Prognostic importance of the transmitral pressure gradient in mitral annular calcification with associated mitral valve dysfunction.

AIMS: The aim of this study was to define the natural history of patients with mitral annular calcification (MAC)-related mitral valve dysfunction and to assess the prognostic importance of mean transmitral pressure gradient (MG) and impact of concomitant mitral regurgitation (MR). METHODS AND RESULTS: The institutional echocardiography database was examined from 2001 to 2019 for all patients with MAC and MG ≥3 mmHg. A total of 5754 patients were stratified by MG in low (3-5 mmHg, n = 3927), mid (5-10 mmHg, n = 1476), and high (≥10 mmHg, n = 351) gradient. The mean age was 78 ± 11 years, and 67% were female. MR was none/trace in 32%, mild in 42%, moderate in 23%, and severe in 3%. Primary outcome was all-cause mortality, and outcome models were adjusted for age, sex, and MAC-related risk factors (hypertension, diabetes, coronary artery disease, chronic kidney disease). Survival at 1, 5, and 10 years was 77%, 42%, and 18% in the low-gradient group; 73%, 38%, and 17% in the mid-gradient group; and 67%, 25%, and 11% in the high-gradient group, respectively (log-rank P < 0.001 between groups). MG was independently associated with mortality (adjusted HR 1.064 per 1 mmHg increase, 95% CI 1.049-1.080). MR severity was associated with mortality at low gradients (P < 0.001) but not at higher gradients (P = 0.166 and 0.372 in the mid- and high-gradient groups, respectively). CONCLUSION: In MAC-related mitral valve dysfunction, mean transmitral gradient is associated with increased mortality after adjustment for age, sex, and MAC-related risk factors. Concomitant MR is associated with excess mortality in low-gradient ranges (3-5 mmHg) but gradually loses prognostic importance at higher gradients, indicating prognostic utility of transmitral gradient in MAC regardless of MR severity.

Atrial Dysfunction in Significant Atrial Functional Mitral Regurgitation: Phenotypes and Prognostic Implications.

BACKGROUND: Atrial functional mitral regurgitation (AFMR) is associated with increased morbidity and mortality. Left atrial (LA) size and function in AFMR are poorly characterized. We aimed to assess LA function by reservoir strain (LASr) and estimated reservoir work (LAWr) and their impact on outcome in AFMR. METHODS: Consecutive patients at our institution between 2001 and 2019 and with significant (moderate or greater) AFMR were examined. LAWr was estimated as LASr×LA reservoir volume, and patients were grouped by median LASr and LAWr. Outcomes were all-cause death or heart failure hospitalizations. RESULTS: Five hundred fifteen AFMR patients were followed up for 5 (1-17) years. Patients had previously documented atrial fibrillation (AF; 37%), heart failure with preserved ejection fraction (HFpEF) without AF (24%), or both (HFpEF+AF, 39%). LA volume was largest in AF, while LA function parameters were most impaired in the combined HFpEF+AF group. During follow-up, patients with low LASr or LAWr had higher risk of death (P<0.001) and heart failure hospitalization (P<0.05). In Cox regression analyses, low LASr and LAWr, but not LA volume or left ventricular function, were associated with a higher risk of death (LASr: hazard ratio, 2.3 [95% CI, 1.6-3.5]; LAWr: hazard ratio, 3.4 [95% CI, 2.4-4.9]; both P<0.001) after adjustment for clinical and echocardiographic confounders. Low LASr and LAWr were strongest associated with death in HFpEF and HFpEF+AF. CONCLUSIONS: LA reservoir function but not LA size is a robust predictor of outcome in significant AFMR. This provides mechanistic insights into the interplay of functional versus geometric LA changes in AFMR.

Real-World Disparities in Remote Follow-Up of Cardiac Implantable Electronic Devices and Impact of the COVID-19 Pandemic: A Single-Center Experience.

Background Remote monitoring (RM) of cardiac implantable electronic devices has been shown to improve cardiovascular morbidity and mortality. To date, no studies have investigated disparities in use and delivery of RM. This study was performed to investigate if racial and socioeconomic disparities are present in cardiac implantable electronic device RM. Methods and Results This was a retrospective observational cohort study at a single tertiary care center in the United States. Patients who received a newly implanted cardiac implantable electronic device or device upgrade between January 2017 and December 2020 were included. Patients were classified as RM positive (RM+) when they underwent at least ≥2 remote interrogations per year during follow-up. Of all eligible patients, 2520 patients were included, and 34% were women. The mean follow-up was 25 months. Mean age was 71±14 years. Pacemakers constituted 66% of implanted devices, whereas 26% were implantable cardioverter-defibrillators, and 8% were cardiac resynchronization therapy with implantable cardioverter-defibrillators. Most patients (83%) were of European American ancestry. During follow-up, 66% of patients were classified as RM+. Patients who were younger, European American, college-educated, lived in a county with higher median household income, and were active on the hospital's patient portals were more frequently RM+. In an adjusted regression model, RM+ remained associated with the use of the online patient portal (odds ratio [OR], 2.889 [95% CI, 2.387-3.497]), presence of an implantable cardioverter-defibrillator (OR, 1.489 [95% CI, 1.207-1.835]), advanced college degree (OR, 1.244 [95% CI, 1.014-1.527]), and lastly with European American ancestry (P<0.05). During the years of the COVID-19 pandemic, the number of RM+ patients increased, whereas the association with ancestry and ethnicity decreased. Conclusions Despite being offered to all patients at implantation, significant disparities were present in cardiovascular implantable electronic device RM in this cohort. Disparities were partly reversed during COVID-19. Further studies are needed to examine health center- and patient-specific factors to overcome these barriers, and to facilitate equal opportunities to participate in RM.

Deep Learning-Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes.

BACKGROUND: Deep learning interpretation of echocardiographic images may facilitate automated assessment of cardiac structure and function. OBJECTIVES: We developed a deep learning model to interpret echocardiograms and examined the association of deep learning-derived echocardiographic measures with incident outcomes. METHODS: We trained and validated a 3-dimensional convolutional neural network model for echocardiographic view classification and quantification of left atrial dimension, left ventricular wall thickness, chamber diameter, and ejection fraction. The training sample comprised 64,028 echocardiograms (n = 27,135) from a retrospective multi-institutional ambulatory cardiology electronic health record sample. Validation was performed in a separate longitudinal primary care sample and an external health care system data set. Cox models evaluated the association of model-derived left heart measures with incident outcomes. RESULTS: Deep learning discriminated echocardiographic views (area under the receiver operating curve >0.97 for parasternal long axis, apical 4-chamber, and apical 2-chamber views vs human expert annotation) and quantified standard left heart measures (R2 range = 0.53 to 0.91 vs study report values). Model performance was similar in 2 external validation samples. Model-derived left heart measures predicted incident heart failure, atrial fibrillation, myocardial infarction, and death. A 1-SD lower model-left ventricular ejection fraction was associated with 43% greater risk of heart failure (HR: 1.43; 95% CI: 1.23-1.66) and 17% greater risk of death (HR: 1.17; 95% CI: 1.06-1.30). Similar results were observed for other model-derived left heart measures. CONCLUSIONS: Deep learning echocardiographic interpretation accurately quantified standard measures of left heart structure and function, which in turn were associated with future clinical outcomes. Deep learning may enable automated echocardiogram interpretation and disease prediction at scale.

Identifying high risk clinical phenogroups of pulmonary hypertension through a clustering analysis.

INTRODUCTION: The classification and management of pulmonary hypertension (PH) is challenging due to clinical heterogeneity of patients. We sought to identify distinct multimorbid phenogroups of patients with PH that are at particularly high-risk for adverse events. METHODS: A hospital-based cohort of patients referred for right heart catheterization between 2005-2016 with PH were included. Key exclusion criteria were shock, cardiac arrest, cardiac transplant, or valvular surgery. K-prototypes was used to cluster patients into phenogroups based on 12 clinical covariates. RESULTS: Among 5208 patients with mean age 64±12 years, 39% women, we identified 5 distinct multimorbid PH phenogroups with similar hemodynamic measures yet differing clinical outcomes: (1) "young men with obesity", (2) "women with hypertension", (3) "men with overweight", (4) "men with cardiometabolic and cardiovascular disease", and (5) "men with structural heart disease and atrial fibrillation." Over a median follow-up of 6.3 years, we observed 2182 deaths and 2002 major cardiovascular events (MACE). In age- and sex-adjusted analyses, phenogroups 4 and 5 had higher risk of MACE (HR 1.68, 95% CI 1.41-2.00 and HR 1.52, 95% CI 1.24-1.87, respectively, compared to the lowest risk phenogroup 1). Phenogroup 4 had the highest risk of mortality (HR 1.26, 95% CI 1.04-1.52, relative to phenogroup 1). CONCLUSIONS: Cluster-based analyses identify patients with PH and specific comorbid cardiometabolic and cardiovascular disease burden that are at highest risk for adverse clinical outcomes. Interestingly, cardiopulmonary hemodynamics were similar across phenogroups, highlighting the importance of multimorbidity on clinical trajectory. Further studies are needed to better understand comorbid heterogeneity among patients with PH.

Indexing Left Atrial Volumes: Alternative Indexing Methods Better Predict Outcomes in Overweight and Obese Populations.

BACKGROUND: Left atrial volume (LAV) is often adjusted for body surface area (BSA). In overweight individuals this may result in underestimation of left atrial (LA) dilation. The authors investigated whether alternative indexing techniques better predict mortality and cardiovascular (CV) events. OBJECTIVES: The purpose of this study was to evaluate the efficacy of different methods of indexing LAV in predicting mortality and CV events across a range of body sizes. METHODS: LAV was adjusted for BSA, idealized BSA (iBSA), height, and height-squared (H2) in patients aged over 50 years who underwent outpatient echocardiography and longitudinal follow-up at our institution. LA dilation was categorized using published criteria. Mortality and CV events were assessed via medical records. RESULTS: LAVs were calculated in 17,454 individuals. In this study, 71.2% were overweight or obese. Indexing using iBSA, height, and H2 resulted in reclassification of LA size in up to 28.4% (P < 0.001) compared with indexing using BSA. In severely obese individuals (body mass index [BMI] ≥40 kg/m2), LA dilation indexed for BSA no longer predicted mortality (P = 0.70). Other indexing methods remained predictive of mortality. Height, H2, and iBSA all had greater performance, compared with BSA, for prediction of mortality and CV events in all overweight patients with H2 showing the best overall performance (P < 0.001). Net reclassification index for mortality was significant for all alternative indexing techniques (P < 0.001) and patients whose LA was reclassified from normal to dilated had increased risk of mortality (P < 0.001) and CV events (P < 0.001) across all BMI categories. CONCLUSIONS: LA dilation based on standard indexing using BSA is nondiscriminatory for prediction of mortality in the severely obese. Indexing using height, H2, or iBSA to diagnose LA dilation better predicts mortality in this population and has better overall predictive performance across all overweight and obese populations. Using BSA indexing may lead to underappreciation of LA dilation and underestimation of patients at increased risk.

Association of Pulmonary Artery Pulsatility Index With Adverse Cardiovascular Events Across a Hospital-Based Sample.

BACKGROUND: The pulmonary artery pulsatility index (PAPi), calculated from the ratio of the pulmonary artery pulse pressure to right atrial pressure, is a predictor of right ventricular failure after inferior myocardial infarction and left ventricular assist device implantation. Whether PAPi is associated with adverse outcomes across a heterogeneous population is unknown. METHODS: We examined consecutive patients undergoing right heart catheterization between 2005 and 2016 in a hospital-based cohort. Multivariable Cox models were utilized to examine the association between PAPi and all-cause mortality, major adverse cardiac events, and heart failure hospitalizations. RESULTS: We studied 8285 individuals (mean age 63 years, 39% women) with median PAPi across quartiles 1.7, 2.8, 4.2, and 8.7, who were followed over a mean follow-up of 6.7±3.3 years. Patients in the lowest PAPi quartile had a 60% greater risk of death compared with the highest quartile (multivariable-adjusted hazard ratio, 1.60 [95% CI, 1.36-1.88], P<0.001) and a higher risk of major adverse cardiac events and heart failure hospitalizations (hazard ratio, 1.80 [95% CI, 1.56-2.07], P<0.001 and hazard ratio, 2.08 [95% CI, 1.76-2.47], P<0.001, respectively). Of note, patients in quartiles 2 and 3 also had increased risk of cardiovascular events compared with quartile 4 (multivariable P<0.05 for all). CONCLUSIONS: Compared with the highest PAPi quartile, patients in PAPi quartiles 1 to 3 had a greater risk of all-cause mortality, major adverse cardiac events, and heart failure hospitalizations, with greatest risk observed in the lowest quartile. A low PAPi, even at values higher than previously reported, may serve an important role in identifying high-risk individuals across a broad spectrum of cardiovascular disease.

Lessons from implementing a combined workflow-informatics system for diabetes management.

Shortcomings surrounding the care of patients with diabetes have been attributed largely to a fragmented, disorganized, and duplicative health care system that focuses more on acute conditions and complications than on managing chronic disease. To address these shortcomings, we developed a diabetes registry population management application to change the way our staff manages patients with diabetes. Use of this new application has helped us coordinate the responsibilities for intervening and monitoring patients in the registry among different users. Our experiences using this combined workflow-informatics intervention system suggest that integrating a chronic disease registry into clinical workflow for the treatment of chronic conditions creates a useful and efficient tool for managing disease.

Current polarity-dependent manipulation of antiferromagnetic domains.

Antiferromagnets have several favourable properties as active elements in spintronic devices, including ultra-fast dynamics, zero stray fields and insensitivity to external magnetic fields 1 . Tetragonal CuMnAs is a testbed system in which the antiferromagnetic order parameter can be switched reversibly at ambient conditions using electrical currents 2 . In previous experiments, orthogonal in-plane current pulses were used to induce 90° rotations of antiferromagnetic domains and demonstrate the operation of all-electrical memory bits in a multi-terminal geometry 3 . Here, we demonstrate that antiferromagnetic domain walls can be manipulated to realize stable and reproducible domain changes using only two electrical contacts. This is achieved by using the polarity of the current to switch the sign of the current-induced effective field acting on the antiferromagnetic sublattices. The resulting reversible domain and domain wall reconfigurations are imaged using X-ray magnetic linear dichroism microscopy, and can also be detected electrically. Switching by domain-wall motion can occur at much lower current densities than those needed for coherent domain switching.

Improving diabetes population management efficiency with an informatics solution.

Despite intensive resource use for diabetes management in the U.S., our care continues to fall short of evidence-based goals, partly due to system inefficiencies. Diabetes registries are increasingly being utilized as a critical tool for population level disease management by providing real-time data. Since the successful adoption of a diabetes registry depends on how well it integrates with disease management workflows, we optimized our current diabetes management workflow and designed our registry application around it.