Impact of Concomitant Mitral Regurgitation on the Hemodynamic Indicators of Aortic Stenosis.
Michael ŠemanAndrew F StephensAntony WaltonStephen J DuffyDavid C McGiffinShane NanayakkaraDavid M KayeShaun D GregoryDion StubPublished in: Journal of the American Heart Association (2023)
Background In patients with aortic stenosis (AS), the presence of mitral regurgitation (MR) can lead to underestimation of AS severity and worse clinical outcomes. The objective of this study was to characterize the magnitude of the effects of concomitant MR on hemodynamic indicators of AS severity using clinical data and a computational cardiovascular simulation. Methods and Results Echocardiographic data from 1427 patients with severe AS were used to inform a computational cardiovascular system model, and varying degrees of MR and AS were simulated. Hemodynamic data, including left ventricular and aortic pressure waveforms, were generated for all simulations. Simulated reduction in mean transaortic pressure gradient (MPG) associated with MR was then used to calculate the adjusted MPG in the clinical cohort. MR was present in 861 (60%) patients. Compared with patients without MR, patients with MR had a lower aortic-valve area (0.83±0.2 cm 2 versus 0.75±0.2; P <0.001) and were more likely to have a low-gradient pattern (MPG <40 mm Hg) (45% versus 54%; P <0.001). Simulations showed that the presence of concomitant mild, moderate, and severe MR with AS was accompanied by a mean reduction in MPG of 10%, 29%, and 40%, respectively. For patients with MR, their calculated adjusted MPG was on average 24% higher than their MPG (52±22 versus 42±16 mm Hg). Of the 467 patients with low-gradient AS and MR, 240 (51%) would reclassify as high gradient based on their adjusted MPG. Conclusions Concomitant MR results in lower MPG and reduced forward flow compared with isolated AS. Careful quantitation of MR should be factored into the assessment of AS severity to mitigate for potential underestimation.
Keyphrases
- aortic stenosis
- aortic valve
- ejection fraction
- contrast enhanced
- left ventricular
- magnetic resonance
- transcatheter aortic valve replacement
- aortic valve replacement
- transcatheter aortic valve implantation
- end stage renal disease
- newly diagnosed
- big data
- chronic kidney disease
- heart failure
- machine learning
- electronic health record
- artificial intelligence
- liquid chromatography tandem mass spectrometry
- molecular dynamics
- mass spectrometry
- atrial fibrillation
- patient reported outcomes
- deep learning
- ms ms
- data analysis
- cardiac resynchronization therapy