Publications by authors named "Tania Ah-Sing"
Article Synopsis
- The study aimed to assess the left atrioventricular coupling index (LACI) using cardiac CT as a tool to predict cardiovascular death in patients without known cardiovascular disease.
- Conducted on 1,444 patients over a median follow-up of 6.8 years, results showed that a higher LACI correlates with increased risks of cardiovascular and all-cause death.
- LACI ≥ 25% was identified as a significant predictor for cardiovascular death, demonstrating additional prognostic value beyond traditional risk factors and cardiac CT angiography findings.
Article Synopsis
- Cardiovascular disease (CVD) is the leading cause of death in chronic kidney disease (CKD) patients, yet the prognostic value of stress cardiovascular magnetic resonance (CMR) in these patients isn't fully established.
- * A study analyzed 825 symptomatic CKD patients, focusing on the safety and predictive value of vasodilator stress CMR, while excluding patients with severe kidney impairment due to risks associated with gadolinium.
- *Results showed that stress CMR was well tolerated and the presence of inducible ischemia significantly increased the risk of major adverse cardiovascular events, highlighting stress CMR as a critical tool for predicting outcomes in CKD patients.
Safety, feasibility, and prognostic value of stress perfusion CMR in patients with MR-conditional pacemaker.
Eur Heart J Cardiovasc Imaging
January 2023
Aims: To assess the safety, feasibility, and prognostic value of stress cardiovascular magnetic resonance (CMR) in patients with pacemaker (PM).
Methods And Results: Between 2008 and 2021, we conducted a bi-centre longitudinal study with all consecutive patients with MR-conditional PM referred for vasodilator stress CMR at 1.5 T in the Institut Cardiovasculaire Paris Sud and Lariboisiere University Hospital.
Background: In patients with suspected or known coronary artery disease, traditional prognostic risk assessment is based on a limited selection of clinical and imaging findings. Machine learning (ML) methods can take into account a greater number and complexity of variables.
Objectives: This study sought to investigate the feasibility and accuracy of ML using stress cardiac magnetic resonance (CMR) and clinical data to predict 10-year all-cause mortality in patients with suspected or known coronary artery disease, and compared its performance with existing clinical or CMR scores.