Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping.

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

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.

Characteristics and Attitudes of Wearable Device Users and Non-Users in a Large Healthcare System.

Introduction: Consumer wearable devices with health and wellness features are increasingly common and may enhance prevention and management of cardiovascular disease. However, the characteristics and attitudes of wearable device users versus non-users are poorly understood. Methods: Wearable Activity Tracking for Comprehensive Healthcare-Integrated Technology (WATCH-IT) was a prospective study of adults aged ≥18 years receiving longitudinal primary or ambulatory cardiovascular care at one of eleven hospitals within the Mass General Brigham multi-institutional healthcare system between January 2010-July 2021. We invited patients, including wearable users and non-users, to participate via an electronic patient portal. Participants were asked to complete a 20-question survey regarding perceptions and use of consumer wearable devices. Responses were linked to electronic health record data. Multivariable logistic regression was used to identify factors associated with device use. Results: Among 280,834 individuals receiving longitudinal primary or cardiovascular care, 65,842 did not have an active electronic portal or opted out of research contact. Of the 214,992 individuals sent a survey link, 11,121 responded (5.2%), comprising the WATCH-IT patient sample. Most respondents (55.8%) reported current use of a wearable device, and most non-users (95.3%) reported they would use a wearable device if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, the majority believed it would be very (20.4%) or moderately (34.4%) important to share device-related health information with providers. In multivariable models, older age (odds ratio [OR] 0.80 per 10-year increase, 95% CI 0.77-0.82), male sex (0.87, 95% CI 0.80-0.95), and heart failure (0.75, 95% CI 0.63-0.89) were associated with lower odds of wearable device use, whereas higher median zip code income (1.08 per 1-quartile increase, 95% CI 1.04-1.12) and care in a cardiovascular medicine clinic (1.17, 95% CI 1.05-1.30) were associated with greater odds of device use. Nearly all respondents (98%) stated they would share device data with researchers studying health outcomes. Conclusions: Within an electronically assembled cohort of patients in primary and cardiovascular medicine clinics with linkage to detailed health records, wearable device use is common. Most users perceive value in wearable data. Our platform may enable future study of the relationships between wearable technology and resource utilization, clinical outcomes, and health disparities.

Effect of clinic-based single-lead electrocardiogram rhythm assessment on oral anticoagulation prescriptions in patients with previously diagnosed atrial fibrillation.

Background: Despite benefits of oral anticoagulation (OAC), many individuals with diagnosed atrial fibrillation (AF) do not receive OAC. Objective: The purpose of this study was to assess whether cardiac rhythm assessment for AF impacted use of OAC in patients with previously diagnosed AF. Methods: VITAL-AF was a cluster randomized controlled trial conducted in 16 primary care practices assessing the efficacy of AF rhythm assessment with single-lead electrocardiogram in routine care. Patients 65 years and older were offered rhythm assessment at visits. In this secondary analysis, we evaluated rhythm assessment uptake and compared initiation and discontinuation of OAC in patients with previously diagnosed AF from intervention and control arms over 1 year. Results: The study included 4593 patients with previously diagnosed AF (2250 intervention; 2343 control). In the intervention arm, 2022 (89.9%) completed rhythm assessment (median 2 visits with rhythm assessment) and 40.1% had ≥1 "Possible AF" result. Initiation of OAC was similar in the intervention (17.7%) and control (19.1%) arms but was influenced by the rhythm assessment result: higher with a "Possible AF" (26.1%; adjusted odds ratio [aOR] 1.62; 95% confidence interval [CI] 1.04-2.51), and lower with a "Normal" result (9.9%; aOR 0.45; 95% CI 0.29-0.71) compared to control. OAC discontinuation was similar in the intervention (6.3%) and control (7.2%) arms, with lower discontinuation with a "Possible AF" result (3.8%; aOR 0.51; 95% CI 0.32-0.81). Conclusions: Including patients with previously diagnosed AF in a point-of-care rhythm assessment strategy did not increase overall OAC use compared to the control arm. However, the rhythm assessment result influenced both initiation and discontinuation of OAC.

Assessment of valvular function in over 47,000 people using deep learning-based flow measurements.

Valvular heart disease is associated with a high global burden of disease. Even mild aortic stenosis confers increased morbidity and mortality, prompting interest in understanding normal variation in valvular function at scale. We developed a deep learning model to study velocity-encoded magnetic resonance imaging in 47,223 UK Biobank participants. We calculated eight traits, including peak velocity, mean gradient, aortic valve area, forward stroke volume, mitral and aortic regurgitant volume, greatest average velocity, and ascending aortic diameter. We then computed sex-stratified reference ranges for these phenotypes in up to 31,909 healthy individuals. In healthy individuals, we found an annual decrement of 0.03cm 2 in the aortic valve area. Participants with mitral valve prolapse had a 1 standard deviation [SD] higher mitral regurgitant volume (P=9.6 × 10 -12 ), and those with aortic stenosis had a 4.5 SD-higher mean gradient (P=1.5 × 10 -431 ), validating the derived phenotypes' associations with clinical disease. Greater levels of ApoB, triglycerides, and Lp(a) assayed nearly 10 years prior to imaging were associated with higher gradients across the aortic valve. Metabolomic profiles revealed that increased glycoprotein acetyls were also associated with an increased aortic valve mean gradient (0.92 SD, P=2.1 x 10 -22 ). Finally, velocity-derived phenotypes were risk markers for aortic and mitral valve surgery even at thresholds below what is considered relevant disease currently. Using machine learning to quantify the rich phenotypic data of the UK Biobank, we report the largest assessment of valvular function and cardiovascular disease in the general population.

Cost-effectiveness of Screening for Atrial Fibrillation Using Wearable Devices.

Importance: Undiagnosed atrial fibrillation (AF) is an important cause of stroke. Screening for AF using wrist-worn wearable devices may prevent strokes, but their cost-effectiveness is unknown. Objective: To evaluate the cost-effectiveness of contemporary AF screening strategies, particularly wrist-worn wearable devices. Design Setting and Participants: This economic evaluation used a microsimulation decision-analytic model and was conducted from September 8, 2020, to May 23, 2022, comprising 30 million simulated individuals with an age, sex, and comorbidity profile matching the US population aged 65 years or older. Interventions: Eight AF screening strategies, with 6 using wrist-worn wearable devices (watch or band photoplethysmography, with or without watch or band electrocardiography) and 2 using traditional modalities (ie, pulse palpation and 12-lead electrocardiogram) vs no screening. Main Outcomes and Measures: The primary outcome was the incremental cost-effectiveness ratio, defined as US dollars per quality-adjusted life-year (QALY). Secondary measures included rates of stroke and major bleeding. Results: In the base case analysis of this model, the mean (SD) age was 72.5 (7.5) years, and 50% of the individuals were women. All 6 screening strategies using wrist-worn wearable devices were estimated to be more effective than no screening (range of QALYs gained vs no screening, 226-957 per 100 000 individuals) and were associated with greater relative benefit than screening using traditional modalities (range of QALYs gained vs no screening, -116 to 93 per 100 000 individuals). Compared with no screening, screening using wrist-worn wearable devices was associated with a reduction in stroke incidence by 20 to 23 per 100 000 person-years but an increase in major bleeding by 20 to 44 per 100 000 person-years. The overall preferred strategy was wearable photoplethysmography, followed conditionally by wearable electrocardiography with patch monitor confirmation, which had an incremental cost-effectiveness ratio of $57 894 per QALY, meeting the acceptability threshold of $100 000 per QALY. The cost-effectiveness of screening was consistent across multiple scenarios, including strata of sex, screening at earlier ages (eg, ≥50 years), and with variation in the association of anticoagulation with risk of stroke in the setting of screening-detected AF. Conclusions and Relevance: This economic evaluation of AF screening using a microsimulation decision-analytic model suggests that screening using wearable devices is cost-effective compared with either no screening or AF screening using traditional methods.

Comparative Clinical Effectiveness of Population-Based Atrial Fibrillation Screening Using Contemporary Modalities: A Decision-Analytic Model.

Background Atrial fibrillation (AF) screening is endorsed by certain guidelines for individuals aged ≥65 years. Yet many AF screening strategies exist, including the use of wrist-worn wearable devices, and their comparative effectiveness is not well-understood. Methods and Results We developed a decision-analytic model simulating 50 million individuals with an age, sex, and comorbidity profile matching the United States population aged ≥65 years (ie, with a guideline-based AF screening indication). We modeled no screening, in addition to 45 distinct AF screening strategies (comprising different modalities and screening intervals), each initiated at a clinical encounter. The primary effectiveness measure was quality-adjusted life-years, with incident stroke and major bleeding as secondary measures. We defined continuous or nearly continuous modalities as those capable of monitoring beyond a single time-point (eg, patch monitor), and discrete modalities as those capable of only instantaneous AF detection (eg, 12-lead ECG). In total, 10 AF screening strategies were effective compared with no screening (300-1500 quality-adjusted life-years gained/100 000 individuals screened). Nine (90%) effective strategies involved use of a continuous or nearly continuous modality such as patch monitor or wrist-worn wearable device, whereas 1 (10%) relied on discrete modalities alone. Effective strategies reduced stroke incidence (number needed to screen to prevent a stroke: 3087-4445) but increased major bleeding (number needed to screen to cause a major bleed: 1815-4049) and intracranial hemorrhage (number needed to screen to cause intracranial hemorrhage: 7693-16 950). The test specificity was a highly influential model parameter on screening effectiveness. Conclusions When modeled from a clinician-directed perspective, the comparative effectiveness of population-based AF screening varies substantially upon the specific strategy used. Future screening interventions and guidelines should consider the relative effectiveness of specific AF screening strategies.

Risk assessment for incident heart failure in individuals with atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a strong risk factor for heart failure (HF); HF onset in patients with AF is associated with increased morbidity and mortality. Risk factors that predict HF in individuals with AF in the community are not well established. METHODS AND RESULTS: We examined clinical variables related to the 10-year incidence of HF in 725 individuals (mean 73.3 years, 45% women) with documented AF in the Framingham Heart Study. Event rates for incident HF (n = 161, 48% in women) were comparable in women (4.30 per 100 person-years) and men (3.34 per 100 person-years). Age, body mass index, ECG LV hypertrophy, diabetes, significant murmur, and history of myocardial infarction were positively associated with incident HF in multivariable models (C-statistic 0.71; 95% confidence interval 0.67-0.75). We developed a risk algorithm for estimating absolute risk of HF in AF patients with good model fit and calibration (adjusted calibration χ2 statistic 7.29; P(χ2) = 0.61). Applying the algorithm, 47.6% of HF events occurred in the top tertile in men compared with 13.1% in the bottom tertile, and 58.4% in women in the upper tertile compared with 18.2% in the lowest category. For HF type, women had a non-significantly higher incidence of HF with preserved EF compared with men. CONCLUSIONS: We describe advancing age, LV hypertrophy, body mass index, diabetes, significant heart murmur, and history of myocardial infarction as clinical predictors of incident HF in individuals with AF. A risk algorithm may help identify individuals with AF at high risk of developing HF.

Outcomes of Medicare beneficiaries undergoing catheter ablation for atrial fibrillation.

BACKGROUND: Atrial fibrillation is common among older persons. Catheter ablation is increasingly used in patients for whom medical therapy has failed. METHODS AND RESULTS: We conducted a retrospective cohort study of all fee-for-service Medicare beneficiaries ≥65 years of age who underwent catheter ablation for atrial fibrillation between July 1, 2007, and December 31, 2009. The main outcome measures were major complications within 30 days and mortality, heart failure, stroke, hospitalization, and repeat ablation within 1 year. A total of 15 423 patients underwent catheter ablation for atrial fibrillation. Mean age was 72 years; 41% were women; and >95% were white. For every 1000 procedures, there were 17 cases of hemopericardium requiring intervention, 8 cases of stroke, and 8 deaths within 30 days. More than 40% of patients required hospitalization within 1 year; however, atrial fibrillation or flutter was the primary discharge diagnosis in only 38.4% of cases. Eleven percent of patients underwent repeat ablation within 1 year. Renal impairment (hazard ratio, 2.07; 95% confidence interval, 1.66-2.58), age ≥80 years (hazard ratio, 3.09; 95% confidence interval, 2.32-4.11), and heart failure (hazard ratio, 2.54; 95% confidence interval, 2.07-3.13) were major risk factors for 1-year mortality. Advanced age was a major risk factor for all adverse outcomes. CONCLUSIONS: Major complications after catheter ablation for atrial fibrillation were associated with advanced age but were fairly infrequent. Few patients underwent repeat ablation. Randomized trials are needed to inform risk-benefit calculations for older persons with drug-refractory, symptomatic atrial fibrillation.

The impact of new and emerging clinical data on treatment strategies for atrial fibrillation.

INTRODUCTION: The Atrial Fibrillation (AF) Exchange Group, an international multidisciplinary group concerned with the management of AF, was convened to review recent advances in the field and the potential impact on treatment strategies. METHODS: Issues discussed included epidemiology and the impact of the rising incidence of AF on health care systems, developments in pharmacological and surgical interventions in the management of arrhythmias and thromboprophylaxis, the potential to affect treatment strategies, and barriers to implementing them. RESULTS: The incidence of AF and the associated burden on health care systems are increasing with aging populations, prevalence of comorbidities and more effective treatment of cardiovascular diseases. Advances in available medical treatments, in particular dronedarone and dabigatran, with other products in development, offer the possibility of changes in treatment paradigms and a greater emphasis on reducing hospitalizations and improvement in long-term outcomes instead of a symptom/safety-driven approach in which the priority is symptom suppression without provoking drug toxicity. Developments in catheter ablation techniques may mean that, in experienced centers, ablation may be offered as first-line treatment in selected patient populations. Barriers to optimal treatment include underdiagnosis, lack of recognition as a serious condition and as a risk factor for stroke, limited access to care, inadequate implementation of guidelines, and poor adherence to treatment. CONCLUSIONS: The focus of the management of AF may be changing as a consequence of new treatments based on the outcome improvements they offer. However, the benefits will not be fully realized if guidelines and guidance are not observed in routine clinical practice.

P-wave indices, distribution and quality control assessment (from the Framingham Heart Study).

BACKGROUND: P-wave indices of maximum P-wave duration and P-wave dispersion have been examined in a broad array of cardiovascular and noncardiovascular disease states. The P-wave indices literature has been highly heterogeneous in measurement methodologies, described quality control metrics, and distribution of values. We therefore sought to determine the reproducibility of P-wave indices in a community-based cohort. METHODS: P-wave indices were measured in sequential subjects enrolled in the Framingham Heart Study. Electrocardiograms were obtained at the 11th biennial visit of the Original Cohort (n = 250) and the initial visit of the Offspring Cohort (n = 252). We determined the mean P-wave durations, interlead correlations, and P-wave indices. We then chose 20 ECGs, 10 from each cohort, and assessed intrarater and interrater variability. RESULTS: The maximum P-wave duration ranged from 71 to 162 ms with mean of 112 + or - 12 ms. The minimum P-wave duration ranged from 35 to 103 ms with mean of 65 + or - 10 ms. P-wave dispersion ranged from 12 to 82 ms. The mean P-wave dispersion was 48 + or - 12 ms (40-56). The intrarater intraclass correlation coefficient (ICC) was r = 0.80 for maximum P-wave duration and r = 0.82 for P-wave dispersion. The interrater ICC was 0.56 for maximum P-wave duration and 0.70 for P-wave dispersion. CONCLUSIONS: We demonstrated excellent intrarater reproducibility and fair interrater reproducibility for calculating P-wave indices. Reproducibility is frequently lacking in studies of P-wave indices, but is an essential component for the field's growth and epidemiologic contribution.

In vivo recording of adult zebrafish electrocardiogram and assessment of drug-induced QT prolongation.

In the last decade the zebrafish has become a major model organism for the study of development and organogenesis. To maximize the experimental utility of this organism, it will be important to establish methods for adult phenotyping. We previously proposed that the embryonic zebrafish may be useful in high-throughput screening for drug-induced cardiotoxicity. We now describe a method for the reproducible recording of the adult zebrafish ECG and illustrate its application in the investigation of QT-prolonging drugs. Zebrafish ECGs were obtained by inserting two needle electrodes through the ventral epidermis. Fish were perfused orally, and motion artifacts were eliminated with a paralytic dose of mu-conotoxin GIIIB. Test compounds were delivered via the perfusion system. Without a means of hydration and oxygenation, the fish succumb rapidly. The use of a perfusion system allowed stable recording for > 6 h. Baseline conduction intervals were as follows: PR, 66 ms (SD 14); QRS, 34 ms (SD 11); QT, 242 ms (SD 54); and R-R, 398 ms (SD 77). The known QT-prolonging agents astemizole, haloperidol, pimozide, and terfenadine caused corrected QT increases of 18% (SD 9), 16% (SD 11), 17% (SD 9), and 11% (SD 6), respectively. The control drugs clonidine, penicillin and propranolol did not prolong the corrected QT interval. In conclusion, perfusion and muscular paralysis allows stable, low-noise recording of zebrafish ECGs. Agents known to cause QT prolongation in humans caused QT prolongation in fish in each case. The development of rigorous tools for the phenotyping of adult zebrafish will complement the high-throughput assays currently under development for embryonic and larval fish.