Top genes associated with stable sinus rhythm after electrical cardioversion.

<p>Fold Change (FC). Confidence Interval (CI).</p

Top genes associated with stable sinus rhythm after electrical cardioversion.

<p>Fold Change (FC). Confidence Interval (CI).</p

Participant demographics for biomarker discovery cohort.

<p>Participant demographics for biomarker discovery cohort.</p

Volcano plot of gene expression changes pre- and post-cardioversion.

<p>Each point represents one of the RNA transcripts tested and the ten most significant genes have been labeled. The x-axis represents the effect of each gene, reported as log2 fold change, and a positive log2 fold change is indicative of increased expression in post-cardioversion samples. The y-axis represents the–log10(P-value). Triangle points represent genes that have significant differential expressed after Bonferroni correction (P-value <3.6x10^-6).</p

Plasma biomarker concentrations in participants pre- and post-cardioversion.

<p>Data are medians (interquartile range).</p

Risk factors for heart failure hospitalizations among patients with atrial fibrillation

<div><p>Background</p><p>Patients with atrial fibrillation (AF) have an increased risk for the development of heart failure (HF). In this study, we aimed to detect predictors of HF hospitalizations in an unselected AF population.</p><p>Methods</p><p>The Basel Atrial Fibrillation Cohort Study is an ongoing observational multicenter cohort study in Switzerland. For this analysis, 1193 patients with documented AF underwent clinical examination, venous blood sampling and resting 12-lead ECG at baseline. Questionnaires about lifestyle and medical history were obtained in person at baseline and during yearly follow-up phone calls. HF hospitalizations were validated by two independent physicians. Cox regression analyses were performed using a forward selection strategy.</p><p>Results</p><p>Overall, 29.8% of all patients were female and mean age was 69 ±12 years. Mean follow-up time was 3.7 ±1.5 years. Hospitalization for HF occurred in 110 patients, corresponding to an incidence of 2.5 events per 100 person years of follow-up. Independent predictors for HF were body mass index (HR 1.40 [95%CI 1.17; 1.66], p = 0.0002), chronic kidney disease (2.27 [1.49; 3.45], p = 0.0001), diabetes mellitus (2.13 [1.41; 3.24], p = 0.0004), QTc interval (1.25 [1.04; 1.49], p = 0.02), brain natriuretic peptide (2.19 [1.73; 2.77], p<0.0001), diastolic blood pressure (0.79 [0.65; 0.96], p = 0.02), history of pulmonary vein isolation or electrical cardioversion (0.54 [0.36; 0.80], p = 0.003) and serum chloride (0.82 [0.70; 0.96], p = 0.02).</p><p>Conclusions</p><p>In this unselected AF population, several traditional cardiovascular risk factors and arrhythmia interventions predicted HF hospitalizations, providing potential opportunities for the implementation of strategies to reduce HF among AF patients.</p></div

Baseline characteristics.

<p>Baseline characteristics.</p

Determinants of Left Atrial Volume in Patients with Atrial Fibrillation

<div><p>Introduction</p><p>Left atrial (LA) enlargement is an important risk factor for incident stroke and a key determinant for the success of rhythm control strategies in patients with atrial fibrillation (AF). However, factors associated with LA volume in AF patients remain poorly understood.</p><p>Methods</p><p>Patients with paroxysmal or persistent AF were enrolled in this study. Real time 3-D echocardiography was performed in all participants and analyzed offline in a standardized manner. We performed stepwise backward linear regression analyses using a broad set of clinical parameters to determine independent correlates for 3-D LA volume.</p><p>Results</p><p>We included 210 patients (70.9% male, mean age 61±11years). Paroxysmal and persistent AF were present in 95 (45%) and 115 (55%) patients, respectively. Overall, 115 (55%) had hypertension, 11 (5%) had diabetes, and 18 (9%) had ischemic heart disease. Mean indexed LA volume was 36±12ml/m². In multivariable models, significant associations were found for female sex (β coefficient -10.51 (95% confidence interval (CI) -17.85;-3.16), p = 0.0053), undergoing cardioversion (β 11.95 (CI 5.15; 18.74), p = 0.0006), diabetes (β 14.23 (CI 2.36; 26.10), p = 0.019), body surface area (BSA) (β 34.21 (CI 19.30; 49.12), p<0.0001), glomerular filtration rate (β -0.21 (CI -0.36; -0.06), p = 0.0064) and plasma levels of NT-pro brain natriuretic peptide (NT-proBNP) (β 6.79 (CI 4.05; 9.52), p<0.0001), but not age (p = 0.59) or hypertension (p = 0.42). Our final model explained 52% of the LA volume variability.</p><p>Conclusions</p><p>In patients with AF, the most important correlates with LA volume are sex, BSA, diabetes, renal function and NT-proBNP, but not age or hypertension. These results may help to refine rhythm control strategies in AF patients.</p></div

Independent determinants of left atrial volume in AF patients.

<p>SE = Standard error; SD = Standard deviation; y/n = yes / no; ECV = Electrical cardioversion; NT-proBNP = N-terminal-pro B-type natriuretic peptide; eGFR = Estimated glomerular filtration rate. R2 is reported for the final multivariable model. The β (95% confidence intervals) represents the increase or decrease in left atrial volume (mL) per unit change of the specific covariate. The multivariable model also included age, atrial fibrillation type (paroxysmal vs. persistent), resting heart rate, left ventricular ejection fraction, left ventricular mass, high-sensitivity troponin T ≥15ng/mL, interleukin-6, history of heart failure, arterial hypertension, moderate or severe mitral regurgitation and sleep apnea syndrome. All above presented variables selected by the stepwise backward regression model were significant at the ≤0.05 level. * log-transformed variables. ^† Estimated by the CKD-EPI formula including creatinine and cystatin C.</p

Baseline characteristics according to underlying atrial fibrillation type.

<p>Baseline characteristics according to underlying atrial fibrillation type.</p