|

 |
Other Issues |
 |
|
VOLUME 10 NO.3 SEPTEMBER 2009 – NOVEMBER 2009
|
 |
PERSPECTIVE
Should we Screen Asymptomatic Diabetics
For Coronary Artery Disease?
1,2Mouaz H. Al-Mallah M.D.,F.A.C.C., 3Alawi A
Alsheikh-Ali, M.D.,
4Jassim Al Suwaidi, M.D., F.A.C.C., 5Mohammad
Zubaid, M.D.6
1Henry Ford Health System, Detroit, MI; 2Wayne
State University School of Medicine,
Department of Internal Medicine, Detroit, MI;
3Institute for Clinical Research and Health
Policy Studies,
Tufts University School of Medicine, Boston, MA;
4Hamad Medical Corporation, Doha, Qatar;
5Department of Medicine, Faculty of Medicine,
Kuwait University, Kuwait
|
|
|
Abstract
Diabetes is a major worldwide healthcare
problem and cardiovascular diseases are the
most common causes of mortality and
morbidity in the type 2 diabetic population
with Coronary artery disease (CAD)
accounting for 65% to 80% of deaths in
diabetic patients. It has been suggested
that screening asymptomatic diabetics could
identify early coronary artery disease which
may improve their outcomes. In this review,
we summarize the data regarding screening
asymptomatic diabetics and provide
recommendations based on the evidence. Heart
Views 2009;10(3)121-127. © Gulf Heart
Association 2009.
Keywords:
¨ diabetes ¨ coronary artery disease
Introduction
Diabetes is a major worldwide healthcare
problem, with 200 million people currently
having diabetes. It is estimated that the
prevalence worldwide will exceed will exceed
300 million by 2025 and 360 million by 2030.
The majority of these patients will have
type 2 diabetes1. A study in the United Arab
Emirates showed that nearly one fifth of the
population had high Framingham risk score
and nearly one fourth had diabetes2.
Cardiovascular diseases are the most common
causes of mortality and morbidity in the
type 2 diabetic population with Coronary
artery disease (CAD) accounting for 65% to
80% of deaths in diabetic patients. Haffner
and colleagues have shown that diabetic
patients without previous myocardial
infarction have as high a risk of myocardial
infarction as nondiabetic patients with
previous myocardial infarction3. In
addition, data from the GULF RACE registry
suggest that diabetic patients with ACS have
worse clinical outcomes than non
diabetics4,5. The current NCEP III
guidelines recommend treating diabetic
patients as a CAD equivalent6.
However, we do not know if all diabetics
have CAD? It is also unclear if identifying
patients with coronary disease impact on the
outcomes of these patients. Thus, accurate
cardiovascular risk stratification in
diabetics is needed. This could be difficult
since the clinical presentation and
progression of CAD differs between diabetic
and nondiabetic patients7. The Framingham
risk score is one of the tools that can be
used to determine 10-year (short-term) and
long-term (30 year) risk for developing
CAD8. However, the Framingham risk score may
provide imprecise estimates of future risk
of cardiovascular (CV) events in
diabetics9,10. Other indicators include
exercise capacity and metabolic activity.
While these measures provide important
prognostic information, their utility alone
in the diagnosis of CAD is limited. Thus,
there is a need for other modalities to
supplement the clinical criteria used in the
risk stratification of diabetic patients.
Multiple screening tests have been proposed
to be used to diagnose CAD in diabetic
patients. In this article, we review the
evidence behind the use of myocardial
perfusion imaging in asymptomatic diabetics.
What is the
prevalence of CAD in asymptomatic diabetics?
Myocardial perfusion imaging (MPI) is a
widely used imaging modality to detect
coronary disease that has high diagnostic
accuracy in evaluating CAD. Kang et al11
evaluated 138 patients with diabetes
who also underwent invasive angiography and
reported a sensitivity of 86% with a lower
specificity of 56%. Other Studies that
evaluated the prevalence of CAD in
asymptomatic patients with DM are summarized
in Table 1. The incidence of abnormal Single
photon emission computed tomography
myocardial perfusion imaging SPECT-MPI in
this patient population ranged between
16-58%. In addition, the incidence of
abnormal SPECT MPI was the same in
symptomatic and asymptomatic patients with
DM (59% vs 60%)12. In multivariate analysis,
Q waves on echocardiogram and peripheral
arterial disease were independently
associated with a high-risk scan and high
annual mortality rate13,14.
However, most of the above mentioned studies
were retrospective in nature and included
different patient populations that had
different pretest likelihood of CAD. To
date, there is only one study that has
prospectively evaluated the prevalence of
silent CAD in diabetic patients. The
Detection of silent myocardial Ischemia in
Asymptomatic Diabetic subjects (DIAD) 15
study enrolled 522 patients who were
screened for the presence of CAD by MPI. Of
these, 22% had an abnormal stress test
result. The number of atherosclerotic risk
factor was not associated with the presence
of a perfusion defect. Cardiac autonomic
neuropathy appeared to be the only
independent predictor of abnormal MPI; none
of the well-known CAD risk factors were.
Given the high prevalence of CAD in
asymptomatic diabetes, the current American
Diabetes Association (ADA) guidelines
recommend stress testing for diabetic
patients who have two other risk factors for
CAD16. Scognamiglio and colleagues17
evaluated the effectiveness of the current
American Diabetes Association screening
guidelines in identifying asymptomatic
patients with CAD in type 2 diabetes in 1899
asymptomatic patients (age £ 60 years) who
underwent dipyridamole myocardial contrast
echocardiography (MCE). In those with
myocardial perfusion defects, the anatomy of
coronary vessels was evaluated by selective
coronary angiography. The prevalence of
abnormal MCE was 60% irrespective of risk
factor profile. On catheterization, there
was higher prevalence of diffuse disease
(18% vs 55%, p < 0.001), and of vessel
occlusion (4% vs 31%, p < 0.001) in patients
with multiple risk factors.
In addition, earlier studies suggested that
screening for asymptomatic CAD in diabetic
patients may be cost effective if exercise
echocardiography was used. Compared with no
screening, incremental cost-effectiveness
ratio of exercise electrocardiography was
$41,600/QALY in 60-year-old asymptomatic
diabetic men with hypertension and smoking,
but was weakly dominated by exercise
echocardiography18.
|
Table 1: Prevalence of Abnormal of
MPI in asymptomatic diabetics
|
|
Fig.1: Changes in Medications in the
DIAD study after the NCEPIII
guidelines publications. |
Prognostic value of
SPECT MPI in diabetics
There is limited data evaluating the
prognosis of asymptomatic diabetic patients
with silent CAD. To date, reports have
consistently shown that normal MPI in
diabetic populations is not associated with
a low level of risk regardless of the
presence of symptoms. Moreover, the
cardiovascular mortality rate is more than
doubled in symptomatic diabetic patients,
especially if they had abnormal imaging
scans19. As shown in Table 2, the annual
event rate could be as high as 12 in
symptomatic diabetic patients. Rajagopalan
et al13 examined mortality rates in 826
asymptomatic diabetic patients. The
mortality rate in high-risk patients was
5.9%, in intermediate-risk patients 5.0%,
and in low-risk patients 3.6% (p < 0.001 for
differences between groups). Post hoc
analyses were performed to determine if a
truly low-risk (annual mortality < 1%)
subset of patients could be identified.
Annual mortality in patients without ECG
Q-waves or peripheral arterial disease and
with a completely normal SPECT imaging scan
(n = 443) was lower but was still 2.9%.
The DIAD study is the first large
prospective study addressing the issue of
whether a strategy of systematic screening
for silent coronary artery disease alters
cardiac outcome. It enrolled 1,123 diabetic
patients without symptomatic or previously
diagnosed CAD who were randomized to either
screening with myocardial perfusion imaging
or standard care without screening. After an
average five-year follow-up, there was a low
overall cardiac event rate and no difference
between the two groups. This could have been
mediated by a high use of
anti-atherosclerotic therapies in this
cohort. Unexpectedly, diabetic patients
without known CAD have an overall highly
favorable five-year prognosis with
contemporary therapy, such as aspirin,
statins, and ACE-inhibitors. (Figure 1)
However, in the group that was screened for
CAD, MPI provided incremental prognostic
information. Asymptomatic diabetic patients
with high risk scans had worse outcomes than
asymptomatic diabetic patients with normal
or low risk scans20.
The DIAD outcomes study suggests that
systematic screening cannot be recommended
in all asymptomatic patients with diabetes.
However, whether targeted screening results
in higher yield and improved outcomes is a
question that is still looking for an
answer. It appears that screening every
diabetic may not be cost effective and may
not alter long-term clinical outcomes.
Whether the value of screening a targeted
population of higher risk diabetics is not
known. These observations reflect the
heterogeneity of cardiovascular risk in
patients with diabetes (i.e. diabetics are
not equal). This heterogeneity may reflect
heterogeneity of the disease itself,
concomitant risk factors, or therapeutic
strategies used to control the underlying
metabolic derangement and associated risk
factors. The dilemma lies in how to identify
the high risk asymptomatic diabetic
population that may benefit from treated
screening by MPI. The DIAD study suggests
that the number of risk factors do not
identify this population. It is unclear
whether there is a biochemical marker that
could make this distinction. We believe that
using another imaging modality as a gate
keeper to screening by MPI may be the way to
go. Using biomarkers may not work. A study
of 44 individual with normal SPECT did not
show any role for the inflammatory markers
in predicating the presence of coronary
artery disease in participants with DM,
without medium size artery disease21.
|
Table 2: Prognostic
Value of SPECT MPI in diabetics |
|
Fig.2: Relation between
perfusion defects and Coronary
Calcium Scores. |
Do we need other
imaging modalities in asymptomatic
diabetics?
While not every diabetic patient has
obstructive coronary disease detectable by a
stress test, coronary calcium scoring (CCS)
provides a tool to identify early
atherosclerosis. It has been shown that CCS
has an excellent prognostic value for
subsequent cardiac events in asymptomatic
individuals22,23. High CCS can modify
predicted risk obtained from Framingham risk
score alone, especially among patients in
the intermediate risk category in whom
clinical decision making is most
uncertain24. A very low rate of cardiac
death and myocardial infarction (0.4%) over
3 to 5 years has been reported for
individuals without detectable calcium. In
contrast, annual event rates as high as 7.1%
have been reported for individuals a CCS >
1,000. The positive relationship between a
high CCS and an elevated cardiac event rate
may be explained by the fact that an
increase in coronary calcium reflects an
increase in overall coronary plaque burden.
More importantly, the absence of coronary
atherosclerosis on CCS or CCTA may
ameliorate the need for further testing
within a 3-5 year period.
Lahiri and colleagues prospectively
evaluated 510 asymptomatic type 2 diabetic
subjects without prior cardiovascular
disease using a strategy that involved CCS
in everyone and MPI in patients with a CCS
more than 10 Agatston units (AU). CCS > 10
AU was found in 46% and CAC > 100 was seen
in 25% of patients. In the subset of
patients with CCS > 1000, 70% of the patient
had an abnormal MPI compared to 48% of
patients with CCS between 400-1000 (Figure
2). Age, systolic blood pressure, the
duration of diabetes, United Kingdom
Prospective Diabetes Study risk score, CAC
score, and extent of MPI abnormality were
significant predictors of time to
cardiovascular events. This early data
suggests that using a hybrid screening
strategy may be beneficial and increases the
diagnostic yield of a screening strategy.
Such a strategy need to be evaluated in a
large multicenter randomized trial before it
is recommended widely.
What about Cardiac
MRI?
Cardiovascular magnetic resonance imaging (CMR)
plays an increasing role in the assessment
of patients with various cardiovascular
disorders. Given its enhanced spatial and
temporal resolution, improved tissue
characterization and lack of ionizing
radiation, it has often become the test of
choice in the evaluation of patients with
various clinical scenarios including
pericardial diseases, myocarditis, heart
failure and coronary artery disease.
Contrast-enhanced cardiac magnetic resonance
imaging (CMR) can determine the extent of
myocardial scar from infarction (MI). Among
patients with a clinical suspicion of
coronary artery disease but without a
history of MI, LGE involving a small amount
of myocardium carries a high cardiac risk25.
In a study of clinically indicated CMR
imaging in 187 diabetic patients, late
gadolinium enhancement (LGE by CMR was
present in 30 of 107 patients (28%) without
known prior CAD. At a median follow-up of 17
months, 38 of 107 patients (36%) experienced
MACE, which included 18 deaths. Presence of
LGE was associated with a > 3-fold hazards
increase for MACE and for death (hazard
ratio, 3.71 and 3.61; P < 0.001 and P =
0.007, respectively)26. Thus, CMR imaging
can characterize occult myocardial scar
consistent with MI in diabetic patients
without clinical evidence of MI. This
imaging finding demonstrates strong
association with MACE and mortality hazards
that is incremental to clinical, ECG, and
left ventricular function combined.
Questions yet to be
answered:
Recently, Coronary CT Angiography (CCTA) has
become a widely accepted for noninvasive
evaluation of the coronary arteries. CCTA
has a very high negative predictive value to
rule out CAD27,28. A particular advantage of
CCTA over CCS is the fact that noncalcified
plaques are also identified, thus providing
a more accurate evaluation of the underlying
atherosclerotic plaque burden. However,
intravenous contrast media has to be used.
At present, it is unclear whether
identifying the noncalcified plaque adds
prognostic information. These questions are
currently being evaluated in the prospective
cardiac imaging in asymptomatic diabetics
Study (CASCAD) which is evaluating the role
of biomarkers, exercise capacity, stress
echocardiography, CCS and CCTA in
asymptomatic diabetics.
Summary
In summary, the current data suggests that
CAD systematic screening of asymptomatic
diabetic patients by MPI will not alter
clinical outcomes of adequately treated
patients. However, whether using a directed
hybrid screening strategy with CCS and MPI
will improve the outcomes of asymptomatic
diabetics remains a question looking for an
answer.¨
References:
1. Wild S, Roglic G, Green A, Sicree R, King
H. Global prevalence of diabetes: estimates
for the year 2000 and projections for 2030.
Diabetes Care 2004; 27:1047-53.
2. Baynouna LM, Revel AD, Nagelkerke NJ, et
al. High prevalence of the cardiovascular
risk factors in Al-Ain, United Arab
Emirates. An emerging health care priority.
Saudi Medical Journal 2008; 29:1173-8.
3. Haffner SM, Lehto S, Ronnemaa T, Pyorala
K, Laakso M. Mortality from coronary heart
disease in subjects with type 2 diabetes and
in nondiabetic subjects with and without
prior myocardial infarction. N Engl J Med
1998;339:229-34.
4. Rashed WA, Singh S, Constandi JN, Memon
A, Al Kandari F, Zubaid M. Thrombolytic
therapy in acute myocardial infarction:
Experience at a university hospital in
Kuwait. Ann Saudi Med 1998;18:301-4.
5. Zubaid M, Rashed WA, Al-Khaja N, et al.
Clinical presentation and outcomes of acute
coronary syndromes in the gulf registry of
acute coronary events (Gulf RACE). Saudi Med
J 2008;29:251-5.
6. Third Report of the National Cholesterol
Education Program (NCEP) Expert Panel on
Detection, Evaluation, and Treatment of High
Blood Cholesterol in Adults (Adult Treatment
Panel III) final report. Circulation
2002;106:3143-421.
7. Hammoud T, Tanguay JF, Bourassa MG.
Management of coronary artery disease:
therapeutic options in patients with
diabetes. J Am Coll Cardiol 2000;36:355-65.
8. Truett J, Cornfield J, Kannel W. A
multivariate analysis of the risk of
coronary heart disease in Framingham. J
Chronic Dis 1967;20:511-24.
9. McEwan P, Williams JE, Griffiths JD, et
al. Evaluating the performance of the
Framingham risk equations in a population
with diabetes. Diabet Med 2004;21:318-23.
10. Morrish NJ, Wang SL, Stevens LK, Fuller
JH, Keen H. Mortality and causes of death in
the WHO Multinational Study of Vascular
Disease in Diabetes. Diabetologia 2001;44
Suppl 2:S14-21.
11. Kang X, Berman DS, Lewin H, et al.
Comparative ability of myocardial perfusion
single-photon emission computed tomography
to detect coronary artery disease in
patients with and without diabetes mellitus.
Am Heart J 1999;137:949-57.
12. Miller TD, Rajagopalan N, Hodge DO, Frye
RL, Gibbons RJ. Yield of stress
single-photon emission computed tomography
in asymptomatic patients with diabetes. Am
Heart J 2004;147:890-6.
13. Rajagopalan N, Miller TD, Hodge DO, Frye
RL, Gibbons RJ. Identifying high-risk
asymptomatic diabetic patients who are
candidates for screening stress
single-photon emission computed tomography
imaging. J Am Coll Cardiol 2005;45:43-9.
14. Janand-Delenne B, Savin B, Habib G, Bory
M, Vague P, Lassmann-Vague V. Silent
myocardial ischemia in patients with
diabetes: who to screen. Diabetes Care
1999;22:1396-400.
15. Wackers FJ, Young LH, Inzucchi SE, et
al. Detection of silent myocardial ischemia
in asymptomatic diabetic subjects: the DIAD
study. Diabetes Care 2004;27:1954-61.
16. Kadiki OA, Roaeid RB, Bhairi AM, et al.
Incidence of insulin-dependent diabetes
mellitus in Benghazi, Libya (1991-1995).
Diabetes & Metabolism 1998;24:424-7.
17. Scognamiglio R, Negut C, Ramondo A,
Tiengo A, Avogaro A. Detection of coronary
artery disease in asymptomatic patients with
type 2 diabetes mellitus. J Am Coll Cardiol
2006;47:65-71.
18. Hayashino Y, Nagata-Kobayashi S,
Morimoto T, Maeda K, Shimbo T, Fukui T.
Cost-effectiveness of screening for coronary
artery disease in asymptomatic patients with
Type 2 diabetes and additional atherogenic
risk factors. J Gen Intern Med
2004;19:1181-91.
19. Giri S, Shaw LJ, Murthy DR, et al.
Impact of diabetes on the risk
stratification using stress single-photon
emission computed tomography myocardial
perfusion imaging in patients with symptoms
suggestive of coronary artery disease.
Circulation 2002;105:32-40.
20. Young LH, Wackers FJ, Chyun DA, et al.
Cardiac outcomes after screening for
asymptomatic coronary artery disease in
patients with type 2 diabetes: the DIAD
study: a randomized controlled trial. JAMA
2009;301:1547-55.
21. Shakir DK, Mohmmed I, Zarie M, Dawod Al
Katee, Kiliyanni AS, Suwaidi JA.
Inflammatory Markers and Intimal Media
Thickness in Diabetics with Negative
Myocardial Perfusion Scan. J Clin Med Res
2009;1:95-101.
22. Nasir K, Shaw LJ, Liu ST, et al. Ethnic
differences in the prognostic value of
coronary artery calcification for all-cause
mortality. J Am Coll Cardiol 2007;50:953-60.
23. Shaw LJ, Raggi P, Schisterman E, Berman
DS, Callister TQ. Prognostic value of
cardiac risk factors and coronary artery
calcium screening for all-cause mortality.
Radiology 2003;228:826-33.
24. Greenland P, LaBree L, Azen SP, Doherty
TM, Detrano RC. Coronary artery calcium
score combined with Framingham score for
risk prediction in asymptomatic individuals.
JAMA 2004;291:210-5.
25. Kwong RY, Chan AK, Brown KA, et al.
Impact of Unrecognized Myocardial Scar
Detected by Cardiac Magnetic Resonance
Imaging on Event-Free Survival in Patients
Presenting With Signs or Symptoms of
Coronary Artery Disease. Circulation
2006;113:2733-43.
26. Kwong RY, Sattar H, Wu H, et al.
Incidence and Prognostic Implication of
Unrecognized Myocardial Scar Characterized
by Cardiac Magnetic Resonance in Diabetic
Patients Without Clinical Evidence of
Myocardial Infarction. Circulation
2008;118:1011-20.
27. Min JK, Shaw LJ, Devereux RB, et al.
Prognostic value of multidetector coronary
computed tomographic angiography for
prediction of all-cause mortality. J Am Coll
Cardiol 2007;50:1161-70.
28. Raff GL, Gallagher MJ, O'Neill WW,
Goldstein JA. Diagnostic accuracy of
noninvasive coronary angiography using
64-slice spiral computed tomography. J Am
Coll Cardiol 2005;46:552-7.
29. Penfornis A, Zimmermann C, Boumal D, et
al. Use of dobutamine stress
echocardiography in detecting silent
myocardial ischaemia in asymptomatic
diabetic patients: a comparison with
thallium scintigraphy and exercise testing.
Diabet Med 2001;18:900-5.
30. De Lorenzo A, Lima RS, Siqueira-Filho
AG, Pantoja MR. Prevalence and prognostic
value of perfusion defects detected by
stress technetium-99m sestamibi myocardial
perfusion single-photon emission computed
tomography in asymptomatic patients with
diabetes mellitus and no known coronary
artery disease. Am J Cardiol 2002;90:827-32.
31. Kang X, Berman DS, Lewin HC, et al.
Incremental prognostic value of myocardial
perfusion single photon emission computed
tomography in patients with diabetes
mellitus. Am Heart J 1999;138:1025-32.
32. Schinkel AF, Elhendy A, van Domburg RT,
et al. Prognostic value of dobutamine-atropine
stress myocardial perfusion imaging in
patients with diabetes. Diabetes Care
2002;25:1637-43.
33. Vanzetto G, Halimi S, Hammoud T, et al.
Prediction of cardiovascular events in
clinically selected high-risk NIDDM
patients. Prognostic value of exercise
stress test and thallium-201 single-photon
emission computed tomography. Diabetes Care
1999;22:19-26.
|
|