Chamberlain, Alanna M.

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— Physical health status measures have been shown to predict death in heart failure (HF); however, few studies found significant associations after adjustment for confounders, and most were not representative of all HF patients. Methods and Results— HF patients from southeastern MN were prospectively enrolled between 10/2007 and 12/2010, completed a 12-item Short Form Health Survey (SF-12) and a 6-minute walk, and were followed through 2011 for death from any cause. Scores ≤25 on the SF-12 physical component indicated low self-reported physical functioning, and the first question of the SF-12 measured self-rated general health. Low functional exercise capacity was defined as ≤300 m walked during a 6-minute walk. Over a mean follow-up of 2.3 years, 86 deaths occurred among the 352 participants. A 1.6-fold (95% confidence interval, 1.0–2.7) and 1.8-fold (95% confidence interval, 1.1–2.9) increased risk of death was observed among patients with low self-reported physical functioning and low functional exercise capacity, respectively. Poor self-rated general health corresponded to a 2.7-fold (95% confidence interval, 1.5–4.9) increased risk of death compared with good to excellent general health. All measures equally discriminated between who would die and who would survive (C-statistics: 0.729, 0.750, and 0.740 for self-reported physical functioning, self-rated general health, and functional exercise capacity, respectively). Conclusions— Three physical health status measures, captured by the SF-12 and a 6-minute walk, equally predict death among community HF patients. Therefore, the first question of the SF-12, which is the least burdensome to administer, may be sufficient to identify HF patients at greatest risk of death.

Background— The increasing prevalence of heart failure (HF) and high associated costs have spurred investigation of factors leading to adverse outcomes in patients with HF. Studies to date report inconsistent evidence on the link between depression and outcomes with only limited data on emergency department and outpatient visits. Methods and Results— Olmsted, Dodge, and Fillmore county, Minnesota residents with HF were prospectively recruited between October 2007 and December 2010 and completed a 1-time 9-item Patient Health Questionnaire for depression categorized as: none to minimal (Patient Health Questionnaire score, 0–4), mild (5–9), or moderate to severe (≥10). Andersen-Gill models were used to determine whether depression predicted hospitalizations and emergency department visits, whereas negative binomial regression models explored the association of depression with outpatient visits. Cox proportional hazards regression characterized the relationship between depression and all-cause mortality. Among 402 patients with HF (mean age, 73±13 years; 58% men), 15% had moderate to severe depression, 26% mild, and 59% none to minimal depression. During a mean follow-up of 1.6 years, 781 hospitalizations, 1000 emergency department visits, 15 515 outpatient visits, and 74 deaths occurred. After adjustment, moderate to severe depression was associated with nearly a 2-fold increased risk of hospitalization (hazard ratio, 1.79; 95% confidence interval, 1.30–2.47) and emergency department visits (hazard ratio, 1.83; 95% confidence interval, 1.34–2.50), a modest increase in outpatient visits (rate ratio, 1.20; 95% confidence interval, 1.00–1.45), and a 4-fold increase in all-cause mortality (hazard ratio, 4.06; 95% confidence interval, 2.35–7.01). Conclusions— In this prospective cohort study, depression independently predicted an increase in the use of healthcare resources and mortality. Greater recognition and management of depression in HF may optimize clinical outcomes and resource utilization.

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.

Background— Atrial fibrillation (AF) is a common finding in patients with myocardial infarction (MI). Atrial fibrillation is not generally perceived by clinicians as a critical event during the acute phase of MI; however, its prognostic influence in MI remains controversial. Furthermore, contradictory data exist concerning the risk of death according to AF timing. This article, a systematic review and first meta-analysis, aims to quantify the mortality risk associated with AF in MI patients and its timing. Methods and Results— A comprehensive search of several electronic databases (1970 to 2010; adults, any language) identified MI studies that evaluated mortality related to AF. Evidence was reviewed by 2 blinded reviewers with a formal assessment of the methodological quality of the studies. Adjusted odds ratios were pooled across studies using the random-effects model. The I 2 statistic was used to assess heterogeneity. In the 43 included studies (278 854 subjects), the mortality odds ratio associated with AF was 1.46 (95% confidence interval, 1.35 to 1.58; I 2 =76%; 23 studies). This worse prognosis persisted regardless of the timing of AF; the odds ratio of mortality for new AF with no prior history of AF was 1.37 (95% confidence interval, 1.26 to 1.49), I 2 =28%, 9 studies), and for prior AF was 1.28 (95% confidence interval, 1.16 to 1.40; I 2 =24%; 4 studies). The sensitivity analysis of new AF studies adjusting for confounding factors did not show a decrease in risk of death. Conclusions— Atrial fibrillation is associated with increased risk of mortality in MI patients. New AF with no history of AF before MI remained associated with an increased risk of mortality even after adjustment for several important AF risk factors. These subsequent increases in mortality suggest that AF can no longer be considered a nonsevere event during MI.