patients records who underwent valve replacement from 2003-2019 were reviewed. RESULTS: Twenty-six patients underwent valve replacement. Mean (SD) age was 61 (11) years, 54% female. Eleven tumours were grade G1, with the remaining G2. NYHA pre-surgery mean (SD) 2.0 (0.7); post-surgery mean 1.2; follow-up mean (SD) 1.6 (0.8). Mean NYHA score difference from pre- to post-surgery -0.71 ( P  = 0.002). 88.5% two (PR & TR), 3.9% one, 3.9% three and 3.9% four valves replaced. 13 patients received Lu177 oxodotreotide; 27% completed four cycles. Mortality at 1 and 5 years follow up was 42% and 50% respectively. Cox proportional hazards model of survival from surgery, adjusting for age [hazard ratio (HR) 0.96 (0.89-1.03) ( P  = 0.25)], four cycles of Lu177 oxodotreotide demonstrated HR 0.087 (0.0079-0.95) ( P  = 0.045) indicating improved survival. DISCUSSION: Surgical patients were often NYHA grade II, and symptoms improved post-surgery. Four cycles of Lu177 oxodotreotide improved survival, although the confidence interval was wide. Further studies should be performed to assess Lu177 oxodotreotide in CHD.

Validation of Risk Stratification for Cardiac Events in Pregnant Women With Valvular Heart Disease.

BACKGROUND: Most risk stratification tools for pregnant patients with heart disease were developed in high-income countries and in populations with predominantly congenital heart disease, and therefore, may not be generalizable to those with valvular heart disease (VHD). OBJECTIVES: The purpose of this study was to validate and establish the clinical utility of 2 risk stratification tools-DEVI (VHD-specific tool) and CARPREG-II-for predicting adverse cardiac events in pregnant patients with VHD. METHODS: We conducted a cohort study involving consecutive pregnancies complicated with VHD admitted to a tertiary center in a middle-income setting from January 2019 to April 2022. Individual risk for adverse composite cardiac events was calculated using DEVI and CARPREG-II models. Performance was assessed through discrimination and calibration characteristics. Clinical utility was evaluated with Decision Curve Analysis. RESULTS: Of 577 eligible pregnancies, 69 (12.1%) experienced a component of the composite outcome. A majority (94.7%) had rheumatic etiology, with mitral regurgitation as the predominant lesion (48.2%). The area under the receiver-operating characteristic curve was 0.884 (95% CI: 0.844-0.923) for the DEVI and 0.808 (95% CI: 0.753-0.863) for the CARPREG-II models. Calibration plots suggested that DEVI score overestimates risk at higher probabilities, whereas CARPREG-II score overestimates risk at both extremes and underestimates risk at middle probabilities. Decision curve analysis demonstrated that both models were useful across predicted probability thresholds between 10% and 50%. CONCLUSIONS: In pregnant patients with VHD, DEVI and CARPREG-II scores showed good discriminative ability and clinical utility across a range of probabilities. The DEVI score showed better agreement between predicted probabilities and observed events.

[Update Valvular Heart Disease: Heart Team Decision-Making Based on Patient Examples]. / Update valvuläre Herzkrankheiten: Entscheidungen im interdisziplinären Herzteam anhand von Beispielen.

INTRODUCTION: In Europe, mitral regurgitation and aortic stenosis are the most common valve lesions requiring interventions. In advanced stages, these valve pathologies affect patients' quality of life and prognosis. The prevalence of mitral regurgitation and aortic stenosis is increasing with age. In view of an aging population and the comorbidities associated with age, these valve defects represent an increasing challenge to health care providers. Nowadays, surgical as well as catheter-based treatment options are available to treat affected patients. Therapeutic strategies suitable to the individual patient should be discussed in interdisciplinary heart teams. The aim of the present article is to give an overview of possible guideline-conform heart team decisions based on patient examples.