9 research outputs found
Clinical and structural risk factors predicting atrial fibrillation
Atrial fibrillation (AF) is associated with a high morbidity and mortality. Early identification of patients with AF may reduce morbidity and mortality. Current models predicting AF have limitations and focus on mainly clinical variables which are not always apparent in AF patients. Models focusing on pathophysiological mechanisms such as blood based biomarkers and ECG markers may be more accurate in identifying patients with AF. This study is based on the Birmingham and Black Country Atrial Fibrillation Registry (BBC-AF Registry) which recruited a cohort of 800 patients with and without AF. Blood based biomarkers and ECG markers were compared between the two groups of patients. The blood based biomarker analysis
using a novel proteomics chip technique demonstrated that BNP and a novel biomarker, fibroblast growth factor 23 (FGF-23) were increased in AF patients and were also independently predictive of AF. In the ECG analysis, QT interval was increased in AF patients and independently predicted AF. A combined model using blood based biomarkers, ECG markers and clinical variables demonstrated that a simple model consisting of simple clinical variables, QT interval, BNP and FGF-23 had a good ability to predict AF and performed better than contemporary AF prediction models in the current literature
An angiopoietin 2, FGF23, and BMP10 biomarker signature differentiates atrial fibrillation from other concomitant cardiovascular conditions
Abstract Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years [Q1, Q3 60, 78]; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 [95% CI 0.712, 0.775]). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 [95% CI 0.745, 0.822]). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation
Oral anticoagulation after catheter ablation of atrial fibrillation:caught in the attribution trap?
This editorial refers to ‘Oral anticoagulation therapy after radiofrequency ablation of atrial fibrillation and the risk of thromboembolism and serious bleeding: long-term follow-up in nationwide cohort of Denmark’, by D. Karasoy et al. on page, doi:10.1093/eurheartj/ehu421 Catheter ablation procedures are performed in 5-10 % of patients suffering from atrial fibrillation (AF).1 – 3 While the main reason for undertaking AF ablation is because the patient is suffering from symptomatic AF, those who undergo AF ablation are younger and ‘generally healthier ’ than patients who do not undergo ablation treat-ment,4 – 6 as reflected by lower stroke risk scores, but also driven by confounders that will inform the clinical decision to submit a patients to catheter ablation procedures. Manipulation in the left atrium, wound healing, and scar formation in the atria, along with other factors, generate a thrombogenic milie
Symptom Burden of Atrial Fibrillation and Its Relation to Interventions and Outcome in Europe.
BACKGROUND
Little is known about the association of atrial fibrillation symptom burden with quality of life and outcomes.
METHODS AND RESULTS
In the Prevention of Thromboembolic Events-European Registry in Atrial Fibrillation (n=6196 patients with atrial fibrillation; mean±SD age, 71.8±10.4 years; 39.7% women), we assessed European Heart Rhythm Association score symptoms and calculated correlations with the standardized health status questionnaire (EQ-5D-5L). Patients were followed up for atrial fibrillation therapies and outcomes (stroke/transient ischemic attack/arterial thromboembolism, coronary events, heart failure, and major bleeding) over 1 year. Most individuals (92%) experienced symptoms. Correlations with health status and quality of life were modest. In multivariable-adjusted regression models, the dichotomized European Heart Rhythm Association score (intermediate/frequent versus never/occasional symptoms) was associated with cardioversions (odds ratio [OR], 1.21; 95% confidence interval [CI], 1.01-1.45) and catheter ablation (OR, 1.97; 95% CI, 1.44-2.69), and inversely related with heart rate control (OR, 0.80; 95% CI, 0.70-0.92) and heart failure incidence (OR, 1.65; 95% CI, 1.16-2.34). Anxiety was inversely related with stroke/transient ischemic attack/arterial thromboembolism (OR, 0.55; 95% CI, 0.32-0.93), whereas chest pain related positively with coronary events (OR, 2.45; 95% CI, 1.42-4.22). Fatigue (OR, 1.84; 95% CI, 1.30-2.60), dyspnea (OR, 2.33; 95% CI, 1.63-3.33), and anxiety (OR, 1.72; 95% CI, 1.16-2.55) were associated with heart failure incidence. Palpitations were positively associated with cardioversion (OR, 1.32; 95% CI, 1.08-1.61) and ablation therapy (OR, 2.02; 95% CI, 1.48-2.76).
CONCLUSIONS
A higher symptom burden, in particular palpitations, predicted interventions to restore sinus rhythm. The score itself had limited predictive value, but its individual components were related to different and specific clinical events, and may thus be helpful to target patient management
Rate vs. rhythmcontrol and adverse outcomes among European patients with atrial fibrillation
Aim The impact of rate and rhythm control strategies on outcomes in patients with atrial fibrillation (AF) remains controversial.
Our aims were: to report use of rate and rhythm control strategies in European patients from the
EURObservational Research Program AF General Pilot Registry. Secondly, to evaluate outcomes according to assigned
strategies.
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Methods
and results
Use of pure rate and rhythm control agents was described according to European regions. 1-year follow-up data
were reported. Among rate control strategies, beta-blockers were the most commonly used drug. Proportions of
patients assigned to rhythm control varied greatly between countries, and amiodarone was the most used rhythm
control drug. Of the original 3119 patients, 1036 (33.2%) were assigned to rate control only and 355 (11.4%) to
rhythm control only. Patients assigned to a rate control strategy were older (P < 0.0001) and more likely female
(P = 0.0266). Patients assigned to a rate control strategy had higher rates for any thrombo-embolic event
(P = 0.0245), cardiovascular death (P = 0.0437), and all-cause death (P < 0.0001). Kaplan–Meier analysis showed that
rate control strategy was associated with a higher risk for all-cause death (P < 0.001). On Cox regression analysis,
rate control strategy was independently associated with all-cause death (P = 0.0256). A propensity matched analysis
only found a trend for the association between rate control and all-cause death (P = 0.0664).
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Conclusion In a European AF patients’ cohort, a pure rate control strategy was associated with a higher risk for adverse events
at 1-year follow-up, and partially adjusted analysis suggested that rate control independently increased the risk for
all-cause death. A fully adjusted propensity score matched analysis found that this association was no longer statistically
significant, suggesting an important role of comorbidities in determining the higher risk for all-cause death
Data-driven discovery and validation of circulating blood-based biomarkers associated with prevalent atrial fibrillation.
AIMS
Undetected atrial fibrillation (AF) is a major health concern. Blood biomarkers associated with AF could simplify patient selection for screening and further inform ongoing research towards stratified prevention and treatment of AF.
METHODS AND RESULTS
Forty common cardiovascular biomarkers were quantified in 638 consecutive patients referred to hospital [mean ± standard deviation age 70 ± 12 years, 398 (62%) male, 294 (46%) with AF] with known AF or ≥2 CHA2DS2-VASc risk factors. Paroxysmal or silent AF was ruled out by 7-day ECG monitoring. Logistic regression with forward selection and machine learning algorithms were used to determine clinical risk factors, imaging parameters, and biomarkers associated with AF. Atrial fibrillation was significantly associated with age [bootstrapped odds ratio (OR) per year = 1.060, 95% confidence interval (1.04-1.10); P = 0.001], male sex [OR = 2.022 (1.28-3.56); P = 0.008], body mass index [BMI, OR per unit = 1.060 (1.02-1.12); P = 0.003], elevated brain natriuretic peptide [BNP, OR per fold change = 1.293 (1.11-1.63); P = 0.002], elevated fibroblast growth factor-23 [FGF-23, OR = 1.667 (1.36-2.34); P = 0.001], and reduced TNF-related apoptosis-induced ligand-receptor 2 [TRAIL-R2, OR = 0.242 (0.14-0.32); P = 0.001], but not other biomarkers. Biomarkers improved the prediction of AF compared with clinical risk factors alone (net reclassification improvement = 0.178; P < 0.001). Both logistic regression and machine learning predicted AF well during validation [area under the receiver-operator curve = 0.684 (0.62-0.75) and 0.697 (0.63-0.76), respectively].
CONCLUSION
Three simple clinical risk factors (age, sex, and BMI) and two biomarkers (elevated BNP and elevated FGF-23) identify patients with AF. Further research is warranted to elucidate FGF-23 dependent mechanisms of AF
Interactions Between Atrial Fibrillation and Natriuretic Peptide in Predicting Heart Failure Hospitalization or Cardiovascular Death.
Background Natriuretic peptides are routinely quantified to diagnose heart failure (HF). Their concentrations are also elevated in atrial fibrillation (AF). To clarify their value in predicting future cardiovascular events, we measured natriuretic peptides in unselected patients with cardiovascular conditions and related their concentrations to AF and HF status and outcomes. Methods and Results Consecutive patients with cardiovascular conditions presenting to a large teaching hospital underwent clinical assessment, 7-day ECG monitoring, and echocardiography to diagnose AF and HF. NT-proBNP (N-terminal pro-B-type natriuretic peptide) was centrally quantified. Based on a literature review, four NT-proBNP groups were defined (<300, 300-999, 1000-1999, and ≥2000 pg/mL). Clinical characteristics and NT-proBNP concentrations were related to HF hospitalization or cardiovascular death. Follow-up data were available in 1616 of 1621 patients (99.7%) and analysis performed at 2.5 years (median age, 70 [interquartile range, 60-78] years; 40% women). HF hospitalization or cardiovascular death increased from 36 of 488 (3.2/100 person-years) in patients with neither AF nor HF, to 55 of 354 (7.1/100 person-years) in patients with AF only, 92 of 369 (12.1/100 person-years) in patients with HF only, and 128 of 405 (17.7/100 person-years) in patients with AF plus HF (<0.001). Higher NT-proBNP concentrations predicted the outcome in patients with AF only (C-statistic, 0.82; 95% CI, 0.77-0.86; <0.001) and in other phenotype groups (C-statistic in AF plus HF, 0.66; [95% CI, 0.61-0.70]; <0.001). Conclusions Elevated NT-proBNP concentrations predict future HF events in patients with AF irrespective of the presence of HF, encouraging routine quantification of NT-proBNP in the assessment of patients with AF
Quantification of fibroblast growth factor 23 and N-terminal pro-B-type natriuretic peptide to identify patients with atrial fibrillation using a high-throughput platform: A validation study.
BACKGROUND
Large-scale screening for atrial fibrillation (AF) requires reliable methods to identify at-risk populations. Using an experimental semi-quantitative biomarker assay, B-type natriuretic peptide (BNP) and fibroblast growth factor 23 (FGF23) were recently identified as the most suitable biomarkers for detecting AF in combination with simple morphometric parameters (age, sex, and body mass index [BMI]). In this study, we validated the AF model using standardised, high-throughput, high-sensitivity biomarker assays.
METHODS AND FINDINGS
For this study, 1,625 consecutive patients with either (1) diagnosed AF or (2) sinus rhythm with CHA2DS2-VASc score of 2 or more were recruited from a large teaching hospital in Birmingham, West Midlands, UK, between September 2014 and February 2018. Seven-day ambulatory ECG monitoring excluded silent AF. Patients with tachyarrhythmias apart from AF and incomplete cases were excluded. AF was diagnosed according to current clinical guidelines and confirmed by ECG. We developed a high-throughput, high-sensitivity assay for FGF23, quantified plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and FGF23, and compared results to the previously used multibiomarker research assay. Data were fitted to the previously derived model, adjusting for differences in measurement platforms and known confounders (heart failure and chronic kidney disease). In 1,084 patients (46% with AF; median [Q1, Q3] age 70 [60, 78] years, median [Q1, Q3] BMI 28.8 [25.1, 32.8] kg/m2, 59% males), patients with AF had higher concentrations of NT-proBNP (median [Q1, Q3] per 100 pg/ml: with AF 12.00 [4.19, 30.15], without AF 4.25 [1.17, 15.70]; p < 0.001) and FGF23 (median [Q1, Q3] per 100 pg/ml: with AF 1.93 [1.30, 4.16], without AF 1.55 [1.04, 2.62]; p < 0.001). Univariate associations remained after adjusting for heart failure and estimated glomerular filtration rate, known confounders of NT-proBNP and FGF23. The fitted model yielded a C-statistic of 0.688 (95% CI 0.656, 0.719), almost identical to that of the derived model (C-statistic 0.691; 95% CI 0.638, 0.744). The key limitation is that this validation was performed in a cohort that is very similar demographically to the one used in model development, calling for further external validation.
CONCLUSIONS
Age, sex, and BMI combined with elevated NT-proBNP and elevated FGF23, quantified on a high-throughput platform, reliably identify patients with AF.
TRIAL REGISTRATION
Registry IRAS ID 97753 Health Research Authority (HRA), United Kingdom