Scott, Christopher

Background Atrial fibrillation (AF) impacts management decisions in valvular heart disease but its significance in patients with chronic aortic regurgitation (AR) is not well established. Objectives To evaluate the prevalence and prognostic role of AF in patients with chronic, haemodynamically significant AR. Methods Adults with chronic ≥moderate-to-severe AR, from March 2004 to April 2019, were retrospectively identified. Those with acute AR, moderate or worse other valve disease or prior valve surgery were excluded. Patients with AF were identified based on 12-lead ECGs, 1-lead ECGs (showing AF for ≥30 s), or episodes recorded by implanted cardiac devices. Primary outcome was all-cause mortality. Cox regression models were used to assess associations with mortality: model 1 adjusted for age, symptoms (New York Heart Association class II–IV), Charlson Comorbidity Index, left ventricle (LV) end-systolic volume index and AF; model 2 added left atrial volume index and model 3 further added systolic pulmonary artery pressure. Results Of the 1006 included patients (age 59±18 years; 822 (82%) men), 446 (46%) had hypertension and 364 (36%) had a bicuspid aortic valve. AF was present in 161 (16%) patients at the time of ≥moderate-to-severe AR diagnosis. During a median follow-up of 1.6 years (IQR 0.2–6.2), AF was associated with an increased mortality risk in univariate and in all three multivariable models (HR 1.61 (95% CI 1.07 to 2.43), HR 2.21 (95% CI 1.31 to 3.72) and HR 2.06 (95% CI 1.21 to 3.52), respectively), including after propensity matching (HR 1.58 (95% CI 1.01 to 2.48)). Conclusions AF is present in one in six patients with chronic≥moderate-to-severe AR and is associated with an increased risk of mortality even after adjusting for measures of LV systolic and diastolic function. There is a need for future prospective studies to validate these findings and evaluate AF as a potential trigger for early surgery.

Background Tricuspid valve surgery is recommended for severe isolated tricuspid regurgitation (TR) if symptoms persist despite optimal medical therapy. The definition of optimal therapy for TR is unclear beyond managing underlying conditions. Diuretics are the primary treatment for volume retention in TR, but it is unknown whether a “safe diuretic dose” exists for conservative management. We sought to evaluate the association between diuretic dose and outcomes. Methods Adult patients with ≥moderate–severe isolated TR were retrospectively identified from echocardiographic reports. Clinical and echocardiographic data were extracted from electronic medical records and manually reviewed. The primary end point was all‐cause mortality. Loop diuretic doses were converted to furosemide equivalent and categorized into 4 groups: <40 mg, 40 to 79 mg, 80 to 159 mg, and ≥160 mg daily. Results Of 1302 patients (age 72±13 years, 60% female), 565 (43%) had moderate–severe TR and 737 (57%) had severe TR. Median follow‐up was 8.7 (1.4, 14.0) years. Comorbidities increased with higher diuretic doses. A linear relationship between diuretic dose and mortality was observed in spline‐curve analysis. Hazard ratios (and CIs) for mortality adjusted for age, sex, coronary disease, chronic kidney disease, mild pulmonary hypertension, and New York Heart Association III/IV symptoms were 1.21 (0.96–1.53) ( P =0.12) for <40 mg, 1.50 (1.23–1.82) ( P <0.001) for 40 to 79 mg, 1.86 (1.46–2.37) ( P <0.001) for 80 to 159 mg, and 2.90 (2.18–3.88) ( P <0.001) for ≥160 mg furosemide equivalent. Any diuretic dose was associated with significant symptoms (New York Heart Association III–IV), with more patients experiencing symptoms at higher doses. Conclusion A daily loop diuretic dose ≥40 mg furosemide equivalent is associated with increased mortality and greater symptom severity in patients with TR.

Three-dimensional radiomic analysis of digital breast tomosynthesis outperformed two-dimensional measures in breast cancer risk assessment.

Abstract Background and Aims Accurate differentiation of cardiac amyloidosis (CA) from phenotypic mimics remains challenging using current clinical and echocardiographic techniques. The accuracy of a novel artificial intelligence (AI) screening algorithm for echocardiography-based CA detection was assessed. Methods Utilizing a multisite, multiethnic dataset (n = 2612, 52% CA), a convolutional neural network was trained to differentiate CA from phenotypic controls using transthoracic apical four-chamber video clips. External validation was conducted globally across 18 sites including 597 CA cases and 2122 controls. Classification accuracy was assessed on the entire external validation dataset, and subgroup analyses were performed both on technetium pyrophosphate scintigraphy referrals, and individuals matched for age, sex, and wall thickness. Model accuracy was also compared with the transthyretin CA score and the increased wall thickness score within a subset of older heart failure with preserved ejection fraction patients with increased wall thickness. Results Cardiac amyloidosis patients and controls displayed similar age, sex, race, and comorbidities. After the removal of uncertain AI predictions (13%), model discrimination and classification were excellent for the entire external validation dataset [area under the receiver operating characteristic curve (AUROC) 0.93, sensitivity 85%, specificity 93%], irrespective of CA subtype (sensitivity: light-chain = 84%, wild-type transthyretin = 85%, and hereditary transthyretin = 86%). Performance was maintained in subgroup analysis in patients clinically referred for technetium pyrophosphate scintigraphy imaging (AUROC 0.86, sensitivity 77%, specificity 86%) and matched patients (AUROC 0.92, sensitivity 84%, specificity 91%). The AI model (AUROC 0.93) also outperformed transthyretin CA score (AUROC 0.73) and increased wall thickness (AUROC 0.80) scores. Conclusions This AI screening model—using only an apical four-chamber view—effectively differentiated CA from other causes of increased left ventricular wall thickness.

Abstract Aims Tricuspid valve regurgitation (TR) is common and associated with increased mortality. The interaction between the pulmonary artery (PA) circulation and the right ventricle (RV) and association with outcomes is incompletely understood. The effective PA elastance (PA Ea) is a composite measure of RV afterload that refers to the pulmonary vascular load that the RV must overcome to eject blood. Whether PA Ea discriminates mortality risk in unselected patients with significant TR is unknown. Methods and results In consecutive patients with ≥moderate TR, we compared all-cause mortality at 5 years based on the PA Ea (defined as the RV systolic pressure/stroke volume as measured by transthoracic echocardiography). In a total of 12 682 patients, the median PA Ea was 0.7 mm Hg/mL (interquartile range 0.5, 0.9). Increasing levels of PA Ea were associated with heart failure, liver and kidney disease, and clinical markers of risk such as the Tricuspid Regurgitation Impact on Outcomes score. Increasing levels of PA Ea were associated with larger RVs, worse RV systolic function, higher N-terminal pro-brain natriuretic peptide levels, and greater degrees of right heart failure. After adjusting for age and sex, PA Ea was associated with higher risk of death (hazard ratio 1.55 per 0.5 mm Hg/mL change of PA Ea; 95% confidence intervals 1.51–1.60; P &lt; 0.0001). In multivariable modelling incorporating available clinical variables, PA Ea was independently predictive of outcome compared with other indexes of RV–PA coupling. Conclusion In patients with significant TR, 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 risk.

Radiomic parenchymal phenotypes on mammograms were used to predict breast cancer risk among both Black and White women, notably for false-negative findings and symptomatic interval cancer.

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.

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.

BACKGROUND: Cardiorenal dysfunction with impaired cyclic GMP (cGMP) response is common in patients presenting with acute heart failure (HF). Type V phosphodiesterase (PDEV) is known to be upregulated in HF and may explain the dysfunction of renal response. The aim of this study was to determine whether B-type natriuretic peptide (BNP) alone or in combination with PDEV inhibition improves renal function and increases urinary sodium and cGMP excretion in acute HF. METHODS: This open-label study included 67 patients hospitalized with acute HF and renal dysfunction. Patients were randomized to standard care, low-dose intravenous BNP (0.005 µg/kg per minute), or combination BNP/PDEV inhibition with sildenafil (25 mg q12 hours) for 48 hours. The coprimary end points were the percent change in estimated glomerular filtration rate and blood urea nitrogen from baseline to 48 hours. RESULTS: Treatment with BNP and BNP/PDEV inhibitor significantly increased plasma cGMP at 24 hours (+25.6% [+9.8%, +84.7%] and +60.8% [+32.3%, +103.8%] for BNP and BNP/PDEV versus −13.5% [−29.1%, +14.2%] with standard care; P =0.001). However, there was no significant change in estimated glomerular filtration rate 0 (−10.8%, +12.7%) for standard care versus 0 (−15.3%, +11.8%) for the BNP group versus –8.8% (−14.3%, +8.3%) for the BNP/PDEV group ( P =0.60) or blood urea nitrogen −1.4% (−10.7%, +12.0%) for standard care versus –5.9% (−14.6%, +9.4%) for the BNP group versus +6.9% (−5.3%, +18.8%) for the BNP/PDEV group ( P =0.38) between groups. Hypotension was more common in the BNP/PDEV inhibitor group. CONCLUSIONS: BNP and combination BNP/PDEV inhibition increased plasma cGMP in patients with acute HF but did not improve renal function or urinary sodium/cGMP excretion. Our study does not support the use of intravenous low-dose BNP with or without PDEV inhibition to enhance renal function in patients admitted with acute HF. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT00972569.

Abstract Background Most breast biopsies are diagnosed as benign breast disease, with 1.5- to 4-fold increased breast cancer risk. Apart from pathologic diagnoses of atypical hyperplasia, few factors aid in breast cancer risk assessment of these patients. We assessed whether a 313–single nucleotide variation (formerly single-nucleotide polymorphism) polygenic risk score stratifies risk of benign breast disease patients. Methods We pooled data from 5 Breast Cancer Association Consortium case-control studies (mean age = 59.9 years), including 6706 participants with breast cancer and 8488 participants without breast cancer. Using logistic regression, we estimated breast cancer risk associations by self-reported benign breast disease history and strata of polygenic risk score, with median polygenic risk score category among women without benign breast disease as the referent. We assessed interactions and mediation of benign breast disease and polygenic risk score with breast cancer risk. Results Benign breast disease history was associated with increased breast cancer risk (odds ratio [OR] = 1.48, 95% confidence interval [CI] = 1.37 to 1.60; P &lt; .001). Polygenic risk score increased breast cancer risk, irrespective of benign breast disease history (Pinteraction = .48), with minimal evidence of mediation of either factor by the other. Women with benign breast disease and polygenic risk score in the highest tertile had more than twofold increased odds of breast cancer (OR = 2.73, 95% CI = 2.41 to 3.09), and those with benign breast disease and polygenic risk score in the lowest tertile experienced reduced breast cancer risk (OR = 0.79, 95% CI = 0.70 to 0.91) compared with the referent group. Women with benign breast disease and polygenic risk score in the highest decile had a 3.7-fold increase (95% CI = 3.00 to 4.61) compared with those with median polygenic risk score without benign breast disease. Conclusion Breast cancer risks are elevated among women with benign breast disease and increase progressively with polygenic risk score, suggesting that optimal combinations of these factors may improve risk stratification.