Neck Circumference and Risk of Incident Atrial Fibrillation in the Framingham Heart Study.

Background Increased neck circumference, a proxy for upper-body subcutaneous fat, is associated with cardiovascular risk and metabolic risk factors, accounting for body mass index (BMI) and waist circumference. The association between neck circumference and incident atrial fibrillation (AF) is unclear. The aim of current study was to evaluate the association between neck circumference and incident AF. Methods and Results We selected participants from the Framingham Heart Study aged ≥55 years without diagnosed AF and with available neck circumference, BMI, and waist circumference measurements. We defined high neck circumference as ≥14 inches in women and ≥17 inches in men on the basis of the Contal and O'Quigley changepoint method. We used Fine-Gray models to estimate subdistribution hazards ratios (sHRs) for the association between neck circumference and incident AF accounting for the competing risk of death. We adjusted models for clinical risk factors. We then additionally adjusted separately for BMI, waist circumference, and height/weight. The study sample included 4093 participants (mean age 64±7 years, 55% female). During 11.2±5.7 mean years of follow-up, incident AF occurred in 571 participants. High neck circumference was associated with incident AF (sHR for high versus low: 1.58; 95% CI, 1.32-1.90, P<0.0001). The association remained significant after adjustment for BMI (sHR, 1.51; 95% CI, 1.21-1.89; P=0.0003), waist circumference (sHR, 1.47; 95% CI, 1.18-1.83; P<0.0001), and height/weight (sHR, 1.37; 95% CI, 1.09-1.72; P=0.007). Conclusions High neck circumference was associated with incident AF adjusting for traditional adiposity measures such as BMI and waist circumference.

Re-CHARGE-AF: Recalibration of the CHARGE-AF Model for Atrial Fibrillation Risk Prediction in Patients With Acute Stroke.

Background Performance of existing atrial fibrillation (AF) risk prediction models in poststroke populations is unclear. We evaluated predictive utility of an AF risk model in patients with acute stroke and assessed performance of a fully refitted model. Methods and Results Within an academic hospital, we included patients aged 46 to 94 years discharged for acute ischemic stroke between 2003 and 2018. We estimated 5-year predicted probabilities of AF using the Cohorts for Heart and Aging Research in Genomic Epidemiology for Atrial Fibrillation (CHARGE-AF) model, by recalibrating CHARGE-AF to the baseline risk of the sample, and by fully refitting a Cox proportional hazards model to the stroke sample (Re-CHARGE-AF) model. We compared discrimination and calibration between models and used 200 bootstrap samples for optimism-adjusted measures. Among 551 patients with acute stroke, there were 70 incident AF events over 5 years (cumulative incidence, 15.2%; 95% CI, 10.6%-19.5%). Median predicted 5-year risk from CHARGE-AF was 4.8% (quartile 1-quartile 3, 2.0-12.6) and from Re-CHARGE-AF was 16.1% (quartile 1-quartile 3, 8.0-26.2). For CHARGE-AF, discrimination was moderate (C statistic, 0.64; 95% CI, 0.57-0.70) and calibration was poor, underestimating AF risk (Greenwood-Nam D'Agostino chi-square, P<0.001). Calibration with recalibrated baseline risk was also poor (Greenwood-Nam D'Agostino chi-square, P<0.001). Re-CHARGE-AF improved discrimination (P=0.001) compared with CHARGE-AF (C statistic, 0.74 [95% CI, 0.68-0.79]; optimism-adjusted, 0.70 [95% CI, 0.65-0.75]) and was well calibrated (Greenwood-Nam D'Agostino chi-square, P=0.97). Conclusions Covariates from an established AF risk model enable accurate estimation of AF risk in a poststroke population after recalibration. A fully refitted model was required to account for varying baseline AF hazard and strength of associations between covariates and incident AF.