Coronary Artery Disease in Patients Undergoing Transvalvular Aortic Valve Implantation

Coronary artery disease (CAD) is common in patients with severe aortic stenosis. With the advent of transcatheter aortic valve implantation (TAVI) as a therapeutic option, management of CAD in such patients has undergone a revolution. Younger patients are now candidates for treatment, and have a greater life-time probability of requiring post-TAVI coronary access. Considerations include pre-procedural assessment and revascularisation, procedural planning to avoid coronary obstruction as well as optimisation of post-procedural coronary access. The authors review the challenges of managing CAD in TAVI patients, shed light on the evidence base, and provide guidance on how to optimise management

Harnessing the power of artificial intelligence in predicting all-cause mortality in transcatheter aortic valve replacement: a systematic review and meta-analysis

ObjectivesIn recent years, the use of artificial intelligence (AI) models to generate individualised risk assessments and predict patient outcomes post-Transcatheter Aortic Valve Implantation (TAVI) has been a topic of increasing relevance in literature. This study aims to evaluate the predictive accuracy of AI algorithms in forecasting post-TAVI mortality as compared to traditional risk scores.MethodsFollowing the Preferred Reporting Items for Systematic Reviews and Meta-analyses for Systematic Reviews (PRISMA) standard, a systematic review was carried out. We searched four databases in total—PubMed, Medline, Embase, and Cochrane—from 19 June 2023–24 June, 2023.ResultsFrom 2,239 identified records, 1,504 duplicates were removed, 735 manuscripts were screened, and 10 studies were included in our review. Our pooled analysis of 5 studies and 9,398 patients revealed a significantly higher mean area under curve (AUC) associated with AI mortality predictions than traditional score predictions (MD: −0.16, CI: −0.22 to −0.10, p < 0.00001). Subgroup analyses of 30-day mortality (MD: −0.08, CI: −0.13 to −0.03, p = 0.001) and 1-year mortality (MD: −0.18, CI: −0.27 to −0.10, p < 0.0001) also showed significantly higher mean AUC with AI predictions than traditional score predictions. Pooled mean AUC of all 10 studies and 22,933 patients was 0.79 [0.73, 0.85].ConclusionAI models have a higher predictive accuracy as compared to traditional risk scores in predicting post-TAVI mortality. Overall, this review demonstrates the potential of AI in achieving personalised risk assessment in TAVI patients.Registration and protocolThis systematic review and meta-analysis was registered under the International Prospective Register of Systematic Reviews (PROSPERO), under the registration name “All-Cause Mortality in Transcatheter Aortic Valve Replacement Assessed by Artificial Intelligence” and registration number CRD42023437705. A review protocol was not prepared. There were no amendments to the information provided at registration.Systematic Review Registrationhttps://www.crd.york.ac.uk/, PROSPERO (CRD42023437705)

Validation of Yeo’s index in assessing severity of rheumatic mitral stenosis in mixed valve lesions

Introduction: Yeo’s Index, product of the mitral leaflet separation index and dimensionless index, is a novel measure of the severity of rheumatic mitral stenosis (MS). We assess Yeo’s index in patients with rheumatic MS with or without mixed valve disease. Methods: In a retrospective cohort study, Yeo’s index was measured in 237 cases of rheumatic MS − 124 in a transthoracic echocardiography validation cohort using mitral valve area (MVA) by pressure half-time and planimetry as comparator and 113 in a transesophageal echocardiography (TEE) validation cohort using TEE three-dimensional MVA as comparator. Patients were considered to have mixed valve disease if they had MS and concomitant mitral regurgitation or aortic valve disease. Results: There were 113 patients with isolated MS and 124 patients with mixed valve disease. Overall, Yeo’s index ≤ 0.26 cm showed 93.0 % sensitivity and 87.5 % specificity for identifying severe MS (MVA ≤ 1.5 cm2). In isolated MS, Yeo’s index ≤ 0.26 cm showed sensitivity of 94.6 % and specificity of 90.0 % for identifying severe MS, while in mixed valve disease sensitivity was 90.6 % and specificity 86.7 %. Overall, Yeo’s index ≤ 0.15 cm showed 83.6 % sensitivity and 94.3 % specificity for very severe MS (MVA ≤ 1.0 cm2). In isolated MS, the threshold of ≤0.15 cm showed sensitivity of 84.4 % and specificity of 92.6 % for very severe MS, while in mixed valve disease sensitivity was 81.3 % and specificity 95.3 %. The presence of atrial fibrillation did not influence the performance of Yeo’s index. Conclusion: Yeo’s Index accurately differentiates severity of rheumatic MS with or without mixed valve disease

Does pulmonary artery pulsatility index predict mortality in pulmonary arterial hypertension?

10.1002/ehf2.13450ESC HEART FAILURE853835-384

Prevalence, risk factors and intervention for depression and anxiety in pulmonary hypertension: a systematic review and meta-analysis

Current guidelines recommend psychological support for patients with pulmonary hypertension suffering from psychological adversity. However, little is known about the prevalence and risk factors of depression and anxiety in patients with pulmonary hypertension (PH).Published versio

Genomics in practice - a review of inherited cardiac conditions

Interest in inherited cardiovascular conditions (ICCs) is fueled by resources devoted to its diagnosis, management, and research. The rapid advancement of DNA genomic sequencing deepens our understanding of ICCs. The ICC genomic landscape empowers the development of diagnostic guidelines and the discovery of potential therapeutic targets and promises novel therapeutics, especially in precision cardiology. Therefore, it is essential for healthcare institutes and systems to develop contextual frameworks based on current guidelines to provide holistic care for patients with ICCs. The clinical frameworks and considerations described in this review provide an overview of the operations of an ICC clinic, including wet and dry lab conditions, work performed by a healthcare professional, and the variety of cases, ranging from cardiomyopathies to arrythmias to aortopathies. Insights from our experience in an ICC clinic in Singapore add to the discussion of the challenges and benefits for patients and clinicians who serve them