BNP and obesity in acute decompensated heart failure with preserved vs. reduced ejection fraction: The Atherosclerosis Risk in Communities Surveillance Study.

BACKGROUND: Levels of B-type natriuretic peptide (BNP), a prognostic marker in patients with heart failure (HF), are lower among HF patients with obesity or preserved Left Ventricular Ejection Fraction (LVEF). We examined the distribution and prognostic value of BNP across BMI categories in acute decompensated heart failure (ADHF) patients with preserved vs. reduced LVEF. METHODS: We analyzed data from the Atherosclerosis Risk in Communities (ARIC) HF surveillance study which sampled and adjudicated ADHF hospitalizations in patients aged ≥55years from 4 US communities (2005-2009). We examined 5 BMI categories: underweight (<18.5kg/m2), normal weight (18.5-<25), overweight (25-<30), obese (30-<40) and morbidly obese (≥40) in HF with preserved LVEF (HFpEF) and reduced LVEF (HFrEF). The outcome was 1-year mortality from admission. We used ANCOVA to model log BNP and logistic regression for 1-year mortality, both adjusted for demographics and clinical characteristics. RESULTS: The cohort included 9820 weighted ADHF hospitalizations (58% HFrEF; 42% HFpEF). BNP levels were lower in HFpEF compared to HFrEF (p<0.001) and decreased as BMI increased within the LVEF groups (p<0.001). After adjustment for covariates, log10 BNP independently predicted 1-year mortality (adjusted OR 1.62 (95% CI 1.17-2.24)) with no significant interaction by BMI or LVEF groups. CONCLUSIONS: BNP levels correlated inversely with BMI, and were higher in HFrEF compared to HFpEF. Obese patients with HFpEF and ADHF had a significant proportion with BNP levels below clinically accepted thresholds. Nevertheless, BNP was a predictor of mortality in ADHF across groups of BMI in HFpEF and HFrEF.

Multiple imputation of cognitive performance as a repeatedly measured outcome.

Longitudinal studies of cognitive performance are sensitive to dropout, as participants experiencing cognitive deficits are less likely to attend study visits, which may bias estimated associations between exposures of interest and cognitive decline. Multiple imputation is a powerful tool for handling missing data, however its use for missing cognitive outcome measures in longitudinal analyses remains limited. We use multiple imputation by chained equations (MICE) to impute cognitive performance scores of participants who did not attend the 2011-2013 exam of the Atherosclerosis Risk in Communities Study. We examined the validity of imputed scores using observed and simulated data under varying assumptions. We examined differences in the estimated association between diabetes at baseline and 20-year cognitive decline with and without imputed values. Lastly, we discuss how different analytic methods (mixed models and models fit using generalized estimate equations) and choice of for whom to impute result in different estimands. Validation using observed data showed MICE produced unbiased imputations. Simulations showed a substantial reduction in the bias of the 20-year association between diabetes and cognitive decline comparing MICE (3-4 % bias) to analyses of available data only (16-23 % bias) in a construct where missingness was strongly informative but realistic. Associations between diabetes and 20-year cognitive decline were substantially stronger with MICE than in available-case analyses. Our study suggests when informative data are available for non-examined participants, MICE can be an effective tool for imputing cognitive performance and improving assessment of cognitive decline, though careful thought should be given to target imputation population and analytic model chosen, as they may yield different estimands.

Heart failure risk across the spectrum of ankle-brachial index: the ARIC study (Atherosclerosis Risk In Communities).

OBJECTIVES: The aim of this study was to describe the relationship between ankle brachial index (ABI) and the risk for heart failure (HF). BACKGROUND: The ABI is a simple, noninvasive measure associated with atherosclerotic cardiovascular disease and death; however, the relationship between ABI and risk for HF is less well characterized. METHODS: Between 1987 and 1989 in the ARIC (Atherosclerosis Risk In Communities) study, an oscillometric device was used to measure blood pressure in a single upper and randomly chosen lower extremity to determine the ABI. Incident HF events were defined by the first hospitalization with an International Classification of Diseases, Ninth Revision, code of 428.x through 2008. The risk for HF was assessed across the ABI range using restricted cubic splines and Cox proportional hazards models. RESULTS: ABI was available in 13,150 participants free from prevalent HF. Over a mean 17.7 years of follow-up, 1,809 incident HF events occurred. After adjustment for traditional HF risk factors, prevalent coronary heart disease, subclinical carotid atherosclerosis, and interim myocardial infarction, compared with an ABI of 1.01 to 1.40, participants with ABIs ≤0.90 were at increased risk for HF (hazard ratio: 1.40; 95% confidence interval: 1.12 to 1.74), as were participants with ABIs of 0.91 to 1.00 (hazard ratio: 1.36; 95% confidence interval: 1.17 to 1.59). CONCLUSIONS: In a middle-age community cohort, an ABI ≤1.00 was significantly associated with an increased risk for HF, independent of traditional HF risk factors, prevalent coronary heart disease, carotid atherosclerosis, and interim myocardial infarction. Low ABI may reflect not only overt atherosclerosis but also pathologic processes in the development of HF beyond epicardial atherosclerotic disease and myocardial infarction alone. A low ABI, as a simple, noninvasive measure, may be a risk marker for HF.