Factors associated with reporting left ventricular ejection fraction with 3D echocardiography in real-world practice.

BACKGROUND: Guidelines recommend 3D echocardiography (3DE) to assess left ventricular ejection fraction (LVEF) on transthoracic echocardiogram (TTE) when possible, but it is unclear which factors are most strongly associated with reporting 3DE LVEF in real-world practice. METHODS: We evaluated 3DE LVEF reporting by age, sex, BMI, TTE location and variation in reporting by sonographer and reader. All TTEs were performed without contrast enhancement agent at a large medical center from 9/2015 to 12/2020 using ultrasound machines capable of 3DE. We used multivariable logistic regression to assess which factors were most associated with reporting 3DE LVEF. RESULTS: Among 35 641 TTEs included in this study, 57.4% were performed on women. 3DE LVEF was reported on 18 391 TTEs (51.6% of cohort; 50.5% for women and 52.4% for men). Portable inpatient TTEs (n = 5569) had the lowest rates of 3DE LVEF reporting (30.9%), while general outpatient TTEs (n = 15 933) had greater reporting (56.9%). Outpatient TTEs with an indication for chemotherapy (n = 3244) had the highest rates of 3DE LVEF (87.2%). The median (IQR) percentage of TTEs reporting 3D LVEF was 52.7% (43.1%-68.1%) among sonographers and 51.6% (46.5%-59.6%) among readers. Among 20082 (56.3%) TTEs with 3DE LVEF measured by sonographers, 91.6% were included by readers in the final report. After adjustment, performing sonographer in the highest reporting quartile was most strongly associated with reporting 3DE LVEF (OR 7.04, 95% CI 6.55-7.56), while an inpatient portable study had the strongest negative association for reporting (OR .38, 95% CI .35-.40). CONCLUSIONS: Use of 3DE LVEF in real-world practice varies substantially based on performing sonographer and is low for hospitalized patients, but can be frequently used for chemotherapy. Initiatives are needed to increase sonographer 3DE acquisition in most clinical settings.

Severe aortic stenosis detection by deep learning applied to echocardiography.

BACKGROUND AND AIMS: Early diagnosis of aortic stenosis (AS) is critical to prevent morbidity and mortality but requires skilled examination with Doppler imaging. This study reports the development and validation of a novel deep learning model that relies on two-dimensional (2D) parasternal long axis videos from transthoracic echocardiography without Doppler imaging to identify severe AS, suitable for point-of-care ultrasonography. METHODS AND RESULTS: In a training set of 5257 studies (17 570 videos) from 2016 to 2020 [Yale-New Haven Hospital (YNHH), Connecticut], an ensemble of three-dimensional convolutional neural networks was developed to detect severe AS, leveraging self-supervised contrastive pretraining for label-efficient model development. This deep learning model was validated in a temporally distinct set of 2040 consecutive studies from 2021 from YNHH as well as two geographically distinct cohorts of 4226 and 3072 studies, from California and other hospitals in New England, respectively. The deep learning model achieved an area under the receiver operating characteristic curve (AUROC) of 0.978 (95% CI: 0.966, 0.988) for detecting severe AS in the temporally distinct test set, maintaining its diagnostic performance in geographically distinct cohorts [0.952 AUROC (95% CI: 0.941, 0.963) in California and 0.942 AUROC (95% CI: 0.909, 0.966) in New England]. The model was interpretable with saliency maps identifying the aortic valve, mitral annulus, and left atrium as the predictive regions. Among non-severe AS cases, predicted probabilities were associated with worse quantitative metrics of AS suggesting an association with various stages of AS severity. CONCLUSION: This study developed and externally validated an automated approach for severe AS detection using single-view 2D echocardiography, with potential utility for point-of-care screening.

Two- Versus 8-Zone Lung Ultrasound in Heart Failure: Analysis of a Large Data Set Using a Deep Learning Algorithm.

OBJECTIVE: Scanning protocols for lung ultrasound often include 8 or more lung zones, which may limit real-world clinical use. We sought to compare a 2-zone, anterior-superior thoracic ultrasound protocol for B-line artifact detection with an 8-zone approach in patients with known or suspected heart failure using a deep learning (DL) algorithm. METHODS: Adult patients with suspected heart failure and B-lines on initial lung ultrasound were enrolled in a prospective observational study. Subjects received daily ultrasounds with a hand-held ultrasound system using an 8-zone protocol (right and left anterior/lateral and superior/inferior). A previously published deep learning algorithm that rates severity of B-lines on a 0-4 scale was adapted for use on hand-held ultrasound full video loops. Average severities for 8 and 2 zones were calculated utilizing DL ratings. Bland-Altman plot analyses were used to assess agreement and identify bias between 2- and 8-zone scores for both primary (all patients, 5728 videos, 205 subjects) and subgroup (confirmed diagnosis of heart failure or pulmonary edema, 4464 videos, 147 subjects) analyses. RESULTS: Bland-Altman plot analyses revealed excellent agreement for both primary and subgroup analyses. The absolute difference on the 4-point scale between 8- and 2-zone average scores was not significant for the primary dataset (0.03; 95% CI -0.01 to 0.07) or the subgroup (0.01; 95% CI -0.04 to 0.06). CONCLUSION: Utilization of a 2-zone, anterior-superior thoracic ultrasound protocol provided similar severity information to an 8-zone approach for a dataset of subjects with known or suspected heart failure.

Abnormal left atrial body stiffness is predicted by appendage size: impact of appendage occlusion on left atrial mechanics assessed by pressure-volume analysis.

Atrial cardiomyopathy has been recognized as having important consequences for cardiac performance and clinical outcomes. The pathophysiological role of the left atrial (LA) appendage and the effect of percutaneous left atrial appendage occlusion (LAAO) upon LA mechanics is incompletely understood. We evaluated if changes in LA stiffness due to endocardial LAAO can be detected by LA pressure-volume (PV) analysis and whether stiffness parameters are associated with baseline characteristics. Patients undergoing percutaneous endocardial LAAO (n = 25) were studied using a novel PV analysis using near-simultaneous three-dimensional LA volume measurements by transesophageal echocardiography (TEE) and direct invasive LA pressure measurements. LA stiffness (dP/dV, change in pressure with change in volume) was calculated before and after LAAO. Overall LA stiffness significantly increased after LAAO compared with baseline (median, 0.41-0.64 mmHg/mL; P ≪ 0.001). LA body stiffness after LAAO correlated with baseline LA appendage size by indexed maximum depth (Spearman's rank correlation coefficient Rs = 0.61; P < 0.01). LA stiffness change showed an even stronger correlation with baseline LA appendage size by indexed maximum depth (Rs = 0.70; P < 0.001). We found that overall LA stiffness increases after endocardial LAAO. Baseline LA appendage size correlates with the magnitude of increase and LA body stiffness. These findings document alteration of LA mechanics after endocardial LAAO and suggest that the LA appendage modulates overall LA compliance.NEW & NOTEWORTHY Our study documents a correlation of LA appendage remodeling with the degree of chronically abnormal LA body stiffness. In addition, we found that LA appendage size was the baseline parameter that best correlated with the magnitude of a further increase in overall LA stiffness after appendage occlusion. These findings offer insights about the LA appendage and LA mechanics that are relevant to patients at risk for adverse atrial remodeling, especially candidates for LA appendage occlusion.

An assessment of transesophageal echocardiography studies rated as rarely appropriate tests for infective endocarditis at an academic medical center.

PURPOSE: Endocardial involvement documented by echocardiography is a major criterion of the modified Duke criteria (MDC) for infective endocarditis (IE). Though transesophageal echocardiography (TEE) is sensitive in the diagnosis of IE, it can be inappropriately used. METHODS: This retrospective study included all patients who underwent TEE due to bacteremia, fever, and/or endocarditis in a single, tertiary academic medical center in 2013. Data collected from electronic medical charts were as follows: demographics, history, physical examination, blood cultures, and transthoracic (TTE) and TEE findings. Cases were categorized based on appropriate use criteria (AUC) and MDC. An infectious disease (ID) specialist reviewed cases with rarely appropriate TEE use. RESULTS: In the 194 patients included, 147 (75.8%) were rated as appropriate, 36 (18.6%) rarely appropriate, and 11 (5.6%) uncertain. Of the 36 with rarely appropriate TEEs, using MDC 31 (86%) were rejected and 5 (14%) were possible for IE. Retrospective chart review by an ID specialist determined that 10 of these patients warranted TEE due to compelling issues, including immunosuppression or complicated infection. CONCLUSIONS: In this retrospective cohort, almost one fifth of cases were rated as rarely appropriate. However, a review of these cases showed that TEE was often pursued when the clinical situation involved immunosuppression or complex infectious process. There remains room for improvement to our screening process for TEE and a need to implement a nuanced educational plan to better precisely identify appropriate cases for TEE usage.

Differentiating spontaneous echo contrast, sludge, and thrombus in the left atrial appendage: Can ultrasound enhancing agents help?

The accurate identification of thrombus in the left atrial appendage with transesophageal echocardiogram (TEE) in patients with atrial fibrillation (AF) before cardioversion is essential. Most of these patients have some grade of spontaneous echo contrast (SEC). Severe SEC is often called "sludge," and its prognosis and treatment are still controversial. Current guidelines suggest the use of ultrasound enhancing agents (UEAs) when significant SEC is present. However, little is known about the utility of the UEAs in the differentiation between sludge and less severe SEC.

Age Differences in Hospital Mortality for Acute Myocardial Infarction: Implications for Hospital Profiling.

BACKGROUND: Publicly reported hospital risk-standardized mortality rates (RSMRs) for acute myocardial infarction (AMI) are calculated for Medicare beneficiaries. Outcomes for older patients with AMI may not reflect general outcomes. OBJECTIVE: To examine the relationship between hospital 30-day RSMRs for older patients (aged ≥65 years) and those for younger patients (aged 18 to 64 years) and all patients (aged ≥18 years) with AMI. DESIGN: Retrospective cohort study. SETTING: 986 hospitals in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry-Get With the Guidelines. PARTICIPANTS: Adults hospitalized for AMI from 1 October 2010 to 30 September 2014. MEASUREMENTS: Hospital 30-day RSMRs were calculated for older, younger, and all patients using an electronic health record measure of AMI mortality endorsed by the National Quality Forum. Hospitals were ranked by their 30-day RSMRs for these 3 age groups, and agreement in rankings was plotted. The correlation in hospital AMI achievement scores for each age group was also calculated using the Hospital Value-Based Purchasing (HVBP) Program method computed with the electronic health record measure. RESULTS: 267 763 and 276 031 AMI hospitalizations among older and younger patients, respectively, were identified. Median hospital 30-day RSMRs were 9.4%, 3.0%, and 6.2% for older, younger, and all patients, respectively. Most top- and bottom-performing hospitals for older patients were neither top nor bottom performers for younger patients. In contrast, most top and bottom performers for older patients were also top and bottom performers for all patients. Similarly, HVBP achievement scores for older patients correlated weakly with those for younger patients (R = 0.30) and strongly with those for all patients (R = 0.92). LIMITATION: Minority of U.S. hospitals. CONCLUSION: Hospital mortality rankings for older patients with AMI inconsistently reflect rankings for younger patients. Incorporation of younger patients into assessment of hospital outcomes would permit further examination of the presence and effect of age-related quality differences. PRIMARY FUNDING SOURCE: American College of Cardiology.

Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization.

BACKGROUND AND PURPOSE: The Centers for Medicare & Medicaid Services publicly reports a hospital-level stroke mortality measure that lacks stroke severity risk adjustment. Our objective was to describe novel measures of stroke mortality suitable for public reporting that incorporate stroke severity into risk adjustment. METHODS: We linked data from the American Heart Association/American Stroke Association Get With The Guidelines-Stroke registry with Medicare fee-for-service claims data to develop the measures. We used logistic regression for variable selection in risk model development. We developed 3 risk-standardized mortality models for patients with acute ischemic stroke, all of which include the National Institutes of Health Stroke Scale score: one that includes other risk variables derived only from claims data (claims model); one that includes other risk variables derived from claims and clinical variables that could be obtained from electronic health record data (hybrid model); and one that includes other risk variables that could be derived only from electronic health record data (electronic health record model). RESULTS: The cohort used to develop and validate the risk models consisted of 188 975 hospital admissions at 1511 hospitals. The claims, hybrid, and electronic health record risk models included 20, 21, and 9 risk-adjustment variables, respectively; the C statistics were 0.81, 0.82, and 0.79, respectively (as compared with the current publicly reported model C statistic of 0.75); the risk-standardized mortality rates ranged from 10.7% to 19.0%, 10.7% to 19.1%, and 10.8% to 20.3%, respectively; the median risk-standardized mortality rate was 14.5% for all measures; and the odds of mortality for a high-mortality hospital (+1 SD) were 1.51, 1.52, and 1.52 times those for a low-mortality hospital (-1 SD), respectively. CONCLUSIONS: We developed 3 quality measures that demonstrate better discrimination than the Centers for Medicare & Medicaid Services' existing stroke mortality measure, adjust for stroke severity, and could be implemented in a variety of settings.

Contemporary risk model for inhospital major bleeding for patients with acute myocardial infarction: The acute coronary treatment and intervention outcomes network (ACTION) registry®-Get With The Guidelines (GWTG)®.

BACKGROUND: Major bleeding is a frequent complication for patients with acute myocardial infarction (AMI) and is associated with significant morbidity and mortality. OBJECTIVE: To develop a contemporary model for inhospital major bleeding that can both support clinical decision-making and serve as a foundation for assessing hospital quality. METHODS: An inhospital major bleeding model was developed using the Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With the Guidelines (ACTION Registry-GWTG) database. Patients hospitalized with AMI between January 1, 2012 and December 31, 2013 across 657 hospitals were used to create a derivation cohort (n=144,800) and a validation cohort (n=96,684). Multivariable hierarchal logistic regression was used to identify significant predictors of major bleeding. A simplified risk score was created to enable prospective risk stratification for clinical care. RESULTS: The rate of major bleeding in the overall population was 7.53%. There were 8 significant, independent factors associated with major bleeding: presentation after cardiac arrest (OR 2.99 [2.77-3.22]); presentation in cardiogenic shock (OR 2.22 [2.05-2.40]); STEMI (OR 1.72 [1.65-1.80]); presentation in heart failure (OR 1.55 [1.47-1.63]); baseline hemoglobin less than 12 g/dL (1.55 [1.48-1.63]); heart rate (per 10 beat per minute increase) (OR 1.13 [1.12-1.14]); weight (per 10 kilogram decrease) (OR 1.12 [1.11-1.14]); creatinine clearance (per 5-mL decrease) (OR 1.07 [1.07-1.08]). The model discriminated well in the derivation (C-statistic = 0.74) and validation (C-statistic = 0.74) cohorts. In the validation cohort, a risk score for major bleeding corresponded well with observed bleeding: very low risk (2.2%), low risk (5.1%), moderate risk (10.1%), high risk (16.3%), and very high risk (25.2%). CONCLUSION: The new ACTION Registry-GWTG inhospital major bleeding risk model and risk score offer a robust, parsimonious, and contemporary risk-adjustment method to support clinical decision-making and enable hospital quality assessment. Strategies to mitigate risk should be developed and tested as a means to lower costs and improve outcomes in an era of alternative payment models.

Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records: 30-Day Risk-standardized Mortality After Acute Myocardial Infarction.

BACKGROUND: Electronic health records (EHRs) offer the opportunity to transform quality improvement by using clinical data for comparing hospital performance without the burden of chart abstraction. However, current performance measures using EHRs are lacking. METHODS: With support from the Centers for Medicare & Medicaid Services (CMS), we developed an outcome measure of hospital risk-standardized 30-day mortality rates for patients with acute myocardial infarction for use with EHR data. As no appropriate source of EHR data are currently available, we merged clinical registry data from the Action Registry-Get With The Guidelines with claims data from CMS to develop the risk model (2009 data for development, 2010 data for validation). We selected candidate variables that could be feasibly extracted from current EHRs and do not require changes to standard clinical practice or data collection. We used logistic regression with stepwise selection and bootstrapping simulation for model development. RESULTS: The final risk model included 5 variables available on presentation: age, heart rate, systolic blood pressure, troponin ratio, and creatinine level. The area under the receiver operating characteristic curve was 0.78. Hospital risk-standardized mortality rates ranged from 9.6% to 13.1%, with a median of 10.7%. The odds of mortality for a high-mortality hospital (+1 SD) were 1.37 times those for a low-mortality hospital (-1 SD). CONCLUSIONS: This measure represents the first outcome measure endorsed by the National Quality Forum for public reporting of hospital quality based on clinical data in the EHR. By being compatible with current clinical practice and existing EHR systems, this measure is a model for future quality improvement measures.

Aortic dissection associated with penetration of a spinal pedicle screw: a case report and review of the literature.

A 30-year-old male underwent a corrective posterior instrumented spinal fusion for scoliosis. Six years later, he was found to have an aortic dissection after aortic penetration of a spinal pedicle screw. We review the literature, including diagnostic modalities, and treatment decision-making for this unusual complication.

Study Protocol for the Artificial Intelligence-Driven Evaluation of Structural Heart Diseases Using Wearable Electrocardiogram (ID-SHD).

Introduction: Portable devices capable of electrocardiogram (ECG) acquisition have the potential to enhance structural heart disease (SHD) management by enabling early detection through artificial intelligence-ECG (AI-ECG) algorithms. However, the performance of these AI algorithms for identifying SHD in a real-world screening setting is unknown. To address this gap, we aim to evaluate the validity of our wearable-adapted AI algorithm, which has been previously developed and validated for detecting SHD from single-lead portable ECGs in patients undergoing routine echocardiograms in the Yale New Haven Hospital (YNHH). Research Methods and Analysis: This is the protocol for a cross-sectional study in the echocardiographic laboratories of YNHH. The study will enroll 585 patients referred for outpatient transthoracic echocardiogram (TTE) as part of their routine clinical care. Patients expressing interest in participating in the study will undergo a screening interview, followed by enrollment upon meeting eligibility criteria and providing informed consent. During their routine visit, patients will undergo a 1-lead ECG with two devices - one with an Apple Watch and the second with another portable 1-lead ECG device. With participant consent, these 1-lead ECG data will be linked to participant demographic and clinical data recorded in the YNHH electronic health records (EHR). The study will assess the performance of the AI-ECG algorithm in identifying SHD, including left ventricular systolic dysfunction (LVSD), valvular disease and severe left ventricular hypertrophy (LVH), by comparing the algorithm's results with data obtained from TTE, which is the established gold standard for diagnosing SHD. Ethics and Dissemination: All patient EHR data required for assessing eligibility and conducting the AI-ECG will be accessed through secure servers approved for protected health information. Data will be maintained on secure, encrypted servers for a minimum of five years after the publication of our findings in a peer-reviewed journal, and any unanticipated adverse events or risks will be reported by the principal investigator to the Yale Institutional Review Board, which has reviewed and approved this protocol (Protocol Number: 2000035532).

High- versus low-gradient aortic stenosis: Is our evaluation limited by aorto-mitral angle on cardiovascular CT?

BACKGROUND: Accurate assessment of aortic valve (AV) stenosis (AS) on transthoracic echocardiogram is crucial for appropriate clinical management. However, discordance between aortic valve area (AVA) and Doppler can complicate the diagnosis of severe AS in low-gradient (LG) AS phenotypes. METHODS: We reviewed 220 consecutive patients with suspected severe AS and AVA ≤1.0 cm2 on transthoracic echocardiogram who were evaluated for transcatheter AV replacement (TAVR) within a large health system from 2015 to 2019. We compared AV calcium score and aorto-mitral angle (AMA) on 3-chamber views from ECG-gated cardiovascular CT among patients with high-gradient (HG) AS (N = 19), paradoxical low-flow low-gradient (PLFLG) AS (N = 24) and normal-flow low-gradient (NFLG) AS (N = 14). RESULTS: All groups had comparable age, comorbidities, and AV calcium scores. Compared to patients with HG AS (mean AMA 120 ± 10°), those with PLFLG AS (104 ± 12°; p < 0.001) and NFLG AS (106 ± 13°; p = 0.008) had narrower mean AMA values on cardiovascular CT. CONCLUSION: LG AS patients have significantly narrower AMA than HG AS patients on cardiovascular CT. Due to difficulty obtaining parallel Doppler alignment, narrower AMA may contribute to AVA-Doppler discordance on echocardiogram. These findings emphasize the need for additional information in the setting of LG AS.

Artificial intelligence-guided detection of under-recognized cardiomyopathies on point-of-care cardiac ultrasound: a multi-center study.

BACKGROUND: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We developed and tested artificial intelligence (AI) models to automate the detection of under-diagnosed cardiomyopathies from cardiac POCUS. METHODS: In a development set of 290,245 transthoracic echocardiographic videos across the Yale-New Haven Health System (YNHHS), we used augmentation approaches and a customized loss function weighted for view quality to derive a POCUS-adapted, multi-label, video-based convolutional neural network (CNN) that discriminates HCM (hypertrophic cardiomyopathy) and ATTR-CM (transthyretin amyloid cardiomyopathy) from controls without known disease. We evaluated the final model across independent, internal and external, retrospective cohorts of individuals who underwent cardiac POCUS across YNHHS and Mount Sinai Health System (MSHS) emergency departments (EDs) (2011-2024) to prioritize key views and validate the diagnostic and prognostic performance of single-view screening protocols. FINDINGS: We identified 33,127 patients (median age 61 [IQR: 45-75] years, n=17,276 [52.2%] female) at YNHHS and 5,624 (57 [IQR: 39-71] years, n=1,953 [34.7%] female) at MSHS with 78,054 and 13,796 eligible cardiac POCUS videos, respectively. An AI-enabled single-view screening approach successfully discriminated HCM (AUROC of 0.90 [YNHHS] & 0.89 [MSHS]) and ATTR-CM (YNHHS: AUROC of 0.92 [YNHHS] & 0.99 [MSHS]). In YNHHS, 40 (58.0%) HCM and 23 (47.9%) ATTR-CM cases had a positive screen at median of 2.1 [IQR: 0.9-4.5] and 1.9 [IQR: 1.0-3.4] years before clinical diagnosis. Moreover, among 24,448 participants without known cardiomyopathy followed over 2.2 [IQR: 1.1-5.8] years, AI-POCUS probabilities in the highest (vs lowest) quintile for HCM and ATTR-CM conferred a 15% (adj.HR 1.15 [95%CI: 1.02-1.29]) and 39% (adj.HR 1.39 [95%CI: 1.22-1.59]) higher age- and sex-adjusted mortality risk, respectively. INTERPRETATION: We developed and validated an AI framework that enables scalable, opportunistic screening of treatable cardiomyopathies wherever POCUS is used.

A Multimodality Video-Based AI Biomarker For Aortic Stenosis Development And Progression.

Importance: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. Objective: A video-based artificial intelligence (AI) biomarker (Digital AS Severity index [DASSi]) can detect severe AS using single-view long-axis echocardiography without Doppler. Here, we deploy DASSi to patients with no or mild/moderate AS at baseline to identify AS development and progression. Design Setting and Participants: We defined two cohorts of patients without severe AS undergoing echocardiography in the Yale-New Haven Health System (YNHHS) (2015-2021, 4.1[IQR:2.4-5.4] follow-up years) and Cedars-Sinai Medical Center (CSMC) (2018-2019, 3.4[IQR:2.8-3.9] follow-up years). We further developed a novel computational pipeline for the cross-modality translation of DASSi into cardiac magnetic resonance (CMR) imaging in the UK Biobank (2.5[IQR:1.6-3.9] follow-up years). Analyses were performed between August 2023-February 2024. Exposure: DASSi (range: 0-1) derived from AI applied to echocardiography and CMR videos. Main Outcomes and Measures: Annualized change in peak aortic valve velocity (AV-Vmax) and late (>6 months) aortic valve replacement (AVR). Results: A total of 12,599 participants were included in the echocardiographic study (YNHHS: n=8,798, median age of 71 [IQR (interquartile range):60-80] years, 4250 [48.3%] women, and CSMC: n=3,801, 67 [IQR:54-78] years, 1685 [44.3%] women). Higher baseline DASSi was associated with faster progression in AV-Vmax (per 0.1 DASSi increments: YNHHS: +0.033 m/s/year [95%CI:0.028-0.038], n=5,483, and CSMC: +0.082 m/s/year [0.053-0.111], n=1,292), with levels ≥ vs <0.2 linked to a 4-to-5-fold higher AVR risk (715 events in YNHHS; adj.HR 4.97 [95%CI: 2.71-5.82], 56 events in CSMC: 4.04 [0.92-17.7]), independent of age, sex, ethnicity/race, ejection fraction and AV-Vmax. This was reproduced across 45,474 participants (median age 65 [IQR:59-71] years, 23,559 [51.8%] women) undergoing CMR in the UK Biobank (adj.HR 11.4 [95%CI:2.56-50.60] for DASSi ≥vs<0.2). Saliency maps and phenome-wide association studies supported links with traditional cardiovascular risk factors and diastolic dysfunction. Conclusions and Relevance: In this cohort study of patients without severe AS undergoing echocardiography or CMR imaging, a new AI-based video biomarker is independently associated with AS development and progression, enabling opportunistic risk stratification across cardiovascular imaging modalities as well as potential application on handheld devices.

A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression.

Importance: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. A video-based artificial intelligence (AI) biomarker (Digital AS Severity index [DASSi]) can detect severe AS using single-view long-axis echocardiography without Doppler characterization. Objective: To deploy DASSi to patients with no AS or with mild or moderate AS at baseline to identify AS development and progression. Design, Setting, and Participants: This is a cohort study that examined 2 cohorts of patients without severe AS undergoing echocardiography in the Yale New Haven Health System (YNHHS; 2015-2021) and Cedars-Sinai Medical Center (CSMC; 2018-2019). A novel computational pipeline for the cross-modal translation of DASSi into cardiac magnetic resonance (CMR) imaging was further developed in the UK Biobank. Analyses were performed between August 2023 and February 2024. Exposure: DASSi (range, 0-1) derived from AI applied to echocardiography and CMR videos. Main Outcomes and Measures: Annualized change in peak aortic valve velocity (AV-Vmax) and late (>6 months) aortic valve replacement (AVR). Results: A total of 12 599 participants were included in the echocardiographic study (YNHHS: n = 8798; median [IQR] age, 71 [60-80] years; 4250 [48.3%] women; median [IQR] follow-up, 4.1 [2.4-5.4] years; and CSMC: n = 3801; median [IQR] age, 67 [54-78] years; 1685 [44.3%] women; median [IQR] follow-up, 3.4 [2.8-3.9] years). Higher baseline DASSi was associated with faster progression in AV-Vmax (per 0.1 DASSi increment: YNHHS, 0.033 m/s per year [95% CI, 0.028-0.038] among 5483 participants; CSMC, 0.082 m/s per year [95% CI, 0.053-0.111] among 1292 participants), with values of 0.2 or greater associated with a 4- to 5-fold higher AVR risk than values less than 0.2 (YNHHS: 715 events; adjusted hazard ratio [HR], 4.97 [95% CI, 2.71-5.82]; CSMC: 56 events; adjusted HR, 4.04 [95% CI, 0.92-17.70]), independent of age, sex, race, ethnicity, ejection fraction, and AV-Vmax. This was reproduced across 45 474 participants (median [IQR] age, 65 [59-71] years; 23 559 [51.8%] women; median [IQR] follow-up, 2.5 [1.6-3.9] years) undergoing CMR imaging in the UK Biobank (for participants with DASSi ≥0.2 vs those with DASSi <.02, adjusted HR, 11.38 [95% CI, 2.56-50.57]). Saliency maps and phenome-wide association studies supported associations with cardiac structure and function and traditional cardiovascular risk factors. Conclusions and Relevance: In this cohort study of patients without severe AS undergoing echocardiography or CMR imaging, a new AI-based video biomarker was independently associated with AS development and progression, enabling opportunistic risk stratification across cardiovascular imaging modalities as well as potential application on handheld devices.

Changes in left atrial appendage orifice following percutaneous left atrial appendage closure using three-dimensional echocardiography.

Percutaneous left atrial appendage (LAA) occlusion is increasingly performed in patients with atrial fibrillation and long-term contraindications for anticoagulation. Our aim was to evaluate the effects of LAA occlusion with the Watchman device on the geometry of the LAA orifice and assess its impact on the adjacent left upper pulmonary vein (LUPV) hemodynamics. We included 50 patients who underwent percutaneous LAA occlusion with the Watchman device and had acceptable three-dimensional transesophageal echocardiography images of LAA pre- and post-device placement. We measured offline the LAA orifice diameters in the long axis, and the minimum and maximum diameters, circumference, and area in the short axis view. Eccentricity index was calculated as maximum/minimum diameter ratio. The LUPV peak S and D velocities pre- and post-procedure were also measured. Patients were elderly (mean age 76 ± 8 years), 30 (60%) were men. There was a significant increase of all LAA orifice dimensions following LAA occlusion: diameter 1 (pre-device 18.1 ± 3.2 vs. post-device 21.5 ± 3.4 mm, p < 0.001), diameter 2 (20.6 ± 3.9 vs. 22.1 ± 3.6 mm, p < 0.001), minimum diameter (17.6 ± 3.1 vs. 21.3 ± 3.4 mm, p < 0.001), maximum diameter (21.5 ± 3.9 vs. 22.4 ± 3.6 mm, p = 0.022), circumference (63.6 ± 10.7 vs. 69.6 ± 10.5 mm, p < 0.001), and area (3.1 ± 1.1 vs. 3.9 ± 1.2 cm2, p < 0.001). Eccentricity index decreased after procedure (1.23 ± 0.16 vs. 1.06 ± 0.06, p < 0.001). LUPV peak S and D velocities did not show a significant difference (0.29 ± 0.15 vs. 0.30 ± 0.14 cm/s, p = 0.637; and 0.47 ± 0.19 vs. 0.48 ± 0.20 cm/s, p = 0.549; respectively). LAA orifice stretches significantly and it becomes more circular following LAA occlusion without causing a significant impact on the LUPV hemodynamics.

Tricuspid and mitral remodelling in atrial fibrillation: a three-dimensional echocardiographic study.

AIMS: Atrial fibrillation (AF) is associated with atrial enlargement, mitral annulus (MA) and tricuspid annulus (TA) dilation, and atrial functional regurgitation (AFR). However, less is known about the impact of AF on both atrioventricular valves in those with normal and abnormal ventricular function. We aimed to compare the remodelling of the TA and MA in patients with non-valvular AF without significant AFR. METHODS AND RESULTS: Ninety-two patients referred for transoesophageal echocardiography were included and categorized into three groups: (i) AF with normal left ventricular (LV) function (Normal LV-AF), n = 36; (ii) AF with LV systolic dysfunction (LVSD-AF), n = 29; and (iii) Controls in sinus rhythm, n = 27. Three-dimensional MA and TA geometry were analysed using automated software. In patients with AF regardless of LV function, the MA and TA areas were larger compared with controls (LVSD-AF vs. Normal LV-AF vs. Controls, end-systolic MA: 5.2 ± 1.1 vs. 4.5 ± 0.7 vs. 3.9 ± 0.7 cm2/m2; end-systolic TA: 5.6 ± 1.3 vs. 5.3 ± 1.3 vs. 4.1 ± 0.7 cm2/m2; P < 0.05 for each comparison with Controls). TA and MA areas were not statistically different between the two AF groups. The TA increase over controls was greater than that of the MA in the Normal LV-AF group (27.7% vs. 15.6%, P = 0.041). Conversely, in the LVSD-AF group, MA and TA increased similarly (35.9% vs. 32.4%, P = 0.660). CONCLUSION: Patients with AF showed dilation of both TA and MA compared with patients in sinus rhythm. In patients with normal LV function, AF was associated with greater TA dilation than MA dilation whereas in patients with LVSD the TA and MA were equally dilated.

Patient Awareness and Clinical Inertia: Obstacles to Hypertension Control in Rural Communities in the Dominican Republic.

BACKGROUND: Many obstacles exist for adequate hypertension control, including low individual awareness and clinical inertia (CI). In this study, we aimed to determine hypertension prevalence, awareness, treatment, and control among community residents of rural areas of Peravia in Dominican Republic (DR), followed by an assessment of CI in their primary care clinics (PCCs). METHODS: We interviewed 827 adults from 8 rural communities of Peravia. Demographics, medical history, health care information, and blood pressure (BP) were obtained. We reviewed the community PCC visits of patients with known hypertension or a BP ≥140/90, abstracting medical history and the physician's action toward uncontrolled BP. RESULTS: Of those interviewed, 57% (95% CI: 53%-60%) had hypertension, with 63% (95% CI: 59%-68%) of those aware of their diagnosis. Among individuals with hypertension, 60% (95% CI: 56%-65%) were receiving pharmacological treatment, and only 35% (95% CI: 31%-40%) were controlled. Characteristics associated with awareness were female sex, age >55 years, diabetes, private insurance, and having at least 1 health care visit within the past year. Of the 507 PCC patients reviewed, 340 (67%) had uncontrolled BP. Of these, 220 had no clinical action to address the uncontrolled BP, corresponding to a CI rate of 65%. CONCLUSIONS: Among rural communities in the DR, undiagnosed hypertension remains common, especially in individuals who are younger, uninsured, or with limited access to health care. For those seen in PCCs, therapeutic intensification to achieve controlled BP is infrequently done. Strategies to address population awareness and CI are needed to improve hypertension control.

Understanding the role of left and right ventricular strain assessment in patients hospitalized with COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) can cause cardiac injury resulting in abnormal right or left ventricular function (RV/LV) with worse outcomes. We hypothesized that two-dimensional (2D) speckle-tracking assessment of LV global longitudinal strain (GLS) and RV free wall strain (FWS) by transthoracic echocardiography can assist as markers for subclinical cardiac injury predicting increased mortality. METHODS: We performed 2D strain analysis via proprietary software in 48 patients hospitalized with COVID-19. Clinical information, demographics, comorbidities, and lab values were collected via retrospective chart review. The primary outcome was in-hospital mortality based on an optimized abnormal LV GLS value via ROC analysis and RV FWS. RESULTS: The optimal LV GLS cutoff to predict death was -13.8%, with a sensitivity of 85% (95% CI 55-98%) and specificity of 54% (95% CI 36-71%). Abnormal LV GLS >-13.8% was associated with a higher risk of death [unadjusted hazard ratio 5.15 (95% CI 1.13-23.45), p = 0.034], which persisted after adjustment for clinical variables. Among patients with LV ejection fraction (LVEF) >50%, those with LV GLS > -13.8% had higher mortality compared to those with LV GLS <-13.8% (41% vs. 10%, p = 0.030). RV FWS value was higher in patients with LV GLS >-13.8% (-13.7 ±â€¯5.9 vs. -19.6 ±â€¯6.7, p = 0.003), but not associated with decreased survival. CONCLUSION: Abnormal LV strain with a cutoff of >-13.8% in patients with COVID-19 is associated with significantly higher risk of death. Despite normal LVEF, abnormal LV GLS predicted worse outcomes in patients hospitalized with COVID-19. There was no mortality difference based on RV strain.