Keywords
pre-diabetes - secondary prevention - total mortality - fatal vascular events - EUROASPIRE
Introduction
Impaired glucose metabolism belongs to classical cardiovascular risk factors. Presence
of overt diabetes mellitus in patients with manifest vascular disease (coronary heart
disease or ischemic stroke) increases mortality risk of these patients more than twofold
[1]. On the other hand, the exact definition of impaired glucose metabolism remains
disputable. It is generally accepted, that several “pre-diabetic” conditions with
identical etiology exists as intermediate state between normoglycemia and overt diabetes
mellitus (metabolic syndrome, impaired glucose tolerance as well as impaired fasting
glycaemia). Several studies, almost exclusively set in general population, have shown
that even pre-diabetic subjects are already at excessive risk of future major cardiovascular
event [2]
[3]
[4]
[5]. Similarly, in patients with manifest coronary heart disease (CHD), there's a plethora
of reports related to overt diabetes mellitus, but the pre-diabetic population is
largely unexplored and available data are more or less anecdotical [6]
[7]
[8]
[9]
[10]. As a consequence, in guidelines related to secondary prevention of CHD, those chapters
dealing with glucose metabolism, predominantly address diabetic patients [11].
Thus, in a present paper we aim to assess the mortality impact of pre-diabetic state,
comparing an attributable risk of impaired fasting glycaemia and overt diabetes mellitus
in well-defined sample of stable patients with chronic CHD.
Methods
Design and study population
The study represents a secondary analysis of EUROASPIRE survey data in the Czech Republic,
a prospective follow-up of four pooled independent cohorts (EUROASPIRE I, II, III,
and IV examined in 1995–96, 1999–2000, 2006–7 and 2012–13) of patients with stable
manifest CHD (i. e. baseline examination was done at least 6 months after its first
manifestation). A detailed sample selection was described elsewhere [12]
[13]
[14]
[15]. Briefly, patients aged less than 71 years hospitalized for any of the following
discharge diagnosis were retrospectively identified from hospital records. The diagnoses
included: first coronary artery bypass grafting (CABG), first percutaneous transluminal
coronary angioplasty (PTCA) and acute myocardial infarction or ischemia. Recruitment
of patients started with the most recent hospital record and proceeded backward until
the required sample of 525 subjects in each campaign (EUROASPIRE I, II, III, and IV)
was achieved. These patients were invited for an interview/clinical examination and
responders (81.8% of the initially identified pool of patients) included in the survey.
All 4 campaigns of the EUROASPIRE survey were conducted in the same two centers in
the Czech Republic: University Hospital in Pilsen and Department of Cardiology, Institute
for Clinical and Experimental Medicine in Prague under an almost identical protocol.
Each interview/clinical examination took place 6–24 months after the qualifying index
event (i. e., acute coronary syndrome or first elective revascularization) and for
the purpose of the present analysis used as baseline visit for prospective follow-up.
Data collection
The standard protocol of EUROASPIRE (EA) survey was followed as described elsewhere
[12]
[13]
[14]
[15]. Information on personal and demographic characteristics, personal and family history
of CHD, lifestyle and pharmacotherapy were obtained. The following standardized examinations
were performed: height and weight were measured in light indoor clothes without shoes
using SECA 707 (EAI and II) and SECA 701 (EA III and IV) scales and measuring stick
(SECA, Hamburg, Germany). Waist circumference was measured using a tape measure. Blood
pressure (BP) was measured twice in the sitting position on the right arm using standard
mercury sphygmomanometers. Breath carbon monoxide was measured by a SMOKERLYSER device
(Bedfont Scientific, Upchurch, UK) to verify smoking status (with 10 ppm of breath
carbon monoxide as the cut-off point). Venous blood samples were drawn after at least
12 hours of overnight fast. Laboratory examinations included estimation of total and
HDL cholesterol, triglycerides (TG) and glucose, and were performed in the central
study laboratory of the respective EUROASPIRE survey. Again, laboratory methods were
described elsewhere [12]
[13]
[14]
[15]. LDL cholesterol was calculated using the Friedewald equation, i. e., LDL = total
cholesterol – HDL – (TG/2.22). HbA1c (glycated hemoglobin) was estimated from frozen
samples by ionex liquid chromatography using G7 analyser (TOSOH, Tokyo, Japan).
Vital status of patients was registered up to March 31, 2017 using the National Registry
of the Institute of Health Information and Statistics of the Ministry of Health. Death
certificates and available documentation in hospital information systems were used
to specify the cause of death.
Outcomes and data management
Death from any cause was used primary outcome. Secondary outcome was defined as death
from any cardiovascular cause as stated in hospital records (discharge letter, inspection
list, etc.) or, if not available (for those dying at home) stated as the primary cause
of death (ICD-10 codes were used) in the death certificate. In patients with active
malignancy, the cause of death was considered non-cardiovascular, even if the immediate
cause of death was cardiovascular (for example, pulmonary embolism). Because of very
variable length of follow-up for the purpose of present analysis it was arbitrary
unified to 1826 days (5 years)
Impaired glucose metabolism as primary exposure was defined in two levels: a) “overt
diabetes mellitus”, i. e. fasting serum glucose ≥ 7 mmol/L and/or use of antidiabetic
treatment and/or self-reported diabetes plus diabetic diet; and “impaired fasting glycaemia“, i. e. fasting serum glucose 5.6–6.99 mmol/L
(and no use of antidiabetic treatment). Other conventional risk factors were dichotomized
using cut-off points proposed by the Joint European Guidelines for Cardiovascular
Prevention [16].
Statistical analyses were performed using STATISTICA 8 (StatSoft Inc, Tulsa, OK, USA)
and STATA 8 (STATA Corp LP, College Station, TX, USA). Conventional descriptive methods
were applied, i. e., mean and standard deviation for continuous variables or frequency
for categorical ones. Using a Cox proportional hazard model, univariate analysis was
performed to identify the crude relation between exposure (overt diabetes or impaired
fasting glycaemia) and total/cardiovascular mortality. As a second step, we adjusted
all models for conventional confounders (age and gender) and then also other (dichotomized)
cardiovascular risk factors (smoking, body mass index, blood pressure, LDL cholesterol),
treatments with a presumable effect on cardiovascular mortality (statin, beta-blockers,
angiotensin-converting enzyme inhibitors or angiotensin receptor blockers), as well
as a history of coronary revascularization (before inclusion into study) and sequence
of the primary survey (i. e. EUROASPIRE I, II, III or IV). Censored data were used
for final analysis. P values < 0.05 were considered significant.
Results
Baseline cross-sectional data and outcomes
Initially, a total of 1717 patients (1312 men and 405 women; mean age 62.7±9.0 years)
after myocardial infarction and/or coronary revascularization were interviewed; median
time (interquartile range) between the qualifying cardiovascular event and interview
was 1.02 (0.96–1.78) years. However, exact information about vital status, cause of
death or any other crucial variable was missing in 32 patients – these subjects were
excluded from the final analysis. Thus, the final cohort consisted of 1285 men and
407 women whose baseline characteristics are listed in [Table 1].
Table 1 Basic characteristics of study sample [mean (standard deviation) or factor proportion]
|
n
|
1685
|
|
age [years]
|
62.1 (9.0)
|
|
gender [% of males]
|
7634
|
|
history of coronary revascularization[%]
|
81.5
|
|
current smoking [%]
|
20.1
|
|
body mass index [kg/m2]
|
29.3 (4.4)
|
|
body mass index ≥30 kg/m
2
[%]
|
38.6
|
|
waist circumference [cm]
|
101.4 (11.8)
|
|
increased waist circumference
#
[%]
|
58.2
|
|
systolic blood pressure [mmHg]
|
140.2 (20.5)
|
|
diastolic blood pressure [mmHg]
|
83.5 (11.3)
|
|
raised blood pressure
#
[%]
|
51.4
|
|
total cholesterol [mmol/L]
|
4.94 (1.28)
|
|
LDL-cholesterol [mmol/L]
|
2.91 (1.08)
|
|
LDL-cholesterol ≥2.5 mmol/L [%]
|
61.0
|
|
HDL- cholesterol [mmol/L]
|
1.21 (0.33)
|
|
low HDL cholesterol
§
[%]
|
31.7
|
|
triglycerides [mmol/L]
|
1.84 (1.42)
|
|
triglycerides ≥1.8 mmol/L [%]
|
42.4
|
|
fasting glycemia [mmol/L]
|
6.99 (2.37)
|
|
concomitant treatments [%]:
|
|
betablockers
|
78.3
|
|
ACEi or ARBs
|
60.9
|
|
statins
|
61.3
|
|
antidiabetics
|
19.1
|
|
glucose metabolism categories:
|
|
overt diabetes
##
[n (%)]
|
623 (37.0)
|
|
impaired fasting glycemia
$$
[n (%)]
|
436 (25.9)
|
|
normoglycemia [n (%)]
|
626 (37.1)
|
LDL, low density lipoprotein; HDL, high density lipoprotein; ACEi, angiotensin-converting
enzyme inhibitors; ARBs, angiotensin II receptor blockers; #waist circumference ≥
102 cm in males or ≥ 88 cm in females;; $ systolic blood pressure ≥ 130 and/or diastolic blood pressure ≥ 85 mmHg; § < 1.0 mmol/L in males or < 1.3 mmol/L in females;
##
fasting glycaemia
≥
7 mmol/L and/or treatment with antidiabetics or self-reporting diabetes mellitus plus diabetic diet; $$ fasting glycemia 5.6–6.9 mmol/L and no treatment with antidiabetics
During follow-up (i. e., between baseline visit and March 31, 2017), death occurred
in 532 patients, of which number the cause of death was identified as cardiovascular
in 395 (74.3%) individuals; median follow-up time (interquartile range) was 3782 days
(1636–6264). During follow-up of 5 years (1826 days) at most, 172 patients (10.2%)
died of which number 122 (7.2%) from a cardiovascular cause (details of the selection
and follow-up processes are shown in [Fig. 1])
Fig 1 Flow chart of sample recruitment process and follow-up. # Deceased between discharge from hospitalization for coronary heart disease manifestation
(qualifying event) and the interview (baseline visit); $ total death; § cardiovascular death;
Glycemic status and mortality
Survival curves according to glucose metabolism categories are shown in [Fig. 2]. Presence of both overt diabetes and impaired fasting glycaemia was associated with
worse survival than normal glycemic status (fasting glycaemia < 5.6 mmol/L). The univariate
(crude) 5-years total hazard risk ratios (HRRs) and 95% confidence intervals (95%
CIs) for overt diabetes or impaired fasting glycaemia were 2.05 (1.40–2.98) or 1.79
(1.19–2.70), respectively. Mortality risk associated with overt diabetes was similar
to impaired fasting glycaemia 1.15 (0.81–1.65).
Fig 2 Kaplan-Meier survival curves according to glucose metabolism categories. (p value
by Mantel-Cox log rank test)
Multivariate regression analyses revealed confirming results ([Table 2]). After adjustment for age, gender, other conventional risk factors and treatments,
impaired fasting glycaemia was associated with more than two-fold higher risk of 5-year
total mortality). Moreover, mortality risk associated with impaired fasting glycaemia
did not statistically differ from risk associated with overt diabetes ([Table 2]).
Table 2 5-years mortality risk associated with categories of impaired glucose metabolism
[Hazard risk ratios (95% confidence intervals] by Cox proportional hazard model]
|
total
|
cardiovascular
|
|
HRR (95% CI)
|
p
|
HRR (95% CI)
|
p
|
|
adjusted for age, gender and survey:
|
|
normoglycaemia
|
1
|
-
|
1
|
-
|
|
impaired fasting glycemia
|
1.85 (1.22–2.79)
|
0.004
|
2.80 (1.67–4.71)
|
<0.0001
|
|
overt diabetes
|
1.77 (1.21–2.61)
|
0.004
|
2.47 (1.49–4.08)
|
<0.0001
|
|
overt diabetes
|
1
|
-
|
1
|
-
|
|
impaired fasting glycemia
|
0.98 (0.68–1.41)
|
0.915
|
0.88 (0.58–1.32)
|
0.531
|
|
fully adjusted
#
:
|
|
normoglycaemia
|
1
|
-
|
1
|
-
|
|
impaired fasting glycemia
|
2.25 (1.45–3.50)
|
<0.0001
|
3.84 (2.19–6.73)
|
<0.0001
|
|
overt diabetes
|
1.63 (1.01–2.61) $
|
0.043
|
1.96 (1.06–3.63) $
|
0.033
|
|
overt diabetes
|
1
|
-
|
1
|
-
|
|
impaired fasting glycemia
|
0.82 (0.53–1.28) $
|
0.328
|
0.63 (0.37–1.07) $
|
0.086
|
# adjusted for age, male gender, survey (EUROASPIRE I, II, III or IV), history of
coronary revascularization, current smoking, BMI≥30 kg/m2, increased waist circumference, raised blood pressure, LDL≥2.5 mmol/L and treatment
with statins, betablockers, ACEi or ARBs; $
plus treatment with antidiabetics
In a next step, we repeated all above described analyses using 5-years cardiovascular
(instead of total) mortality as outcome with analogous results to former one ([Fig. 2] – unadjusted analysis; [Table 2] – adjusted analysis) .The observed association between glucose metabolism categories
and cardiovascular mortality was even stronger. Indeed, impaired fasting glycaemia
was associated with more than 3.8 times higher risk of 5-years cardiovascular mortality
(after full adjustment for potential covariates).
Furthermore, in exploratory analysis we investigate potential role of HbA1c. Concentrations
of HbA1c were available in 972 patients (≈58% subsample, EUROASPIRE III and IV subjects
only), mean age 64.3(±SD 9.0) years, 79.4% of males; mean concentration of HbA1c was
44.2 mmol/mol (±SD 12.7) and frequency of primary outcome (5-year total death) was
11.5%. Taking HbA1c ≥ 48 mmol/mol as an alternate criterion for pre-diabetic status
did not change real prevalence of impaired fasting glucose category (23.7% with HbA1c
≥ 48 mmol/mol as alternate criterion). Its predictive power in terms of primary outcome
risk was as follows: HRR 2.22 (95%CI: 1.44–3.50). Further, we tested lower cut-off
point for HbA1c ≥ 42 mmol/mol for pre-diabetic status definition. The prevalence of
pre-diabetic status, defined as fasting glucose 5.6–6.99
or
HbA1c ≥ 42 mmol/mol raised to 27.6% , but was no longer associated with primary outcome
[HRR 1.65 (95%CI: 0.93–2.91), p=0.085].
Discussion
The key finding of our study is that impaired fasting glycemia represents major indicator
of increased residual mortality risk in patients with stable manifest CHD. Pre-diabetic
subjects had more than 3.8 times higher relative risk of fatal cardiovascular event
during 5- years of follow-up comparing to those with fasting glucose in physiological
range. Moreover, patients with impaired fasting glycemia had comparable mortality
risk as patients with overt diabetes mellitus. It is also necessary to stress that
impaired fasting glycemia is highly prevalent condition in CHD patients (one quarter
of patients in our sample) with evident increase over time in last 20 years [17].
In contrast, using different cut-off values for HbA1c did not improve either diagnostics
of the pre-diabetic state or assessment of risk associated with pre-diabetes better
than fasting glucose concentration to rule-out. Cut-off point of HbA1c ≥ 48 mmol/mol
(proposed by Guidelines[16] as “maximal safe treatment target” in diabetic patients) was not in our study associated
with substantially better sensitivity. In fact, only three patients with HbA1c ≥
48 mmol/mol (0.3% among those with available HbA1c value) were “misclassified” as
normoglycemic (based on fasting glycemia criterion only), while 9 patients (0.9%)
re-classified into pre-diabetes category. We also repeated the mortality analysis
after “re-classification” according to HbA1c concentration (i. e. subjects with ≥
48 mmol/mol were considered as overt diabetes), with very similar results. Moreover,
when we used HbA1c 42–47 mmol/mol as alternate criterion to fasting glucose (5.6–6.9 mmol/l)
of pre-diabetes classification, its predictive power is no more significant. This
negative result contrasts to those from general population. A prospective cohort analysis
by Warren and colleagues reported that pre-diabetes definition based on HbA1c provided
at least modest improvements in the risk discrimination for cardiovascular outcomes
and other diabetes complications [18]. Another way how to increase sensitivity of glucose metabolism disorder screening
is measurement of 2-hour post-load glucose concentrations - this approach was applied
in EUROASPIRE IV cohort; we have data available in ≈29% of sample). In this subsample,
none of nominally normoglycemic patients (with fasting glucose<5.6 mmol/L) had the
2-hour post-load glucose level over 11 mmol/L (WHO criteria for overt diabetes). However,
another 51 normoglycemic patients had 2-hour post-load glucose concentrations ≥ 7.8 mmol/L.
Use of this alternate criterion increased prevalence of pre-diabetes to 27%. Shahim
and colleague [10] recently reported that CHD patients with 2-hour post-load glucose concentrations
≥ 7.8 mmol/L showed significant 38% higher risk of fatal or non-fatal cardiovascular
events. Furthermore, the CHD patients with 2-hour post-load glucose concentrations
≥ 7.8 mmol/L had higher risk of incident diabetes during 2-years of follow-up [10]. Thus, 2-hour post-load glucose concentrations may further improve the screening
for individual high-risk CHD patients, moderated by impaired glucose metabolism.
The crucial practical question is whether we should apply any specific therapeutic
intervention in pre-diabetic CHD patients. Recent guidelines on cardiovascular prevention
[11] mentioned pre-diabetic disorders in secondary prevention of CHD only anecdotically,
while standards of care of diabetes are in the field of pre-diabetic disorders focused
mainly to decreased the rate of “conversion” to overt diabetes (prevention or delay)
[19]. Certainly we can recommend, as to all CHD patients, a tight control of other conventional
risk factors and intensive non-pharmacologic treatment (specific diet recommendations,
weight loss, intensive physical activity…). Randomized controlled trials revealed
that intensive life-style modification was in general patients with pre-diabetic disorders
very effective in terms of delayed conversion to overt diabetes [20]
[21]. In spite, that we are lacking equivalent data, focused to recurrent cardiovascular
events prevention in pre-diabetic patients with manifest CHD, life-style intervention
remains first line measure. Theoretically we can start antidiabetic treatment earlier
than in usual practice however there are several exclusions and whole concept remains
in secondary prevention of CHD controversial, mainly because of lacking evidence.
First of all, traditional antidiabetic drugs such as insulin and sulfonylureas showed
U-shaped association between mortality and glycemic control. Stricter treatment targets
were associated with increased risk of major cardiovascular events (MACE) [22]
[23]
[24]. Dipeptidyl-peptidase-4 inhibitors effectively decreased fasting glycaemia without
substantial risk of hypoglycemia. Nonetheless their benefit in term of reduction of
MACE was not observed [25] (several existing studies were pointed to cardiovascular safety only). Metformin
is routinely used also in other indication than diabetes mellitus and in normoglycemic
patients, but proof of cardiovascular benefit is lacking again [26]. In the recent studies, glucagon-like propeptide-1 and sodium-glucose transport
protein-1 antagonists (liraglutid and empagliflozin) [27]
[28] not only decreased glycaemia in patients with diabetes, but were also followed by
reduction of MACE. However, no satisfactory evidence exists for these drugs in terms
of safety and efficacy in CHD patients without overt diabetes. To our knowledge, only
one study reported positive effect of antidiabetic treatment in pre-diabetic subjects
regarding cardiovascular events incidence. STOP-NIDDM trial reported that treatment
impaired glucose tolerance patients with acarbose was associated with a significant
49% reduction of cardiovascular events [29]. Despite relative small sample size (less than 1400 subjects) and for clinical practice
more-than-less useless drug class (acarbose is very poorly tolerated), this study
represents single positive piece of knowledge in a whole concept of antidiabetic treatment
in pre-diabetic patients.
Study limitations
First, we pooled four samples of patients interviewed at four different occasions.
The initial management, control of risk factors, as well as related background mortality
risk substantially changed (generally improved) over time [17]- we did our best to adjust data for all these factors to minimize their impact.
From similar reasons we have available HbA1c concentrations only in part of the sample
(EUROASPIRE III and IV) and this factor can be investigated only in the exploratory
sub-analysis.
Second, our sample consisted from rather stable and probably initially less affected
patients. Due to inclusion criteria (qualifying cardiovascular event at least 6 months
before baseline visit), most severe patients died before inclusion into follow-up
(≈ 7% of identified pool of CHD patients) or were not physically fit to attend the
interview. Therefore, any implications of our results should be limited to well-stabilized
patients.
Moreover, no non-fatal cardiovascular events data were available to us.
Conclusions
In patients with stable CHD, mild increase of fasting glycaemia effectively identified
subjects at high mortality risk. The risk associated with impaired fasting glycaemia
was similar to overt diabetes. Interventional studies are needed to assess the therapeutic
strategy in this prevalent subgroup of CHD patients.
Ethical Statement
All procedures performed in this study were in accordance with the Good Clinical Practice
principles and ethical standards formulated in the 1964 Declaration of Helsinki and
its later amendments. The study protocols were approved by the Ethics Committees of
the University Hospital in Pilsen and Institute for Clinical and Experimental Medicine
in Prague. The data were stored and evaluated under the provisions of the Czech Data
Protection Act. Written informed consent was obtained from all participants included
in the study at baseline visit.
