BACKGROUND:The long-term probability of developing atrial fibrillation (AF) considering genetic predisposition and clinical risk factor burden is unknown.
METHODS:We estimated the lifetime risk of AF ...in individuals from the community-based Framingham Heart Study. Polygenic risk for AF was derived using a score of ≈1000 AF-associated single-nucleotide polymorphisms. Clinical risk factor burden was calculated for each individual using a validated risk score for incident AF comprised of height, weight, systolic and diastolic blood pressure, current smoking status, antihypertensive medication use, diabetes mellitus, history of myocardial infarction, and history of heart failure. We estimated the lifetime risk of AF within tertiles of polygenic and clinical risk.
RESULTS:Among 4606 participants without AF at 55 years of age, 580 developed incident AF (median follow-up, 9.4 years; 25th–75th percentile, 4.4–14.3 years). The lifetime risk of AF >55 years of age was 37.1% and was substantially influenced by both polygenic and clinical risk factor burden. Among individuals free of AF at 55 years of age, those in low-polygenic and clinical risk tertiles had a lifetime risk of AF of 22.3% (95% confidence interval, 15.4−9.1), whereas those in high-risk tertiles had a risk of 48.2% (95% confidence interval, 41.3−55.1). A lower clinical risk factor burden was associated with later AF onset after adjusting for genetic predisposition (P<0.001).
CONCLUSIONS:In our community-based cohort, the lifetime risk of AF was 37%. Estimation of polygenic AF risk is feasible and together with clinical risk factor burden explains a substantial gradient in long-term AF risk.
Scleroderma-associated pulmonary arterial hypertension (SSc-PAH) is a rare disease characterized by a very dismal response to therapy and poor survival. We assessed the effects of up-front ...combination PAH therapy in patients with SSc-PAH.
In this prospective, multicenter, open-label trial, 24 treatment-naive patients with SSc-PAH received ambrisentan 10 mg and tadalafil 40 mg daily for 36 weeks. Functional, hemodynamic, and imaging (cardiac magnetic resonance imaging and echocardiography) assessments at baseline and 36 weeks included changes in right ventricular (RV) mass and pulmonary vascular resistance as co-primary endpoints and stroke volume/pulmonary pulse pressure ratio, tricuspid annular plane systolic excursion, 6-minute walk distance, and N-terminal pro-brain natriuretic peptide as secondary endpoints.
At 36 weeks, we found that treatment had resulted in significant reductions in median (interquartile range IQR) RV mass (28.0 g IQR, 20.6-32.9 vs. 32.5 g IQR, 23.2-41.4; P < 0.05) and median pulmonary vascular resistance (3.1 Wood units IQR, 2.0-5.7 vs. 6.9 Wood units IQR, 4.0-12.9; P < 0.0001) and in improvements in median stroke volume/pulmonary pulse pressure ratio (2.6 ml/mm Hg IQR, 1.8-3.5 vs. 1.4 ml/mm Hg IQR 8.9-2.4; P < 0.0001) and mean ( ± SD) tricuspid annular plane systolic excursion (2.2 ± 0.12 cm vs. 1.65 ± 0.11 cm; P < 0.0001), 6-minute walk distance (395 ± 99 m vs. 343 ± 131 m; P = 0.001), and serum N-terminal pro-brain natriuretic peptide (647 ± 1,127 pg/ml vs. 1,578 ± 2,647 pg/ml; P < 0.05).
Up-front combination therapy with ambrisentan and tadalafil significantly improved hemodynamics, RV structure and function, and functional status in treatment-naive patients with SSc-PAH and may represent a very effective therapy for this patient population. In addition, we identified novel hemodynamic and imaging biomarkers that could have potential value in future clinical trials. Clinical trial registered with www.clinicaltrials.gov (NCT01042158).
Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified.
We assessed the contribution ...of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability,
) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated
using a variance components method with variants having a minor allele frequency ≥1%. We evaluated
in age, sex, and genomic strata of interest. The
for AF was 22.1% (95% confidence interval, 15.6%-28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%-25.6%). Only 6.4% (95% confidence interval, 5.1%-7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions.
Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that further genetic discovery, with an emphasis on common variation, is warranted to understand the causal genetic basis of AF.
BACKGROUND:Atrial fibrillation (AF) may occur after an acute precipitant and subsequently resolve. Management guidelines for AF in these settings are unclear as the risk of recurrent AF and related ...morbidity is poorly understood. We examined the relations between acute precipitants of AF and long-term recurrence of AF in a clinical setting.
METHODS:From a multi-institutional longitudinal electronic medical record database, we identified patients with newly diagnosed AF between 2000 and 2014. We developed algorithms to identify acute AF precipitants (surgery, sepsis, pneumonia, pneumothorax, respiratory failure, myocardial infarction, thyrotoxicosis, alcohol, pericarditis, pulmonary embolism, and myocarditis). We assessed risks of AF recurrence in individuals with and without a precipitant and the relations between AF recurrence and heart failure, stroke, and mortality.
RESULTS:Among 10 723 patients with newly diagnosed AF (67.9±9.9 years, 41% women), 19% had an acute AF precipitant, the most common of which were cardiac surgery (22%), pneumonia (20%), and noncardiothoracic surgery (15%). The cumulative incidence of AF recurrence at 5 years was 41% among individuals with a precipitant compared with 52% in those without a precipitant (adjusted hazard ratio HR, 0.75 95% CI, 0.69–0.81; P<0.001). The lowest risk of recurrence among those with precipitants occurred with postoperative AF (5-year incidence 32% in cardiac surgery and 39% in noncardiothoracic surgery). Regardless of the presence of an initial precipitant, recurrent AF was associated with increased adjusted risks of heart failure (hazard ratio, 2.74 95% CI, 2.39–3.15; P<0.001), stroke (hazard ratio, 1.57 95% CI, 1.30–1.90; P<0.001), and mortality (hazard ratio, 2.96 95% CI, 2.70–3.24; P<0.001).
CONCLUSIONS:AF after an acute precipitant frequently recurs, although the risk of recurrence is lower than among individuals without an acute precipitant. Recurrence is associated with substantial long-term morbidity and mortality. Future studies should address surveillance and management after newly diagnosed AF in the setting of an acute precipitant.
BACKGROUND AND PURPOSE—Classification of stroke as cardioembolic in etiology can be challenging, particularly since the predominant cause, atrial fibrillation (AF), may not be present at the time of ...stroke. Efficient tools that discriminate cardioembolic from noncardioembolic strokes may improve care as anticoagulation is frequently indicated after cardioembolism. We sought to assess and quantify the discriminative power of AF risk as a classifier for cardioembolism in a real-world population of patients with acute ischemic stroke.
METHODS—We performed a cross-sectional analysis of a multi-institutional sample of patients with acute ischemic stroke. We systematically adjudicated stroke subtype and examined associations between AF risk using CHA2DS2-VASc, Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score, and the recently developed Electronic Health Record–Based AF score, and cardioembolic stroke using logistic regression. We compared the ability of AF risk to discriminate cardioembolism by calculating C statistics and sensitivity/specificity cutoffs for cardioembolic stroke.
RESULTS—Of 1431 individuals with ischemic stroke (age, 65±15; 40% women), 323 (22.6%) had cardioembolism. AF risk was significantly associated with cardioembolism (CHA2DS2-VAScodds ratio OR per SD, 1.69 95% CI, 1.49–1.93; Cohorts for Heart and Aging Research in Genomic Epidemiology-AF scoreOR, 2.22 95% CI, 1.90–2.60; electronic Health Record–Based AFOR, 2.55 95% CI, 2.16–3.04). Discrimination was greater for Cohorts for Heart and Aging Research in Genomic Epidemiology-AF score (C index, 0.695 95% CI, 0.663–0.726) and Electronic Health Record–Based AF score (0.713 95% CI, 0.681–0.744) versus CHA2DS2-VASc (C index, 0.651 95% CI, 0.619–0.683). Examination of AF scores across a range of thresholds indicated that AF risk may facilitate identification of individuals at low likelihood of cardioembolism (eg, negative likelihood ratios for Electronic Health Record–Based AF score ranged 0.31–0.10 at sensitivity thresholds 0.90–0.99).
CONCLUSIONS—AF risk scores associate with cardioembolic stroke and exhibit moderate discrimination. Utilization of AF risk scores at the time of stroke may be most useful for identifying individuals at low probability of cardioembolism. Future analyses are warranted to assess whether stroke subtype classification can be enhanced to improve outcomes in undifferentiated stroke.
Background
Oral anticoagulants reduce the risk of stroke in patients with atrial fibrillation. However, many patients with atrial fibrillation at elevated stroke risk are not treated with oral ...anticoagulants.
Objective
To test whether electronic notifications sent to primary care physicians increase the proportion of ambulatory patients prescribed oral anticoagulants.
Design
Randomized controlled trial conducted from February to May 2017 within 18 practices in an academic primary care network.
Participants
Primary care physicians (
n
= 175) and their patients with atrial fibrillation, at elevated stroke risk, and not prescribed oral anticoagulants.
Intervention
Patients of each physician were randomized to the notification or usual care arm. Physicians received baseline email notifications and up to three reminders with patient information, educational material and primary care guidelines for anticoagulation management, and surveys in the notification arm.
Main Measures
The primary outcome was the proportion of patients prescribed oral anticoagulants at 3 months in the notification (
n
= 972) vs. usual care (
n
= 1364) arms, compared using logistic regression with clustering by physician. Secondary measures included survey-based physician assessment of reasons why patients were not prescribed oral anticoagulants and how primary care physicians might be influenced by the notification.
Key Results
Over 3 months, a small proportion of patients were newly prescribed oral anticoagulants with no significant difference in the notification (3.9%, 95% CI 2.8–5.3%) and usual care (3.2%, 95% CI 2.4–4.2%) arms (
p
= 0.37). The most common, non-exclusive reasons why patients were not on oral anticoagulants included atrial fibrillation was transient (30%) or paroxysmal (12%), patient/family declined (22%), high bleeding risk (20%), fall risk (19%), and frailty (10%). For 95% of patients, physicians stated they would not change their management after reviewing the alert.
Conclusions
Electronic physician notification did not increase anticoagulation in patients with atrial fibrillation at elevated stroke risk. Primary care physicians did not prescribe anticoagulants because they perceived the bleeding risk was too high or stroke risk was too low.
Trial Registration
ClinicalTrials.gov
identifier NCT02950285
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This study sought to determine whether the risk of atrial fibrillation AF can be estimated accurately by using routinely ascertained features in the electronic health record (EHR) and whether AF risk ...is associated with stroke.
Early diagnosis of AF and treatment with anticoagulation may prevent strokes.
Using a multi-institutional EHR, this study identified 412,085 individuals 45 to 95 years of age without prevalent AF between 2000 and 2014. A prediction model was derived and validated for 5-year AF risk by using split-sample validation and model performance was compared with other methods of AF risk assessment.
Within 5 years, 14,334 individuals developed AF. In the derivation sample (7,216 AF events of 206,042 total), the optimal risk model included sex, age, race, smoking, height, weight, diastolic blood pressure, hypertension, hyperlipidemia, heart failure, coronary heart disease, valvular disease, prior stroke, peripheral arterial disease, chronic kidney disease, hypothyroidism, and quadratic terms for height, weight, and age. In the validation sample (7,118 AF events of 206,043 total) the AF risk model demonstrated good discrimination (C-statistic: 0.777; 95% confidence interval CI: 0.771 to 0.783) and calibration (0.99; 95% CI: 0.96 to 1.01). Model discrimination and calibration were superior to CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) (C-statistic: 0.753; 95% CI: 0.747 to 0.759; calibration slope: 0.72; 95% CI: 0.71 to 0.74), C2HEST (Coronary artery disease / chronic obstructive pulmonary disease; Hypertension; Elderly age ≥75 years; Systolic heart failure; Thyroid disease hyperthyroidism) (C-statistic: 0.754; 95% CI: 0.747 to 0.762; calibration slope: 0.44; 95% CI: 0.43 to 0.45), and CHA2DS2-VASc (Congestive heart failure, Hypertension, Age ≥75 years, Diabetes mellitus, Prior stroke, transient ischemic attack TIA, or thromboembolism, Vascular disease, Age 65–74 years, Sex category female) scores (C-statistic: 0.702; 95% CI: 0.693 to 0.710; calibration slope: 0.37; 95% CI: 0.36 to 0.38). AF risk discriminated incident stroke (n = 4,814; C-statistic: 0.684; 95% CI: 0.677 to 0.692) and stroke within 90 days of incident AF (n = 327; C-statistic: 0.789; 95% CI: 0.764 to 0.814).
A model developed from a real-world EHR database predicted AF accurately and stratified stroke risk. Incorporating AF prediction into EHRs may enable risk-guided screening for AF.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective: Accurate ascertainment of comorbidities is paramount in clinical research. While manual adjudication is labor‐intensive and expensive, the adoption of electronic health records enables ...computational analysis of free‐text documentation using natural language processing (NLP) tools.
Hypothesis: We sought to develop highly accurate NLP modules to assess for the presence of five key cardiovascular comorbidities in a large electronic health record system.
Methods: One‐thousand clinical notes were randomly selected from a cardiovascular registry at Mass General Brigham. Trained physicians manually adjudicated these notes for the following five diagnostic comorbidities: hypertension, dyslipidemia, diabetes, coronary artery disease, and stroke/transient ischemic attack. Using the open‐source Canary NLP system, five separate NLP modules were designed based on 800 “training‐set” notes and validated on 200 “test‐set” notes.
Results: Across the five NLP modules, the sentence‐level and note‐level sensitivity, specificity, and positive predictive value was always greater than 85% and was most often greater than 90%. Accuracy tended to be highest for conditions with greater diagnostic clarity (e.g. diabetes and hypertension) and slightly lower for conditions whose greater diagnostic challenges (e.g. myocardial infarction and embolic stroke) may lead to less definitive documentation.
Conclusion: We designed five open‐source and highly accurate NLP modules that can be used to assess for the presence of important cardiovascular comorbidities in free‐text health records. These modules have been placed in the public domain and can be used for clinical research, trial recruitment and population management at any institution as well as serve as the basis for further development of cardiovascular NLP tools.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Oral anticoagulation (OAC) is effective yet reportedly underutilized for stroke prevention in atrial fibrillation (AF). Factors associated with delayed OAC after incident AF are unknown. Using a ...large electronic medical record, we identified incident episodes of AF diagnosed in 2006 to 2014 using a validated algorithm. Among patients with a Congestive heart failure, Hypertension, Age, Diabetes, and Stroke (CHADS2) score ≥1 started on OAC within 1 year, we examined baseline characteristics at AF diagnosis and their association with time to OAC using multivariable Cox proportional hazards modeling. Of 4,388 patients with incident AF and CHADS2 score ≥1 who were started on OAC within 1 year, the mean age was 72.6, and 41% were women. Median time to OAC was 5 days (interquartile range 1 to 43), and most patients received warfarin (86.3%). Among patients without prevalent stroke, 98 strokes (2.2% of the sample) occurred between AF diagnosis and OAC initiation. In multivariable analyses, several factors were associated with delayed OAC including female gender (hazard ratio HR 1.08, 95% confidence interval CI 1.01 to 1.15), absence of hypertension (HR 1.15, 95% CI 1.03 to 1.27), previous fall (HR 1.53, 95% CI 1.08 to 2.17), and chronic kidney disease (HR 1.12, 95% CI 1.04 to 1.21). Among women, OAC prescription at 1, 3, and 6 months was 70.0%, 81.7%, and 89.5%, respectively, whereas for men, OAC prescription was 73.4%, 84.0%, and 91.5%, respectively. Most patients with new AF and elevated stroke risk started on OAC receive it within 1 week, although the promptness of initiation varies. The stroke rate is substantial in the period between AF diagnosis and OAC initiation. Interventions targeting identified risk factors for delayed OAC may result in improved outcomes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Lipoprotein(a) Lp(a) is independently associated with atherosclerotic cardiovascular disease and calcific aortic valve stenosis. Elevated Lp(a) affects approximately one in five individuals and ...meaningfully contributes to the residual cardiovascular risk in individuals with otherwise well‐controlled risk factors. With targeted therapies in the therapeutic pipeline, there is a need to further characterize the clinical phenotypes and outcomes of individuals with elevated levels of this unique biomarker. The Mass General Brigham Lp(a) Registry will be built from the longitudinal electronic health record of two large academic medical centers in Boston, Massachusetts, to develop a detailed cohort of patients who have had their Lp(a) measured. In combination with structured data sources, clinical documentation will be analyzed using natural language processing techniques to accurately characterize baseline characteristics. Important outcome measures including all‐cause mortality, cardiovascular mortality, and cardiovascular events will be available for analysis. Approximately 30 000 patients who have had their Lp(a) tested within the Mass General Brigham system from January 2000 to July 2019 will be included in the registry. This large Lp(a) cohort will provide meaningful observational data regarding the differential risk associated with Lp(a) values and cardiovascular disease. With a new frontier of targeted Lp(a) therapies on the horizon, the Mass General Brigham Lp(a) Registry will help provide a deeper understanding of Lp(a)'s role in long term cardiovascular outcomes.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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