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.

Incidence and prognostic significance of newly-diagnosed atrial fibrillation among older U.S. veterans hospitalized with COVID-19.

Most prior studies on the prognostic significance of newly-diagnosed atrial fibrillation (AF) in COVID-19 did not differentiate newly-diagnosed AF from pre-existing AF. To determine the association between newly-diagnosed AF and in-hospital and 30-day mortality among regular users of Veterans Health Administration using data linked to Medicare. We identified Veterans aged ≥ 65 years who were hospitalized for ≥ 24 h with COVID-19 from 06/01/2020 to 1/31/2022 and had ≥ 2 primary care visits within 24 months prior to the index hospitalization. We performed multivariable logistic regression analyses to estimate adjusted risks, risk differences (RD), and odds ratios (OR) for the association between newly-diagnosed AF and the mortality outcomes adjusting for patient demographics, baseline comorbidities, and presence of acute organ dysfunction on admission. Of 23,299 patients in the study cohort, 5.3% had newly-diagnosed AF, and 29.2% had pre-existing AF. In newly-diagnosed AF adjusted in-hospital and 30-day mortality were 16.5% and 22.7%, respectively. Newly-diagnosed AF was associated with increased mortality compared to pre-existing AF (in-hospital: OR 2.02, 95% confidence interval [CI] 1.72-2.37; RD 7.58%, 95% CI 5.54-9.62) (30-day: OR 1.86; 95% CI 1.60-2.16; RD 9.04%, 95% CI 6.61-11.5) or no AF (in-hospital: OR 2.24, 95% CI 1.93-2.60; RD 8.40%, 95% CI 6.44-10.4) (30-day: 2.07, 95% CI 1.80-2.37; RD 10.2%, 95% CI 7.89-12.6). There was a smaller association between pre-existing AF and the mortality outcomes. Newly-diagnosed AF is an important prognostic marker for patients hospitalized with COVID-19. Whether prevention or treatment of AF improves clinical outcomes in these patients remains unknown.

The GenoVA study: Equitable implementation of a pragmatic randomized trial of polygenic-risk scoring in primary care.

Polygenic risk scores (PRSs) hold promise for disease risk assessment and prevention. The Genomic Medicine at Veterans Affairs (GenoVA) Study is addressing three main challenges to the clinical implementation of PRSs in preventive care: defining and determining their clinical utility, implementing them in time-constrained primary care settings, and countering their potential to exacerbate healthcare disparities. The study processes used to test patients, report their PRS results to them and their primary care providers (PCPs), and promote the use of those results in clinical decision-making are modeled on common practices in primary care. The following diseases were chosen for their prevalence and familiarity to PCPs: coronary artery disease; type 2 diabetes; atrial fibrillation; and breast, colorectal, and prostate cancers. A randomized clinical trial (RCT) design and primary outcome of time-to-new-diagnosis of a target disease bring methodological rigor to the question of the clinical utility of PRS implementation. The study's pragmatic RCT design enhances its relevance to how PRS might reasonably be implemented in primary care. Steps the study has taken to promote health equity include the thoughtful handling of genetic ancestry in PRS construction and reporting and enhanced recruitment strategies to address underrepresentation in research participation. To date, enhanced recruitment efforts have been both necessary and successful: participants of underrepresented race and ethnicity groups have been less likely to enroll in the study than expected but ultimately achieved proportional representation through targeted efforts. The GenoVA Study experience to date offers insights for evaluating the clinical utility of equitable PRS implementation in adult primary care.

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.

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.

ReducinG stroke by screening for UndiAgnosed atRial fibrillation in elderly inDividuals (GUARD-AF): Rationale and design of the GUARD-AF randomized trial of screening for atrial fibrillation with a 14-day patch-based continuous ECG monitor.

BACKGROUND: Screening for atrial fibrillation (AF) is attractive because AF independently raises the risk of ischemic stroke, this risk is largely reversible by long-term oral anticoagulant therapy (OAC), and many patients with AF remain undiagnosed and untreated. Recent trials of one-time brief screening for AF have not produced a significant increase in the proportion of patients diagnosed with AF. Trials of longer-term screening have demonstrated an increase in AF diagnoses, primarily paroxysmal AF. To date, however, no trials have demonstrated that screening for AF results in lower rates of stroke. Clinical practice guidelines conflict in their level of support for screening for AF. METHODS: The GUARD-AF individually randomized trial is designed to test whether screening for AF in individuals age 70 years or greater using a 2-week single-lead electrocardiographic patch monitor can identify patients with undiagnosed AF and lead to treatment with OAC, resulting in a reduced rate of stroke in the screened population. The trial's efficacy end point is hospitalization for stroke (either ischemic or hemorrhagic) and the trial's safety end point is hospitalization for a bleeding event. End points will be ascertained via Medicare claims or electronic health records at 2.5 years after study start. Enrollment is based in primary care practices and the OAC decision for screen-detected cases is left to the patient and their physician. The initial planned target sample size was 52,000, with 26,000 allocated to either screening or to usual care. RESULTS: Trial enrollment was severely hampered by the novel coronavirus disease 2019 (COVID-19) pandemic and stopped at a total enrollment of 11,931 participants. Of 5,965 randomized to the screening arm, 5,713 patients (96%) returned monitors with analyzable results. Incidence of screen-detected and clinically detected AF and associated stroke and bleeding outcomes will be ascertained. CONCLUSIONS: GUARD-AF is the largest AF screening randomized trial using a longer-term patch-based continuous electrocardiographic monitor. The results will contribute important information on the yield of patch-based AF screening, the "burden" of AF detected (percent time in AF, longest episode), and physicians' OAC decisions as a function of AF burden. GUARD-AF's stroke and bleed results will contribute to pooled trial analyses of AF screening, thereby informing future studies and guidelines.

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.

Comparative Effectiveness of Implantable Defibrillators for Asymptomatic Brugada Syndrome: A Decision-Analytic Model.

Background Optimal management of asymptomatic Brugada syndrome (BrS) with spontaneous type I electrocardiographic pattern is uncertain. Methods and Results We developed an individual-level simulation comprising 2 000 000 average-risk individuals with asymptomatic BrS and spontaneous type I electrocardiographic pattern. We compared (1) observation, (2) electrophysiologic study (EPS)-guided implantable cardioverter-defibrillator (ICD), and (3) upfront ICD, each using either subcutaneous or transvenous ICD, resulting in 6 strategies tested. The primary outcome was quality-adjusted life years (QALYs), with cardiac deaths (arrest or procedural-related) as a secondary outcome. We varied BrS diagnosis age and underlying arrest rate. We assessed cost-effectiveness at $100 000/QALY. Compared with observation, EPS-guided subcutaneous ICD resulted in 0.35 QALY gain/individual and 4130 cardiac deaths avoided/100 000 individuals, and EPS-guided transvenous ICD resulted in 0.26 QALY gain and 3390 cardiac deaths avoided. Compared with observation, upfront ICD reduced cardiac deaths by a greater margin (subcutaneous ICD, 8950; transvenous ICD, 6050), but only subcutaneous ICD improved QALYs (subcutaneous ICD, 0.25 QALY gain; transvenous ICD, 0.01 QALY loss), and complications were higher. ICD-based strategies were more effective at younger ages and higher arrest rates (eg, using subcutaneous devices, upfront ICD was the most effective strategy at ages 20-39.4 years and arrest rates >1.37%/year; EPS-guided ICD was the most effective strategy at ages 39.5-51.3 years and arrest rates 0.47%-1.37%/year, and observation was the most effective strategy at ages >51.3 years and arrest rates <0.47%/year). EPS-guided subcutaneous ICD was cost-effective ($80 508/QALY). Conclusions Device-based approaches (with or without EPS risk stratification) can be more effective than observation among selected patients with asymptomatic BrS. BrS management should be tailored to patient characteristics.

Rationale and design of a large population study to validate software for the assessment of atrial fibrillation from data acquired by a consumer tracker or smartwatch: The Fitbit heart study.

BACKGROUND: Early detection of atrial fibrillation or flutter (AF) may enable prevention of downstream morbidity. Consumer wrist-worn wearable technology is capable of detecting AF by identifying irregular pulse waveforms using photoplethysmography (PPG). The validity of PPG-based software algorithms for AF detection requires prospective assessment. METHODS: The Fitbit Heart Study (NCT04380415) is a single-arm remote clinical trial examining the validity of a novel PPG-based software algorithm for detecting AF. The proprietary Fitbit algorithm examines pulse waveform intervals during analyzable periods in which participants are sufficiently stationary. Fitbit consumers with compatible wrist-worn trackers or smartwatches were invited to participate. Enrollment began May 6, 2020 and as of October 1, 2020, 455,699 participants enrolled. Participants in whom an irregular heart rhythm was detected were invited to attend a telehealth visit and eligible participants were then mailed a one-week single lead electrocardiographic (ECG) patch monitor. The primary study objective is to assess the positive predictive value of an irregular heart rhythm detection for AF during the ECG patch monitor period. Additional objectives will examine the validity of irregular pulse tachograms during subsequent heart rhythm detections, self-reported AF diagnoses and treatments, and relations between irregular heart rhythm detections and AF episode duration and time spent in AF. CONCLUSIONS: The Fitbit Heart Study is a large-scale remote clinical trial comprising a unique software algorithm for detection of AF. The study results will provide critical insights into the use of consumer wearable technology for AF detection, and for characterizing the nature of AF episodes detected using consumer-based PPG technology.

Assessment of the Relationship Between Genetic Determinants of Thyroid Function and Atrial Fibrillation: A Mendelian Randomization Study.

Importance: Increased free thyroxine (FT4) and decreased thyrotropin are associated with increased risk of atrial fibrillation (AF) in observational studies, but direct involvement is unclear. Objective: To evaluate the potential direct involvement of thyroid traits on AF. Design, Setting, and Participants: Study-level mendelian randomization (MR) included 11 studies, and summary-level MR included 55 114 AF cases and 482 295 referents, all of European ancestry. Exposures: Genomewide significant variants were used as instruments for standardized FT4 and thyrotropin levels within the reference range, standardized triiodothyronine (FT3):FT4 ratio, hypothyroidism, standardized thyroid peroxidase antibody levels, and hyperthyroidism. Mendelian randomization used genetic risk scores in study-level analysis or individual single-nucleotide polymorphisms in 2-sample MR for the summary-level data. Main Outcomes and Measures: Prevalent and incident AF. Results: The study-level analysis included 7679 individuals with AF and 49 233 referents (mean age [standard error], 62 [3] years; 15 859 men [29.7%]). In study-level random-effects meta-analysis, the pooled hazard ratio of FT4 levels (nanograms per deciliter) for incident AF was 1.55 (95% CI, 1.09-2.20; P = .02; I2 = 76%) and the pooled odds ratio (OR) for prevalent AF was 2.80 (95% CI, 1.41-5.54; P = .003; I2 = 64%) in multivariable-adjusted analyses. The FT4 genetic risk score was associated with an increase in FT4 by 0.082 SD (standard error, 0.007; P < .001) but not with incident AF (risk ratio, 0.84; 95% CI, 0.62-1.14; P = .27) or prevalent AF (OR, 1.32; 95% CI, 0.64-2.73; P = .46). Similarly, in summary-level inverse-variance weighted random-effects MR, gene-based FT4 within the reference range was not associated with AF (OR, 1.01; 95% CI, 0.89-1.14; P = .88). However, gene-based increased FT3:FT4 ratio, increased thyrotropin within the reference range, and hypothyroidism were associated with AF with inverse-variance weighted random-effects OR of 1.33 (95% CI, 1.08-1.63; P = .006), 0.88 (95% CI, 0.84-0.92; P < .001), and 0.94 (95% CI, 0.90-0.99; P = .009), respectively, and robust to tests of horizontal pleiotropy. However, the subset of hypothyroidism single-nucleotide polymorphisms involved in autoimmunity and thyroid peroxidase antibodies levels were not associated with AF. Gene-based hyperthyroidism was associated with AF with MR-Egger OR of 1.31 (95% CI, 1.05-1.63; P = .02) with evidence of horizontal pleiotropy (P = .045). Conclusions and Relevance: Genetically increased FT3:FT4 ratio and hyperthyroidism, but not FT4 within the reference range, were associated with increased AF, and increased thyrotropin within the reference range and hypothyroidism were associated with decreased AF, supporting a pathway involving the pituitary-thyroid-cardiac axis.

Association of insurance type with receipt of oral anticoagulation in insured patients with atrial fibrillation: A report from the American College of Cardiology NCDR PINNACLE registry.

BACKGROUND: It is poorly understood whether insurance type may be a major contributor to the underuse of oral anticoagulation (OAC) among patients with atrial fibrillation (AF), particularly for novel oral anticoagulants (NOACs). METHODS: We performed a retrospective cohort registry study of patients with insurance, AF, CHA2DS2-VASc ≥2, and at least one outpatient encounter recorded in the ACC NCDR's PINNACLE Registry between January 1, 2011 and December 31, 2014. We used hierarchical regression, adjusting for patient characteristics and clustering by physician, to evaluate the association of insurance type (Private, Military, Medicare, Medicaid, Other) with receipt of OAC (any OAC, warfarin, or NOAC). RESULTS: In 363,309 patients (age 75±10; 48% female), we found a significant difference in proportions of OAC and NOAC prescription across insurance types (OAC: Military 53%, Private 53%, Medicare 52%, Other 41%, Medicaid 41%, P<.001; NOAC: Military 24%, Private 19%, Medicare 17%, Other 17%, Medicaid 8%, P<.001). After adjustment for patient characteristics and facility, private, Medicaid, and other insurance were independently associated with a lower odds of OAC prescription relative to Medicare, but military insured patients were not significantly different. After adjustment, military and private insurance were independently associated with a higher odds of NOAC prescription relative to Medicare, while Medicaid and other insurance were associated with a lower odds of NOAC prescription. CONCLUSIONS: In a contemporary US AF population, there was significant variation of OAC prescription across insurance plans, with the highest among private and Medicare insured patients. These differences may indicate that insurance plan, and its associated pharmacy benefits, affect the pace of diffusion of new therapies.

Contemporary Trends in Oral Anticoagulant Prescription in Atrial Fibrillation Patients at Low to Moderate Risk of Stroke After Guideline-Recommended Change in Use of the CHADS2 to the CHA2DS2-VASc Score for Thromboembolic Risk Assessment: Analysis From the National Cardiovascular Data Registry's Outpatient Practice Innovation and Clinical Excellence Atrial Fibrillation Registry.

BACKGROUND: Use of the CHA2DS2-VASc score instead of the CHADS2 score for thromboembolic risk stratification and initiation of oral anticoagulation (OAC) was recommended in the 2014 American Heart Association/American College of Cardiology/Heart Rhythm Society atrial fibrillation (AF) guidelines. We sought to define the proportion of patients with AF qualifying for and receiving OAC in contemporary practice by applying the CHA2DS2-VASc score to patients with a low CHADS2 score. METHODS AND RESULTS: Among patients with AF enrolled in the American College of Cardiology National Cardiovascular Data Registry's outpatient Practice Innovation and Clinical Excellence registry (2008-2014) CHADS2 score of 0 or 1, we calculated the impact of adoption of the CHA2DS2-VASc score on the proportion of patients with an indication for OAC. We examined trends in prescription of OAC overall, direct OAC (dabigatran/rivaroxaban/apixaban), and multivariable associations between clinical characteristics and OAC use. Of 346 068 patients with AF aged 65±12 years, 61% were men and 65% were white. In total, 24% of those with CHADS2=0 and 81% of those with a CHADS2=1 were reclassified as having a definite indication for OAC (CHA2DS2-VASc score ≥2). OAC use increased from 37% to 48% during the study period, and direct OAC use increased from 5% to 30%. Increasing CHA2DS2-VASc score (odds ratio, 2.07; 95% confidence interval, 1.97-2.19 for score of 4 versus 0) and rhythm control strategy (odds ratio, 1.34; 95% confidence interval, 1.30-1.39) were associated with increased OAC use. CONCLUSIONS: Adoption of the CHA2DS2-VASc score reclassifies 64.5% of patients with AF with low CHADS2 scores into a class I indication for OAC prescription. Overall OAC prescription increased between 2011 and 2014.

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.

A novel clinical prediction rule for 30-day mortality following balloon aortic valuloplasty: the CRRAC the AV score.

OBJECTIVES: We seek to identify predictors of 30-day mortality after balloon aortic valvuloplasty (BAV). BACKGROUND: To date, there is no validated method of predicting patient outcomes after percutaneous aortic valve interventions. METHODS: Data for consecutive patients with severe aortic stenosis who underwent BAV at the Mount Sinai Medical Center from January 2001 to July 2007 were retrospectively reviewed. Cox-proportional hazards regression was used to identify significant predictors of 30-day mortality, and the resultant model was compared to the EuroSCORE using Akaike's Information Criterion and area under the receiver-operating curve (AUC). RESULTS: The analysis included 281 patients (age 83 ± 9 years, 61% women, aortic valve area: 0.64 ± 0.2 cm(2)) and 36 (12.8%) of whom died within 30 days of BAV. With identified risk factors for 30-day mortality, critical status, renal dysfunction, right atrial pressure, and cardiac output, we constructed the CRRAC the AV risk score. Thirty-day survival was 72% in the highest tertile versus 94% in the lower two tertiles of the score. Compared to the additive and logistic EuroSCORE, the risk score demonstrated superior discrimination (AUC = 0.75 vs. 0.60 and 0.63, respectively). CONCLUSIONS: We derived a risk score, the CRRAC the AV score that identifies patients at high-risk of 30-day mortality after BAV. Validation of the developed risk prediction score, the CRRAC the AV score, is needed in other cohorts of post-BAV patients and potentially in patients undergoing other catheter-based valve interventions.