Sasso FC, Carbonara O, Nasti R, Campana B, Marfella R, Torella M, Nappi G, Torella R, Cozzolino D. Glucose Metabolism and Coronary Heart Disease in Patients With Normal Glucose Tolerance. JAMA. 2004;291(15):1857-1863. doi:10.1001/jama.291.15.1857
Author Affiliations: Institutes of Internal Medicine (Drs Sasso, Carbonara, Nasti, Campana, Marfella, R. Torella, and Cozzolino) and Cardiovascular Surgery (Drs M. Torella and Nappi), Faculty of Medicine, Second University of Naples, Naples, Italy.
Context Several investigations as well as prospective studies have shown a significant
correlation between glucose metabolism and atherosclerosis in patients without
diabetes, but differences in parameters of glucose metabolism among the various
degrees of coronary disease in such patients have not been specifically evaluated.
Objective To investigate glucose metabolism in patients with normal glucose tolerance
(NGT) and coronary heart disease (CHD).
Design, Setting, and Participants Cross-sectional study of 234 men (mean [SD] age, 56.2 [6.1] years) with
NGT and suspected CHD who were admitted from January 1 through June 30, 2001,
to an academic medical center in Italy for coronary angiography.
Main Outcome Measures Correlation of glucose metabolic factors and extent of atherosclerosis
determined by coronary angiography. Factors included levels of fasting and
postload glucose and insulin, glycosylated hemoglobin (HbA1c),
and lipids, as well as insulin resistance measured by homeostasis model assessment
Results Patients were divided into 4 groups based on coronary angiography: no
significant stenosis (n = 42), 1-vessel disease (n = 72), 2-vessel disease
(n = 64), and 3-vessel disease (n = 56). Simple correlation analysis showed
that the factors correlated with the extent of atherosclerosis were levels
of postload glucose (r = 0.667), HbA1c (r = 0.561), postload insulin (r =
0.221), and fasting insulin (r = 0.297), as well
as HOMA-IR (r = 0.278) (P<.001
for all). Multiple stepwise regression analysis suggested that the factors
independently associated with the number of stenosed coronary arteries were
levels of postload plasma glucose (r = 0.572), HbA1c (r = 0.413), postload insulin (r = 0.267), and fasting insulin (r = 0.174),
as well as HOMA-IR (r = 0.250) (P<.001 for all). Similar results were obtained after grouping patients
by Duke Myocardial Jeopardy Score.
Conclusions For patients with NGT and different extents of atherosclerotic disease,
postload glycemia and HbA1c level are not equally distributed but
are significantly higher in those with more severe disease. This suggests
that the glycemic milieu correlates with the cardiovascular risk according
to a linear model.
Diabetes mellitus is one of the classic risk factors for coronary heart
disease (CHD). It is well known, in fact, that the risk of CHD is 2- to 6-fold
higher in patients with type 2 diabetes than in patients without diabetes1- 3 and that men with diabetes
have a worse survival from CHD than do those without diabetes.4 Patients
with diabetes but without prior myocardial infarction have for some years
been considered to have the same risk of CHD events as patients without diabetes
but with a prior myocardial infarction,5 as
recently acknowledged by the recommended treatment goals for lipoprotein therapy.6
A body of information now available suggests the need for a careful
consideration not only of diabetes, but also of other disturbances of glucose
metabolism, such as impaired glucose tolerance (IGT), that have emerged as
independent risk factors for cardiovascular disease mortality.7,8 Moreover,
several prospective studies have shown a significant correlation between glycemic
variables and morbidity from CHD in patients without diabetes.4,9- 13 Generally,
the prevalence of impairments of glucose metabolism, such as diabetes or IGT,
in patients with CHD confirmed by coronary arteriography is established by
the medical history or by the presence of fasting glycemia. Such diagnostic
criteria, however, are not able to correctly classify the true glycemic status
of patients with CHD. Some observations,14,15 in
fact, have estimated the prevalence of impaired glucose metabolism to be between
30% and 67% in patients with CHD, often in patients without a previous diagnosis
of metabolic disease.
This evidence raises 2 questions. First, of the glycemic variables,
which are the best indicators of cardiovascular risk in patients with normal
glucose tolerance (NGT)? And second, do their values correlate with the severity
of CHD? The results of the Rancho-Bernardo Study10 show
that level of glycosylated hemoglobin (HbA1c) is a better predictor
of CHD and ischemic heart disease mortality than is fasting or postload glycemia,
while the results of the Hoorn Study11 indicate
that postload glycemia and to a lesser extent HbA1c level are associated
with increased cardiovascular mortality. Moreover, some data are consistent
with a linear association16 and others with
a threshold effect.4
Finally, the results of a recent study17 of
men with CHD but without a history of diabetes confirmed the high prevalence
of glycemic imbalance (approximately 50%) in these patients and showed that
more-pronounced metabolic disturbances were present in patients with greater
changes in the coronary arteries. However, this was established by diagnosis
of diabetes, IGT, or NGT, irrespective of oral glucose tolerance test (OGTT)
results. Therefore, differences in metabolic parameters among the various
degrees of coronary disease in patients with NGT were not evaluated alone.
The aim of this study was to specifically investigate glucose metabolism in
patients with NGT and CHD.
From January 1 through June 30, 2001, 602 consecutive men with suspected
CHD were admitted to the hospital of the Second University of Naples, Naples,
Italy, to undergo coronary angiography. A total of 358 patients (59.5%) were
initially excluded because they met 1 or more of the following exclusion criteria:
diabetes and/or family history of diabetes (160 patients [26.6%]), acute coronary
event in the last 3 months (227 patients [37.7%]), left ventricular ejection
fraction less than 40% and/or valve disease and/or cardiomyopathy (83 patients
[13.8%]). After providing written informed consent, the remaining 244 (40.5%)
underwent a standard 75-g OGTT, which revealed impaired glucose metabolism
(ie, IGT or diabetes mellitus) in 10 patients, leaving 234 (38.8%) eligible
for the study. All patients had previous clinical symptoms of CHD and/or positive
result of exercise testing and/or history of myocardial infarction. The clinical
characteristics of the patients appear in Table 1.
The patients were treated with nitrates (n = 217 [92.3%]), platelet
aggregation inhibitors (n = 201 [85.5%]), angiotensin-converting enzyme inhibitors
or angiotensin II type 1 receptor antagonists (n = 133 [56.5%]), selective α-blockers
(n = 126 [53.6%]), calcium channel blockers (n = 116 [49.4%]), and inhibitors
of hydroxymethyl glutaryl coenzyme A (n = 96 [40.8%]).
The study protocol was in accordance with the Helsinki Declaration and
was approved by the ethical committee of the Second University of Naples.
The OGTT was performed in the morning after an overnight fast at least
3 months after an acute coronary event. This was to avoid any influence on
glucose tolerance or levels of HbA1c. Blood samples for determination
of glucose and insulin levels were collected before and 120 minutes after
loading. The American Diabetes Association criteria18 were
used to classify results of the patients with NGT and to exclude patients
with IGT or diabetes. The insulin resistance index was measured by homeostasis
model assessment (HOMA-IR) (HOMA-IR = fasting insulin level [mU/L] ×
fasting plasma glucose level [mmol/L]/22.5).19 We
used HOMA-IR instead of the better euglycemic-hyperinsulinemic glucose clamp
technique20 because of the number of patients
studied; however, HOMA-IR is a valid indicator of insulin resistance in patients
Blood samples were collected before the OGTT for determination of levels
of HbA1c, total cholesterol, high-density lipoprotein cholesterol
(HDL-C), and triglycerides. The concentration of low-density lipoprotein cholesterol
(LDL-C) was determined using the Friedewald formula (LDL-C level = total cholesterol
level – HDL-C level – triglycerides level/5).
Plasma glucose level was assessed by a glucose oxidase method (Beckman
Glucose Analyzer II, Fullerton, Calif). Level of HbA1c was determined
by column chromatography using a commercial kit (Bio-Rad Laboratories, Richmond,
Calif); reference levels were 4% to 6%, and the interassay coefficient of
variation was 3%. Insulin concentration was assessed using enzyme-linked immunosorbent
assay (AIA-PACK IRI, Euro Genetics, Saran, France). Levels of total cholesterol,
HDL-C, and triglycerides were assessed by enzymatic methods using a commercial
kit (Spinreact, Sant Esteve De Bas, Girona, Spain).
Coronary angiography was performed after positive results of exercise
testing in patients with clinical evidence of angina pectoris. All patients
requiring urgent percutaneous transluminal coronary angioplasty, as judged
by coronary angiography, were excluded from the study. Analyses of coronary
angiograms were performed by independent experienced cardiologists. Internal
luminal narrowing greater than 50% in 1 major coronary artery or its major
branches was considered significant evidence of CHD. To classify the extent
of CHD, coronary arteries were grouped as left anterior descending artery
or diagonal and septal branch; as left circumflex artery or obtuse marginal
branch; and as right coronary artery or posterior descending and posterolateral
Based on coronary angiography, patients were divided into 4 groups:
no significant stenosis, 1-vessel disease, 2-vessel disease, and 3-vessel
disease (Table 1).
Quantitative variables were expressed as mean (SD). Differences between
the 4 groups of patients were compared by 1-way analysis of variance with
the Bonferroni correction for multiple comparisons. A test for linearity was
used to evaluate the trend with increased number of stenosed vessels. Categorical
variables were presented as No. (%) and the significance of difference between
percentages in the 4 groups was evaluated with the χ2 test.
Statistical analysis was performed with 80% power to detect a between-group
difference in means of at least 10%, with an α level of less than .05.
Correlations between the metabolic parameters and the number of stenosed
vessels were examined by determination of the Pearson correlation coefficient.
Metabolic factors independently related to the number of involved vessels
were established through multiple stepwise regression analysis (with stepping
method criteria: probability of F to enter ≤.05 and to remove ≥.10).
All statistical analyses were performed using SPSS version 7.5 (SPSS Inc,
Chicago, Ill), and all tests were conducted at the 5% level of significance.
A total of 234 patients were studied, grouped according to those with
no-vessel disease (group 0, n = 42), 1-vessel disease (group 1, n = 72), 2-vessel
disease (group 2, n = 64), and 3-vessel disease (group 3, n = 56) (Table 1).
Treatment regimens, including drugs that potentially interfere with
glucose metabolism, as well as family history of CHD and other cardiovascular
diseases, were not statistically different among the 4 groups.
There was a significant difference between groups for mean (SD) age
(group 0, 55.3 [4.8] years; group 1, 55.2 [6.4] years; group 2, 54.6 [6.5]
years; and group 3, 57.7 [3.6] years; P<.005),
but linearity with the number of increased stenosed vessels was not demonstrated
(P = .13)(Table
1). Mean (SD) body mass index was different among the groups, even
if multiple comparison showed a statistically significant difference only
for group 1 vs group 3 (23.7 [2.6] vs 24.1 [1.7], respectively; P = .001). Mean (SD) systolic blood pressure was statistically higher
in group 2 (128.5 [14.8] mm Hg) when compared with the other groups (P<.001). Diastolic blood pressure tended to be higher
in the groups of patients with CHD (groups 1, 2, and 3), even if statistically
significant only in group 0 vs group 3 (74.0 [8.1] vs 75.0 [7.5] mm Hg; P<.001), but with a significant linearity (P<.001). Mean (SD) left ventricular ejection fraction was similar
in the 4 groups (Table 1).
The metabolic syndrome, as defined by the Adult Treatment Panel III,23 was diagnosed in 19.7% (46/234) of the patients,
and was statistically more prevalent in group 3 (30.4% [n = 17]) than in group
0, group 1, and group 2 (19% [n = 8]; 8.3% [n = 6]; and18.7% [n = 12], respectively; P<.001).
The 4 groups of patients had similar levels of fasting plasma glucose
(Table 2). All the groups showed
statistically different concentrations of postload glucose, total cholesterol,
and LDL-C (P<.001 for all). Significantly different
HDL-C concentrations were observed between the groups (P<.001 for all), except for group 1 vs group 2 (P = .97). Serum levels of fasting insulin, postload insulin, and triglycerides,
as well as HOMA-IR, were statistically different between the groups (P<.001), except when patients with 1-vessel disease
were compared with those with no-vessel disease (P =
.58 for fasting insulin; P>.99 for postload insulin;
P>.99 for triglycerides; and P = .75 for HOMA-IR).
Mean (SD) levels of HbA1c were statistically different in all the
comparisons between groups (P<.001), except when
group 0 was compared with group 2 (4.7% [0.4%] vs 4.9% [0.6%], P = .09).
The increase in the number of stenosed vessels was accompanied by an
increasing linear trend for levels of postload glucose, fasting and postload
insulin, HbA1c, total cholesterol, LDL-C, and triglycerides, as
well as for HOMA-IR (P<.001 for trend), while
a decreasing linear trend was observed for levels of HDL-C (P<.001 for trend) (Table 2).
As shown in Table 3, the
number of stenosed vessels was correlated with levels of postload plasma glucose,
HbA1c, postload insulin, fasting insulin, triglycerides, total
cholesterol, HDL-C, and LDL-C, and as well as with HOMA-IR, diastolic blood
pressure, and smoking. The multiple stepwise regression analysis suggested
that the factors independently associated with the number of involved vessels
were levels of postload plasma glucose, HbA1c, postload insulin,
fasting insulin, triglycerides, total cholesterol, HDL-C, and LDL-C, as well
as HOMA-IR and diastolic blood pressure (P<.001
For greater prognostic value, we successively reanalyzed patients after
grouping them by the Duke Myocardial Jeopardy Score24 (Table 4). Based on the distribution of
the coronary tree, the patients were divided into 7 groups: score 0 (n = 44),
score 2 (n = 56), score 4 (n = 33), score 6 (n = 28), score 8 (n = 26), score
10 (n = 23) and score 12 (n = 24). An examination of baseline characteristics
showed no difference in BMI (P = .05), age (P = .27), and left ventricular ejection fraction (P = .65), and a statistically significant difference (P<.001) in systolic and diastolic blood pressure. The
percentage of smokers was higher in the patients with the lower score, while
the percentage of those with the metabolic syndrome was statistically higher
in the group with the highest score (P<.001).
Analysis of variance showed that the statistically different metabolic parameters
(P<.001) with a linear trend (P<.001) among the 7 groups of patients were levels of postload glucose,
HbA1c, postload and fasting insulin, triglycerides, total cholesterol,
and LDL-C, as well as HOMA-IR. Simple regression analysis showed that the
Duke score was correlated with levels of postload plasma glucose (r = 0.603, P<.001), HbA1c (r = 0.514, P<.001), postload
insulin (r = 0.216, P<.001),
fasting insulin (r = 0.275, P<.001),
triglycerides (r = 0.513, P<.001),
total cholesterol (r = 0.401, P<.001), HDL-C (r = −0.182, P<.001), and LDL-C (r = 0.420, P<.001), as well as with HOMA-IR (r = 0.379, P<.001), diastolic blood pressure
(r = 0.052, P<.001),
and systolic blood pressure (r = 0.067, P<.001). Multiple stepwise regression analysis suggested that all
these factors were independently associated with the Duke stratification groups
(P<.001 for all, except for diastolic blood pressure, P = .02).
The role of diabetes and IGT in cardiovascular risk, as well as the
high prevalence of impairments of glucose metabolism among people with CHD,
has been well investigated.1- 8 All
these studies showed a consistent gradient across categories of worsening
glucose intolerance. Moreover, some reports indicate a correlation between
glucose metabolism and CHD even in patients without diabetes or IGT.4,5,10- 13 Instead,
there is no consensus regarding the better metabolic predictors of CHD in
patients with NGT, whether their effect is linear or threshold, and if their
values are correlated with the severity of CHD.
The present study showed that, among patients with NGT and CHD: (1)
postload glycemia was statistically higher in all groups of patients with
CHD, while fasting insulinemia, postload insulinemia, and HOMA-IR were significantly
higher in patients with 2- or 3-vessel disease and HbA1c level
was significantly higher in those with 1- or 3-vessel disease; (2) these parameters
were independently correlated to the number of involved vessels, as assessed
by coronary angiography; (3) postload glycemia and HbA1c level
were the glycemic variables having the higher correlation with CHD.
These data support some previous prospective studies of the associations
of glycemic variables with cardiovascular mortality in patients without diabetes.
The Hoorn Study11 reported that postload glycemia
and HbA1c level were associated with an increased risk of cardiovascular
mortality in patients without diabetes after adjustment for age, sex, and
known cardiovascular risk factors. The combined analysis of the 20-year mortality
from CHD of men without diabetes in 3 European studies4 showed
that, even if their distributions of postload glycemia were not fully comparable
because of the different protocols used, those in the upper 2.5% of the postload
glycemia distribution were at higher risk. The Rancho Bernardo Study10 concluded that HbA1c level is predictive
for future cardiovascular disease and CHD mortality in women without diabetes.
In our study fasting glycemia was not statistically different between
patients with and without CHD, while some previous data4 reported
an increased risk for death from CHD in the upper percentiles of this variable.
Otherwise, other investigations10 found no
relationship between fasting glycemia and risk of CHD in patients with NGT.
Most of the previous prospective studies did not apply current American
Diabetes Association criteria for the definition of impaired glucose metabolism;
thus, many of the patients in the upper percentiles of the glycemic values
would now be classified as having diabetes or impaired fasting glucose. However,
the effect of HbA1c level was evident both at the upper end10,11 and at the lower end12 of
the population distribution. Interestingly, the results of the European Prospective
Investigation of Cancer and Nutrition (EPIC)-Norfolk Study12 showed
that an increase of 1% in HbA1c level was associated with a significant
increase in risk of cardiovascular death in men without diabetes (relative
risk, 1.46) and with no apparent threshold effect. The mean difference in
levels of HbA1c (approximately 1%) we found between patients without
coronary stenosis and those with 3-vessel disease seems to indirectly confirm
the findings of the EPIC-Norfolk Study.12
The correlation between glucose metabolism and the severity of CHD has
recently been investigated by a Polish study,17 the
aims of which were to use the OGTT to detect the actual prevalence of glycemic
impairments among patients with CHD but without a previous history of diabetes,
and to correlate this prevalence with the number of stenosed vessels. Kowalska
et al17 observed that approximately 50% of
patients had impairments of glucose metabolism (16% had type 2 diabetes mellitus,
36% had IGT) and that those with advanced damage in the coronary arteries
experienced a higher prevalence of glycemic disturbances. Moreover, from the
analysis of glucose variables in the different groups of CHD disease, these
authors also observed that postload glycemia and levels of fasting plasma
insulin, postload plasma insulin, and HbA1c significantly, but
not independently, correlated with the number of involved vessels.
Instead, our data are consistent with an independent correlation between
postload glycemia, fasting and postload insulinemia, HbA1c levels,
and HOMA-IR and the number of substantially stenosed vessels. This different
result could be explained because we investigated the differences in metabolic
parameters among the various degrees of coronary damage specifically in OGTT-screened
patients with NGT, while the study by Kowalska et al17 considered
patients with diabetes, IGT, and NGT together.
This was designed as a prevalence study and hence does not attempt to
offer a pathogenic explanation for the relationship between glucose metabolism
and CHD in patients with NGT. In this regard, some authors suggest that advanced
glycation end products (AGEs) could play a pathogenic role by impairing cytokine
production,25 monocyte activation,26 or endothelial function.27 Deposits
of AGEs have been detected in the atherosclerotic plaques of patients with
diabetes28 but also in normoglycemic patients.29 Similarly, serum concentrations of AGEs were statistically
higher not only in patients with CHD and type 2 diabetes,30 but
also in patients with CHD and with IGT and NGT31 when
compared with those without CHD. The finding that AGE concentrations correlated
with the severity of CHD in patients without diabetes31 seems
to indirectly confirm the hypothesis of a gradient in tissue damage by glucose
variables. Even oxidative stress is thought to be involved in macroangiopathic
complications,32 but similar data in patients
with NTG are lacking. Otherwise, AGE concentrations and oxidative stress are
We found that glucose parameters, especially postload glycemia and HbA1c levels, in patients with NGT and with different atherosclerotic damage
are not equally distributed but are significantly higher in those with more
severe disease. There appears to be a linear relationship between glucose
metabolism and the severity of CHD, even when glucose values are within the
"normal" range. Like other metabolic variables such as serum cholesterol,3 the glycemic milieu may also correlate with the cardiovascular
risk according to a linear model.
Classifying patients according to the number of stenosed vessels could
lack great prognostic value. Otherwise, many studies exploring the relation
between 1 or more factors and the extent and severity of CHD classify coronary
angiography data anatomically (ie, as single-, double-, or triple-vessel disease).
On the other hand, a number of classifications of coronary lesions were developed
mainly to predict morbidity and mortality in patients with CHD.24,34 In
order to provide more prognostic value, we successively reanalyzed patients
after grouping them according to Duke Myocardial Jeopardy Score and found
that parameters of glucose metabolism also correlated with this classification.
However, our results suggest an association that can only be validated by
specifically designed prospective studies.