mPAP/CO Slope and Oxygen Uptake Add Prognostic Value in Aortic Stenosis.

BACKGROUND: Recent guidelines redefined exercise pulmonary hypertension as a mean pulmonary artery pressure/cardiac output (mPAP/CO) slope >3 mm Hg·L-1·min-1. A peak systolic pulmonary artery pressure >60 mm Hg during exercise has been associated with an increased risk of cardiovascular death, heart failure rehospitalization, and aortic valve replacement in aortic valve stenosis. The prognostic value of the mPAP/CO slope in aortic valve stenosis remains unknown. METHODS: In this prospective cohort study, consecutive patients (n=143; age, 73±11 years) with an aortic valve area ≤1.5 cm2 underwent cardiopulmonary exercise testing with echocardiography. They were subsequently evaluated for the occurrence of cardiovascular events (ie, cardiovascular death, heart failure hospitalization, new-onset atrial fibrillation, and aortic valve replacement) during a follow-up period of 1 year. Findings were externally validated (validation cohort, n=141). RESULTS: One cardiovascular death, 32 aortic valve replacements, 9 new-onset atrial fibrillation episodes, and 4 heart failure hospitalizations occurred in the derivation cohort, whereas 5 cardiovascular deaths, 32 aortic valve replacements, 1 new-onset atrial fibrillation episode, and 10 heart failure hospitalizations were observed in the validation cohort. Peak aortic velocity (odds ratio [OR] per SD, 1.48; P=0.036), indexed left atrial volume (OR per SD, 2.15; P=0.001), E/e' at rest (OR per SD, 1.61; P=0.012), mPAP/CO slope (OR per SD, 2.01; P=0.002), and age-, sex-, and height-based predicted peak exercise oxygen uptake (OR per SD, 0.59; P=0.007) were independently associated with cardiovascular events at 1 year, whereas peak systolic pulmonary artery pressure was not (OR per SD, 1.28; P=0.219). Peak Vo2 (percent) and mPAP/CO slope provided incremental prognostic value in addition to indexed left atrial volume and aortic valve area (P<0.001). These results were confirmed in the validation cohort. CONCLUSIONS: In moderate and severe aortic valve stenosis, mPAP/CO slope and percent-predicted peak Vo2 were independent predictors of cardiovascular events, whereas peak systolic pulmonary artery pressure was not. In addition to aortic valve area and indexed left atrial volume, percent-predicted peak Vo2 and mPAP/CO slope cumulatively improved risk stratification.

The Oxygen Cascade According to HFpEF Likelihood: A Focus on Sex Differences.

Background: Women are at greater risk for heart failure with preserved ejection fraction (HFpEF). Objectives: The aim of the study was to compare sex differences in the pathophysiology of exertional breathlessness in patients with high vs low HFpEF likelihood. Methods: This cohort study evaluated consecutive patients (n = 1,936) with unexplained dyspnea using cardiopulmonary exercise testing and simultaneous echocardiography and quantified peak oxygen uptake (peak VO2) and its determinants. HFpEF was considered likely when the H2FPEF or HFA-PEFF score was ≥6 or ≥5, respectively. Sex differences were evaluated with the Student's t-test or Mann-Whitney U test and determinants of exercise capacity with a multivariable linear regression. Results: The cohort included 1,963 patients (49% women and 28% [n = 555] with a high HFpEF likelihood). HFpEF likelihood did not impact the magnitude of sex differences in peak VO2 and its determinants. Overall, women had lower peak VO2 (mean difference -4.4 mL/kg/min [95% CI: -3.7 to -5.1 mL/kg/min]) secondary to a reduced O2 delivery (-0.5 L/min [95% CI: -0.4 to -0.6 L/min]) and less oxygen extraction (-2.9 mL/dL [95% CI: -2.5 to -3.2 mL/dL]). Reduced O2 delivery was due to lower hemoglobin (-1.2 g/dL [95% CI: -0.9 to -1.5 g/dL]) and smaller stroke volume (-15 mL [95% CI: -14 to -17 mL]). Women demonstrated increased mean pulmonary artery pressure/cardiac output slope (+0.5 mm Hg/L/min [95% CI: 0.3-0.7 mm Hg/L/min]) and left ventricular ejection fraction (+1% [95% CI: 1%-2%]), while they had smaller left ventricular end-diastolic volumes (-9 mL/m2 [95% CI: -8 to -11 mL/m2]) and mass (-12 g/m2 [95% CI: -9 to -14 g/m2]) and more often iron deficiency (55% vs 33%; P < 0.001). Conclusions: Women with unexplained dyspnea had significantly lower peak VO2, regardless of HFpEF likelihood, attributed to both lower peak exercise O2 delivery and extraction. This suggests that physiologic sex differences, and not HFpEF likelihood, are an important factor contributing to functional limitations in females with exertional breathlessness.

Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.

Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials and Methods This retrospective study included patients with MVP without hemodynamically significant mitral regurgitation or left ventricular (LV) dysfunction undergoing late gadolinium enhancement (LGE) cardiac MRI between October 2007 and June 2020 in 15 European tertiary centers. The study end point was a composite of sustained ventricular tachycardia, (aborted) sudden cardiac death, or unexplained syncope. Unsupervised data-driven hierarchical k-mean algorithm was utilized to identify phenotypic clusters. The association between clusters and the study end point was assessed by Cox proportional hazards model. Results A total of 474 patients (mean age, 47 years ± 16 [SD]; 244 female, 230 male) with two phenotypic clusters were identified. Patients in cluster 2 (199 of 474, 42%) had more severe mitral valve degeneration (ie, bileaflet MVP and leaflet displacement), left and right heart chamber remodeling, and myocardial fibrosis as assessed with LGE cardiac MRI than those in cluster 1. Demographic and clinical features (ie, symptoms, arrhythmias at Holter monitoring) had negligible contribution in differentiating the two clusters. Compared with cluster 1, the risk of developing the study end point over a median follow-up of 39 months was significantly higher in cluster 2 patients (hazard ratio: 3.79 [95% CI: 1.19, 12.12], P = .02) after adjustment for LGE extent. Conclusion Among patients with MVP without significant mitral regurgitation or LV dysfunction, unsupervised machine learning enabled the identification of two phenotypic clusters with distinct arrhythmic outcomes based primarily on cardiac MRI features. These results encourage the use of in-depth imaging-based phenotyping for implementing arrhythmic risk prediction in MVP. Keywords: MR Imaging, Cardiac, Cardiac MRI, Mitral Valve Prolapse, Cluster Analysis, Ventricular Arrhythmia, Sudden Cardiac Death, Unsupervised Machine Learning Supplemental material is available for this article. © RSNA, 2024.