Alonso, Alvaro

Background Atrial fibrillation ( AF ) is associated with increased risk of hospitalization. Little is known about the impact of AF on utilization of noninpatient health care or about sex or race differences in AF ‐related utilization. We examined rates of inpatient and outpatient utilization by AF status in the Atherosclerosis Risk in Communities study. Methods and Results Participants with incident AF enrolled in fee‐for‐service Medicare for at least 12 continuous months between 1991 and 2009 (n=932) were matched on age, sex, race and field center with up to 3 participants without AF (n=2729). Healthcare utilization was ascertained from Medicare claims and classified by primary International Classification of Diseases, ninth revision code. The average annual numbers of days hospitalized were 13.2 (95% CI 11.6 to 15.0) and 2.8 (95% CI 2.5 to 3.1) for those with and without AF , respectively. The corresponding numbers of annual outpatient claims were 53.3 (95% CI 50.5 to 56.3) and 22.9 (95% CI 22.1 to 23.8) for those with and without AF , respectively. Most utilization among AF patients was attributable to non‐ AF conditions. The adjusted rate ratio for annual days hospitalized for other cardiovascular disease–related reasons was 4.58 (95% CI : 3.41 to 6.16) for those with AF versus those without AF . The association between AF and healthcare utilization was similar among men and women and among white and black participants. Conclusions Participants with AF had considerably greater healthcare utilization, and the difference in utilization for other cardiovascular disease –related reasons was substantial. In addition to rate or rhythm treatment, AF management should focus on the accompanying cardiovascular comorbidities.

Background and purposeSome recent studies in older, largely white populations suggest that vitamin D, measured by 25‐hydroxyvitamin D [25(OH)D], is important for cognition, but such results may be affected by reverse causation. Measuring 25(OH)D in late middle age before poor cognition affects behavior may provide clearer results.MethodsThis was a prospective cohort analysis of 1652 participants (52% white, 48% black) in the Atherosclerosis Risk in Communities (ARIC) Brain MRI Study. 25(OH)D was measured from serum collected in 1993–1995. Cognition was measured by the delayed word recall test (DWRT), the digit symbol substitution test (DSST) and the word fluency test (WFT). Dementia hospitalization was defined by ICD‐9 codes. Adjusted linear, logistic and Cox proportional hazards models were used.ResultsMean age of participants was 62 years and 60% were female. Mean 25(OH)D was higher in whites than blacks (25.5 vs. 17.3 ng/ml, P < 0.001). Lower 25(OH)D was not associated with lower baseline scores or with greater DWRT, DSST or WFT decline over a median of 3 or 10 years of follow‐up (P > 0.05). Over a median of 16.6 years, there were 145 incident hospitalized dementia cases. Although not statistically significant, lower levels of 25(OH)D were suggestive of an association with increased dementia risk [hazard ratio for lowest versus highest race‐specific tertile: whites 1.32 (95% confidence interval 0.69, 2.55); blacks 1.53 (95% confidence interval 0.84, 2.79)].ConclusionsIn contrast to prior studies performed in older white populations, our study of late middle age white and black participants did not find significant associations between lower levels of 25(OH)D with lower cognitive test scores at baseline, change in scores over time or dementia risk.

Background— Reduced low forced expiratory volume in 1 second (FEV 1 ) is reportedly associated with an increased risk of atrial fibrillation (AF). Extant reports do not provide separate estimates for never smokers or for blacks, who incongruously have lower AF incidence than whites. Methods and Results— We examined 15 004 middle-aged blacks and whites enrolled in the Atherosclerosis Risk in Communities (ARIC) cohort study. Standardized spirometry data were collected at the baseline examination. Incident AF was identified from the first among the following: International Classification of Diseases codes for AF on hospital discharge records or death certificates or 12-lead ECGs performed during 3 triennial follow-up visits. Over an average follow-up of 17.5 years, a total of 1691 participants (11%) developed new-onset AF. The rate of incident AF was inversely associated with FEV 1 in each of the 4 race and sex groups. After multivariable adjustment for traditional cardiovascular disease risk factors and height, hazard ratios of AF comparing the lowest with the highest quartile of FEV 1 were 1.37 (95% confidence interval, 1.02–1.83) for white women, 1.49 (95% confidence interval, 1.16–1.91) for white men, 1.63 (95% confidence interval, 1.00–2.66) for black women, and 2.36 (95% confidence interval, 1.30–4.29) for black men. The above associations were observed across all smoking status categories. Moderate/severe airflow obstruction (FEV 1 /forced vital capacity <0.70 and FEV 1 < 80% of predicted value) was also associated with higher AF incidence. Conclusions— In this large population-based study with a long-term follow-up, reduced FEV 1 and obstructive respiratory disease were associated with a higher AF incidence after adjustment for measured confounders.

Background Tools for the prediction of atrial fibrillation ( AF ) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. Methods and Results Individual‐level data from 3 large cohorts in the U nited S tates (Atherosclerosis Risk in Communities [ ARIC ] study, the Cardiovascular Health Study [ CHS ], and the Framingham Heart Study [ FHS ]), including 18 556 men and women aged 46 to 94 years (19% A frican A mericans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study ( AGES ) and the Rotterdam Study ( RS ). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI , 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI , 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI , −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable ( AGES C‐statistic, 0.664; 95% CI , 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI , 0.664 to 0.747) and calibration was adequate. Conclusion A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the U nited S tates and E urope.

Background— Heart failure (HF) and atrial fibrillation (AF) share common risk factors and often coexist. The combination of HF and AF may carry a worse prognosis than either condition alone; however, the magnitude of this risk remains controversial and it is not known whether the timing of AF influences the risk of death. Methods and Results— We determined the risk of all-cause mortality in relation to the presence of AF prior to or after HF diagnosis in a community-based cohort of persons diagnosed as having HF between 1983 and 2006. Of 1664 individuals with HF, 553 had a history of AF and 384 developed AF after HF. During a median follow-up of 4.0 years, 450 deaths occurred among persons with prior AF, 314 among those with AF after HF, and 572 among patients without AF. In fully adjusted models, compared with patients without AF, those with AF prior to HF had a 29% increased risk of death, whereas those who developed AF after HF exhibited >2-fold increased risk of death. Conclusions— In the community, AF is frequent in the setting of HF and is associated with a large excess risk of death. The magnitude of this excess risk differs markedly according to the timing of AF, with AF developing after HF conferring the largest increased risk of death compared with HF patients without AF.