Clinical and Echocardiographic Factors Associated With New-Onset Atrial Fibrillation in Heart Failure　– Subanalysis of the WARCEF Trial –

Abstract

Background: Heart failure (HF) patients have a high incidence of new-onset AF. Given the adverse prognostic influence of AF in HF, identifying patients at high risk of developing AF is important.

Methods and Results: The incidence and factors associated with new-onset AF were investigated in patients in sinus rhythm with reduced LVEF enrolled in the Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) trial. Analyses involved clinical factors alone (n=2,219), and clinical plus echocardiographic findings (n=1,125). During 3.5±1.8 years of follow-up, 212 patients (9.6% of total cohort) developed AF. In both samples, new-onset AF was associated with age, male sex, White race, and IHD. Among echocardiographic variables, only LAD predicted AF. On multivariate Cox modeling, age (HR, 1.02; 95% CI: 1.00–1.03, P=0.008), IHD (HR, 1.37; 95% CI: 1.02–1.84, P=0.036) and LAD (HR, 1.48; 95% CI: 1.15–1.91, P=0.003) remained associated with AF onset. Patients with IHD, LAD>4.5 cm and age>50 years had a 2.5-fold higher risk of AF than patients without any of these characteristics (HR, 2.52; 95% CI: 1.72–3.69, P<0.0001).

Conclusions: Age, IHD and LAD independently predict new-onset AF in HF patients in sinus rhythm, at younger age and smaller LAD than generally believed. This information may be useful to risk-stratify HF patients for AF development, allowing close monitoring and possibly early detection. (Circ J 2016; 80: 619–626)

Atrial fibrillation (AF) is the most common significant cardiac arrhythmia. The current prevalence of AF estimated in the developed countries is approximately 1.5–2% of the general population.¹ Furthermore, the prevalence and incidence of heart failure (HF), which now affects more than 5 million patients in the USA, are also increasing.² AF can be a cause of HF development because it negatively affects left ventricular ejection fraction (LVEF) by altering LV function;³ patients with AF carry a risk for the development of HF ranging from 10% to 50%.^4,5 Several studies suggest that patients with HF and coexisting AF have a worse prognosis.^6,7 In particular, patients with HF who subsequently develop AF have higher mortality rates.^8,9

Editorial p 587

Few studies have attempted to risk-stratify HF patients for development of AF, especially by incorporating echocardiographic parameters. Given the adverse prognostic influence of AF in the HF population, the identification of patients at high risk for AF while they are still in sinus rhythm can be of great clinical value, possibly allowing for earlier identification and treatment of incident AF. We therefore evaluated the possibility of identifying clinical or echocardiographic predictors of new-onset AF in a cohort of HF patients in sinus rhythm enrolled in a prospective HF clinical trial.

Methods

Study Design

We used data from the Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) trial, which compared warfarin and aspirin in a double-blind, randomized design.¹⁰ The results of the primary analysis have been previously published.^10,11 WARCEF obtained data from 168 centers in 11 countries, and enrolled 2,305 patients with follow-up periods of up to 6 years (mean, 3.5±1.8 years). Patients were >18 years of age and had normal sinus rhythm and LVEF≤35% within 3 months before randomization.

We conducted 2 analyses using the WARCEF data to examine the incidence and factors associated with new-onset AF. The first focused on clinical factors alone. New-onset AF was defined as an adverse event report giving it as a specific reason for patients beginning interruption of therapy (ie, stopping standard study medication). Excluding patients with a history of AF left 2,219 patients for this analysis. The second analysis was restricted to the 1,125 patients for whom echocardiographic left atrial diameter (LAD) information as well as clinical data were available (Figure).

Figure.

Subject selection. AF, atrial fibrillation; LAD, left atrial diameter; LVEDD, left ventricular end-diastolic dimension; LVM, left ventricular mass; WARCEF, Warfarin versus Aspirin in Reduced Cardiac Ejection Fraction.

Clinical characteristics included in both analyses were age, sex, ethnicity, body mass index (BMI), etiology of HF (ischemic or non-ischemic), comorbidities previously reported to frequently coexist with AF and risks for AF development such as prior stroke, diabetes mellitus, hypertension, peripheral vascular disease and renal insufficiency,^12–14 tobacco and alcohol consumption, and advanced stage of HF defined as New York Heart Association (NYHA) class 3 and 4. As a variable of renal function, we used estimated glomerular filtration rate (eGFR); and renal insufficiency was defined as chronic kidney disease (CKD) ≥stage 3 (eGFR<60 ml/min/1.73 m²).¹⁵ LVEF on either quantitative echocardiography (or wall-motion index≤1.2), radionuclide or contrast ventriculography was obtained in all patients within 3 months before randomization for WARCEF enrollment and included in the analysis of clinical characteristics.¹¹ Beta-blocker usage was included in the analyses because it may affect the risk of AF development.¹⁶ Although angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers may also affect AF development,¹⁶ they could not be included in the analyses because they were used in the overwhelming majority of patients (>98%).¹¹

Echocardiographic parameters (other than LVEF) included in the second analysis were LV end-diastolic dimension (LVEDD), LAD, and LV mass index (LVMI). LVMI was calculating using Devereux’s formula as previously described.¹⁷ The 1,125 patients included were those with complete data on these echocardiographic parameters. The study was approved by the institutional review boards and ethics boards of participating centers.

Statistical Analysis

Patients with and without new-onset AF were compared on baseline clinical and echocardiographic characteristics using 2-sided Student’s t-test for continuous variables and chi-squared test for categorical variables. Univariate Cox proportional hazards models were used to assess the independent effect of each variable on new-onset AF. One multivariate Cox model was constructed using stepwise forward-backward selection, with entry and removal criteria of P=0.05, to assess the joint effects of variables on new-onset AF in the clinical sample, and one in the sample with echocardiographic data. Missing values of basic clinical factors were assigned using means for continuous variables and model values for categorical variables. In the multivariate models we used BMI category instead of continuous BMI, and eGFR (continuous) instead of presence or absence of renal insufficiency, on the basis of univariate results (not shown). P-values were calculated using the Wald test.

After review of the multivariate models, to identify patients at high risk of AF, we dichotomized continuous AF risk factor variables in univariate analyses, using the echocardiographic sample. We then developed multivariate models to assess the likelihood of developing AF for different risk factor combinations.

Results

During 3.5±1.8 years of follow-up, 212 of the 2,219 patients (9.6%) in the overall sample and 110 of the 1,125 patients (9.8%) in the echocardiographic sample developed AF. The 2 samples differed only by race-ethnicity distribution, smoking status, alcohol consumption and marginally by BMI (Table S1).

New-Onset AF

Table 1 lists clinical and echocardiographic characteristics according to presence of new-onset AF. Patients who developed AF were older, more likely to be male, less likely to be African-merican and Hispanic, and had a higher frequency of ischemic heart disease (IHD). The distribution of patients with comorbidities associated with AF development such as diabetes mellitus, hypertension and peripheral vascular disease was not significantly different between the groups. The frequency of patients with renal insufficiency tended to be higher in the new-onset AF group. LVEF, severity of HF defined as higher NYHA class and pacemaker/device requirement were not different between the 2 groups. Patients who developed new-onset AF were more frequently treated with β-blockers. Among the echocardiographic variables, patients with new-onset AF had larger LAD than patients who remained in sinus rhythm. Other parameters such as LVEDD and LVMI were not significantly different between the groups.

Table 1. Clinical and Echocardiographic Parameters in Patients With and Without New-Onset AF

Variables	New-onset AF (n=212)	No AF (n=2,007)	P-value
Clinical characteristics
Age (years)	62.4±10.8 (n=212)	60.5±11.5 (n=2,007)	0.026
Men	182/212 (85.8)	1,589/2,002 (79.4)	0.025
Ethnicity			0.019
White non-Hispanic	178/212 (84.0)	1,494/2,001 (74.7)
Black non-Hispanic	20/212 (9.4)	293/2,001 (14.6)
Hispanic	8/212 (3.8)	154/2,001 (7.7)
Other	6/212 (2.8)	60/2,001 (3.0)
BMI (kg/m2)	29.1±5.5 (n=209)	29.1±5.9 (n=1,991)	0.938
BMI category			0.497
<25	45/209 (21.5)	493/1,991 (24.8)
25–30	88/209 (42.1)	769/1,991 (38.6)
>30	76/209 (36.4)	729/1,991 (36.6)
IHD	139/210 (66.2)	1,144/1,997 (57.3)	0.013
Diabetes mellitus	65/210 (31.0)	622/1,998 (31.1)	0.958
Hypertension	119/207 (57.5)	1,192/1,945 (61.3)	0.287
PVD	26/212 (12.3)	223/2,007 (11.1)	0.613
Smoking			0.595
Current smoker	41/212 (19.3)	354/1,998 (17.7)
Former smoker	112/212 (52.8)	1,023/1,998 (51.2)
Never smoked	59/212 (27.8)	621/1,998 (31.1)
Alcohol consumption			0.890
Current drinker, >60 ml/day	56/212 (26.4)	499/2,000 (25.0)
Former drinker, >60 ml/day	45/212 (21.2)	440/2,000 (22.0)
Never consumed alcohol	111/212 (52.4)	1,061/2,000 (53.1)
eGFR (ml/min/1.73 m2)	66.2±20 (n=211)	68.9±20.7 (n=1,984)	0.068
Renal insufficiency	84/211 (39.8)	674/1,984 (34.0)	0.090
Prior stroke or TIA	27/210 (12.9)	257/1,999 (12.9)	0.9998
NYHA class 3 and 4	68/209 (32.5)	608/1,996 (30.5)	0.536
β-blockers	201/211 (95.3)	1,785/1,997 (89.4)	0.007
Pacemaker/CR/defibrillator	55/210 (26.2)	429/1,999 (21.5)	0.115
LVEF, any method (%)	23.9±7.3 (n=211)	24.7±7.6 (n=2,001)	0.114
Echocardiographic variables
LAD (cm)	4.6±0.8 (n=114)	4.5±0.7 (n=1,035)	0.038
LVEF (%)	24.6±6.8 (n=136)	25.3±7.9 (n=1,221)	0.212
LV end-diastolic dimension (cm)	6.2±0.9 (n=127)	6.3±1 (n=1,139)	0.240
LV mass index (g/m2)	128.4±40.1 (n=124)	133.1±47.3 (n=1,126)	0.223

Data given as mean±SD or n (%). AF, atrial fibrillation; BMI, body mass index; CR, cardiac resynchronization; eGFR, estimated glomerular filtration rate; IHD, ischemic heart disease; LAD, left atrial diameter; LV, left ventricular; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; PVD, peripheral vascular disease; TIA, transient ischemic attack.

The results from univariate and multivariate Cox models for the overall sample are summarized in Table 2. On univariate analysis, older age, male sex, ischemic etiology of HF, lower eGFR and β-blocker usage were significantly associated with new-onset AF. Ethnicity and eGFR were significant predictors in the univariate models but, after adjustment for other covariates by stepwise forward-backward selection methods, these variables were no longer significant and were not included in the multivariate model. This was because eGFR and ethnicity are highly correlated with age, gender, IHD, and other variables in the clinical sample. In the multivariate model, age, gender and IHD remained significant, whereas eGFR and ethnicity were no longer significant. In the multivariate stepwise forward-backward selection model, age, male sex, ischemic etiology, and β-blocker usage remained significant. Although LVEF was not significant in a univariate model, it was significant based on the stepwise forward-ackward selection methods, and therefore included, in the multivariate model. Previously reported risk factors for AF development including obesity, diabetes mellitus, hypertension, and renal dysfunction were not found to be associated with AF in the present cohort.

Table 2. Clinical Factors Associated With New-Onset AF in the Overall Sample (n=2,219)

Characteristic	HR (95% CI)	P-value
Univariate model (unadjusted)
Age (years)	1.02 (1.01–1.03)	0.002
Male	1.60 (1.09–2.36)	0.017
Ethnicity (reference: White, non-Hispanic)		0.032
Black, non-Hispanic	0.55 (0.34–0.87)
Hispanic	0.55 (0.27–1.12)
Other	0.86 (0.38–1.94)
BMI category (reference: <25 kg/m2)		0.431
25–30	1.23 (0.86–1.76)
>30	1.05 (0.72–1.51)
IHD	1.57 (1.18–2.08)	0.002
Diabetes mellitus	1.04 (0.78–1.39)	0.791
Hypertension	0.87 (0.67–1.15)	0.332
PVD	1.22 (0.81–1.84)	0.347
Smoking (reference: Never)		0.635
Current	1.20 (0.81–1.79)
Previous	1.13 (0.82–1.55)
Alcohol consumption (reference: Never)		0.793
Current	1.06 (0.77–1.46)
Previous	0.92 (0.65–1.30)
eGFR (ml/min/1.73 m2)	0.99 (0.98–1.00)	0.014
NYHA class 3 and 4	1.16 (0.87–1.56)	0.303
Prior stroke or TIA	1.06 (0.71–1.59)	0.776
β-blockers	2.20 (1.17–4.15)	0.015
Pacemaker/CR/defibrillator	1.33 (0.97–1.80)	0.073
LVEF (%)	0.99 (0.97–1.00)	0.126
Multivariate model
Age (years)	1.01 (1.01–1.03)	0.002
Male	1.51 (1.02–2.23)	0.039
IHD	1.37 (1.02–1.84)	0.035
β-blockers	2.37 (1.25–4.49)	0.008
LVEF (%)	0.98 (0.96–1.00)	0.045

Abbreviations as in Table 1.

Clinical and Echo-Derived Factors Associated With New-Onset AF

Table 3 summarizes results from univariate and multivariate Cox models based on the combination of clinical and echocardiographic parameters. Again, older age, male sex and ischemic etiology were significantly associated with new-onset AF on univariate analysis, as was LAD among the echocardiographic variables. On multivariate analysis, age, ischemic etiology and LAD remained significantly associated with AF development.

Table 3. Clinical and Echo-Derived Factors Associated With New-Onset AF (n=1,125)

Characteristic	HR (95% CI)	P-value
Univariate model (unadjusted)
Age (years)	1.02 (1.01–1.04)	0.007
Male	1.72 (1.00–2.97)	0.050
Ethnicity (reference: White, non-Hispanic)		0.090
Black, non-Hispanic	0.40 (0.19–0.86)
Hispanic	0.64 (0.24–1.75)
Other	0.59 (0.15–2.39)
BMI category (reference: <25 kg/m2)		0.678
25–30	1.25 (0.76–2.06)
>30	1.18 (0.71–1.97)
IHD	1.85 (1.23–2.79)	0.003
Diabetes mellitus	1.02 (0.68–1.54)	0.919
Hypertension	1.06 (0.72–1.55)	0.771
PVD	0.86 (0.43–1.70)	0.663
Smoking (reference: Never)		0.460
Current	1.39 (0.78–2.48)
Previous	1.28 (0.81–2.03)
Alcohol consumption (reference: Never)		0.970
Current	1.06 (0.68–1.66)
Previous	1.01 (0.62–1.64)
eGFR (ml/min/1.73 m2)	1.00 (0.99–1.01)	0.807
NYHA class 3 and 4	0.92 (0.61–1.39)	0.680
Prior stroke or TIA	0.51 (0.24–1.10)	0.087
β-blockers	2.11 (0.86–5.17)	0.104
Pacemaker/CR/defibrillator	1.39 (0.92–2.11)	0.117
LVEF (%)	0.99 (0.96–1.01)	0.358
LAD (cm)	1.47 (1.14–1.89)	0.003
LV end-diastolic dimension (cm)	0.99 (0.82–1.21)	0.936
LV mass index (g/m2)	1.00 (0.99–1.00)	0.473
Multivariate model
Age (years)	1.02 (1.002–1.04)	0.030
IHD	1.65 (1.09–2.51)	0.018
LAD (cm)	1.48 (1.15–1.91)	0.003

Abbreviations as in Table 1.

AF Risk Model Based on Echocardiography

Univariate Cox models were used to evaluate potential cut-off points of age and LAD for increased risk for new-onset AF. The best cut-off for LAD was 4.5 cm, whereas 75 years was the best age cut-off. Given that, however, only 10% of the patients were older than 75, we also considered the next best cut-off (50 years) in the subsequent analysis (Table 4). Table 5 summarizes the multivariate models based on dichotomized LAD and age, and presence or absence of IHD.

Table 4. Dichotomized LAD and Age as Univariate Indicators of AF

Cut-off	HR (95% CI)	P-value
LAD dichotomization (cm)
>3.5 vs. ≤3.5	1.16 (0.59–2.30)	0.6673
>4 vs. ≤4	1.34 (0.85–2.12)	0.2114
>4.5 vs. ≤4.5	1.67 (1.14–2.44)	0.0080†
>5 vs. ≤5	1.61 (1.06–2.44)	0.0269
>5.5 vs. ≤5.5	1.63 (0.89–2.97)	0.1115
Age dichotomization (years)
>45 vs. ≤45	1.69 (0.78–3.63)	0.181
>50 vs. ≤50	2.18 (1.17–4.06)	0.014‡
>55 vs. ≤55	1.26 (0.84–1.90)	0.266
>60 vs. ≤60	1.42 (0.97–2.07)	0.072
>65 vs. ≤65	1.46 (1.00–2.15)	0.051
>70 vs. ≤70	1.65 (1.08–2.51)	0.020
>75 vs. ≤75	2.19 (1.34–3.60)	0.002‡

^†Best cut-off point for LAD. ^‡75 years is the best cut-off point for age followed by 50 years as the second best cut-off point. Abbreviations as in Table 1.

Table 5. Predictors of New-Onset AF in the Echocardiographic Sample: Multivariate Analysis

Model 1: Age as a continuous variable			Model 2: Age dichotomized at 50 years			Model 3: Age dichotomized at 75 years
Variables	HR (95% CI)	P-value	Variables	HR (95% CI)	P-value	Variables	HR (95% CI)	P-value
Age	1.02 (1.00–1.04)	0.031	Age>50 vs. ≤50 years	1.93 (1.03–3.62)	0.042	Age>75 vs. ≤75 years	2.11 (1.28–3.46)	0.003
LAD>4.5 vs. ≤4.5 cm	1.67 (1.15–2.44)	0.008	LAD>4.5 vs. ≤4.5 cm	1.67 (1.14–2.43)	0.008	LAD>4.5 vs. ≤4.5 cm	1.67 (1.15–2.44)	0.008
IHD	1.66 (1.09–2.52)	0.017	IHD	1.70 (1.13–2.57)	0.011	IHD	1.77 (1.18–2.67)	0.006
			Highest risk subgroup based on model 2 Patients with IHD+(LAD>4.5 cm)+ (age>50 years) vs. others			Highest risk subgroup based on model 3 Patients with IHD+(LAD>4.5 cm)+ (age>50 years) vs. others
				HR (95% CI)	P-value		HR (95% CI)	P-value
			–	2.52 (1.72–3.69)	<0.001	–	3.24 (1.64–6.42)	<0.001

Abbreviations as in Table 1.

Patients with ischemic etiology of HF, LAD>4.5 cm and age>50 years (n=272) were at increased risk of developing new-onset AF (HR, 2.52; P<0.0001) compared with others (n=854). Patients with ischemic HF etiology, LAD>4.5 cm and age>75 years (n=36) had a risk of new-onset AF with a HR of 3.24 (P=0.001) vs. others (n=1,089).

Discussion

In the present study, we showed that (1) the incidence of new-onset AF in patients with reduced LVEF in sinus rhythm was approximately 3% per year; (2) older age, ischemic HF etiology and increased LAD were independently associated with the development of new-onset AF; and (3) patients with IHD, LAD>4.5 cm and age>50 years had a 2.5-fold higher risk of AF than patients without any of these characteristics, and the risk increased to 3.2-fold with age >75.

A number of studies have suggested the adverse role of AF in patients with HF, in terms of both morbidity and mortality.^6,7,18,19 Mountantonakis et al analyzed 99,810 patients hospitalized with HF, of whom one-third had AF, and reported longer hospital stay and higher mortality in AF patients as compared with those in sinus rhythm.¹⁸ Indeed, patients with HF who subsequently develop AF have a higher mortality rate.^8,9,20 A Carvedilol or Metoprolol European Trial (COMET) sub-analysis showed that overall mortality was markedly increased when AF developed (relative risk, 1.9; P<0.0001).⁸ Sub-analysis of the J-RHYTHM Registry, which investigated Japanese patients with non-valvular AF, also found that both cardiac and non-cardiac mortality increased with aging, but mortality rates could be reduced by therapeutic anticoagulation with warfarin.²¹ Therefore, identification of patients with high risk for AF while they are still in sinus rhythm can be of great clinical value. As far as we know, however, no study on the identification of patients at risk of developing new-onset AF has included echocardiographic parameters.

The incidence rate of new-onset AF in the present study cohort was consistent with several previous studies including Eplerenone in Mild Patients Hospitalization And Survival Study in Heart Failure (EMPHASIS-HF),²² COMET,²³ and Systolic Heart failure treatment with the I_f inhibitor ivabradine Trial (SHIFT),²⁴ which showed an annual incidence of AF in HF patients of 3–5%. The Framingham study found that patients with HF carried a lifetime risk for developing AF of 10% in men and 12% in women.⁴ Norberg et al recently conducted a survey to determine the prevalence of AF in the general population of 75,945 subjects in northern Sweden, and found that the overall AF prevalence was 3.0% and increased steadily with age, to 16.8% in those ≥75 years, and 21.9% in those ≥85 years.²⁵ We think that an AF annual incidence of 2.9% per year, or presumably almost 30% over a 10-year period, is reasonable given the significantly higher risk in HF patients than in the general population.

Of note, previously reported AF risk factors in the general population such as obesity, diabetes, peripheral vascular disease and renal dysfunction^17–20 were not found to be associated with new AF in the present cohort. These factors predispose to IHD and possibly AF development, but their individual effect may become less important for risk stratification of patients for new-onset AF once the condition they predispose to and which is a strong AF predictor (ie, IHD), has already developed. In addition, patients with and without new-onset AF had similar exposure to the previously known risk factors such as hypertension and diabetes, which may contribute to the difference of the present results with those of previous studies. In contrast, AF and HF frequencies are known to increase with advancing age, but the age cut-off of 50 years associated with new-onset AF in the present study was unexpectedly low (Tables 4,5). This suggests that monitoring of patients with HF in sinus rhythm for new-onset AF should begin at a relatively young age, especially when IHD and even mild-moderate LA enlargement are present. Considering the fact that reduced systolic function itself can predispose to new-onset AF, and that subjects aged >50 years carried an incremental risk of AF development even in community based studies,^26,27 we believe that the present finding of a lower than expected age cut-off for AF development risk in HF patients is a valid one, and is consistent with the literature.

In the present study, LAD was found to be the only echocardiographic predictor of new-onset AF among HF patients. The association of large LAD and AF development has been reported in previous papers.²⁸ LA dilation itself can be a trigger of AF, but it can also be a result of long-term LV compliance/relaxation abnormality, especially in patients with reduced LVEF. Interestingly, the present study showed that a relatively mild enlargement of LA (≥4.5 cm) was associated with increased risk, especially in patients with ischemic HF etiology. The comparison of LAD between patients with and without AF showed only a small difference; nevertheless, those with LAD>4.5 mm had a 70% higher risk of developing AF than those with LAD≤4.5 mm. This again provides useful information to clinicians to identify patients at high risk for new-onset AF for monitoring and possibly early intervention. Although the prevalence of AF has been reported to be associated with the severity of HF and NYHA class,⁷ to our knowledge no data showing a relationship between LVEF and the incidence of AF exist. The present analysis also failed to demonstrate a relationship between LVEF and new-onset AF.

The efficacy of β-blockers in preventing AF has been widely recognized, especially in patients with HF,²⁹ although the optimal β-blocking agent for prevention of AF is still under debate.^30,31 In WARCEF, 90% of patients were on β-blockers, 98% were on ACEI/ARB, 60% were on an aldosterone blocker, 80% were on loop diuretics, and 80% on a statin.¹¹ ACEI/ARB have emerged as promising drugs for prevention of the development of AF.³² Because almost all of the present patients received ACEI/ARB at the time of enrollment, and the frequency of patients in both groups who received this treatment was similar, we could not evaluate the effect of this type of treatment on AF development. Furthermore, the proportions of patients receiving loop diuretics and aldosterone blockers were not significantly different between patients who did and did not develop new-onset AF; therefore, this information was not included in the analysis. Beta-blocker usage, however, although highly prevalent, was different between the groups and therefore remained as a factor associated with AF development/prevention.

Even under optimal medical treatment for HF with the use of drugs known to prevent AF, we found that nearly 10% of patients had new-onset AF during a mean 3.5-year follow-up. This suggests that the effectiveness of these drugs in preventing AF occurrence is only partial, further underlining the importance of AF early detection and treatment. In the overall sample, the incidence of AF was higher in patients with β-blocker usage than in those without. This was observed in the echo sample as well, although it was not statistically significant, likely because of the small sample size. We speculate that a possible reason for this unexpected finding is that patients who were on β-blockers at enrollment were already at a greater risk for AF than those who were not. We do not believe β-blocker use was in itself associated with AF development; rather, a greater frequency of conditions for which β-blocking treatment is indicated and that also predispose to AF development (tachycardia and other arrhythmias, coronary artery disease, hypertension) might contribute to this apparently paradoxical finding.

The strengths of the present study include the relatively large sample size of HF patients in sinus rhythm and the centralized reading of echocardiographic tests. Also, HF patients in the USA number an estimated 5.7 million, and approximately 70% of them are believed to be in sinus rhythm.³³ Therefore, the present findings apply to a large patient population. Limitations of the study include the availability of echocardiographic LA data in only approximately 50% of patients; the analyses were adjusted, however, for variables that differed between patients with and without LAD information, which should have lessened the possibility of an effect of selection bias on the results. Furthermore, the prevalence of some previously known AF risk factors was not different between patients with and without new-onset AF. Another limitation is that some pertinent echocardiographic variables, especially diastolic function on more modern assessment such as tissue Doppler examination, were not available. In the present study, we did not include a detailed electrocardiographic analysis, in particular with regard to variables that are associated with new-onset AF such as P-wave amplitude.³⁴

Conclusions

Age, ischemic etiology of HF and increased LAD independently predict new-onset AF in patients with HF and sinus rhythm, and their combination increases the risk even at an age and with an LA diameter lower than expected. These results may help in the risk stratification of HF patients for new-onset AF, and perhaps select a subgroup of patients in whom prolonged cardiac rhythm monitoring may be warranted to facilitate the detection of silent AF episodes. Considering the millions of patients with HF and sinus rhythm in the USA,³³ and worldwide, even a slight improvement in the ability to predict new AF might result in an important stroke risk reduction at a population level, allowing the use of appropriate anticoagulant therapy at the appropriate time.³⁵

Acknowledgments

The present study was funded by U01-NS-043975 (S.H.) and U01-NS-039143 (J.L.P.T.) from the National Institute of Neurological Diseases and Stroke.

Disclosures

The authors declare no conflicts of interest.

Supplementary Files

Supplementary File 1

Table S1. Baseline characteristics in patients with and without echo covariates

Please find supplementary file(s);

http://dx.doi.org/10.1253/circj.CJ-15-1054

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