Download Echocardiographic diastolic parameters and risk of atrial

CLINICAL RESEARCH
European Heart Journal (2012) 33, 904–912
doi:10.1093/eurheartj/ehr378
Heart failure/cardiomyopathy
Echocardiographic diastolic parameters
and risk of atrial fibrillation: the Cardiovascular
Health Study
Michael A. Rosenberg 1*, John S. Gottdiener 2, Susan R. Heckbert 3,
and Kenneth J. Mukamal 4
1
Beth Israel Deaconess Medical Center, Cardiovascular Institute, 185 Pilgrim Road, Baker 4, Boston, MA 02215, USA; 2Department of Medicine, University of Maryland Hospital,
Baltimore, MD, USA; 3Department of Epidemiology, University of Washington, Seattle, WA, USA; and 4Department of General Medicine and Primary Care, Beth Israel Deaconess
Medical Center, Boston, MA, USA
Received 13 April 2011; revised 16 August 2011; accepted 13 September 2011; online publish-ahead-of-print 11 October 2011
Aims
Atrial fibrillation (AF) is the most common sustained arrhythmia in the elderly, and shares several risk factors with
diastolic dysfunction, including hypertension and advanced age. The purpose of this study is to examine diastolic
dysfunction as a risk for incident AF.
.....................................................................................................................................................................................
Methods
We examined the association of echocardiographic parameters of diastolic function with the incidence of AF in 4480
and results
participants enrolled in the Cardiovascular Health Study, an ongoing cohort of community-dwelling older adults from
four US communities. Participants underwent baseline echocardiography in 1989–1990 and were followed for
incident AF on routine follow-up and hospitalizations. After 50 941 person-years of follow-up (median follow-up
time 12.1 years), 1219 participants developed AF. In multivariable-adjusted age-stratified Cox models, diastolic echocardiographic parameters were significantly associated with the risk of incident AF. The most significant parameters
were the Doppler peak E-wave velocity and left atrial diameter, which demonstrated a positive nonlinear association
[HR 1.5 (CI 1.3 –1.9) and HR 1.7 (CI 1.4 –2.1) for highest vs. lowest quintile, respectively], and Doppler A-wave
velocity time integral, which displayed a U-shaped relationship with the risk of AF [HR 0.7 (CI 0.6 –0.9) for
middle vs. lowest quintile]. Each diastolic parameter displayed a significant association with adjusted NT-proBNP
levels, although the nature of the association did not entirely parallel the risk of AF. Further cluster analysis revealed
unique patterns of diastolic function that may identify patients at risk for AF.
.....................................................................................................................................................................................
Conclusion
In a community-based population of older adults, echocardiographic measures of diastolic function are significantly
associated with an increased risk of AF.
----------------------------------------------------------------------------------------------------------------------------------------------------------Keywords
Atrial fibrillation † Diastolic dysfunction † Ageing † Echocardiography
Introduction
The prevalence of atrial fibrillation (AF) in the population is
increasing.1 Some 2.3 million adults in the USA currently have
AF, a figure expected to increase to 5.6 million by the year
2050, with more than 50% being more than 80 years of age.2 In
addition to advanced age, hypertension is a well-known risk
factor for AF,3 and has been shown to be predictive for the
development of AF in large population studies.4 Despite these
well-known associations, the specific mechanisms through which
these processes act to cause AF are less well known.
Diastolic dysfunction refers to impairment in the ventricular filling
phase of the cardiac cycle. It is often broken down into several components, including impaired myocardial relaxation, increased left
atrial pressure, decreased left ventricular compliance, and deficiencies
in atrial contraction.5 Impairment in any single component, or often
several at once, can cause increased pressure to be transmitted
back to the atria, pulmonary veins, and lungs. As a result, diastolic
dysfunction has been associated with increased mortality,6 as well as
increased risk of hospitalization7 and congestive heart failure.8
Atrial fibrillation and diastolic dysfunction share many common
risk factors, including ageing and hypertension.9 – 11 Hypertension
* Corresponding author. Tel: +1 617 667 8800, Fax: +1 617 206 9570, Email: [email protected]
Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2011. For permissions please email: [email protected]
905
Echocardiographic diastolic parameters and risk of AF
itself, as well as left-ventricular hypertrophy that occurs as a result
of chronic hypertension, is a well-known risk factor for diastolic
dysfunction.12 In addition, diastolic dysfunction, such as AF,
increases with age,13 and patients given the diagnosis of diastolic
dysfunction were more likely to have AF at the time of diagnosis.14
Smaller, shorter-term studies have shown that certain subtypes of
diastolic dysfunction are at greater risk of AF.15 Yet, despite their
shared risk factors and association, large studies with long-term
follow-up examining the relationship between diastolic dysfunction
and incident AF are lacking.
In this study, we examined the characteristics of diastolic
function measured by echocardiography on the incidence of AF
in a large cohort of participants over 65 years of age adjusting
for known risk factors for AF.
Methods
Population
The design and objectives of the Cardiovascular Health Study have
been previously described.16 In brief, CHS is a longitudinal study of
5201 men and women aged 65 years, randomly selected from Medicare lists in Pittsburgh, PA; Forsyth County, NC; Sacramento, CA;
and Hagerstown, MD. The original cohort was enrolled in 1989 –
1990; a second cohort of 687 African-Americans was recruited in
1992– 1993, but is not included in these analyses as they did not
undergo baseline echocardiography. The institutional review board at
each centre approved the study, and each participant gave informed
consent.
The baseline examination included a standardized questionnaire,
validated previously by Psaty et al.,17 assessing a variety of risk
factors, including smoking, alcohol intake, history of stroke, coronary
heart disease, and heart failure, self-reported health status, and medications on enrolment. The physical examination included measurements of height, weight, and seated blood pressure measured with a
random-zero sphygmomanometer,17 as well as a resting 12-lead
ECG. Laboratory examinations included measurement of total cholesterol, high-density lipoprotein cholesterol, fasting glucose, C-reactive
protein, serum creatinine,18 and NT-proBNP,19 although NT-proBNP
was only available in 3464 individuals in the analytic data set
(see below).
Of the initial 5201 individuals in the original population, 130 people
were excluded due to prevalent AF. We also excluded an additional
130 participants due to the presence of mitral stenosis or greater
than moderate aortic insufficiency or mitral regurgitation. We
excluded 180 participants with a confirmed history of stroke due to
concerns that prevalent AF, and subsequent thromboembolism, may
have been the aetiology of the stroke; these subjects had a particularly
high risk of subsequent stroke that validated this concern. An
additional 281 participants were excluded due to the absence of
major echocardiography information used in this study to analyse diastolic dysfunction, leaving a final study population of 4480 subjects.
Echocardiography
The design of the echocardiography protocol used in CHS has been
described in detail elsewhere.20 Briefly, for each subject, a baseline
echocardiogram was recorded onto super-VHS tape with a Toshiba
SSH-160A cardiac ultrasound machine using a standardized protocol.
Videotapes were reviewed at the central Echocardiography Reading
Center using an offline image-analysis system equipped with
customized computer algorithms. Quality-control measures included
standardized training of echo technicians and readers, periodic technician observation by a trained echocardiographer, blind duplicate
readings to establish interreader and intrareader measurement variabilities, periodic reader review sessions, phantom studies on the ultrasound equipment, and quality-control audits. Echocardiographic
parameters included qualitative two-dimensional left ventricular systolic function, qualitative two-dimensional left ventricular chamber size,
M-mode-based parasternal long-axis left atrial dimension (LA diameter), and Doppler mitral valve inflow consisting of early and late
peak velocity (peak E and A velocity, respectively), and velocity time
integral (E and A wave VTI, respectively) and Doppler mitral valve
first third of early filling velocity.20 The Doppler mitral valve inflow
images were obtained from two averaged beats of pulse-wave
Doppler image obtained through placement of the cursor at the
mitral valve leaflet tips in the apical four-chamber view,20 with
measurements of peak E and A velocities, and velocity time integrals
taken on the same image. We also included ratios of peak early-to-late
velocity (E/A ratio) and ratio of early-to-late velocity time integrals
(E/A VTI ratio). M-mode-based quantitative measurements of fractional
shortening and left ventricular dimensions were only available in a
subset of individuals, and thus were excluded from the analysis.
Although left atrial volume has been described as a more accurate
measure of left atrial size than two-dimensional left atrial diameter,21
only the M-mode-based parasternal long-axis-derived left atrial diameter was available in most participants. To evaluate how closely this
single linear measure estimated left atrial volume, we used results
from a second echocardiogram from 1994 to 1995 in which left
atrial volume was measured in a subset of CHS participants.21 We
found a Spearman correlation of parasternal long-axis LA diameter
with LA volume of 0.73 among 372 participants free of prevalent or
incident congestive heart failure.
Determination of incident atrial fibrillation
Participants were contacted every 6 months for follow-up, alternating
between a telephone interview and a clinic visit for the first 10 years
and by telephone interview only after that. An annual resting ECG
was obtained yearly through the ninth year of follow-up. Discharge
diagnoses for all hospitalizations were entered into the database.
Adjudication of cardiovascular events was performed by a centralized
events committee.22 Annual study ECGs were interpreted by the
EPICARE ECG reading centre, where the diagnoses of AF or atrial
flutter were verified.23 When hospital discharge diagnosis International
Classification of Diseases, Ninth Revision, code identified AF or atrial
flutter, AF was considered to be present as of the date of hospital
admission. [A prior study determined the positive predictive value of
hospital discharge diagnosis to be 98.6% for diagnosis of AF in
CHS23 and a Holter substudy identified that only 1 in 819 subjects
(0.1%) had persistent or intermittent AF not identified by the above
measures.]24
Analysis
SAS version 9.2 (SAS Institute, Cary, NC, USA) was used for all
analyses. The primary outcome was the development of incident AF,
with the follow-up time being that from baseline until first episode
of AF, death, or end of follow-up. We used Cox proportional
hazards models, with independent hazard functions for each year of
participant age. The initial base model incorporated the following covariates, selected based on relevance from prior studies and univariate
associations with the risk of AF within this cohort: gender; height; BMI;
ECG findings of first degree AV block (PR interval greater than
906
200 ms), bradycardia (heart rate , 60 b.p.m.), Q waves in a regional
distribution or any ventricular conduction delay (including right
bundle branch block, left bundle branch block, or intraventricular conduction delay);25,26 history of congestive heart failure (based on clinical
diagnosis by the treating physician), diabetes (American Diabetic
Association definition), hypertension (defined as blood pressure
greater than 140/90 mmHg, or on medications to reduce high blood
pressure), or self-reported history of myocardial infarction;17 systolic
and diastolic blood pressure, fasting glucose and creatinine level
measured on enrolment; the use of diuretics beta-blockers, calcium
channel blockers and ACE inhibitors on enrolment; and peak FEV-1,
also measured on enrolment.
To avoid assumptions about linearity, echocardiographic variables
were examined in quintiles, and were initially inserted into the
model and tested for heterogeneity across quintiles using the Wald
Chi-square test. These were then examined simultaneously, with
exclusion of non-significant echocardiographic variables from the
model. Schoenfeld residuals and time-varying covariates were used
to test for violation of the proportional hazards assumption; none
were noted.
We performed a sensitivity analysis on the 3464 participants in
whom NT-proBNP levels were available, further adjusting our Cox
models for NT-proBNP. We also tested adjusted mean NT-proBNP
levels for each quintile of significant echocardiographic parameter
using generalized linear models.
As an additional exploration, hierarchical cluster analysis was
performed using the Ward method27 in which individuals were clustered into six groups according to the three primary echocardiographic parameters. Initial studies revealed that this clustering
algorithm divided participants relatively evenly, with the exception of
one group of four individual outliers, who were excluded from the
analysis, leaving five well-balanced groups. Qualitative graphical examination of eigenvalues confirmed reasonable separation of clusters.
Clusters were analysed within the base model as mentioned above,
as well as in a substudy of the 3464 participants with NT-proBNP
levels. NT-proBNP levels were also measured for each cluster.
Results
Of 4480 participants studied for median follow-up of 12.1 years
(interquartile range 6.6 –17.2 years; total 50 941 person-years),
1219 developed AF. Characteristics of the study population are
shown in Table 1. The diastolic parameters we studied had
values consistent with prior studies of elderly populations,28 – 31
and were normally distributed across the population.
When inserted into the base model, we found that M-mode
parasternal long-axis LA diameter, early Doppler mitral valve
inflow velocity (peak E velocity), and late inflow Doppler mitral
valve velocity time integral (A wave VTI) were the strongest predictors of incident AF. The Doppler mitral valve late inflow velocity
(peak A wave velocity) was significantly associated with incident
AF, but only when the A wave VTI was excluded; thus we did
not include it in our final model. We also did not include the
mitral valve Doppler peak velocity E/A ratio, the VTI E/A ratio,
or the first third filling of early diastole in the final model, as
none of these parameters was significantly associated with the
AF incidence. Table 2 demonstrates the hazard ratio for quintiles
of each of these diastolic parameters, as well as qualitative LV
function and chamber size, when all three significant diastolic
M.A. Rosenberg et al.
Table 1 Selected baseline characteristics of 4480 CHS
participants, including echocardiography parameters
and incidence of AF
Characteristic
................................................................................
Demographics
Age (years, mean + SD)
72.6 + 5.5
Male gender, n (%)
BMI (mean + SD)
1880 (42)
26.4 + 4.5
................................................................................
Medical history
CHF, n (%)
MI, n (%)
139 (3)
415 (9)
DM, n (%)
1263 (28)
HTN, n (%)
2493 (56)
Medications
Diuretics, n (%)
1082 (24)
................................................................................
Beta-blockers, n (%)
556 (12)
Calcium channel blockers, n (%)
ACE inhibitor, n (%)
509 (11)
272 (6)
Digoxin, n (%)
277 (6)
................................................................................
Cardiac function
Normal systolic function, n (%)
Mildly depressed systolic function, n (%)
4103 (92)
230 (5)
Severely depressed systolic function, n (%)
133 (3)
................................................................................
Echocardiography
Doppler peak E velocity, m/s (mean + SD)
Doppler peak A velocity, m/s (mean + SD)
0.71 + 0.17
0.80 + 0.21
Doppler E wave velocity time integral, cm
(mean + SD)
12.0 + 5.0
Doppler A wave velocity time integral, cm
(mean + SD)
8.7 + 3.2
M-Mode left atrial diameter, cm (mean + SD)
3.9 + 0.6
E/A velocity ratio (mean + SD)
0.93 + 0.35
................................................................................
Outcome
Atrial fibrillation, n (%)
1219 (27.2)
Data presented in the table are mean and SD for continuous variables and number
of cases with percentage in parentheses for categorical variables.
BMI, body mass index; CHF, congestive heart failure; MI, history of myocardial
infarction; DM, diabetes mellitus; HTN, hypertension. See Text for details of
echocardiography data.
parameters are included in the model. Both the LA diameter and
peak E velocity displayed an increasing relationship with the risk
of AF. The A wave VTI displayed a U-shaped relationship with
the AF incidence, with the lowest risk in the middle quintile and
highest risk in the two extreme quintiles. Kaplan –Meier curves
for the predictive diastolic parameters of peak E velocity, A wave
VTI, and LA diameter are shown in Figure 1.
The serum NT-proBNP level has been shown to be linearly
associated with the risk of incident and prevalent AF.19 Within
the subset of the larger sample in whom levels had been obtained,
we found NT-pro-BNP was strongly associated with the risk of AF
when inserted in the base model along with predictive diastolic
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Echocardiographic diastolic parameters and risk of AF
Table 2
Hazard ratio for incident atrial fibrillation according to echocardiographic parametersa
Parameter
Quantile/group
Adjusted HR
95% CI
P heterogeneity
Peak E velocity
1 (0.16– 0.56 m/s)
2 (0.57– 0.65 m/s)
3 (0.66– 0.73 m/s)
4 (0.74– 0.83 m/s)
5 (0.84– 1.85 m/s)
1.0
0.983
1.095
1.172
1.549
–
0.807–1.197
0.900–1.334
0.961–1.429
1.275–1.883
,0.001
1 (1 –6 cm)
2 (7 –7 cm)
3 (8 –9 cm)
4 (10–10 cm)
5 (11–80 cm)
1.0
0.881
0.742
0.803
0.946
–
0.716–1.085
0.622–0.886
0.645–1.001
0.772–1.160
0.005
1 (1.5–3.3 cm)
2 (3.3–3.7 cm)
3 (3.7–4.0 cm)
4 (4.0–4.4 cm)
5 (4.4–6.5 cm)
1.0
1.002
0.954
1.176
1.696
–
0.818–1.228
0.774–1.177
0.961–1.440
1.386–2.075
,0.001
Normal
Mildly depressed
Severely depressed
1.0
1.227
1.077
–
0.937–1.605
0.694–1.670
0.33
Normal
1.0
–
0.55
Mildly dilated
Severely dilated
1.072
1.212
0.839–1.368
0.844–1.741
...............................................................................................................................................................................
...............................................................................................................................................................................
A wave VTI
...............................................................................................................................................................................
Left atrial diameter
...............................................................................................................................................................................
LV systolic function
...............................................................................................................................................................................
LV chamber size
a
Adjusted for gender, height, BMI, any AV block on ECG, bradycardia on ECG, any Q waves on ECG, any history of ventricular conduction disease on ECG, history of congestive
heart failure, diabetes, hypertension, or myocardial infarction, systolic, and diastolic blood pressure, random glucose and creatinine level, diuretic use, beta-blockers, calcium
channel blockers, and ACE inhibitors, and peak FEV-1, as well as peak E velocity, A wave VTI, LA diameter, qualitative LV systolic function, and qualitative LV chamber size.
Figure 1 (A) Kaplan– Meier curve for quantiles of Doppler early mitral inflow velocity on survival free from atrial fibrillation, with adjustment
for risk factors (see text). (B) KM curve for Doppler late mitral inflow velocity time integral. (C ) KM curve for M-mode derived left atrial size.
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M.A. Rosenberg et al.
Figure 2 BNP levels according to specified quantiles of Doppler early MV inflow velocity, late MV inflow VTI, and M-mode LA size, with
adjustment for base model variables (see text for details). *P , 0.05 vs. lowest quintile. †P , 0.05 vs. middle quintile.
parameters (HR 3.80, 95% CI, 2.92–4.95, for quintile 5 vs. quintile 1).
Diastolic parameters remained significantly associated with the risk
even with adjustment for NT-proBNP, although inclusion modestly
reduced the risk estimates associated with diastolic parameters.
For example, the HR for the highest quintile vs. the lowest quintile
of peak E velocity decreased from 1.58 (CI 1.26–1.970) to 1.46
(CI 1.17–1.83) and HR for the highest quintile vs. lowest quintile
of LA size decreased from 1.76 (CI 1.41– 2.21) to 1.63 (CI
1.30 –2.04). Likewise, the hazard ratio for the middle quintile vs.
the lowest quintile of late flow velocity integral increased from
0.70 (0.57–0.86) to 0.78 (0.64–0.96).
To further explore the relationship between serum NT-proBNP
and diastolic function, we examined levels of NT-proBNP for each
of the predictive diastolic parameters, LA diameter, peak E velocity, and A wave VTI, after adjustment for base model co-variates
(Figure 2). Both peak E velocity and LA diameter displayed a trend
toward increased NT-proBNP with increasing velocity and size
(Figure 2, peak E velocity Ptrend , 0.001; LA diameter Ptrend ¼
0.02). A wave VTI displayed a decreasing relationship with the
NT-proBNP level, with the lowest quintile having the highest
mean NT-proBNP level (Ptrend , 0.001).
Although we found certain individual metrics of diastolic function
to be independently associated with the AF incidence, a number of
studies have used multiple diastolic parameters to classify patients
into categories of diastolic dysfunction.6,15,32 As we were missing
many of the parameters used in these studies, such as deceleration
time, pulmonary vein inflow, and tissue Doppler, rather than
attempting to ‘fit’ the patients into one of these categorization
schemes, we chose to explore patterns of diastolic dysfunction
based on echocardiographic parameters of diastolic function
through the use of cluster analysis. We clustered participants using
the three predictive diastolic parameters LA diameter, peak E velocity, and A wave VTI (for details, see Analysis in the Methods
section). The characteristic diastolic echocardiographic parameters
of each of the five clusters are shown in Table 3. Notably, only Clusters 4 and 5 were associated with increased risk of incident AF when
included in the base model, with HR of 1.65 and 1.67, respectively
(Table 4). These clusters had the common characteristic of having
peak E velocity increased from the population mean. Cluster 2, in
which the LA size alone was increased, and Cluster 3, in which the
A wave VTI alone was increased, were not associated with the risk
of AF. When NT-proBNP was examined with the cluster data (Supplementary material online, Table S1), we found that interestingly,
only Cluster 5 displayed evidence of effect attenuation with
regards to risk for incident AF—HR 1.67 (CI 1.38– 2.01) for
Cluster 5 without NT-proBNP and HR 1.53 (CI 1.23–1.91) with
NT-proBNP included. Compared with the other groups, Cluster 5
also had an average higher unadjusted NT-proBNP level of 380 +
55 pg/dL, compared with the other clusters, with the next highest
level in Cluster 4 of 293 + 32 pg/dL (Supplementary material
online, Table S1).
Discussion
In this large population of older adults, with over 1000 cases of AF,
we found a strong relationship between ventricular diastolic filling
parameters and the risk of incident AF. Each of three markers of
diastolic function—LA size, peak E velocity, and A wave VTI—independently predicted the development of incident AF. In addition,
through the application of a novel technique in the study of diastolic function called cluster analysis, we identified groups of individuals at increased risk for AF, based on these variables.
The importance of left atrial enlargement has been well
described as a risk factor for incident AF,19,33 and thus our
finding that increased LA diameter independently predicts AF is
not surprising. However, to our knowledge, few if any of the
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Echocardiographic diastolic parameters and risk of AF
Table 3
Cluster
Echocardiography parameters of clustersa
Number
Doppler MV early inflow
velocity, m/s (mean + SD)
Doppler MV late inflow
VTI, cm (mean + SD)
Left atrial size, cm (mean + SD)
...............................................................................................................................................................................
1
1377
0.71 + 0.11
7.6 + 1.7
3.33 + 0.48
2
1246
0.57 + 0.099
7.9 + 1.9
4.20 + 0.46
3
4
643
631
0.61 + 0.12
0.80 + 0.11
10.5 + 1.9
10.1 + 3.0
3.53 + 0.33
4.53 + 0.45
579
0.97 + 0.14
8.8 + 2.9
4.00 + 0.58
4476
0.71 + 0.17
8.7 + 3.2
3.86 + 0.60
5
Total/mean
a
See text for details of cluster analysis.
Table 4 Hazard ratios for incident atrial fibrillation
for each cluster with adjustment for base model
variables*
Cluster
HR
95% CI
................................................................................
1
1.0
–
2
3
1.04
1.03
0.88–1.24
0.84–1.27
4
1.65
1.36–1.99
5
1.67
1.38–2.01
Adjusted for gender, height, BMI, any AV block on ECG, bradycardia on ECG, any
Q waves on ECG, any history of ventricular conduction disease on ECG, history of
congestive heart failure, diabetes, hypertension, or myocardial infarction, systolic
and diastolic blood pressure, random glucose and creatinine level, diuretic use,
beta-blockers, calcium channel blockers, and ACE inhibitors, and peak FEV-1.
*P(heterogeneity) , 0.001.
Doppler-based echocardiographic variables have independently
been shown to change the risk for incident AF. Our finding that
both peak E velocity and the A wave VTI can be used in the prediction of AF in older individuals thus supports what many
clinicians had long assumed: that there is a physiological mechanism
for how certain risk factors like hypertension contribute to the
development of AF, and that mechanism might be diastolic dysfunction. However, although our results suggest that even limited
measures of diastolic dysfunction (compared with what is available
with tissue Doppler, strain imaging, and pulmonary vein flow
assessment) can be used to predict the development of AF, the
complexity of the relationship demonstrates that much more
needs to be learned about diastolic dysfunction and how it
affects the electrical activity in the atrium. In this study, we found
that such complexity may require novel analytical tools, and
perhaps changes in some of the prior assumptions about how
we describe diastolic function in terms of categorization.
One important approach we used in this study was to examine
diastolic parameters jointly and without assumptions about linearity. This approach was important because we found that all three
significant diastolic parameters displayed nonlinear associations
with the risk of incident AF. That risk would not have been
detected had we simply included the continuous variables into a
linear model, as prior studies have done.19 Instead, we were able
to demonstrate that above ‘high’ peak E velocities (.0.84 m/s),
the risk of AF increased nonlinearly, and at ‘normal’ A wave
velocity time integrals (8–9 cm), the risk is nonlinearly decreased.
In addition, through this method, we also found that prior relationships of diastolic parameters may not be useful, at least in regard to
predicting AF. One example was our finding that the relationship
between AF and diastolic filling patterns did not appear to
follow the established pattern determined by the E/A ratio.14,15
In our population, because risk was increased with increased
peak early filling velocity, but U-shaped with the A wave VTI, a
simple ratio of these two factors was unlikely to categorize risk
appropriately; hence, even with adjustments for nonlinearity, we
did not detect a significant effect from the E/A ratio. Other
studies have shown a similar U-shaped relationship between late,
atrial-based, ventricular filling and risk of AF,34 supporting our
finding that the nature of the early and late ventricular filling
relationship is more complex with regard to risk of incident AF.
The second approach employed in this study to explore the
complex relationship between diastolic parameters and AF was
to use an unsupervised hierarchical cluster analysis based on the
diastolic echocardiography parameters. Many studies of diastolic
dysfunction have used pre-determined classification schemes to
group individuals to predict risk of AF,15 CHF,32 or mortality.6
One key limitation to this approach was demonstrated in the analysis by Tsang et al.,15 in their study of diastolic dysfunction on AF
risk in 840 elderly men and women, in which the only diastolic parameter that individually was correlated with AF risk was left atrial
volume. As a result, although they developed and utilized a categorical approach to diastolic classification based on prior studies of
diastolic function, the only clinically important factor was the LA
volume, raising the question of whether categorization of diastolic
function was even necessary. Although we found that other diastolic parameters were independently associated with AF risk, we
still had no method to determine whether the highest risk individuals had the highest risk values for all diastolic parameters (i.e.
largest LA diameter and peak E velocity, and most abnormal A
wave VTI) or whether these parameters tended to segregate independently as well. To explore this question further, we employed
the cluster analysis, in which we found that when ‘forced’ to divide
into five groups based on diastolic function, it was two groups
(Clusters 4 and 5) that were at increased risk. From this analysis,
we made several interesting observations.
910
The first was the recognition that there might be groups not
previously identified in standard classification schemes of diastolic
dysfunction that were at an increased risk for incident AF. For
example, Cluster 4 had both increased early and late filling
(increased A wave VTI) compared with the mean, along with an
increased LA diameter, and had a 65% increase in the risk of incident AF compared with Cluster 1. The diastolic properties of this
group would not fall into one of the standard patterns of diastolic
dysfunction (i.e. impaired relaxation, pseudonormalization, or
restrictive filling),6,35 – 37 but may represent a separate AF risk
group in whom larger atria and more atrial-based ventricular
filling is associated with an increased risk of AF. Cluster 5, in
which the peak E velocity was elevated, but atrial filling was relatively normal and the LA size was mildly increased, may correspond to the ‘pseudonormal’ or restrictive filling patterns, which
have been associated with increased risk of AF,15 and perhaps
might also explain why it was the only category in which inclusion
of NT-proBNP appeared to attenuate the risk of AF, as this pseudonormal or restrictive filling patterns have been shown to have
elevated natriuretic peptide levels.32,38
A second observation was that increased peak E velocity, common
to both Clusters 4 and 5, appeared to be required for the development of incident AF, as neither increased LA size (Cluster 2) nor
increased atrial-based ventricular filling (Cluster 3) in isolation was
associated with an increased risk. This finding may have important
clinical implications, since it suggests that in an older population,
the peak E velocity may be the most important determinant of AF
risk, with increased LA diameter and changes in the A wave VTI
from normal being of secondary importance, although further
studies would be necessary to validate this finding.
A prior study by Patton et al.19 in this same elderly population
demonstrated that random serum NT-proBNP level was highly
predictive of AF incidence, when adjustments were made for
known confounders. That study included only limited analysis of
echocardiographic diastolic parameters, although subgroup analysis
failed to identify an interaction between LA size and NT-proBNP
level on AF incidence. One of the challenges of inclusion of
biomarkers in regression models is that the impact of inclusion
or exclusion of parameters rests primarily in the mechanism, and
thus confounding relationship, by which the biomarker is associated with the increased AF incidence. For this reason, we chose
not to include NT-proBNP in the original model since it remains
unclear whether NT-proBNP itself causes AF or whether it is
simply a marker of cardiac disease. When NT-proBNP was
included in the model during a secondary analysis, we found that
the predictiveness of each individual diastolic parameter decreased,
suggesting a mechanistic link. However, both diastolic variables and
NT-proBNP remained significantly predictive, indicating that each
may be acting via other mechanisms to increase AF incidence.
One interesting possibility mentioned earlier is that there may be
a separate population of patients, as identified in Cluster 4, who
have high atrial-based filling (increased A wave VTI) and LA enlargement, but relatively normal NT-proBNP levels, who are also at
increased risk of AF, although further research is necessary to
validate this finding.
Few previous prospective studies have attempted to examine
the association between diastolic function and AF, and none of
M.A. Rosenberg et al.
this size to our knowledge. One reason is that such a large
number of factors have been associated with the risk of AF, such
as hypertension, age, gender,3,4,39 BMI,40 GFR,41 bradycardia,42
FEV-1,43 as well as NT-proBNP level,19 that relatively large
studies are needed to account fully for important confounders.
One example of this limitation was demonstrated by Vasan
et al.,34 who examined diastolic parameters in the Framingham
cohort and found a trend towards increased risk of AF, although
the association was not significant (P ¼ 0.08), likely as a result of
being underpowered—only 85 individuals developed AF in their
study. Other groups have examined the unadjusted risk,15 although
such associations are limited by the inability to account for the
multiple confounders associated with AF.
A principal limitation of this study was that we were unable to
incorporate many of the more ‘modern’ measures of diastolic function including tissue Doppler, strain rate and strain analysis, and left
atrial volume applied across the entire population. This limitation
was an expected consequence of a study spanning two decades;
tissue Doppler, strain imaging, and other more advanced metrics
were unavailable at the time of study enrolment. It is possible,
but not yet proven, that more nuanced measures of diastolic function will in time demonstrate the importance of diastolic filling
properties on risk of AF, since an evident weakness of many
present non-invasive measures is that they are indirect measures
of diastolic function. In addition, it also possible that quantitative,
rather than qualitative, measures of LV size and function would
change the predictability of diastolic measures on predicting AF
incidence; further studies would be necessary to explore this
potential effect.
Another important caveat to this study is that its findings may
not necessarily be applicable to younger populations. It has been
well described that the E wave velocity decreases naturally with
ageing,44 and thus an elevated level that might be associated with
pathology in an older population may be within normal range
and not associated with increased AF risk in a younger population.
Future studies in younger populations will be necessary to answer
this question.
In conclusion, in this study we found that diastolic filling parameters are predictive of increased risk of AF incidence. This
association is complex, and required that we use an approach
that made no assumptions about linearity, as well as a secondary
analysis using the novel technique of hierarchical cluster analysis,
to uncover some of the potential clinical and mechanistic associations. Further studies will be necessary to demonstrate whether
changes in clinical practice, such as treatment adjustments based
on diastolic filling parameters, can decrease the incidence of AF
in patients at risk.
Supplementary material
Supplementary material is available at European Heart Journal
online.
Funding
The research reported in this article was supported by contracts N01HC-85239, N01-HC-85079 through N01-HC-85086, N01-HC-35129,
N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC-45133,
911
Echocardiographic diastolic parameters and risk of AF
and grant HL080295 and HL068986 from the National Heart, Lung,
and Blood Institute (NHLBI), with additional contribution from the
National Institute of Neurological Disorders and Stroke (NINDS).
Additional support was provided through AG-023629, AG-15928,
AG-20098, and AG-027058 from the National Institute on Aging
(NIA). A full list of principal CHS investigators and institutions can
be found at http://www.chs-nhlbi.org/pi.htm. S.R.H. also has received
funding from the NHLBI grant R01 HL068986.
20.
21.
22.
Conflict of interest: none declared.
23.
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