nursing

Select a research article, other than the articles from your assignments, from the GCU library (article is attached). Provide an overview of the study and describe the strategy that was used to select the sample from the population. Evaluate the effectiveness of the sampling method selected. Provide support for your answer. Include the article title and permalink in your post. 

© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2018;10(11):6137-

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Original Article

Triglyceride glucose index for predicting cardiovascular outcomes
in patients with coronary artery disease

Jing-Lu Jin1, Ye-Xuan Cao1, Li-Guo Wu2, Xiang-Dong You2, Yuan-Lin Guo1, Na-Qiong Wu1,
Cheng-Gang Zhu1, Ying Gao1, Qiu-Ting Dong1, Hui-Wen Zhang1, Di Sun1, Geng Liu1, Qian Dong1,
Jian-Jun Li1

1Division of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, Fu Wai Hospital, National Center for Cardiovascular Diseases, Chinese

Academy of Medical Sciences, Peking Union Medical College, Beijing 100037, China; 2Department of Cardiology, TangXian People’s Hospital,

Baoding 072350, China

Contributions: (I) Conception and design: JJ Li; (II) Administrative support: None; (III) Provision of study materials or patients: None; (IV) Collection

and assembly of data: D Sun, YX Cao, HW Zhang, XD You, NQ Wu, CG Zhu, YL Guo, Y Gao, Q Dong, G Liu, QT Dong; (V) Data analysis and

interpretation: JL Jin, JJ Li; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Professor Jian-Jun Li, MD, PhD. Division of Dyslipidemia, State Key Laboratory of Cardiovascular Disease, Fu Wai Hospital,

National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, BeiLiShi Road 167, Beijing

100037, China. Email: lijianjun938@126.com

Background: Triglyceride glucose (TyG) index is a novel marker for metabolic disorders and recently it
has been reported to be associated with cardiovascular disease (CVD) risk in apparently healthy individuals.
However, the prognostic value of TyG index in patients with stable coronary artery disease (CAD) is not
determined.
Methods: We conducted a nested case-control study among 3,745 patients with stable CAD. Patients
were followed up for 11,235 person-years. The cardiovascular events (CVEs) were defined as all-cause
death, non-fatal myocardial infarction (MI), stroke and post-discharge revascularization [percutaneous
coronary intervention (PCI) coronary artery bypass grafting (CABG)]. In total, 290 (7.7%) patients with
CVEs and 1,450 controls were matched according to age, gender, previous history of PCI or CABG and
the duration of follow-up. TyG index was calculated as formula: ln[fasting triglycerides (mg/dL) × fasting
plasma glucose (mg/dL)/2].
Results: Multivariable Cox proportional hazards models revealed that TyG index was positively associated
with CVEs risk (hazard ratio: 1.364, 95% confidence interval: 1.100–1.691, P=0.005). The Kaplan-Meier
analysis indicated that patients within the highest quartile of TyG index presented the lowest event-free
survival (P=0.029). Moreover, a 1-standard deviation (SD) increment in TyG index was associated with
23.2% [hazard ratio (HR): 1.232, 95% confidence interval (95% CI): 1.084–1.401] higher risk of CVEs,
which was superior to other triglyceride or glycemic related markers.
Conclusions: The present study, firstly, showed that TyG index was positively associated with future
CVEs, suggesting that TyG may be a useful marker for predicting clinical outcomes in patients with CAD.

Keywords: Triglyceride glucose index (TyG index); stable coronary artery disease; outcome

Submitted Jun 01, 2018. Accepted for publication Sep 30, 2018.

doi: 10.21037/jtd.2018.10.79

View this article at: http://dx.doi.org/10.21037/jtd.2018.10.79

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Jin et al. TyG index and outcomes in CAD

Introduction

It has been well recognized that the development of
cardiovascular disease (CVD) is driven by multiple
contributing factors including glycemic abnormality and
lipid disorder (1,2). Hypertriglyceridemia (HTG) is a
common dyslipidemia and the association of triglyceride
(TG) with CVD risk remains controversial (3,4). However,
judging from a credible body of evidence, we can conclude
that HTG is an independent risk factor of developing
glucose metabolism disorders (5). Plasma TG levels are
strongly associated with raised glucose levels because of the
interactions between fat, muscle and function of pancreatic
β-cells (6,7). Moreover, accumulation of TG in the liver
may cause fatty liver disease, which can increase the risk of
type 2 diabetes mellitus (T2DM) (8). Prospective studies
have revealed that plasma TG is an independent risk factor
for developing T2DM (9,10). Additionally, it has been
demonstrated that lowering TG, such as fibrates do, can
significantly attenuate the process of developing insulin
resistance (11). Furthermore, it also has been reported that
both fasting glucose and TG within the high normal range
may predict CVD risk (12,13). Hence, evaluating the joint
value of TG and fasting glucose in patients with stable

coronary artery disease (CAD) may be clinically in need.
Triglyceride glucose (TyG) index is a novel marker,

which has been demonstrated to have a high sensitivity and
specificity in identifying metabolic syndrome (14). Previous
studies have shown that TyG index is associated with carotid
atherosclerosis, coronary artery calcification and high risk
of CVD. Unfortunately, no data is currently available with
regard to the effects of TyG index on clinical outcomes in
patients with stable CAD (15-17). Therefore, the primary
objective of the study was to investigate the prognostic role
of TyG index in a large Chinese cohort with stable CAD.

Methods

Study design and population

Our study complied with the Declaration of Helsinki and
was approved by the hospital’s ethical review board (Fu Wai
Hospital & National Center for Cardiovascular Diseases,
Beijing, China, approval number: 2013–442). Informed
written consents were obtained from all patients enrolled in
this study.

As described in Figure 1, from March 2011 to October
2014, 5,437 consecutive patients were scheduled for coronary

5,437 eligible patients from
March 2011 to October 2014

3,745 patients enrolled
in the study

3,448 patients without CVEs297 patients with CVEs

290 patients with CVEs 1,450 patients in control group

7 CVEs patients
without controls

972 non-CAD patients

183 patients did not
complete 36 months

following-up
198 patients were excluded for heart failure or ACS;
103 patients were excluded for liver or renal
insufficiency;
72 patients were excluded for thyroid dysfunction;
164 patients were excluded for other mentioned
exclusion criteria.

matched

Figure 1 Flowchart of the study. CAD, coronary artery disease; ACS, acute coronary syndrome; CVEs, cardiovascular events.

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Journal of Thoracic Disease, Vol 10, No 11 November 2018

angiography because of angina-like chest pain and/or
positive treadmill exercise test or clinically suspected CAD
in our division. Among these patients, 972 were excluded
because they were not angiography-proven CAD. Patients
with acute coronary syndrome (ACS), heart failure (left
ventricular ejection fraction, LVEF <45%), severe liver and/or renal insufficiency, thyroid dysfunction, malignant disease, extreme body mass index (BMI >45 kg/m 2),
s u s p e c t e d f a m i l i a l H T G [ p l a s m a T G ≥5 0 0 m g / d L
(5.65 mmol/L) or more than one first-degree relative
with TG ≥500 mg/dL] were also excluded. Patients were
prospectively followed up at 6, 12, 24, 36 months by means
of interviewing directly or using telephone conducted by
trained nurses or doctors who were blinded to the clinical
data. The cardiovascular events (CVEs) were all-cause
death, non-fatal myocardial infarction (MI), stroke and
post-discharge revascularization [percutaneous coronary
intervention (PCI) coronary artery bypass grafting
(CABG)]. Cardiovascular death was defined as death
primarily caused by acute MI, congestive heart failure,
stroke, malignant arrhythmia and other structural or
functional cardiac diseases. Non-fatal MI was diagnosed
as positive cardiac troponins along with typical chest pain
or typical electrocardiogram serial changes. Stroke was
diagnosed by the presence of typical symptoms or imaging.
Finally, we identified 3,745 patients with stable CAD who
completed our follow-up for the present analysis. During a
follow-up of per 11,235 person-years, 297 CVEs occurred
and individually matched to 5 randomly selected controls
on age, gender, previous history of PCI and CABG, and the
duration of follow-up.

Hypertension was defined as a self-reported hypertension,
currently taking anti-hypertensive drugs or recorded
systolic blood pressure (SBP) ≥140 mmHg and/or diastolic
blood pressure (DBP) ≥90 mmHg for three or more
consecutive times. T2DM was defined as fasting serum
glucose ≥7.0 mmol/L or the 2-h serum glucose of the oral
glucose tolerance test ≥11.1 mmol/L or currently using
hypoglycaemic drugs or insulin. BMI was calculated as
weight divided by height squared. Information of other
disease, family history and current therapy of every patient
was collected from self-reported medical history.

Laboratory analysis

Blood samples were obtained from each patient from the
cubital vein after at least 12-h fasting. Concentrations
of total cholesterol (TC), TG, low density lipoprotein

cholesterol (LDL-C), high density lipoprotein cholesterol
(HDL-C) were measured using automatic biochemistry
analyzer (Hitachi 7150, Japan) in an enzymatic assay.
Non-HDL-C was calculated as TC minus HDL-C. The
concentrations of glucose were measured by enzymatic
hexokinase method. HbA1c was measured using Tosoh
Automated Glycohemoglobin Analyser (HLC-723G8,
Tokyo, Japan). TyG index was calculated as formula:
ln[fasting TG (mg/dL) × fasting plasma glucose (mg/dL)/2].

Statistical analysis

The values were expressed as the mean ± standard deviation
(SD) or median (Q1–Q3 quartiles) for the continuous
variables and the number (percentage) for the categorical
variables. The differences of clinical characteristics between
groups were analyzed using Student t-test, χ2-tests,
and Fisher’s exact test where appropriate. Univariate and
multivariate Cox regression analyses were performed
to estimate the association TyG index with CVEs. We
electively included traditional risk factors [hypertension,
DM, lipid, family history of CAD, smoke, BMI, hsCRP
(high sensitive C-reactive protein)] and clinical factors with
significant differences between CVEs and control group. A
P value <0.05 was considered statistically significant. The statistical analysis was performed with SPSS version 21.0 software (SPSS Inc., Chicago, IL, USA).

Results

Cardiovascular events during follow-up

During a follow-up of per 11,235 person-years, 297 CVEs
occurred. Each patient experienced CVEs was matched
to 5 randomly selected controls on age (±2 years), gender,
previous history of PCI and CABG, and the duration of
follow-up. 7 patients with CVEs were excluded because
they were without matched controls. Among 290 patients
with CVEs, 35 (12.07%) died, 70 (24.14%) had stroke,
41 (14.13%) developed non-fatal MI and 144 (49.66%)
underwent unplanned PCI or CABG. Patients who
experienced non-fatal MI and underwent PCI or CABG
were analyzed as one single event.

Baseline characteristics

As presented in Table 1, patients in CVEs group had
higher levels of TyG index compared to the control group.

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Jin et al. TyG index and outcomes in CAD

Table 1 Baseline characteristics of studied patients

Variables Control group, N=1,450 CVEs group, N=290 P

Clinical factors

Age, years 59.5±10.8 59.4±10.0 0.836

Male, n (%) 1,045 (72.1) 209 (72.1) 0.999

BMI (kg/m2) 25.8±3.2 25.5±3.3 0.187

HT, n (%) 921 (63.5) 207 (71.4) 0.010

DM, n (%) 368 (25.4) 100 (34.5) 0.002

DM duration 5.7±4.8 6.5±5.3 0.149

Family history of CAD, n (%) 200 (13.8) 40 (13.8) 0.942

Current Smoker, n (%) 770 (54.5) 158 (53.1) 0.667

Drinking, n (%) 417 (28.2) 81 (28.9) 0.807

PrePCI, n (%) 310 (21.4) 62 (21.4) 1

PreCABG, n (%) 25 (1.7) 5 (1.7) 1

PreMI, n (%) 422 (29.1) 97 (33.4) 0.140

Laboratory factors

Glucose (mmol/L) 5.6±1.5 5.9±2.0 0.001

HbA1c (%) 6.4±1.1 6.6±1.3 <0.001

ALT (IU/L) 23.0 (17.0–33.0) 24.0 (17.0–34.0) 0.115

AST (IU/L) 17.0 (14.0–22.0) 18.0 (14.0–23.0) 0.077

Creatinine (μmol) 75.8±16.8 77.3±16.4 0.141

UA (μmol/L) 351.3±87.5 365.3±95.6 0.022

hsCRP (μmol/L) 1.42 (0.72–3.13) 1.63 (0.83–3.30) 0.250

TC (mmol/L) 4.13±1.19 4.20±1.15 0.338

HDL-C (mmol/L) 1.06±0.28 1.07±0.30 0.825

LDL-C (mmol/L) 2.53±1.04 2.50±0.92 0.673

Non-HDL-C (mmol/L) 3.14±1.10 3.07±1.16 0.348

TG (mmol/L) 1.46 (1.09–2.03) 1.57 (1.15–2.18) 0.014

Lp(a) (mg/L) 158.6 (64.7–363.8) 363.8 (77.5–431.4) 0.369

TyG index 8.80±0.57 8.91±0.66 0.002

TG/HDL-C 1.44 (0.96–2.22) 1.56 (1.01–2.47) 0.046

LVEF (%) 63.7±7.6 61.8±9.0 0.001

Medications, n (%)

Lipid lowering agents 1,109 (74.7) 218 (73.4) 0.644

ACEIs/ARBs 205 (14.1) 35 (12.1) 0.351

β-blockers 410 (28.2) 78 (26.9) 0.396

Aspirin 1,421 (98.0) 282 (97.2) 0.414

Antidiabetic drug, n (%)

OADs 207 (14.3) 52 (17.9) 0.110

Insulin 103 (7.1) 24 (8.3) 0.484

Data were expressed as median ± SD, 25th and 75th percentile or n (%). BMI, body mass index; HT, hypertension; DM, diabetes mellitus;
ALT, alanine aminotransferase; AST, aspartate aminotransferase; UA, uric acid; PCI, percutaneous coronary intervention; CABG, coronary
artery bypass grafting; MI, myocardial infarction; hsCRP, high sensitive C-reactive protein; TG, triglyceride; LDL-C, low density lipoprotein
cholesterol; HDL-C, high density lipoprotein cholesterol; Lp(a), lipoprotein (a); TyG index, triglyceride glucose index; LVEF, left ventricular
ejection fraction; ACEIs, angiotensin-converting enzymes; ARBs, angiotensin receptor blocker.

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Journal of Thoracic Disease, Vol 10, No 11 November 2018

Patients in CVEs group also showed higher proportions
of hypertension (71.4% vs. 63.5%, P=0.010) and diabetes
(34.5% vs. 25.4%, P=0.002), elevated concentrations of
plasma glucose, TG, HbA1C but lower levels of LVEF
(all P<0.05). There were no significant differences in TC, HDL-C, LDL-C, lipoprotein (a), hsCRP, the proportions of current smoking, and family history of CAD between the two groups (all P>0.05).

Cardiovascular risk factors according to quartiles of TyG
index

We also analyzed the distribution of cardiovascular risk
factors according to quartiles of TyG index (I quart n=429,
II quart n=444, III quart n=434, IV quart n=433). As shown
in Table 2, TyG index was positively associated with BMI,
UA, hsCRP, HDL–C, LDL-C, DM and hypertension while
it was negatively related to age (all P<0.05).

Predictive role of TyG index on cardiovascular events

In the present study, univariate Cox proportional hazard
regression analysis showed that TyG index was associated
with CVEs (hazard ratio: 1.356, 95% confidence interval:
1.123–1.639, P=0.002, Table 3). Hypertension, DM and UA
were also risk factors of CVEs (P<0.05) while LVEF played a protective role. In multivariate Cox proportional hazard regression analysis, we further examined the independent risk value of TyG index on CVEs (Table 3). After adjustment of BMI, LVEF, hypertension, DM, UA, smoke, hsCRP, HDL-C and LDL-C, TyG index was independently associated with CVEs [hazard ratio (HR): 1.364, 95% confidence interval (95% CI): 1.100–1.691, P=0.005]. The Kaplan–Meier analysis revealed that the patients within the highest quartile of TyG index presented the lowest event-free survival (P=0.029, Figure 2). In addition, a 1-SD increment in TyG index was associated with 23.2%

Table 2 TyG index and cardiovascular risk factors

Variables
I quart, n=429

(<8.40) II quart, n=444

(8.41–8.78)
III quart, n=434

(8.79–9.16)
IV quart, n=433

(>9.17)
P

Male, n (%) 311 (72.5) 334 (75.2) 298 (68.7) 311 (71.8) 0.191

Age, years 61.2±9.4 60.2±9.6 58.2±9.9 57.7±10.1 <0.001

BMI (kg/m2) 24.5±3.3 25.6±3.2 26.3±3.1 26.6±2.9 <0.001

Family history of CAD, n (%) 63 (14.7) 54 (12.2) 66 (15.3) 57 (13.2) 0.753

Current Smoker, n (%) 231 (53.8) 237 (53.4) 219 (50.5) 241 (55.7) 0.489

HT, n (%) 251 (58.5) 278 (62.6) 276 (63.6) 323 (74.6) <0.001

DM, n (%) 60 (14) 80 (18.1) 114 (26.3) 214 (49.7) <0.001

UA (μmol/L) 330.8±80.5 351.0±81.3 356.4±87.1 377.4±98.6 <0.001

hsCRP (mg/L) 1.1 (0.55–2.24) 1.3 (0.72–2.97) 1.6 (0.78–3.37) 1.8 (0.98–4.29) <0.001

HDL–C (mmol/L) 1.18±0.29 1.09±0.27 1.03±0.26 0.95±0.23 <0.001

LDL-C (mmol/L) 2.23±1.00 2.52±1.14 2.63±0.89 2.71±0.99 <0.001

Non-HDL-C (mmol/L) 2.52±0.97 2.90±0.90 3.23±1.28 3.66±1.09 <0.001

LVEF (%) 63.1±7.5 62.9±8.5 63.1±7.2 63.5±8.2 0.571

PrePCI, n (%) 99 (23.1) 89 (20.0) 100 (23.0) 84 (19.4) 0.403

PreCABG, n (%) 3 (0.7) 8 (1.8) 10 (2.3) 9 (2.1) 0.277

Events, n (%) 69 (16.1) 57 (12.8) 76 (17.5) 88 (20.3) 0.027

Data were expressed as mean ± SD, 25th and 75th percentile or n (%). BMI, body mass index; HT, hypertension; DM, diabetes mellitus;
LVEF, left ventricular ejection fraction; UA, uric acid; hsCRP, high sensitive C-reactive protein; TG, triglyceride; LDL-C, low density
lipoprotein cholesterol; HDL-C, high density lipoprotein cholesterol; PCI, percutaneous coronary intervention; CABG, coronary artery
bypass grafting.

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Jin et al. TyG index and outcomes in CAD

(HR: 1.232, 95% CI: 1.084–1.401, P<0.05) higher risk of CVEs, which was superior to other TG or glycemic related markers [TG: HR per 1-SD increment 1.104 (95% CI: 1.006–1.212), P<0.05; TG/HDL-C: HR per 1-SD

increment 1.105 (95% CI: 0.955–1.227), P>0.05; HbA1c:
HR per 1-SD increment 1.211 (95% CI: 1.093–1.341),
P<0.05; glucose: HR per 1-SD increment 1.183 (95% CI: 1.074–1.303), P<0.05, Figure 3A]. Furthermore, TyG index was also positively associated with CVEs in subgroup analysis according to the different status of DM and LVEF [DM group: adjusted HR 1.574 (95% CI: 1.090–2.272), P<0.05; non-DM group: 1.434 (95% CI: 1.039–1.979), P<0.05; low LVEF group: adjusted HR 1.396 (95% CI: 1.036–1.882), P<0.05; high LVEF group: adjusted HR 1.521 (95% CI: 1.079–2.143), P<0.05; Figure 3B,C]. Finally, the predictive value of TyG index remained significant after adjustment of HbA1c in the multivariate model [adjusted HR 1.282 (95% CI: 1.006–1.634), P<0.05, Figure 3D].

Discussion

TyG index has been reported to be associated with CVD
risk in apparently healthy individuals (17). However, the
prognostic value of TyG index in patients with stable
CAD remains undetermined. Using nested case-control
analysis, the data suggested that TyG index was higher in
patients who experienced CVEs. In addition, TyG index
was found to be positively related to cardiovascular risk
factors and presented the lowest event-free survival in its
top quartered group. To our knowledge, the present study
firstly demonstrated that TyG index was an independent

Table 3 Univariate and multivariate Cox proportional hazards regression analysis of the events

Variables
Univariate Cox regression Multivariate Cox regression

HR (95% CI) P HR (95% CI) P

BMI 0.975 (0.940–1.012) 0.187 –

LVEF 0.975 (0.962–0.987) <0.001 0.976 (0.963–0.989) <0.001

HT 1.410 (1.092–1.812) 0.008 1.317 (1.004–1.727) 0.047

DM 1.479 (1.161–1.885) 0.020 1.350 (1.040–1.777) 0.025

hsCRP 1.010 (0.983–1.050) 0.339 – –

UA 1.002 (1.001–1.003) 0.013 1.002 (1.001–1.003) 0.007

Smoke 1.056 (0.838–1.331) 0.646 – –

HDL-C 1.031 (0.685–1.552) 0.882 – –

LDL-C 0.973 (0.866–1.092) 0.638 – –

TyG index 1.356 (1.123–1.639) 0.002 1.364 (1.100–1.691) 0.005

HR, hazard ratio; 95% CI, 95% confidence intervals; BMI, body mass index; LVEF, left ventricular ejection fraction; HT, hypertension; DM,
diabetes mellitus; hsCRP, high sensitive C-reactive protein; UA, uric acid; LDL-C, low density lipoprotein cholesterol; HDL-C, high density
lipoprotein cholesterol; UA, uric acid; TyG index, triglyceride glucose index.

1.00

0.95

0.90

0.85

0.80

0.75

0.70

C
u
m

s
u
rv

iv
a
l

0 10 20 30 40 50

Follow-up months

Log rank P=0.029

TyG index quartile

I quart
II quart
III quart
IV quart

Figure 2 The event-free survival analysis according to the quartiles
of TyG index. TyG index, triglyceride glucose index.

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Journal of Thoracic Disease, Vol 10, No 11 November 2018

risk marker for evaluating future CVEs in patients with
stable CAD.

TyG index was firstly studied as a marker of identifying
insulin resistance with a high sensitivity and specificity (18-20).
It was demonstrated that TyG index was a useful predictor
o f t y p e 2 d i a b e t e s a n d m e t a b o l i c s y n d r o m e w h i c h
contributed to cardiometabolic risk (21,22). Subsequently,
several studies were conducted and found a positive
relationship between TyG index and CVD. Two of such
studies demonstrated that TyG index was associated
with the presence of cardiovascular risk factors (23,24).
Moreover, Irace et al. evaluated the association between
carotid atherosclerosis and TyG index in two different
cohorts and provided consistent, positive results (15). In
addition to this, a study enrolled 4,319 Korean adults also
indicated that TyG index was significantly associated with
the presence of coronary calcification (16). Furthermore, a

study including 888 asymptomatic type 2 diabetic patients
showed that the higher TyG index was associated with
increased risk of coronary stenosis (25). Of the note, studies
mentioned above did not evaluated the prognostic value of
TyG index in CVD risk.

In fact, a few prospective studies were conducted on
the link between TyG index and CVEs. Vega et al. firstly
investigated the relation of TyG index to mortality from
cardiovascular causes, CAD, or CVD in 39,447 men and
proved that TyG index did not predict CVD mortality (26).
Apparently, this study was limited by gender selection.
Another study enrolled 5,014 apparently healthy individuals
and identified that the higher level of TyG index was
significantly associated with an increased risk of developing
CVD (17). They also developed a new model containing the
TyG index in addition to Framingham variables and resulted
in a higher predictive efficiency in the risk of developing

TyG index

TG

TG/ HDL-C

HbA1C

Glucose

Low LVEF

High-LVEF

Low LVEF
High-LVEF

1.232 (1.084−1.401)

1.104 (1.006−1.212)

1.105 (0.955−1.227)

1.211 (1.093−1.341)

1.183 (1.074−1.303)

1.533 (1.121−2.097)

1.317 (1.012−1.713)

1.574 (1.090−2.272)

1.434 (1.039−1.979)

1.365 (1.056−1.763)

1.378 (1.041−1.825)

1.396 (1.036−1.882)

1.521 (1.079−2.143)

1.069 (0.941−1.216)

1.282 (1.006−1.634)

HR per 1-SD increment
(95% CI)

HR (95% CI)

HR (95% CI) HR (95% CI)

0.8 1.0 1.2 1.4 1.6

0.8 1.0 1.2 1.4 1.6 1.8

1.0 1.5 2.0

1.0 1.5 2.0

0.5

0.5

Harzard ratio

Harzard ratio
Harzard ratio
Harzard ratio

DM

DM

Non-DM

Undjusted
model

Undjusted
model

adjusted
model

adjusted
model
Non-DM
HbA1C
TyG index

A B

C D

Figure 3 Predictive value of TyG index for CVEs in the different models. (A) HR for cardiovascular events risk elevation associated with 1-SD
increment in triglyceride or glycemic related markers; (B) predictive value of TyG index for CVEs in diabetic and non-diabetic patients; (C)
predictive value of TyG index for CVEs in patients with high and low LVEF; (D) predictive value of TyG index for CVEs after adjusting for
HbA1c and other confounding variables. Adjusted model included BMI, smoking, hypertension, non-LDL-C, hs-CRP, UA (age, sex, DM
and LVEF when appropriate). TyGindex, triglyceride glucose index; CVEs, cardiovascular events; HR, hazard ratio; LVEF, left ventricle
ejection fraction; LDL-C, low density lipoprotein cholesterol; DM, diabetes mellitus.

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Jin et al. TyG index and outcomes in CAD

CVD. However, their study focused only on the healthy
individuals. Consequently, determination of the prognostic
role of TyG index in patients with CAD might be greatly
of interest. That was the reason why we performed such
study. As shown in the tables and figures, our study, for the
first time, indicated that TyG index was significantly higher
in patients with CVEs and had better predictive value than
TG or glucose alone, suggesting that TyG index might be
a simple, easy-to-use, reliable parameter in predicting the
prognosis in patients with stable CAD. Moreover, we also
compared the prognostic value of TyG index with HbA1c.
As we well known, plasma HbA1c, the most reliable marker
in evaluating long term glycemic control, had similar HR
to TyG index in our study. To our knowledge, both markers
were associated with insulin resistance in certain patients
and only the predictive value of TyG index stayed significant
when the two markers were in the same model (Figure 3D).

The exact mechanism underlying the relationship
between the TyG index and CVEs has not been fully
elucidated. The formula of TyG index is composed of TG
and glucose. Although the association of TG with CVD
risk is still under debate (3,4), a body of recent evidence
has proved that TG and TG-rich lipoproteins are causal
factors of CVD (27). Additionally, the concurrence of
HTG also promotes the formation of small dense LDL
particles (28). Despite the fact that most studies evaluate the
CVD risk of TG only in HTG patients, a few studies have
demonstrated that plasma TG within high normal range
also predict CVEs. In fact, glucose disorder is another CVD
risk factor frequently coexisting with HTG. Achievement
of favorable goal in plasma TG by means of losing weight

or drugs often helps improve glycemic control (29,30).
Genetic polymorphisms affecting TG metabolism may
also be associated with higher fasting plasma glucose (31).
The Prospective Urban Rural Epidemiology (PURE)
study demonstrated that high carbohydrate intake, which
might increase plasma TG and glucose, was associated
with greater risk of the total mortality (32). Therefore,
using TyG index may better interpret their joint roles in
CVD risk prediction. As we previously described, TyG
index was also a useful marker in identifying metabolic
disorder (22,23). Notably, inflammatory markers causing
atherosclerotic plaque instability, including tumor necrosis
factor-α, interleukins, leukocytes and fibrinogen, also
played a crucial role in metabolic syndrome and related
disorders (33,34). Therefore, TyG index might be a better
marker of cardiometabolic risk estimation (Figure 4).

There were several limitations in the present study.
Firstly, the sample size might be not large enough and the
follow-up time might be not long enough. Secondly, the
measurements of TG and fasting glucose had unavoidable
intra-individual biological variation and changed over time.
Previous studies demonstrated that increment in TyG
index over time could predict the incidence of diabetes
and was positively related to the value of TyG index at first
measurement (35,36). We measured TG and fasting glucose
only at the baseline and did not evaluate the predictive value
of the changes in TyG index for CVEs. Moreover, other
confounding factors such as exercise habit, participation to
cardiac rehab program and cardiorespiratory fitness were
not included in the model. Finally, we did not assess the
relationship between TyG index and all metabolic factors

Triglyceride

Triglyceride-
glucose Index

Accumulation
of TRLs;

Formation of
sd-LDL-C;

Related low
HDL-C levels;

Dyslipidemia;
Dysfunction of

platelet;
Endothelial cells

activation; Hormone
disturbance;

Better identifying
cardiometabolic

Disorders

Stroke

death

Non-fatal MI

Cardiovascular
Events

Revascularization

Glucose

Figure 4 Mechanism of TyG index associated with cardiovascular outcomes. TyGindex, triglyceride glucose index; TRLs, triglyceride-rich
lipoproteins; sd-LDL-C, small dense LDL-C; MI, myocardial infarction.

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© Journal of Thoracic Disease. All rights reserved. J Thorac Dis 2018;10(11):6137-6146jtd.amegroups.com
Journal of Thoracic Disease, Vol 10, No 11 November 2018

including waist circumstance due to a lack of data. Hence,
larger sample and long-term studies are needed to confirm
our findings.

Conclusions

Although previous studies indicated an association of
TyG with the cardiovascular risk, the present study firstly
reported that TyG index was associated with future CVEs
in patients with stable CAD using nested case-control study.

Acknowledgements

Funding: This work was partially supported by the Capital
Health Development Fund (201614035) and CAMS
Major Collaborative Innovation Project (2016-I2M-1-011)
awarded to Dr. Jian-Jun Li, MD, PhD.

Footnote

Conflicts of Interest: The authors have no conflicts of interest
to declare.

Ethical Statement: Our study complied with the Declaration
of Helsinki and was approved by the hospital’s ethical
review board (Fu Wai Hospital & National Center for
Cardiovascular Diseases, Beijing, China, approval number:
2013–442). Informed written consents were obtained from
all patients enrolled in this study.

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Cite this article as: Jin JL, Cao YX, Wu LG, You XD, Guo
YL, Wu NQ, Zhu CG, Gao Y, Dong QT, Zhang HW, Sun D,
Liu G, Dong Q, Li JJ. Triglyceride glucose index for predicting
cardiovascular outcomes in patients with coronary artery
disease. J Thorac Dis 2018;10(11):6137-6146. doi: 10.21037/
jtd.2018.10.79

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