Predisposing Factors Associated With Development of Persistent Compared With Paroxysmal Atrial Fibrillation

Background: Once atrial fibrillation (AF) progresses to sustained forms, adverse outcomes increase and treatment success rates decrease. Therefore, identification of risk factors predisposing to persistence of AF may have a significant impact on AF morbidity. Methods and Results: We prospectively examined the differential associations between traditional, lifestyle, and biomarker AF risk factors and development of paroxysmal versus nonparoxysmal AF (persistent/permanent) among 34 720 women enrolled in the Women's Health Study who were free of cardiovascular disease and AF at baseline. AF patterns were defined based on current guidelines and classified according to the most sustained form of AF within 2 years of diagnosis. During a median follow‐up of 16.4 years, 690 women developed paroxysmal AF and 349 women developed nonparoxysmal AF. In multivariable time‐varying competing risk models, increasing age (hazard ratio [HR] 1.11, 95% CI 1.10 to 1.13, versus HR 1.08, 1.07 to 1.09, per year), body mass index (HR 1.07, 1.05 to 1.09, versus HR 1.03, 1.02 to 1.05, per kg/m2), and weight (HR 1.30, 1.22 to 1.39, versus HR 1.14, 1.08 to 1.20, per 10 kg) were more strongly associated with the development of nonparoxysmal AF compared with paroxysmal AF. Hemoglobin A1c levels at baseline were directly related to the development of nonparoxysmal AF but inversely associated with paroxysmal AF in multivariable competing risk models (P for nonequal association=0.01). Conclusions: In women without AF or CVD at baseline, increasing age, adiposity, and higher hemoglobin A1c levels were preferentially associated with the early development of nonparoxysmal AF. These data raise the hypothesis that efforts aimed at weight reduction or glycemic control may affect the proportion of the population with sustained AF

Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality

Background. Pre-operative risk assessments used in clinical practice are limited in their ability to identify risk for post-operative mortality. We hypothesize that electrocardiograms contain hidden risk markers that can help prognosticate post-operative mortality. Methods. In a derivation cohort of 45,969 pre-operative patients (age 59+- 19 years, 55 percent women), a deep learning algorithm was developed to leverage waveform signals from pre-operative ECGs to discriminate post-operative mortality. Model performance was assessed in a holdout internal test dataset and in two external hospital cohorts and compared with the Revised Cardiac Risk Index (RCRI) score. Results. In the derivation cohort, there were 1,452 deaths. The algorithm discriminates mortality with an AUC of 0.83 (95% CI 0.79-0.87) surpassing the discrimination of the RCRI score with an AUC of 0.67 (CI 0.61-0.72) in the held out test cohort. Patients determined to be high risk by the deep learning model's risk prediction had an unadjusted odds ratio (OR) of 8.83 (5.57-13.20) for post-operative mortality as compared to an unadjusted OR of 2.08 (CI 0.77-3.50) for post-operative mortality for RCRI greater than 2. The deep learning algorithm performed similarly for patients undergoing cardiac surgery with an AUC of 0.85 (CI 0.77-0.92), non-cardiac surgery with an AUC of 0.83 (0.79-0.88), and catherization or endoscopy suite procedures with an AUC of 0.76 (0.72-0.81). The algorithm similarly discriminated risk for mortality in two separate external validation cohorts from independent healthcare systems with AUCs of 0.79 (0.75-0.83) and 0.75 (0.74-0.76) respectively. Conclusion. The findings demonstrate how a novel deep learning algorithm, applied to pre-operative ECGs, can improve discrimination of post-operative mortality

Estimated stroke risk, yield, and number needed to screen for atrial fibrillation detected through single time screening: a multicountry patient-level meta-analysis of 141,220 screened individuals

BackgroundThe precise age distribution and calculated stroke risk of screen-detected atrial fibrillation (AF) is not known. Therefore, it is not possible to determine the number needed to screen (NNS) to identify one treatable new AF case (NNS-Rx) (i.e., Class-1 oral anticoagulation [OAC] treatment recommendation) in each age stratum. If the NNS-Rx is known for each age stratum, precise cost-effectiveness and sensitivity simulations can be performed based on the age distribution of the population/region to be screened. Such calculations are required by national authorities and organisations responsible for health system budgets to determine the best age cutoffs for screening programs and decide whether programs of screening should be funded. Therefore, we aimed to determine the exact yield and calculated stroke-risk profile of screen-detected AF and NNS-Rx in 5-year age strata.Methods and findingsA systematic review of Medline, Pubmed, and Embase was performed (January 2007 to February 2018), and AF-SCREEN international collaboration members were contacted to identify additional studies. Twenty-four eligible studies were identified that performed a single time point screen for AF in a general ambulant population, including people ≥65 years. Authors from eligible studies were invited to collaborate and share patient-level data. Statistical analysis was performed using random effects logistic regression for AF detection rate, and Poisson regression modelling for CHA2DS2-VASc scores. Nineteen studies (14 countries from a mix of low- to middle- and high-income countries) collaborated, with 141,220 participants screened and 1,539 new AF cases. Pooled yield of screening was greater in males across all age strata. The age/sex-adjusted detection rate for screen-detected AF in ≥65-year-olds was 1.44% (95% CI, 1.13%–1.82%) and 0.41% (95% CI, 0.31%–0.53%) for <65-year-olds. New AF detection rate increased progressively with age from 0.34% (<60 years) to 2.73% (≥85 years). Neither the choice of screening methodology or device, the geographical region, nor the screening setting influenced the detection rate of AF. Mean CHA2DS2-VASc scores (n = 1,369) increased with age from 1.1 (<60 years) to 3.9 (≥85 years); 72% of ≥65 years had ≥1 additional stroke risk factor other than age/sex. All new AF ≥75 years and 66% between 65 and 74 years had a Class-1 OAC recommendation. The NNS-Rx is 83 for ≥65 years, 926 for 60–64 years; and 1,089 for <60 years. The main limitation of this study is there are insufficient data on sociodemographic variables of the populations and possible ascertainment biases to explain the variance in the samples.ConclusionsPeople with screen-detected AF are at elevated calculated stroke risk: above age 65, the majority have a Class-1 OAC recommendation for stroke prevention, and >70% have ≥1 additional stroke risk factor other than age/sex. Our data, based on the largest number of screen-detected AF collected to date, show the precise relationship between yield and estimated stroke risk profile with age, and strong dependence for NNS-RX on the age distribution of the population to be screened: essential information for precise cost-effectiveness calculations

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

Multi-ethnic genome-wide association study for atrial fibrillation

Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF

Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec

Impact of Rural Residence on Warfarin Use and Clinical Events in Patients with Non-Valvular Atrial Fibrillation: A Canadian Population Based Study.

We studied whether anticoagulant use and outcomes differed between rural versus urban Canadian non-valvular atrial fibrillation (NVAF) patients prior to the introduction of direct oral anticoagulant drugs.Retrospective cohort study of 25,284 adult Albertans with NVAF between April 1, 1999 and December 31, 2008.Compared to urban patients, rural patients were older (p = 0.0009) and had more comorbidities but lower bleeding risk at baseline. In the first year after NVAF diagnosis, urban patients were less likely to be hospitalized (aOR 0.82, 95%CI 0.77-0.89) or have an emergency department visit for any reason (aOR 0.61, 95%CI 0.56-0.66) but warfarin dispensation rates (72.2% vs 71.8% at 365 days, p = 0.98) and clinical outcomes were similar: 7.8% died in both groups, 3.2% rural vs. 2.8% urban had a stroke or systemic embolism (SSE) (aOR 0.92, 95%CI 0.77-1.11), and 6.6% vs. 5.7% (aOR 0.93, 95%CI 0.81-1.06) had a bleed. Baseline SSE risk did not impact warfarin dispensation (73.0% in those with high vs. 72.8% in those with low CHADS2 score, p = 0.85) but patients at higher baseline bleeding risk were less likely to be using warfarin (69.2% high vs. 73.6% low HASBLED score, p<0.0001) in the first 365 days after diagnosis. In warfarin users, bleeding was more frequent (7.5% vs 6.2%, aHR 1.51 [95%CI 1.33-1.72]) but death or SSE was less frequent (7.0% vs 18.1%, aHR 0.60 [0.54-0.66]).Warfarin use and clinical event rates did not differ between rural and urban NVAF patients in a universal access publically-funded healthcare system

Trends in Uptake and Adherence to Oral Anticoagulation for Patients With Incident Atrial Fibrillation at High Stroke Risk Across Health Care Settings

Background Oral anticoagulation (OAC) therapy prevents morbidity and mortality in nonvalvular atrial fibrillation; whether location of diagnosis influences OAC uptake or adherence is unknown. Methods and Results Retrospective cohort study (2008–2019), identifying adults with incident nonvalvular atrial fibrillation across health care settings (emergency department, hospital, outpatient) at high risk of stroke. OAC uptake and adherence via proportion of days covered for direct OACs and time in therapeutic range for warfarin were measured. Proportion of days covered was categorized as low (0–39%), intermediate (40–79%), and high (80–100%). Warfarin control was defined as time in therapeutic range ≥65%. All‐cause mortality was examined at a 3‐year landmark. Among 75 389 patients with nonvalvular atrial fibrillation (47.0% women, mean 77.4 years), 19.7% were diagnosed in the emergency department, 59.1% in the hospital, and 21.2% in the outpatient setting. Ninety‐day OAC uptake was 51.6% in the emergency department, 50.9% in the hospital, and 67.9% in the outpatient setting (P<0.0001). High direct OAC adherence increased from 64.9% to 80.3% in the emergency department, 64.3% to 81.7% in the hospital, and 70.9% to 88.6% in the outpatient setting over time (P values for trend <0.0001). Warfarin control was 40.3% overall and remained unchanged. In multivariable analysis, outpatient diagnosis compared with the hospital was associated with greater OAC uptake (odds ratio [OR], 1.79; [95% CI, 1.72–1.87]) and direct OAC (OR, 1.42; [95% CI, 1.27–1.59]) and warfarin (OR, 1.49; [95% CI, 1.36–1.63]) adherence. Varying or persistently low adherence was associated with a poor prognosis, especially for warfarin. Conclusions Locale of nonvalvular atrial fibrillation diagnosis is associated with varying OAC uptake and adherence. Interventions specific to health care settings are needed to improve stroke prevention

Risk Factors for the Development of New-Onset Persistent Atrial Fibrillation: Subanalysis of the VITAL Study.

BACKGROUND Sustained forms of atrial fibrillation (AF) are associated with lower treatment success rates and poorer prognosis compared with paroxysmal AF. Yet, little is known about risk factors that predispose to persistent AF on initial presentation. Our objective was to define risk factors associated with new-onset persistent AF. METHODS We prospectively examined the differential associations between lifestyle, clinical, and socioeconomic risk factors and AF pattern (persistent versus paroxysmal) at the time of diagnosis among 25 119 participants without a history of cardiovascular disease, AF, or cancer in the VITAL rhythm study (Vitamin D and Omega-3). RESULTS During a median follow-up of 5.3 years, 900 participants developed AF and 346 (38.4%) were classified as persistent at the time of diagnosis. In multivariable competing risk models, increasing age, male sex, White race, height, weight, body mass index ≥30 kg/m2, hypertension, current or past smoking, alcohol intake ≥2 drinks/day, postcollege education, and randomized treatment with vitamin D were significantly associated with incident persistent AF. Compared with paroxysmal AF, increasing age, male sex, weight, body mass index ≥30 kg/m2, and postcollege education were more strongly associated with persistent AF in multivariable models regardless of whether interim cardiovascular disease and heart failure events were censored. CONCLUSIONS In a prospective cohort without baseline AF or cardiovascular disease, over one-third of AF at the time of diagnosis is persistent. Older age, male sex, postcollege education, and obesity were preferentially associated with persistent AF and represent a high-risk AF subset for population-based intervention