Key words
metabolic syndrome - stable coronary artery disease - cardiovascular mortality - all-cause
mortality
Introduction
Stable coronary artery disease (CAD) is a common type of ischemic heart disease. This
condition refers to the patients stabilized after acute coronary syndrome (ACS), or
documented plaque by catheterization or angiography [1]. Clinically, asymptomatic, or controlled angina patients are
considered stable [2]. Despite the advance in
evidence-based therapies and vascular technique, patients with stable CAD are still
suffered from premature mortality and recurrent cardiovascular events [3]
[4]
[5]. Therefore, improving risk
stratification remains a challenge in stable CAD patients.
Metabolic syndrome (MetS) refers to a condition of physiological and metabolic
abnormalities including hyperglycemia, abdominal obesity, hypertension,
dyslipidemia, and insulin resistance. A recently published meta-analysis concluded
that MetS was associated with higher risk of long-term all-cause death in patients
with acute coronary syndrome [6]. However,
this well-designed meta-analysis only focused on the acute phase CAD patients. The
reported prevalence of MetS was 47.3% in patients with stable CAD [7], indicating MetS is also a common condition
in the stable phase. A consensus has not been reached on the association between
MetS and survival outcomes in patients with stable CAD [8]
[9]
[10]
[11]
[12].
These conflicting results may be linked to the different definitions of MetS or
follow-up duration.
Given these controversial findings, we performed the present systematic review and
meta-analysis to clarify the prognostic implication of MetS in patients with stable
CAD, in terms of major adverse cardiovascular events (MACEs), cardiovascular or
all-cause mortality.
Materials and Methods
Literature search
We report this study according to the checklists of the Preferred Reporting Items
for Systematic Reviews and Meta-Analyses [13]. Two independent authors comprehensively searched articles
indexing in PubMed and Embase databases until August 14, 2022, using the
combined items: (“metabolic syndrome”) AND (“coronary
artery disease” OR “coronary heart disease” OR
“ischemic heart disease”) AND (“stable” OR
“stabilized” OR “chronic”) AND
(“follow-up” OR “follow up”). No language
restriction was imputed. The detailed search strategy is summarized in
Supplemental Text S1. References of pertinent articles were also manually
searched for identification of additional studies.
Study selection
Two authors independently scanned the titles and/or abstracts and then
retrieved the potentially eligible articles for full-text eligibility
assessment. Inclusion criteria included: 1) participants: patients with a
diagnosis of stable CAD; 2) predictor: MetS; 3) comparison: patients with MetS
vs. those without; 4) outcomes of interest: major adverse cardiovascular events
(MACEs, including cardiac arrest, myocardial infarction, angina admission,
revascularization, cardiovascular death or, all-cause mortality); 5) type of
study: post hoc analysis of randomized controlled trials or cohort studies; and
6) reported multivariable adjusted risk summary of above-mentioned outcomes for
patients with MetS vs. those without. Exclusion criteria included: 1) patients
with acute stage of CAD; 2) reported unadjusted risk estimate; and 3) lack of
value of MetS in predicting outcomes of interest.
Data extraction and quality assessment
Two independent authors recorded the following information from the included
studies: first author’ name, publication year, country of region, number
of patients, gender distributions, baseline age of the patients, definition of
MetS, prevalence of MetS, definition of MACEs, follow-up duration, risk estimate
adjusted for the maximal covariates, adjustment for covariates. Methodological
quality of these included studies was evaluated by two independent authors using
a 9-point Newcastle-Ottawa Scale (NOS) for cohort [14]. Studies with 4 to 6 points were deemed
to have moderate quality and those with 7 to 9 points were graded as high
quality. Disagreements on the data extraction and quality assessment were
settled by discussion.
Data analysis
The association of MetS with adverse outcomes was summarized by pooling the
adjusted risk ratio (RR) with 95% confidence interval (CI) reported from
the individual study. The degree of heterogeneity was checked via the
I2 statistic (I2≥50% indicating
statistically significant) and/or Cochrane Q-test (p<0.10
indicating statistically significant). A random effect model was selected for
meta-analysis when there was significant heterogeneity; otherwise, a
fixed-effect model was selected for meta-analysis. Both the Begg’s test
[15] and the Egger’s test
[16] were used to explore the
likelihood of publication bias. To investigate the robustness of the pooling
result, we run a leave-one-out sensitivity analysis. Moreover, subgroup analyses
were performed according to study design, sample sizes, and duration of
follow-up. All data were analyzed using Stata 12.0 software (Stata Corporation,
College Station, TX, USA).
Results
Search results and study characteristics
Of 469 records identified in the electronic database search, a total of 7 studies
[8]
[9]
[10]
[11]
[12]
[17]
[18] satisfied the inclusion criteria. The
detailed studies selection process is summarized in [Fig. 1]. [Table 1] shows the main features of the included studies. The
demographic characteristic and comorbidities of the included studies summarized
in Supplemental Table S1. These eligible studies were published from 2006
to 2018. Three studies [8]
[9]
[11] were post hoc analysis of clinical trials and others were cohort
designs A total of 32 736 patients with stable CAD were identified, with sample
size ranging between 589 and 15 524. The length of follow-up varied from 2.0
years to 20 years. One study [10] used the
modified WHO criteria to define the MetS and others selected the National
Cholesterol Education Program’s Adults Treatment Panel III (NCEP-ATP
III) criteria. The reported prevalence of MetS ranged from 23.4% to
63%. The quality score of the included studies was at least 7
(Supplemental Table S2), indicating high methodological quality.
Fig. 1 Flow chart showing selection process of the study.
Table 1 Main characteristic of the included
studies.
|
Author/year [Ref]
|
Region
|
Design
|
Sample size
|
Definition of MetS
|
Prevalence of MetS (%)
|
Definition of MACEs
|
Outcomes HR/RR (95% CI)
|
Follow-up
|
Adjustment for covariates
|
|
Aguilar 2006 [8]
|
Multi- nations
|
Post hoc
|
3319
|
NCEP-ATP III
|
53.3
|
Death, recurrent MI, revascularization, or angina
admission
|
Total death 1.14 (0.90–1.45)
MACEs1.33 (1.15–1.53)
|
3.1 years
|
Age, sex, high-sensitivity CRP
|
|
Daly 2007 [9]
|
Europe
|
Post hoc
|
8937
|
NCEP-ATP III
|
23.4
|
Cardiovascular death, MI, or cardiac arrest
|
Total death 1.16 (0.91–1.47)
CV death 1.39 (1.03–1.86)
MACEs 1.63 (1.39–1.92)
|
4.2 years
|
Age, sex, TC, smoking status, DM
|
|
Kragelund 2007 [10]
|
Denmark
|
Cohort
|
1041
|
Modified WHO
|
30
|
–
|
Total death 1.3 (0.7–2.3)
|
9.2 years
|
Age, sex, family history, previous MI, hypercholesterolemia,
smoking, creatinine clearance, LVEF, TC, severity of CAD,
insulin resistance, fasting glucose, hypertension, TG, HDL,
BMI, DM
|
|
Lopes 2008 [11]
|
Brazil
|
Post hoc
|
589
|
NCEP-ATP III
|
52.3
|
–
|
Total death 2.5 (1.15–5.47)
|
2.0 years
|
Age, sex, smoking status, ethnicity, TC, number of diseases,
treatment allocation
|
|
Arbel 2015 [12]
|
Israel
|
Cohort
|
1634
|
NCEP-ATP III
|
27.7
|
–
|
Total death 1.55 (1.10–2.18)
|
4.4 years
|
Multivariate Cox proportional hazard analysis
|
|
Younis 2016 [17]
|
Israel
|
Cohort
|
15524
|
NCEP-ATP III
|
48
|
–
|
Total death 1.21 (1.14–1.29)
|
20 years
|
Age, sex, smoking, creatinine, DM, hypertension, heart
failure, previous MI, or stroke, medication
|
|
Mayer Jr 2018 [18]
|
Czech Republic
|
Cohort
|
1692
|
NCEP-ATP III
|
63
|
–
|
CV death 1.82 (1.10–3.00)
|
5.0 years
|
Multivariate Cox proportional hazard analysis
|
HR: Hazard ratio; RR: Risk ratio; CI: Confidence intervals; P:
Prospective; R: Retrospective; NP: Not provided; MetS: Metabolic
syndrome; MI: Myocardial infarction; BMI: Body mass index; DM: Diabetes
mellitus; HF: Heart failure; PCI: Percutaneous coronary intervention;
CRP: C-reactive protein; eGFR: Estimated glomerular filtration rate;
WBC: White blood cell; ACEI: Angiotensin-converting enzyme inhibitors;
NCEP-ATP III: National Cholesterol Education Program’s Adults
Treatment Panel III.
All-cause mortality
Data on all-cause mortality were reported in 6 studies [8]
[9]
[10]
[11]
[12]
[17]. A fixed-effect model
meta-analysis ([Fig. 2]) indicated that
patients with MetS conferred an increased risk of all-cause mortality (RR 1.22;
95% CI 1.15–1.19) compared with those without MetS, without
significant heterogeneity (I2=12.6%;
p=0.335). Leave-one out sensitivity analysis showed the pooled RR of
all-cause mortality ranged from 1.21 to 1.25 and low 95% CI ranged from
1.09 to 1.15 (All p-values<0.05). When we removal of one study [17] with the largest sample size, the
pooled of all-cause mortality was 1.25 (95% CI 1.09–1.45). [Table 2] summarizes the results of
subgroup analysis and the value of MetS in predicting all-cause mortality was
not obviously affected by study design, sample size, or length of follow-up.
Fig. 2 Forest plots showing pooled RR with 95% CI of
all-cause mortality for patients with versus without metabolic
syndrome.
Table 2 Subgroup analysis on all-cause
mortality.
|
Subgroup
|
No. of studies
|
Pooled RR
|
95% CI
|
Heterogeneity between studies
|
|
Publication year
|
|
Before 2015
|
4
|
1.20
|
1.02–1.41
|
p=0.292; I2=12.5%
|
|
Since 2015
|
2
|
1.22
|
1.15–1.30
|
p=0.163; I2=48.7%
|
|
Sample size
|
|
≥2000
|
3
|
1.20
|
1.13–1.27
|
p=0.853; I2=0.0%
|
|
<2000
|
3
|
1.58
|
1.20–2.09
|
p=0.416; I2=0.0%
|
|
Study design
|
|
Cohort
|
3
|
1.22
|
1.15–1.30
|
p=0.369; I2=0.0%
|
|
Post hoc analysis
|
3
|
1.19
|
1.01–1.40
|
p=0.161; I2=45.2%
|
|
Follow-up duration
|
|
≥5 years
|
2
|
1.21
|
1.14–1.29
|
p=0.814; I2=0.0%
|
|
<5 years
|
4
|
1.25
|
1.08–1.45
|
p=0.139; I2=45.5%
|
RR: Risk ratio; CI: Confidence interval; MetS: Metabolic syndrome.
Cardiovascular mortality
Two studies [9]
[18] reported the data on cardiovascular
mortality. A fixed-effect meta-analysis indicated that patients with MetS had an
increased risk of cardiovascular mortality (RR 1.49; 95% CI
1.16–1.92; [Fig. 3]) compared
with those without MetS, without significant heterogeneity
(I2=0.0%; p=0.364).
Fig. 3 Forest plots showing pooled RR with 95% CI of
cardiovascular mortality for patients with versus without metabolic
syndrome.
Major adverse cardiovascular events
Two studies [8]
[9] reported the data on MACEs. [Fig. 3] shows significant heterogeneity
between these two studies (I2=70.8%, p=0.064;
[Fig. 4]). A random effect model
meta-analysis showed that patients with MetS conferred an increased risk of
MACEs (RR 1.47; 95% CI 1.20–1.79) compared with those without
MetS,
Fig. 4 Forest plots showing pooled RR with 95% CI of major
adverse cardiovascular events for patients with versus without metabolic
syndrome.
Publication bias
The Begg’s test and Egger’s test were not run to investigate
publication bias because less than recommended arbitrary number of 10 studies in
each analyzed outcome. These statistical tests are potentially unreliable under
such circumstance [19].
Discussion
The current systematic review and meta-analysis consolidated the evidence that MetS
was associated with higher risk of MACEs, cardiovascular or all-cause mortality in
patients with stable CAD. Patients with stable CAD having MetS conferred a
22%,49%, and 47% higher risk of all-cause mortality,
cardiovascular mortality, and MACEs, respectively. Presence of MetS may provide
important prognostic information in patients with stable CAD.
An early meta-analysis has concluded that MetS was associated with higher risk of
all-cause mortality patients with CAD undergoing revascularization [20]. A recent meta-analysis demonstrated that
the presence of MetS was associated with 2.35-fold and 25% higher risk of
in-hospital and long-term all-cause mortality, respectively [6]. By contrast, the current meta-analysis
focused on the stable CAD patients. Besides all-cause mortality outcome, the values
of MetS in predicting cardiovascular mortality and MACEs were also evaluated.
One [10] of the included study has investigated
the gender-specific effect of MetS on all-cause mortality in patients with stable
CAD. In the multivariable Cox regression analysis, MetS only provided prognostic
information in women (Relative risk 2.2; 95% CI: 1.1–4.3) but not in
men (Relative risk 1.0; 95% CI 0.5–1.9). However, more studies
should address the gender-specific effect of MetS on adverse outcomes in patients
with stable CAD.
This meta-analysis has important implications for clinical practice. Depending on
the
assessment tool used for MetS, the reported prevalence of MetS ranged from
23.4% to 63% in the stable CAD patients. Given the higher prevalence
of MetS and its negative effect on the prognosis, metabolic status should be
monitored closely in patients with stable CAD. Active management of individual
components of MetS may improve secondary prevention for these high-risk subgroup
patients.
This systematic review and meta-analysis have several limitations. First, most of
the
included studies defined the MetS by the NCEP-ATP III criteria, which prevented us
to compare the prognostic impact with other criteria. Second, different degree of
confounding factors was adjusted in the included studies. Lack of adjusting residual
confounders may lead to overestimate the risk summary. Moreover, therapeutic options
may also affect the prognostic utility of MetS. Third, results of subgroup analysis
are potentially unreliable due to the small number of studies included. Fourth,
significant heterogeneity existed in pooling MACEs outcome. Different definition of
MACEs, length of follow-up, or adjusting covariates may be correlated with the
significant heterogeneity. Fifth, this systematic review and meta-analysis was not
prospectively registered in PROSPERO database. Finally, apart from diabetes,
individual components of MetS had varying associations with all-cause mortality
[9]
[11]. However, we could not determine whether the excessive risk was
driven by the specific component of MetS due to insufficient of such data.
Conclusions
MetS may be an independent predictor of adverse outcomes in patients with stable CAD.
However, additional studies are required to consolidate the current evidence due to
the small number of studies included. Whether intervention on MetS could improve the
prognosis of stable CAD patients should be further investigated in future
studies.
