Devereux, Richard B.

Background Right ventricular (RV) maladaptation to elevated pulmonary afterload is the primary determinant of outcomes in pulmonary artery (PA) hypertension; however, the pathobiological mechanisms underlying RV decompensation remain poorly understood. Methods We performed global untargeted metabolomics on plasma from 55 patients who underwent gold‐standard RV‐PA coupling measurements using multibeat pressure volume loop assessment in a single‐center cohort and from 1027 patients with coupling surrogate measurements in a larger multicenter cohort, the PVDOMICS (Pulmonary Vascular Disease Phenomics) study. Age and sex‐adjusted linear regression was performed to identify associations between metabolites and coupling metrics. Additionally, we performed a metabolic flux analysis using gene expression data from RV tissue in an independent cohort of 32 patients. Partial least squares–discriminant analysis was used to identify metabolites and reactions characteristic of the decompensated RV. Results RV‐PA coupling was negatively associated with tricarboxylic acid (TCA) cycle intermediate levels. Specifically, plasma α‐ketoglutarate and fumarate were significantly associated with all coupling metrics in both cohorts. Metabolic flux analysis indicated that decompensated RVs exhibited aberrant TCA cycle activity, including reduced acetyl coenzyme A entry and increased lactate elimination, suggesting a shift from the TCA cycle toward glycolysis at the RV tissue level. Conclusions We identify an association between circulating TCA cycle intermediate levels and RV‐PA uncoupling in 2 independent cohorts, and dysregulated TCA cycle metabolism in decompensated PA hypertension RVs, suggesting that aberrant TCA cycle metabolism could represent a hallmark of RV maladaptation in PA hypertension. Further study of this pathway is warranted to develop novel biomarkers of RV function or RV‐targeted therapies.

Abstract Background and Aims Classification and risk stratification in aortic (AR), mitral (MR), and tricuspid regurgitation (TR) remains a significant clinical challenge. This study aimed to develop an artificial intelligence (AI) system to assess valvular regurgitation and stratify MR-progression risk. Methods Using transthoracic echocardiograms (TTEs) at two sites (internal development/test, external test), the DELINEATE-Regurgitation system was developed to classify AR, MR, and TR severity using colour Doppler videos. Methods of summating video-level classifications into study-level predictions were tested, comparing single-view with multiview approaches integrating predictions across multiple videos. Model agreement with cardiologists was assessed by weighted kappa. A separate AI system (DELINEATE-MR-Progression) analysing colour Doppler videos was developed to predict which patients with mild, mild–moderate, and moderate MR were most likely to progress to moderate–severe or severe MR with analysis by Kaplan–Meier and Cox proportional hazards models. Results A total of 71 660 TTEs with 1 203 980 colour Doppler videos were included. The weighted kappa in internal/external test sets for regurgitation classification was 0.81/0.76 for AR, 0.76/0.72 for MR, and 0.73/0.64 for TR using a multiview approach taking all colour Doppler videos in a study, demonstrating substantial agreement with cardiologist interpretation with superiority of multiview over single view approaches. In the progression analysis, the AI score stratified MR-progression risk even when controlled for clinical factors known to be associated with MR progression [internal test set hazard ratio 4.1 (95% confidence interval 2.5–6.6)]. Conclusions An AI system can accurately classify AR, MR, and TR and predict MR progression beyond currently known risk factors.

Abstract This International Consensus Classification and Nomenclature for the congenital bicuspid aortic valve condition recognizes 3 types of bicuspid valves: 1. The fused type (right-left cusp fusion, right-non-coronary cusp fusion and left-non-coronary cusp fusion phenotypes); 2. The 2-sinus type (latero-lateral and antero-posterior phenotypes); and 3. The partial-fusion (forme fruste) type. The presence of raphe and the symmetry of the fused type phenotypes are critical aspects to describe. The International Consensus also recognizes 3 types of bicuspid valve-associated aortopathy: 1. The ascending phenotype; 2. The root phenotype; and 3. Extended phenotypes.

Abstract This International evidence-based nomenclature and classification consensus on the congenital bicuspid aortic valve and its aortopathy recognizes 3 types of bicuspid aortic valve: 1. Fused type, with 3 phenotypes: right-left cusp fusion, right-non cusp fusion and left-non cusp fusion; 2. 2-sinus type with 2 phenotypes: Latero-lateral and antero-posterior; and 3. Partial-fusion or forme fruste. This consensus recognizes 3 bicuspid-aortopathy types: 1. Ascending phenotype; root phenotype; and 3. extended phenotypes.

Abstract Purpose Echocardiography (echo) is widely used for right ventricular (RV) assessment. Current techniques for RV evaluation require additional imaging and manual analysis; machine learning (ML) approaches have the potential to provide efficient, fully automated quantification of RV function. Methods An automated ML model was developed to track the tricuspid annulus on echo using a convolutional neural network approach. The model was trained using 7791 image frames, and automated linear and circumferential indices quantifying annular displacement were generated. Automated indices were compared to an independent reference of cardiac magnetic resonance (CMR) defined RV dysfunction (RVEF < 50%). Results A total of 101 patients prospectively underwent echo and CMR: Fully automated annular tracking was uniformly successful; analyses entailed minimal processing time (<1 second for all) and no user editing. Findings demonstrate all automated annular shortening indices to be lower among patients with CMR‐quantified RV dysfunction (all P < .001). Magnitude of ML annular displacement decreased stepwise in relation to population‐based tertiles of TAPSE, with similar results when ML analyses were localized to the septal or lateral annulus (all P ≤ .001). Automated segmentation techniques provided good diagnostic performance (AUC 0.69–0.73) in relation to CMR reference and compared to conventional RV indices (TAPSE and S ′) with high negative predictive value (NPV 84%–87% vs 83%–88%). Reproducibility was higher for ML algorithm as compared to manual segmentation with zero inter‐ and intra‐observer variability and ICC 1.0 (manual ICC: 0.87–0.91). Conclusions This study provides an initial validation of a deep learning system for RV assessment using automated tracking of the tricuspid annulus.

Objective Cardiac changes of hypertensive pregnancy include left ventricular hypertrophy (LVH) and diastolic dysfunction. These are thought to regress postpartum. We hypothesised that women with a history of hypertensive pregnancy would have altered LV geometry and function when compared with women with only normotensive pregnancies. Methods In this cohort study, we analysed echocardiograms of 2637 women who participated in the Family Blood Pressure Program. We compared LV mass and function in women with hypertensive pregnancies with those with normotensive pregnancies. Results Women were evaluated at a mean age of 56 years: 427 (16%) had at least one hypertensive pregnancy; 2210 (84%) had normotensive pregnancies. Compared with women with normotensive pregnancies, women with hypertensive pregnancy had a greater risk of LVH (OR: 1.42; 95% CI 1.01 to 1.99, p=0.05), after adjusting for age, race, research network of the Family Blood Pressure Program, education, parity, BMI, hypertension and diabetes. When duration of hypertension was taken into account, this relationship was no longer significant (OR: 1.19; CI 0.08 to 1.78, p=0.38). Women with hypertensive pregnancies also had greater left atrial size and lower mitral E/A ratio after adjusting for demographic variables. The prevalence of systolic dysfunction was similar between the groups. Conclusions A history of hypertensive pregnancy is associated with LVH after adjusting for risk factors; this might be explained by longer duration of hypertension. This finding supports current guidelines recommending surveillance of women following a hypertensive pregnancy, and sets the stage for longitudinal echocardiographic studies to further elucidate progression of LV geometry and function after pregnancy. Clinical trial registrations GENOA- NCT00005269; HyperGEN- NCT00005267; Sapphire- NCT00005270; GenNet- NCT00005268.

Background— There are few published data on the incidence of fatal and nonfatal stroke in American Indians. The aims of this observational study were to determine the incidence of stroke and to elucidate stroke risk factors among American Indians. Methods and Results— This report is based on 4549 participants aged 45 to 74 years at enrollment in the Strong Heart Study, the largest longitudinal, population-based study of cardiovascular disease and its risk factors in a diverse group of American Indians. At baseline examination in 1989 to 1992, 42 participants (age- and sex-adjusted prevalence proportion 1132/100 000, adjusted to the age and sex distribution of the US adult population in 1990) had prevalent stroke. Through December 2004, 306 (6.8%) of 4507 participants without prior stroke suffered a first stroke at a mean age of 66.5 years. The age- and sex-adjusted incidence was 679/100 000 person-years. Nonhemorrhagic cerebral infarction occurred in 86% of participants with incident strokes; 14% had hemorrhagic stroke. The overall age-adjusted 30-day case-fatality rate from first stroke was 18%, with a 1-year case-fatality rate of 32%. Age, diastolic blood pressure, fasting glucose, hemoglobin A 1c, smoking, albuminuria, hypertension, prehypertension, and diabetes mellitus were risk factors for incident stroke. Conclusions— Compared with US white and black populations, American Indians have a higher incidence of stroke. The case-fatality rate for first stroke is also higher in American Indians than in the US white or black population in the same age range. Our findings suggest that blood pressure and glucose control and smoking avoidance may be important avenues for stroke prevention in this population.

Background and Purpose— Mitral annular calcification (MAC) and aortic valve (AV) sclerosis have each been linked to cardiovascular disease. Whether MAC and AV sclerosis are risk factors for stroke independent of other echocardiographic or laboratory predictors has not been established. We evaluated the relationship between MAC, AV sclerosis, and first stroke events in a population-based cohort. Methods— Our study cohort consisted of 2723 American Indians participating in the Strong Heart Study who were free of prevalent cardiovascular disease. Participants underwent standardized clinical, echocardiographic, and laboratory evaluation, and incident stroke was ascertained using validated methods. Results— During a median follow-up of 7 years, 86 strokes occurred. Age- and sex-adjusted incidence rates of stroke were significantly increased for MAC (rate ratio [RR], 3.12; 95% CI, 1.77 to 5.25) but not for AV sclerosis (RR, 1.15; 95% CI, 0.45 to 2.49). MAC was also associated with a reduced time to first stroke events after adjustment for clinical variables and the inflammatory markers C-reactive protein and fibrinogen (hazard ratio [HR], 2.42; 95% CI, 1.39 to 4.21) or the echocardiographic covariates left ventricular hypertrophy and left atrial enlargement (HR, 1.89; 95% CI, 1.04 to 3.41). Individuals with and without AV sclerosis showed no significant difference in stroke-free survival in unadjusted analyses ( P =0.698). Crossing of the survival curves precluded multivariable analysis using Cox models. Conclusions— In this cohort of American Indians without clinical cardiovascular disease, the presence of MAC, but not AV sclerosis, proved to be a strong risk factor for incident stroke after extensive adjustment for other predictors. Individuals exhibiting MAC may benefit from aggressive risk factor modification, but this will require further investigation.