Nkomo, Vuyisile T.

Abstract Background/Introduction Close monitoring of aortic stenosis (AS) by follow-up echocardiography is recommended by all Cardiology and Imaging Societies’ guidelines. Whether these guidelines are strictly followed is unknown. Purpose We aimed to describe our institution’s practice patterns for echocardiographic monitoring in patients with aortic sclerosis (AScl) and AS of any severity. Methods Adult patients residing in our institution’s county with an echocardiographic diagnosis of AScl or AS between 01/2005-01/2022 were identified and classified into 4 groups: AScl, mild AS, moderate AS, or severe AS, at each echocardiogram during the study timeframe. Kaplan Meier analyses were used to evaluate the composite outcome, the occurrence of follow-up echocardiogram or death. Patients were censored at the time of aortic valve replacement/repair, heart transplant, or last clinical follow-up. Guideline follow-up was considered appropriate when the primary outcome occurred by 5 years (AScl/mild AS), 2 years (moderate AS), and 1 year (severe AS). Results A total of 23,726 echocardiograms from 9,578 unique patients were included. At index echocardiogram, median patient age was 74 years (IQR 65-82) and 4,806 (50.2%) were women. AScl was observed in 7,358 (76.8%) cases, mild AS in 1,442 (15.1%) cases, moderate AS in 479 (5%), and severe AS in 301 (3.1%) cases. Rates of composite outcome achievement by the end of the guideline-recommended interval were 81%, 90%, 80%, and 72% in AScl, mild, moderate, and severe AS, respectively. Rates for men were 83%, 92%, 82%, and 75% in these groups, while rates for women were 78%, 88%, 78%, and 68%, respectively (Figure 1). Follow-up rates were similar before and after 2012 (when transcatheter aortic valve replacement was approved for treatment of severe AS in high-risk surgical patients in the USA). Follow-up rates were higher in patients managed by cardiovascular providers compared to non-cardiovascular providers (Figure 2). Conclusion Depending on disease severity, between one fourth and one tenth of patients remained alive and unfollowed at the end of their guideline-recommended surveillance interval. There is significant variability in echocardiogram monitoring based on sex and referring provider specialty. Figure 1 Figure 2

Abstract Background Transthoracic echocardiography is the primary modality used for the assessment of the pericardial space. Guidelines recommend semi-qualitative assessment of the size of a pericardial effusion with characterization as trace, small, moderate or large. The reproducibility and association of this characterization is variable. Whether simple 2D-based quantitative measures of effusion size better associate with pericardial volumes is unclear. An accurate measure of pericardial volume would be helpful for tracking patients over time. Purpose To test whether 2D-based measures of the pericardial space could accurately predict pericardial volumes. Methods We retrospectively assessed a series of echos performed immediately prior to pericardiocentesis. 2D-based area tracings from the parasternal long and short axis at the papillary muscle level as well as 2D volumetric tracings from the apical 4 chamber view using the Simpson's method were tested with the operator blinded to the true pericardial volume (recorded at pericardiocentesis). Patients who underwent pericardiocentesis in setting of acute perforation were excluded as were patients where pericardiocentesis was unsuccessful or incomplete. Pericardial fluid area or volume was calculated by taking the difference between the measures obtained by tracing the epicardial border of the heart and pericardium (figure 1). Results The median pericardiocentesis (n=118) fluid volume was 500 mL (IQR 350 – 750 mL) with a range, 95–2300 mL. The pericardial fluid was serous (22%), sero-sanguineous (37%) and sanguineous in 41%. The effusion was malignant in 24 cases and due to inflammation in 42 cases. Pericardial area traces from either the parasternal short (r=0.56, p<.0001) or long axis (r=0.62, p<.0001) correlated modestly with measured pericardial volume. The average volume estimated echocardiographically by the Simpson’s method was 580 ± 359 mL (range, 85.8–2419 mL). There was stronger linear correlation between echocardiographic (apical 4-chamber measurement) and pericardiocentesis-derived volumes (r=0.92, p < 0.0001; figure 2A). Etiology of the pericardial effusion was not associated with estimates of pericardial volumes. There was a large overlap in pericardial volume amongst the reading physician qualitative grading of effusion size (figure 2B). Categorization of pericardial effusion size was improved when based on volumetric estimates (Kappa 0.65) rather than physician estimates (Kappa 0.32; Figure 2B). Variation between measured pericardial volume and actual pericardial volume was most related to the quality of the image and the likely extent to which the pericardial fluid was not entirely captured in the image window. Conclusion Two-dimensional transthoracic echocardiography using biplane Simpson’s method of disks can simply and reasonably accurately estimate the pericardial effusion volume. This technique may add value in the serial assessment of pericardial effusions. Figure 2

Abstract Background/Introduction Tricuspid valve regurgitation (TR) is a common valvular disease associated with increased mortality. There is a need for tools to assess the interaction between the pulmonary artery (PA) circulation and the right ventricle (RV) in patients with TR and to investigate their association with outcomes. Various echo parameters have emerged that assess RV-PA coupling, including the ratio of TAPSE to RV systolic pressure (RVSP) and the PA pulsatility index (PAPi). The effective PA elastance (PA Ea) is a composite measure of RV afterload that refers to the measure of the pulmonary vascular load that the RV must overcome to eject blood into the PA. PA Ea is simple to estimate by echo and found to be an independent haemodynamic risk measure in various left heart and pulmonary hypertension (PH) diseases. Whether PA Ea discriminates risk in unselected patients with significant TR and how it compares to other measures of RV-PA coupling is untested. Purpose To ascertain the prognostic value of PA Ea in patients with TR. Methods In consecutive patients with a first diagnosis of ≥ moderate TR (regardless of aetiology), we compared all-cause mortality at five years based on the PA Ea (defined as the RVSP/stroke volume as measured by transthoracic echocardiography). As stroke volume was measured by Doppler at the left ventricular (LV) outflow tract, patients with > moderate aortic valve regurgitation were excluded. The Tricuspid Regurgitation Impact on Outcomes (TRIO) score was calculated as previously described. PA Ea was separated into 4 groups for comparison based on the separation of quartiles of PA Ea rounded to one decimal place. Results In the 13,608 patients studied, PA Ea could be calculated in 12,682 patients (94.4%). The median PA Ea was 0.68 mmHg/mL (IQR 0.50, 0.92). Increasing levels of PA Ea were associated with clinical comorbidities including heart failure, liver and kidney disease and clinical markers of risk such as the TRIO score. Increasing levels of PA Ea were also associated with larger RVs, worse RV systolic function, higher NT-pro BNP levels, and greater degrees of right heart failure (Table). Each quartile of PA Ea was associated with a significant increase in all-cause mortality (Figure). After adjusting for age and sex, PA Ea was associated with higher risk of death (HR 2.41 (2.28-2.56); p<.0001). While worsening degrees of PA Ea correlated with both declining levels of TAPSE/PASP and PAPi (Table), PA Ea was independently predictive of outcome in a combined model: PA Ea HR 1.65 (1.51-1.80, Chi-squ 120, p<.0001); PAPi HR 0.84 (0.80-0.89, Chi-squ 48, p<.0001) and TAPSE/PASP HR 0.32 (017-0.60, Chi-squ 12, p=.0004). Conclusion(s) In patients with significant TR, PA Ea is highly feasible and higher PA Ea is progressively associated with RV dysfunction, right heart failure, and worse survival. Incorporating PA Ea into the routine echo assessment may help stratify disease severity in patients with significant TR. Table Assoc. of PA Ea with mortality in TR

Abstract Aims Pulmonary regurgitation (PR) after reparative intervention for congenital heart disease has been studied extensively. However, the burden, distribution of causes, and outcome of PR in adults is unknown. The study aimed to evaluate the prevalence, types, and outcomes of moderate/severe PR in adults in the community setting. Methods and results A total of 398 adult residents of Olmsted County who had clinically indicated echocardiography 2004–2023 at Mayo Clinic, Rochester, and had moderate or severe PR were identified retrospectively. The median age was 77 years, 48% were females, and 61 (51%) had severe PR. The age- and sex-adjusted US prevalence was 0.11% (vs. 0.67% for ≥moderate tricuspid regurgitation). Moderate/severe PR was due to pulmonary hypertension in 77%, congenital/iatrogenic in 11%, primary pulmonary valve disease in 2% (88% due to carcinoid), and idiopathic isolated in 10%. In contrast, severe PR was due to congenital/iatrogenic disease in 52%, pulmonary hypertension in 39%, primary PR in 5%, and isolated idiopathic in 3%. The all-cause mortality rate per 100 person-year was 73 in primary (mostly carcinoid) PR, 16 in pulmonary hypertension–related PR (not different vs. propensity-matched patients without PR), and 6 in isolated idiopathic PR (not different vs. matched patients without PR). Conclusion Moderate or severe PR had a lower prevalence vs. TR. The most frequent cause was pulmonary hypertension for ≥moderate PR and congenital/iatrogenic for severe PR. Mortality in patients with acquired ≥moderate PR appeared to be related to the underlying cause, with no excess mortality compared with matched patients without PR. Whether specifically severe PR confers excess mortality requires future investigation.

Background: Atrial functional mitral regurgitation (AFMR) constitutes ~25% of ≥moderate MR and has been associated with a high prevalence and incidence of HFpEF. Transcatheter edge-to-edge repair (TEER) has shown effectiveness in improving symptoms in AFMR, but its impact on mortality and HF hospitalizations is unknown. Objective: Evaluate rates of mortality and HF hospitalizations in patients with ≥moderate AFMR treated with TEER and compare them to conservative management. Methods: Consecutive adults with ≥moderate AFMR (functional MR with left atrial enlargement, ejection fraction≥50%, and absent >mild left ventricular enlargement) were identified retrospectively. Ecxlusion criteria were previous cardiac surgery, ≥moderate aortic regurgitation/stenosis, infiltrative/hypertrophic cardiomyopathy, regional wall motion abnormalities or malignancy. Propensity score matching was performed (1:1 ratio) between patients treated with TEER and patients treated conservatively based on age, sex, EuroScore II, effective regurgitant orifice area, and the integrative MR severity. To ensure similar technique in evaluation in the 2 groups, variables were obtained from the closest transthoracic echocardiogram before TEER in the TEER group [median 65 (IQR 29-111) days]. Results: Overall, 46 patients with ≥moderate AFMR treated by TEER and 46 treated conservatively were included, Table 1 . Patients undergoing TEER had more frequent atrial fibrillation and NYHA class ≥III. MR improved to ≤moderate in 93% of patients undergoing TEER on procedural transesophageal echocardiography, Figure 1 . On 1–3-month post-TEER follow-up, 64% had NYHA class I/II (vs 33% pre-TEER), Figure 1 . Over median 2.2 (IQR 1.2-3.1) years, 32 patients died (rate 13%/year in each group, log-rank p=0.85), Figure 2 . When adjusted for baseline NYHA, rates of HF hospitalizations were not different between the groups (Wald-test p-value=0.48). Residual ≥moderate AFMR in the TEER group was not associated with mortality (log-rank p=0.83), but ≥1 class improvement of NYHA in patients with baseline NYHA >1 was associated with decreased mortality, Figure 2 . Conclusion: MR severity and NYHA class improved with TEER for AFMR, and improved NYHA class was associated with decreased mortality. However, the association of TEER with decreased risk of mortality or HF hospitalization remains unproven, and larger randomized studies are needed to evaluate the potential role of TEER on these outcomes in AFMR.

Background: Aortic regurgitation (AR) is a prevalent valve disease with a long latent period to symptoms. Recent data has suggested the role of novel markers of myocardial overload in assessing onset of decompensation. Method: We sought to evaluate the role of unsupervised cluster analyses in identifying different clinical clusters, including clinical status, and a large number of echocardiographic variables including left ventricular (LV) volumes, and their association with mortality. Patients with ≥moderate-severe chronic AR identified using echocardiography at Mayo Clinic, Rochester were retrospectively analyzed. Primary outcome was all-cause mortality censored at aortic valve surgery/last follow-up. Uniform Manifold Approximation and Projection (UMAP) with K -means algorithm was used to cluster patients using clinical and, echocardiographic variables at the time of presentation. Missing data were imputed with the Multiple Imputation by Chained Equations (MICE) method. A supervised approach trained on the training set was used to find cluster membership in a hold-out validation set. Log-rank tests were used to assess differences in mortality rates between the clusters, both in the training and validation sets. Results: Three distinct clusters were identified among 1100 patients (log-rank P for survival <0.001). Cluster 1 (n=337), which included younger males with severe AR but fewer symptoms, showed the best survival, 75.6% (69.5, 82.3). Cluster 2 (n=235), older and more females with elevated filling pressures, showed intermediate survival of 64.2 % (56.8, 72.5). Cluster 3 (n=253), characterized by severe symptomatic AR, demonstrated the lowest survival of 45.3 % (34.4, 59.8) at 5 years. Similar clusters were formed in the internal validation cohort. Conclusion: Distinct clusters with variable echocardiographic features and mortality differences exist within patients with chronic ≥moderate-severe AR. Recognizing these clusters can refine individual risk stratification and clinical decision-making after verification in future prospective studies.

Background: Optimum timing of surgery for severe primary mitral regurgitation (MR) particularly in the absence of significant symptoms or echo evidence of LV impairment remains unclear. Other modalities of assessment include cardiopulmonary exercise testing (CPET) and novel echo measurements, such as LV global longitudinal strain (LVGLS). We sought to evaluate whether pre-op CPET or LVGLS are associated with survival after surgery. Methods: We identified consecutive patients who had surgery for severe primary MR between 2007 and 2017 and had pre-op CPET. Clinical and mortality data were collected from chart review and our institutional database. LVGLS was retrospectively collected by a single person blinded to patient outcomes. Primary outcome was post surgery all cause death, and we used univariable analysis to identify variables associated with all cause death. Results: We included 176 patients with median age 63 (IQR 51, 71) years, 63 patients (35.8%) were female and 31 patients (14.8%) had a history of atrial fibrillation. 165 patients (93.8%) had mitral repair, 18 (10.2%) had concomitant CABG, 22 (12.5%) had concomitant ablation procedure and 14 (8.0%) had concomitant tricuspid procedure. 114 patients (64.8%) were in NYHA Class I and 56 (31.8%) were in NYHA Class II. There was no operative mortality. Median % predicted peak VO2 (ppVO2) was 89 (74, 101), median ventilatory equivalent of carbon dioxide (VE/VCO2) was 28.0 (25.7, 31.0) l/min/l/min and median respiratory exchange ratio was 1.2 (1.1, 1.2). 73 patients (41.5%) had abnormal CPET (defined as ppVO2<85%). Median LVEF was 65 (60, 68) %, median LVESD was 35 (32, 38) mm and median LVGLS was 18.5 (16.6, 20.3) %. 45 patients (25.9%) had abnormal LVEF (defined as ≤ 60%), 11 patients (6.7%) had abnormal LVESD (defined as ≥45mm) and 35 patients (20.8%) had abnormal LVGLS (defined as <16%). At a median follow up of 10.2 (6.8, 13.2) years, there were 19 (10.8%) deaths. In the univariate analysis, age at surgery (HR 1.12, p<0.001), LVESD (HR 1.11, p=0.009), LVGLS (HR 1.11, p=0.013) and VE/VCO2 (HR 1.08, p=0.044) were associated with all cause mortality. Conclusion: A significant proportion of patients with no or mild symptoms exhibit echocardiographic evidence of LV impairment when having surgery for severe primary MR. CPET parameters such as VE/VCO2 and novel echocardiographic measurements such as LVGLS may predict risk of long term mortality and potentially inform timing of surgery in these patients.

Abstract Aims Aortic stenosis (AS) is a common and progressive disease, which, if left untreated, results in increased morbidity and mortality. Monitoring and follow-up care can be challenging due to significant variability in disease progression. This study aimed to develop machine learning models to predict the risks of disease progression and mortality in patients with mild AS. Methods and results A comprehensive database including 9611 patients with serial transthoracic echocardiograms was collected from a single institution across three clinical sites. The data set included parameters from echocardiograms, electrocardiograms, laboratory values, and diagnosis codes. Data from a single clinical site were preserved as an independent test group. Machine learning models were trained to identify progression to severe stenosis and all-cause mortality and tested in their performance for endpoints at 2 and 5 years. In the independent test group, the AS progression model differentiated those with progression to severe AS within 2 and 5 years with an area under the curve (AUC) of 0.86 for both. The feature of greatest importance was aortic valve mean gradient, followed by other valve haemodynamic measurements including valve area and dimensionless index. The mortality model identified those with mortality within 2 and 5 years with an AUC of 0.84 and 0.87, respectively. Smaller reduced-input validation models had similarly robust findings. Conclusion Machine learning models can be used in patients with mild AS to identify those at high risk of disease progression and mortality. Implementation of such models may facilitate real-time, patient-specific follow-up recommendations.