Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

The association of hypertriglyceridemia with cardiovascular events and pancreatitis: a systematic review and meta-analysis

  • M Hassan Murad1, 2Email author,
  • Ahmad Hazem1, 2, 3,
  • Fernando Coto-Yglesias1,
  • Svitlana Dzyubak1,
  • Shabnum Gupta1,
  • Irina Bancos1, 5,
  • Melanie A Lane1,
  • Patricia J Erwin1,
  • Lars Berglund4,
  • Tarig Elraiyah1 and
  • Victor M Montori1, 5
BMC Endocrine Disorders201212:2

DOI: 10.1186/1472-6823-12-2

Received: 6 January 2012

Accepted: 31 March 2012

Published: 31 March 2012

Abstract

Background

Hypertriglyceridemia may be associated with important complications. The aim of this study is to estimate the magnitude of association and quality of supporting evidence linking hypertriglyceridemia to cardiovascular events and pancreatitis.

Methods

We conducted a systematic review of multiple electronic bibliographic databases and subsequent meta-analysis using a random effects model. Studies eligible for this review followed patients longitudinally and evaluated quantitatively the association of fasting hypertriglyceridemia with the outcomes of interest. Reviewers working independently and in duplicate reviewed studies and extracted data.

Results

35 studies provided data sufficient for meta-analysis. The quality of these observational studies was moderate to low with fair level of multivariable adjustments and adequate exposure and outcome ascertainment. Fasting hypertriglyceridemia was significantly associated with cardiovascular death (odds ratios (OR) 1.80; 95% confidence interval (CI) 1.31-2.49), cardiovascular events (OR, 1.37; 95% CI, 1.23-1.53), myocardial infarction (OR, 1.31; 95% CI, 1.15-1.49), and pancreatitis (OR, 3.96; 95% CI, 1.27-12.34, in one study only). The association with all-cause mortality was not statistically significant.

Conclusions

The current evidence suggests that fasting hypertriglyceridemia is associated with increased risk of cardiovascular death, MI, cardiovascular events, and possibly acute pancreatitis.

Précis: hypertriglyceridemia is associated with increased risk of cardiovascular death, MI, cardiovascular events, and possibly acute pancreatitis

Keywords

Hypertriglyceridemia Cardiovascular disease Pancreatitis Systematic reviews and meta-analysis

Background

Hypertriglyceridemia is a manifestation of several common metabolic disorders in the western world. A recent cross-sectional study found that over 33% of adults in the United States had hypertriglyceridemia (serum triglyceride levels over 150 mg/dl (1.7 mmol/L)) of whom over 50% had serum triglyceride levels exceeding 200 mg/dl (2.2 mmol/L) [1].

The association of hypertriglyceridemia and clinically important complications such as cardiovascular events and acute pancreatitis has been suggested by several studies. Previous epidemiologic studies demonstrated increase in the risk of cardiovascular events although there has always been significant confounding due to varying levels of adjustments for traditional risk factors and other lipid subfractions [24]. As for pancreatitis, case series and uncontrolled studies reported that very severely elevated triglyceride levels are associated with lipemic serum, chylomicronemia syndrome, and increased risk of pancreatitis [57]. Serum triglycerides levels of 1000 mg/dl (11.3 mmol/L) and higher have been observed in 12% to 38% of patients presenting with acute pancreatitis [5]. However, the association with pancreatitis has not been evaluated in controlled studies or with less severe hypertriglyceridemia.

To update the evidence base to the present time (last meta-analysis [2] was performed 6 years ago), we conducted this systematic review and meta-analysis. Our goal was to assess the magnitude of association and the quality of supporting evidence linking hypertriglyceridemia with cardiovascular events, mortality and pancreatitis. We specifically aimed at comparing association measures in studies with varying levels of adjustment for cardiovascular risk factors and to search for controlled studies evaluating the risk of pancreatitis.

Methods

This systematic review was conducted according to a priori established protocol that was commissioned and funded by the Endocrine Society and is reported according to the PRISMA statement (Preferred Reporting Items for Systematic Reviews and Meta-analyses) [8].

Eligibility criteria

Eligible studies were randomized and observational studies that enrolled patients with untreated hypertriglyceridemia and reported a relative association measure between fasting serum triglycerides levels and the outcomes of interest: all-cause mortality, cardiovascular death, cardiovascular events and pancreatitis. We excluded uncontrolled studies and studies of nonfasting hypertriglyceridemia.

Study identification and data extraction

An expert reference librarian (P.J.E) created and implemented the electronic search strategy with input from study investigators (V.M.M. & M.H.M). We searched Ovid MEDLINE, Ovid EMBASE, Web of Science and SCOPUS through August of 2010. The detailed search strategy is available in Additional file 1. We also sought recommendations from content expert for potentially relevant studies to be included in the screening process.

Reviewers working independently and in duplicate assessed each abstract for eligibility. Disagreements yielded an automatic inclusion into the following level of screening. Included studied were retrieved and full text screening commenced in duplicate as well. Disagreements in this level were resolved by discussion and consensus. Online reference management system was used to conduct this review and it reported a real-time chance-adjusted agreement (kappa) statistic to evaluate the agreement among reviewers. Kappa averaged 0.80. Two reviewers working independently and in duplicate extracted baseline and outcome data and assessed the quality of included study. A third reviewer compared the reviewer's data and resolved inconsistencies by referring to the full text article.

Quality

Using the Newcastle-Ottawa scale, [9] reviewers assessed the quality of included observational studies (and control arms of RCT, considered as observational cohorts) by determining outcome ascertainment, adjustment for confounders, proportion of patients lost to follow-up as well as sample selection. We used the GRADE approach in evaluating the evidence yielded from included studies[10].

Statistical analysis

We pooled the relative association measures of relevant complications from included studies and analyzed the data using the random-effects model described by DerSimonian and Laird [11]. Heterogeneity in results across studies was measured using the I 2 statistic, which estimates the proportion of variation in results across studies that is not due to chance. An I 2 of 50% or more indicates large inconsistency between studies. Meta-analysis was completed using Comprehensive Meta-analysis (CMA) version 2.2 (Biostat Inc., Englewood, NJ).

Subgroup analyses and publication bias

A priori hypotheses were designed to explain between-study inconsistencies in results. These analyses sought an interaction with whether triglycerides levels were adjusted for other lipid fractions or not; whether the underlying metabolic disorder was diabetes vs. not; and whether the association differed between men and women. Publication bias was evaluated by assessing the symmetry of funnel plots and using Egger's regression test. In this regression, the size of the treatment effect is captured by the slope of the regression line and bias is captured by the intercept [12].

Results

Search results and included studies

Electronic search yielded 760 potentially eligible studies. Following screening, 60 studies met inclusion criteria, of which 35 reported data sufficient for meta-analysis [Figure 1].
https://static-content.springer.com/image/art%3A10.1186%2F1472-6823-12-2/MediaObjects/12902_2012_Article_123_Fig1_HTML.jpg
Figure 1

Study selection process.

Methodological quality and risk of bias

Included studies had a fair methodological quality (Table 2) with follow-up period reported by 85% of studies averaging 114 months; 58% of studies reported loss to follow-up of participants that ranged 0% to 27%. Adjustment for potential confounders was reported in 90% of studies and the outcome ascertainment method was reported in all studies. Cohort selection was random in 18% of the studies.
Table 1

Baseline Characteristics of Included Studies

Study Label

Design

Objective of Study

Population

Age (mean)

Sample Size

Length of Follow-up

Definition of CV

events

Acarturk, 2004[13]

Prospective cohort

to investigate the relation

between age and gender differences in plasma TG and

CAD in patients with angiographically proven

CAD

patients

admitted for

diagnostic

coronary

angiography

due to chest

pain

54.9 +/-10.26

937

NR

Coronary artery

disease

Bansal, 2007[14]

Prospective cohort

To determine the association

of triglyceride levels (fasting

vs nonfasting) and risk of

future cardiovascular events.

healthy women

54.2 +/-

7.06

26,509

136.8

Months (median)

composite of

confirmed nonfatal

MI, nonfatal ischemic stroke, coronary revascularization, or death due to cardiovascular causes

Barrett-Connor, 1987[15]

Prospective cohort

To examine the independent

effect of triglyceride on the prediction of cardiovascular disease after the effects of cholesterol and other heart

disease risk factors have been accounted for

healthy fasting

men without

known CVD

57.7

1,589

144 months

N/A

Bass, 1993[16]

Prospective cohort

To further explore the relationships between lipid

and lipoprotein levels and

other conventional CVD risk factors and CVD death on women

women 30

years of age

and older

58.2 +/-

5.5

1,405

Mean 168 months

N/A

Bonaventure, 2010[17]

Prospective cohort

To find the association

pattern between serum TG

and incident intracerebral hemorrhage as compared

with coronary events and ischemic stroke

Population-

based, elderly participants

free from institutionalization were recruited from the electoral

rolls of three

French cities

74.03

years

8,393

mean of 5 years

MI, hospitalized

angina pectoris, acute coronary

syndrome, coronary endovascular

dilatation, coronary bypass, or death due to a coronary event

Carlson, 1988[18]

RCT

To obtain a pronounced

serum lipid lowering by combined use of clofibrate

and nicotinic acid in an effort

to reduce the risk of IHD

Survivors of

MI < 70 years

of age

58.9 + -0.4 males and 62.5 + -0.9 females

Control group (n = 276)

60 months

N/A

Chan, 2005[19]

Prospective cohort

To examine the lipid profiles

in Chinese type 2 diabetic patients and their relationship with anthropometric parameters, glycemic control and cardiovascular mortality.

Chinese

patients with

type 2 DM

54.0 +/-

14.0

517

Mean 55.2 +/-10.8 months

N/A

Chester, 1995[20]

Prospective cohort

To determine the standard clinical or angiographic variables or both present at initial angiography associated with the development of adverse coronary events in patients awaiting routine

PTCA

Patients

awaiting

routine

percutaneous transluminal

coronary

angioplasty

(PTCA)

57

215

Median 8 months

fatal or non-fatal MI, unstable angina or angiographic new total coronary occlusion

Czernichow, 2007[21]

Prospective cohort

To investigated the

relationship of baseline 'hypertriglyceridemic waist' (HTGW) status with CVD

risk in middle-aged French

men

middle-aged

French men,

included

diabetics

51.9 +/-

4.7

3,430

90 months

new-onset angina,

fatal and non-fatal MI or stroke, transient ischemic attack,

sudden death or intermittent claudication

Drexel, 2005[22]

Prospective cohort

To evaluate the

atherogenicity of lipids in coronary patients with

normal fasting glucose

(NFG), impaired fasting glucose (IFG), and type 2

DM

Caucasian

patients who

were referred

to coronary angiography

62.4 +/-

10.6

750

27.6 +/- 4.8 months

N/A

Eberly, 2003[23]

Prospective cohort

To determine whether HTG

is an independent risk factor

for coronary heart disease (CHD), and whether fasting

and nonfasting triglyceride (TG) levels are equally predictive

men at increased

risk but without clinical

evidence of

definite CHD

at baseline

46.3

2809

304.8 months

either a clinical MI or

a significant serial electrocardiogram change indicative of

MI

Egger, 1999[24]

Prospective cohort

To assess the influence of differential precision in the measurement of the

correlated variables total cholesterol and HDL cholesterol on estimates of

risk of IHD associated with

TG levels

Middle aged

men living in

the town of

Caerphilly,

South Wales,

UK

52.1 +/-

4.48

2,512

5 and 10 years after baseline

death from ischemic heart disease, clinical non-fatal MI, electrocardiographic

MI

Ellingsen, 2003[25]

Prospective cohort

to examine the effect of

group assignment on IHD mortality in subjects with normal or high fasting TG

healthy men

who had an

elevated serum

total

cholesterol concentration

or coronary

risk score

46 +/-3

1232

276 months

N/A

Gaziano, 1997[26]

Case controlled study

To examine the interrelationships of the

fasting TG level other lipid parameters and nonlipid risk factors with risk of MI.

Patients -

coronary care

and other

intensive care

units patients

(no history of

MI and angina pectoris) with

whom

symptoms of

MI had begun

24 h of

admission,

control -

residents of

home towns.

57.7 +/-

9.65

680

NR

N/A

Goldberg, 2009[27]

Prospective/

case controlled

To ascertain coronary artery disease outcomes and

predictive factors in patients with SLE and matched

healthy controls

prospectively

Patients with

systemic lupus erythematosus

(SLE) and

matched

healthy

controls

SLE cases 44.2 +/-12.2, controls 44.5 +/-

4.4

237 controls and 241 SLE cases

86.4 months

Defined as the occurrence of MI and/or angina pectoris due to atherosclerosis.

Habib, 2006[28]

Prospective cohort

To evaluate the association of serum TC and TG with

clinical outcomes in chronic peritoneal dialysis (PD)

patients.

Patients on

chronic

peritoneal

dialysis; only

in end-stage

renal disease

(ESRD) or

patients those

very ill

patients who

died rapidly

due to unrelated conditions.

57.2 +/

15.3

1,053

23 +/- 14 months

N/A

Haim, 1999[29]

Prospective cohort

To investigate the association between elevated blood triglyceride levels and subsequent mortality risk in patients with established coronary heart disease

(CHD)

patients with a diagnosis of CHD

59.76 +/- 6.96

11,546

61.2 months

N/A

Hoogeveen, 2001[30]

Case controlled study

To determine the effect of immigration to the USA ion plasma levels of lipoprotein a and other independent risk factors for CHD in Asian Indians

Asian Indians

and Asian

Indians living

in the USA

with and

without CHD

44.2 +/- 12.79

309

NR

Coronary heart disease - incidents not specifically defined

Jonsdottir, 2002[31]

Prospective cohort

To examine the relationship between the relative risk of baseline variables and

verified MI or coronary death

in individuals with no prior history of MI

male and

female from

Reykjavik and adjusted

communities

52.7 +/-

8.71

18,569

Mean 208.8 months

N/A

Lamarche, 1995[32]

Prospective cohort

To confirm the importance of both elevated plasma cholesterol and decreased

high density lipoprotein cholesterol levels as risk

factors for ischemic heart disease

men without

ischemic heart

disease

57.5

2,103

60 months

Effort angina pectoris, coronary

insufficiency, nonfatal MI, and coronary

death

Lloret Linares, 2008[33]

Retrospective cohort

to assess retrospectively the prevalence and the predictive factors of acute pancreatitis (AP)

Patients

referred by

their general practitioner or

general

hospital for

very high TG

levels.

47 +/-

10.7

129

NR

N/A

Lu, 2003[34]

Prospective cohort

To determine whether non-

HDL cholesterol, a measure

of total cholesterol minus

HDL cholesterol, is a

predictor of CVD in patients with DM

American

Indians with

DM

57.28 +/-

8

2,108

108 months

Coronary heart

disease,

MI, stroke, and other CVD

Malone, 2009[35]

Prospective cohort

This study evaluated cardiometabolic risk factors

and their relationship to prevalent diagnosis of acute

MI (AMI) and stroke.

People

continuously

receiving

health

insurance

benefits during

study

56.8 +/- 0.03

170,648

24 months

N/A

Mazza, 2005[36]

Prospective cohort

To evaluate whether TG level

is a risk factor for CHD in elderly people from general population, and to look for interactions between TG and other risk factors.

elderly people

from general population

CHD in elderly

people from

general

population

73.8 +/- 5

3,257

144 months

N/A

Mora, 2008[37]

Prospective cohort

To evaluate levels of lipids

and apolipoproteins after a typical meal and to determine whether fasting compared

with non-fasting alters the association of these lipids

and apolipoproteins with incident CVD.

Healthy

women, aged

> = 45 years,

who were free

of self-

reported CVD

or cancer at

study entry and with follow-up for

incident CVD.

54.7

26,330

136.8 months

Nonfatal MI, percutaneous

coronary

intervention,

coronary artery

bypass grafting, nonfatal stroke,

or

cardiovascular

death

Noda, 2010[38]

Case controlled study

To examine the prediction of coronary risk factors and evaluation of the predictive value for MI among Japanese middle-aged male workers.

Japanese male

workers

cases 50.4 + -5.3, controls 50.4 + -5.5 years

cases 204 and controls 408

36 months

N/A

Rubins, 1999[39]

RCT

To analyze the role of raising HDL cholesterol level and lowering triglyceride levels

to reduce the rate of coronary events in patients with

existing cardiovascular

disease

men with

coronary heart

disease with

absence of

serious

coexisting

conditions

64 + -7

1267 (placebo)

61.2 months

combined incidence of nonfatal MI or death from coronary heart disease

Samuelsson, 1994[40]

Prospective cohort

To analyze the importance of DM and HTG as potential

risk factors for CHD in

middle-aged, treated hypertensive men

middle aged

treated

hypertensive

men

52 +/- 2.3

686

180 months

Non-fatal MI, a fatal MI, a death certificate statement of coronary atherosclerosis as the cause of death

Schupf, 2005[41]

Prospective cohort

To investigate the

relationship between plasma lipids and risk of death from

all causes in non demented elderly

Community-

based sample

of Medicare

recipients

without

dementia

76.1

2,277

Mean 36 +/- 30 months

N/A

Sprecher, 2000[42]

Prospective cohort

To evaluate the predictive

value of serum triglyceride levels on mortality in post coronary artery bypass graft(CABG) diabetic

patients with subsequent analysis by sex

Diabetic post

CABG patients

at a large

metropolitan

hospital

63 +/- 9

1,172

84 months

N/A

Tanko, 2005[43]

Prospective cohort

To investigate the relative utility of enlarged waist combined with elevated TG (EWET) compared with the National Cholesterol

Education Program (MS-NCEP) criteria in estimating future risk of all-cause and cardiovascular mortality

Postmenopausal women

60.4 +/-

7.1

557

8.5 +/- 0.3 years

N/A

Tsai, 2008[44]

Retrospective cohort

To assess the effect of a

single and a combination of "pre-disease" risk factors of metabolic syndrome on the overall and cardiac mortality.

civil servants

and teachers

40 years and

older

52.4 + -

8.0

35,259

median follow-up of 15 years

N/A

Upmeier, 2009[45]

Prospective cohort

To determine whether high levels of serum total

cholesterol and low levels of HDL are related to increased mortality in elderly

Home

dwelling older

adults residents in Finland

70 years

877

144 months

N/A

Valdivielso, 2009[46]

Prospective cohort

To study the prevalence, risk factors and vascular disease associated with moderate and sever HTG in an active

working population

Active

working

population of

Spain

36 ± 10 years

594,701

NR

documented prior medical

diagnosis of heart disease, cerebrovascular

disease or peripheral arterial disease

Wier, 2003[47]

Prospective cohort

To investigate the

relationship between triglyceride and stroke

outcome

nondiabetic

patients

presenting to

acute stroke

unit

Median

70 years

1310

mean 1195 days

N/A

UC/NR: unclear, not reported; TG: Triglycerides; HTG, hypertriglyceridemia; MI, myocardial infarction; DM, diabetes, BP, blood pressure, HTN, hypertension

Triglycerides Conversion: from mg/dL to mmol/L: multiply by (x) 0.01129; from mmol/L to mg/dL: multiply by (x) 88.6

Table 2

Quality of Included Studies

Study Label

Cohort Selection (sampling)

Outcome ascertainment*

Adjustments for variables

% lost to follow-up

Definition of hypertriglyceridemia

Acarturk, 2004[13]

not random; all patients

admitted for diagnostic

coronary angiography

chart review, angiography results

NR

NR

TG value in the blood was used

as a continuous number

(variable). OR expresses

increased risk per unit of serum

TG level

Bansal, 2007[14]

derived from women health study, previously completed randomized controlled trial of aspirin and vitamin E

chart review, events adjudicated by

an end point committee

adjusted for treatment

assignment to ASA,

vitamin E, beta

carotene, age, BP,

smoking status, and use

of hormone therapy,

levels of total

cholesterol and HDL-C,

history of DM, BMI,

high-sensitivity C-

reactive protein

0

TG value in the blood was used

as a continuous number

(variable). OR expresses increased risk per unit of serum TG level

Barrett-Connor, 1987[15]

random sample

chart review, ICD or billing codes,

death certificates

adjust by TG level, age,

BP, BMI, smoking

habit, DM, family

history of heart attack

0.5%

Compared normal to "borderline HTG", defined as TG between

240-500 mg/dL (2.7-5.65

mmol/L)

Bass, 1993[16]

subset of female participants

in the Lipid Research Clinics' Follow-up Study

chart review, annual checkups

Adjusted for age, HTN,

DM, smoking, history

of heart disease and

estrogen use

NR

Compared TG < 200 mg/dL

(< 2.25 mmol/L) to elevated 200

to 399 mg/dL (2.25 to 4.49

mmol/L) and high > 400 mg/dL (> 4.50 mmol/L)

Bonaventure, 2010[17]

not random and not consecutive: recruited from electoral rolls

Death certificates and autopsy

reports, ascertained the same way

in cases and controls

medical history of MI,

stroke, or peripheral

arterial disease, as well

as smoking and alcohol consumption status

(never, former, current),

excess weight, elevated

BP, DM, apolipoprotein

E (APOE) genotype,

low-dose aspirin intake, and lipid-lowering treatment

NR

They compared tertiles or

quintiles: TG < 83.4 mg/dL

(< 0.94), 84.2-117.8 mg/L (0.95-1.33), and > 118.7 mg/dL (1.34 mmol/L)

Carlson, 1988[18]

consecutive sample (all patients presenting with HTG)

chart review, ascertained the same

way in cases and controls, done

without knowledge of patients' TG

level

NR

13.4%

3 groups according to TG levels. Low = TG < 132.9 mg/dL (1.5 mmol/L), intermediate = TG

132.9-177.2 mg/dL (1.5-2.0 mmol/L), high = TG > 177.2 (2.0 mmol/L).

Chan, 2005[19]

not random;

consecutive patients with type 2 DM, not HPTG

chart review, death registry

Adjusted for sex

and age. stepwise linear regression with BMI,

WC, HbA1c, FPG and

HOMA as independent

variables and lipid

profile as dependent

variable

0

Unclear

Chester, 1995[20]

consecutive sample (all men presenting with HTG and are awaiting routine angioplasty)

chart review,

done without knowledge of

patients' TG level

The potential predictor

variables-that is, risk

factors assessed at

baseline angiography,

for adverse events were

analyzed using the

multiple logistic

regression models.

2

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: mmol/L

Czernichow, 2007[21]

consecutive sample

self report, chart review, ICD or

billing codes, ascertained

differently: self report in all

patients, however if a CVD event

was reported -- chart review and

ICD billing codes were reviewed

for those individuals only

Age

NR

Age-adjusted relative risk

correlate to one standard

deviation increase in TG levels

Drexel, 2005[22]

consecutive sample

follow up investigation after 2.3

years, Time and causes of death

were obtained from national

surveys, hospital records

age, sex, and use of

lipid-lowering

medication

0

Unclear

Eberly, 2003[23]

not random; likely consecutive sample: 2863 men with both nonfasting and fasting TG levels measured at screens 1 and 2

self report, chart review, ICD or

billing codes, death certificates

age, lipids subfractions,

glucose level, BP,

cigarettes smoked per

day, alcohol use, BMI

and race

0

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: mg/dL

Egger, 1999[24]

not random; likely consecutive sample: Participants of the Caerphilly Heart Disease Study

self report, chart review, ICD or

billing codes

age, all three lipid

factors, laboratory error

and within person

variation, blood

glucose and diastolic

BP, BMI, smoking and

markers for pre-existent

disease

12.5

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: mmol/L

Ellingsen, 2003[25]

not random; likely

consecutive sample: 1232

healthy men with elevated cholesterol or coronary risk

score included in the study

from a pool of 16202

screened men

chart review, ICD or billing codes, ascertained the same way in cases

and controls

adjusted for age, BMI,

cigarette smoking, total cholesterol,

triacylglycerol, glucose,

BP, dietary score,

alcohol intake, and

activity level

0

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: high TG > or = 178.1 mg/dL (2.01 mmol/L)

Gaziano, 1997[26]

not random, likely

consecutive sample:

Men/women < 76 yrs. age

with no prior history of CAD discharged from one of 6

Boston area hospitals with the diagnosis of confirmed MI

chart review, medical exam/lab

analysis,

ascertained differently: cases were interviewed 8 weeks after MI

Adjusted for age, sex,

history of HTN, history

of DM, body mass

index, type A

personality, family

history of previous MI,

alcohol consumption,

physical activity,

smoking, caloric intake

12

they compared quintiles, highest compared to lowest

Goldberg, 2009[27]

consecutive sample (all

patients presenting with HTG)

chart review, telephone calls,

ascertained the same way in cases

and controls

A time-to-event

regression model was

performed to establish

the role of baseline lipid subfractions, other

metabolic risk factors,

lifestyle variables, and demographic

characteristics in

relation to the development

of CAD.

3.8

high triglyceride level > = 248.1 mg/dL (2.8 mmol/L)

Habib, 2006[28]

Data from the United States Renal Data System database collected during the

prospective Dialysis

Morbidity and Mortality

Study Wave 2 study

chart review

age, gender, race,

weight, height, primary

cause of ESRD,

hemoglobin, serum

albumin, serum calcium phosphate product,

serum bicarbonate,

residual kidney

creatinine clearance, PD parameters (dialysate

effluent volume,

dialysis creatinine

clearance, D/P creatinine ratio after a 4 h dwell), use of lipid-modifying medications and comorbidity characteristics

0

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: HR is using a

reference of TG levels 200-300

mg/dl (2.2-3.4 mmol/L)

Haim, 1999[29]

not random; likely

consecutive sample

chart review, ICD or billing codes

age, previous MI, DM,

NYHA class, HTN,

LDL cholesterol,

glucose, chronic

obstructive pulmonary

disease, peripheral

vascular disease, stroke,

angina pectoris,

smoking, and lipids

0.37

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: mg/dL

Hoogeveen, 2001[30]

Random sample

chart review, clinical exam and investigations,

ascertained the same way in cases

and controls

Logistic regression

applied but no specific adjustments are

mentioned

12

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: 10 mg/dL (0.11 mmol/L)

Jonsdottir, 2002[31]

not random; likely

consecutive: subjects of the Reykjavik Study

self report, chart review, ICD or billing codes

age, high-density lipoprotein cholesterol, total/low-density lipoprotein cholesterol, smoking, body mass index and BP

0.6

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: mmol/L

Lamarche, 1995[32]

random sample

chart review, Examination/EKG/death certificate

Adjusted for age,

systolic BP, DM,

alcohol consumption,

and tobacco use

27

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: TG > 203.8 mg/dL (2.3 mmol/L)

Lloret Linares, 2008[33]

not random and not

consecutive: Patients referred

by their general practitioner

or general hospital for very

high TG levels to

Endocrinology Dept. between 2000 and 2005

self report, chart review

Adjusted for age at hospitalization

NR

TG: lowest 95.1-180 mg/dL

(1.1-2.0 mmol/L) vs. highest

360-1505 gm/dL (4.1-17

mmol/L).

Lu, 2003[34]

not random; likely

consecutive: cohort chosen

from the strong heart study to include only DM, no baseline CVD

through death certificates and tribal

and Indian Health Service hospital records and by direct contact of

study personnel with the study participants and their families

Adjusted for age, BMI,

smoking status, study

center, systolic BP,

HbA1c, fibrinogen,

insulin, and ratio of

albumin to creatinine

0

They compared tertiles or

quintiles: TG: lower < 111; 111-

175; higher > 175 mg/dL

(lower < 1.2; 1.2-2.0; higher > 2.0 mmol/L)

Malone, 2009[35]

Not random; likely

consecutive: Retrospective

data from 3 integrated health-care systems that

systematically collect

and store detailed patient-level data.

Chart review, ICD or billing codes

Adjusted for age, sex,

smoking status and site

N/A

lower/normal TG - 80.0 mg/dl

(0.9 mmol/L); higher TG - TG = 217.4 mg/dl (2.4 mmol/L)

Mazza, 2005[36]

random sample

chart review, ICD or billing codes, through the Register Office, general practitioners

Gender, age, DM,

obesity, lipids

subfractions, serum uric

acid, BP, smoking,

alcohol and proteinuria

0

They compared tertiles or

quintiles: TG: First (low) < 97.5 mg/dL (1.01 mmol/L); Fifth (high) > = 156.8 mg/dL (1.77 mmol/L)

Mora, 2008[37]

Random sample enrolled in

the Women's Health Study

Follow-up questionnaires every 6-

12 months

Adjusted for age,

randomized treatment assignment, smoking

status, menopausal

status, postmenopausal

hormone use, BP, DM,

and BMI

NR

They compared tertiles or

quintiles: TG: First (low) < 89.5 mg/dL (1.01 mmol/L); Fifth (high) > = 180.7 mg/dL (2.04 mmol/L)

Noda, 2010[38]

not random and not

consecutive: death related to a MI defined a case, then 2 controls were selected

randomly matched by age

Death registration from 1997-2000,

done without knowledge of

patients' TG level,

ascertained the same way in cases

and controls

Adjusted for age and 6

risk factors for MI

NR

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum TG level: High TG > = 150 mg/dL (1.7 mmoml/L)

Rubins, 1999[39]

not random and not

consecutive: to obtain

population with appropriate

lipid levels, a multi stage screening method that

included two lipid profiles obtained one week apart

chart review, clinical and radiologic

data, ascertained the same way in

cases and controls

Adjustment for baseline

variables in the Cox

models had a trivial

effect on the estimates

of the hazard ratios

2.3%

Two groups: TG < 150 mg/dl (1.7 mmol/L) and TG > 150 mg/dl (1.7 mmol/L)

Samuelsson, 1994[40]

random sample

chart review

traditional risk factors,

end-organ damage

status

NR

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: RR reported for every

88.6 mg/dL (1 mmol/L) increase

in TG level

Schupf, 2005[41]

random sample

self report, chart review,

interviewing relatives

Adjusted for age, sex,

ethnicity, and level of

education, for BMI or

APOE; a history of

HTN, DM, heart

disease, stroke, or

cancer; or current

smoking

0

They compared tertiles or

quintiles: Lowest - < = 98.9 mg/dl

(1.1 mmol/L), highest

- > 191.2 mg/dl (2.1 mmol/L); RR compared the lowest quartile to

the highest quartile.

Sprecher, 2000[42]

not random; likely

consecutive: diabetic patients undergoing primary isolated CABG between 1982 and

1992 at Cleveland Clinic

chart review, clinical exam, labs

and CVIR (Cardiovascular

Information Registry)

age, sex, left ventricular

function, coronary

anatomy, history of

HTN, BMI, and total

cholesterol

NR

highest quartile compared to

lower three quartiles (normal)

Tanko, 2005[43]

not random and not

consecutive:

recruited via a questionnaire surveys

self report, chart review: Central

Registry of the Danish Ministry of

Health

Adjusted for age,

smoking, and LDL-C),

waist circumference

NR

TG value in the blood was used

as a continuous number

(variable). Here OR expresses increased risk per unit of serum

TG level: presented as 2 cutoffs - > 128.5 mg/dL (1.45 mmol/L) - > 149.7 mg/dL (1.69 mmol/L)

Tsai, 2008[44]

not random; likely

consecutive:

civil servants and teachers

who took the annual physical examination at the Taipei Outpatient Center

chart review, annual exam, national

death files

Adjusted for age,

gender, fasting glucose,

BP, BMI, smoking

NR

They compared tertiles or

quintiles: TG

normal < 150 mg/dL (1.7

mmol/L, abnormal 150 mg/dL

(1.7 mmol/L)-199 mg/dL (2.2 mmol/L), and high abnormal

> 200 mg/dL (2.25 mmol/L)

Upmeier, 2009[45]

not random and not

consecutive:

mailed invitation to

participate to all residents of Turku born in 1920

Self report, chart review,

ICD or billing codes

Adjusted for gender,

body mass index,

smoking and any history

of angina pectoris,

stroke, DM, and HTN

NR

They compared TG level

quartiles, highest to lowest

Valdivielso, 2009[46]

not random; likely consecutive

Chart review and self report

age, sex, smoking,

HTN, DM, and lipids

fractions

NR

Categorized as normal when TG

was < 150 mg/dL (< 1.69

mmol/L); the remainder were considered to be HTG

Wier, 2003[47]

not random; likely

consecutive

chart review,

done without knowledge of

patients' TG level

age, time of resolution

of symptoms, smoking,

BP, presence of atrial

fibrillation and

hyperglycemia

0

They compared tertiles or

quintiles: TG, mmol/l: < = 0.9;

1.0-1.3; 1.4-1.8; > = 1.9.

Mg/dL: < = 79.7; 88.6-115.2;

124.0-159.5; > = 168.3

UC/NR: unclear, not reported; TG: Triglycerides; HTG, hypertriglyceridemia; MI, myocardial infarction; DM, diabetes, BP, blood pressure, HTN, hypertension

* It was unclear in most studies if enrolled patients did not have the outcomes pre-existent at baseline. In most studies, it was also unclear if patients were treated with drugs that can affect TG level (both of these elements lower the observed strength of association)

Triglycerides Conversion from mg/dL to mmol/L: multiply by (x) 0.01129; from mmol/L to mg/dL: multiply by (x) 88.6

Meta-analysis

The total number of included studies was 35 enrolling 927,218 patients who suffered 132,460 deaths and 72,654 cardiac events; respectively. Hypertriglyceridemia was significantly associated with cardiovascular death, cardiovascular events, myocardial infarction, and pancreatitis; with odds ratios (95% confidence interval) of 1.80 (1.31-2.49), 1.37 (1.23-1.53), 1.31 (1.15-1.49) and 3.96 (1.27-12.34); respectively. There was nonsignificant association with all-cause mortality (OR: 1.10; 95% CI: 0.90-1.36). Forest plots depicting the results of random effects meta-analysis are presented in Figures 2, 3, 4 and 5.
https://static-content.springer.com/image/art%3A10.1186%2F1472-6823-12-2/MediaObjects/12902_2012_Article_123_Fig2_HTML.jpg
Figure 2

Random effects meta-analysis (all-cause mortality).

https://static-content.springer.com/image/art%3A10.1186%2F1472-6823-12-2/MediaObjects/12902_2012_Article_123_Fig3_HTML.jpg
Figure 3

Random effects meta-analysis (cardiovascular death).

https://static-content.springer.com/image/art%3A10.1186%2F1472-6823-12-2/MediaObjects/12902_2012_Article_123_Fig4_HTML.jpg
Figure 4

Random effects meta-analysis (cardiac events).

https://static-content.springer.com/image/art%3A10.1186%2F1472-6823-12-2/MediaObjects/12902_2012_Article_123_Fig5_HTML.jpg
Figure 5

Random effects meta-analysis (myocardial infarction).

It is worth noting that the association with acute pancreatitis was estimated by only one eligible study that included 129 patients with severe hypertriglyceridemia (119 with type IV phenotypes and 10 with type V phenotypes according to Fredrickson's classification) of whom 26 suffered acute pancreatitis [33]. In this study, subjects in the third tertile of TG had a 4.0-fold increased risk (95% confidence interval, 1.3-12.3) compared with the first tertile and those diagnosed with dyslipidemia at a younger age also had increased risk.

All analyses were associated with important heterogeneity (I 2 > 50%) that our planned subgroup analyses could only partially explain (Table 3). The association of hypertriglyceridemia with mortality and cardiovascular mortality seemed to be stronger in women. These findings are consistent with a previous meta-analysis published in 1996. Hokanson and Austin estimated adjusted relative risks for incident cardiovascular events of 1.14 (95% Cl 1.05-1.28) in men and 1.37 (95% Cl 1.13-1.66) in women. The association with cardiovascular events was somewhat stronger in patients with diabetes although this effect was not statistically significant. Hence, there were no other significant subgroup interactions to explain heterogeneity (based on the level of adjustment for lipids subfractions, sex or the presence of diabetes).
Table 3

Subgroup analysis

Subgroup

No.

studies

OR

LL

UL

P-effect

Size

P-

interaction

Mortality

Men

3

1.03

0.95

1.12

0.49

0.04

Women

3

1.55

1.05

2.27

0.03

 

adequate adjustment

9

1.09

0.83

1.43

0.55

0.54

inadequate adjustment

3

1.22

0.94

1.59

0.14

 

General population

10

1.09

0.87

1.37

0.46

0.49

Diabetes

2

1.37

0.75

2.50

0.31

 

Cardiovascular death

Men

3

1.14

0.92

1.40

0.23

0.00

Women

2

4.73

2.15

10.37

0.00

 

adequate adjustment

5

1.88

1.12

3.15

0.02

0.84

inadequate adjustment

4

1.76

1.18

2.62

0.01

 

General population

8

1.75

1.26

2.43

0.00

0.36

Diabetes

1

2.97

1.00

8.80

0.05

 

Cardiovascular events

Men

6

1.29

1.13

1.47

0.00

0.67

Women

2

1.21

0.94

1.57

0.14

 

adequate adjustment

12

1.39

1.23

1.58

0.00

0.91

inadequate adjustment

4

1.37

1.01

1.84

0.04

 

General population

15

1.37

1.22

1.54

0.00

0.81

Diabetes

1

1.42

1.11

1.81

0.00

 

Myocardial infarction

Men

2

1.22

1.09

1.37

0.00

0.24

Women

1

1.40

1.15

1.70

0.00

 

adequate adjustment

3

1.72

0.98

3.01

0.06

0.29

inadequate adjustment

3

1.26

1.15

1.39

0.00

 

General population

5

1.27

1.13

1.44

0.00

0.13

Diabetes

1

2.04

1.12

3.70

0.02

 

*Only feasible analyses are shown

There was no evidence of publication bias (P value for Eggers test > 0.05 for all outcomes) although these analyses were underpowered to detect this problem and the presence of heterogeneity further limits the ability to detect publication bias.

Discussion

We conducted a systematic review and meta-analysis and documented an association between fasting hypertriglyceridemia and the risk of several cardiovascular adverse events and with pancreatitis.

Limitations, strengths and comparison with other reports

The main limitation of association studies is the observational nature of the existing evidence. Therefore, confounders (particularly, baseline risk of patients for developing cardiovascular disease and the effect of other lipid subfractions abnormalities) threaten the validity of results. In meta-analyses of observational studies, the ability to adjust for confounding is limited by the level of adjustment conducted in the original studies. We attempted to evaluate confounding by conducting subgroup analysis; however, this analysis was underpowered. Other limitations pertain to heterogeneity of the meta-analytic estimates, publication bias (which remains likely in the context of observational studies that do not require prospective registration) and reporting bias (which is also likely considering that several studies met the eligibility criteria for this review but did not report the outcomes of interest) [48]. It was unclear in most studies if enrolled patients did not have some of the outcomes pre-existent at baseline and it was also unclear if patients were treated with drugs that can affect TG level (both of these elements lower the confidence in the observed associations). We only found one controlled study that evaluated the association with acute pancreatitis.

The overall confidence in the estimated magnitude of associations is low [10]considering the described methodological limitations in evaluating the association with cardiovascular events; and imprecision (small number of events) in evaluating the association with pancreatitis.

The strengths of this study stems from the comprehensive literature search that spans across multiple databases and duplicate appraisal and study selection. Our results are consistent with previous evidence synthesis reports about the association of hypertriglyceridemia with cardiovascular events. We estimated increased odds by 37% (odds ratio of 1.37). Hokanson and Austin [3] estimated adjusted relative risks of 1.14 (95% Cl 1.05-1.28) in men and 1.37 (95% Cl 1.13-1.66) in women. Sarwar et al. [2] reported odds ratio of 1.73 in prospective cohort studies published prior to 2006. A systematic review by Labreuche et al. [49] demonstrated that baseline triglyceride levels in randomized trials is associated with increased stroke risk (adjusted RR, 1.05 per 10-mg/dL (0.1 mmol/L) increase; 95% CI, 1.03-1.07). To our knowledge, this is the first systematic review that sought to identify controlled studies evaluating the association with pancreatitis.

Implications

The associations demonstrated between hypertriglyceridemia and cardiovascular risk should not necessarily translate into a recommendation for treatment. It is plausible that the benefits of lowering triglycerides do not merely depend on how much the level is lowered, but rather on how it is lowered (i.e., lifestyle interventions vs. pharmacological therapy). Therefore, randomized trials of the different approaches with patient-important outcomes [50] used as primary endpoints are needed for making policy and clinical decisions.

Several systematic reviews and meta-analyses [49, 5154] have summarized the evidence from randomized trials of fibrate therapy and demonstrated that fibrate therapy reduced the risk of vascular events (RR 0.75, 95% CI 0.65 to 0.86) in patients with high triglyceride levels or atherogenic dyslipidemia (low HDL cholesterol combined with high triglyceride level) although all-cause mortality and non cardiovascular mortality were both significantly increased in clofibrate trials. Meta-analyses [55, 56] of niacin therapy demonstrate significant reduction in the risk of major coronary events (25% reduction in relative odds; 95% CI 13, 35), stroke (26%; 95% CI 8, 41) and any cardiovascular events (27%; 95% CI 15, 37). However, contemporary trials in the statin era have failed to substantiate these findings with fenofibrate among patients with diabetes [57] and with niacin in high risk patients [58]. Also, to our knowledge, there are no trials assessing the value of triglyceride lowering to reduce the risk of pancreatitis. Thus, lifestyle changes should remain the mainstay of therapy. Treatment of the underlying metabolic disorder (e.g., insulin resistance) should also be an essential and first step in the management plan of hypertriglyceridemia.

Conclusions

The current evidence suggests that hypertriglyceridemia is associated with increased risk of cardiovascular death, MI, cardiovascular events, and acute pancreatitis. The strength of inference is limited by the unexplained inconsistency of results and high risk of confounding and publication bias.

Declarations

Acknowledgements

This review was funded by a contract from the Endocrine Society. The funder had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the manuscript; and in the decision to submit the manuscript for publication.

Disclosure statement

MM, AH, FC, SD, SG, IB, ML, LB and VM have nothing to declare.

Financial support

This review was funded by a contract from the Endocrine Society.

Authors’ Affiliations

(1)
Knowledge and Evaluation Research Unit, Mayo Clinic
(2)
Division of Preventive Medicine, Mayo Clinic
(3)
Department of Internal Medicine, University of North Dakota
(4)
Davis and the VA Northern California Health Care System, University of California
(5)
Division of Endocrinology, Diabetes, Metabolism, Nutrition, Mayo Clinic

References

  1. Ford ES, Li C, Zhao G, Pearson WS, Mokdad AH: Hypertriglyceridemia and its pharmacologic treatment among US adults. Arch Intern Med. 2009, 169 (6): 572-578. 10.1001/archinternmed.2008.599.View ArticlePubMedGoogle Scholar
  2. Sarwar N, Danesh J, Eiriksdottir G, Sigurdsson G, Wareham N, Bingham S, Boekholdt SM, Khaw KT, Gudnason V: Triglycerides and the risk of coronary heart disease: 10,158 incident cases among 262,525 participants in 29 Western prospective studies. Circulation. 2007, 115 (4): 450-458. 10.1161/CIRCULATIONAHA.106.637793.View ArticlePubMedGoogle Scholar
  3. Hokanson JE, Austin MA: Plasma triglyceride level is a risk factor for cardiovascular disease independent of high-density lipoprotein cholesterol level: a meta-analysis of population-based prospective studies. J Cardiovasc Risk. 1996, 3 (2): 213-219. 10.1097/00043798-199604000-00014.View ArticlePubMedGoogle Scholar
  4. Patel A, Barzi F, Jamrozik K, Lam TH, Ueshima H, Whitlock G, Woodward M: Serum triglycerides as a risk factor for cardiovascular diseases in the Asia-Pacific region. Circulation. 2004, 110 (17): 2678-2686.View ArticlePubMedGoogle Scholar
  5. Toskes PP: Hyperlipidemic pancreatitis. Gastroenterol Clin North Am. 1990, 19 (4): 783-791.PubMedGoogle Scholar
  6. Brunzell JD, Schrott HG: The interaction of familial and secondary causes of hypertriglyceridemia: role in pancreatitis. Trans Assoc Am Physicians. 1973, 86: 245-254.PubMedGoogle Scholar
  7. Familial lipoprotein lipase deficiency, ApoC-II deficiency, and hepatic lipase deficiency. The Metabolic Basis of Inherited Disease. Edited by: Scriver C, Beaudet A, Sly W, Valle D, Brunzell J, Deeb SI. 2001, New York: McGraw-Hill, 2789-2816. 8
  8. Moher D, Liberati A, Tetzlaff J, Altman DG: Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009, 6 (7): e1000097-10.1371/journal.pmed.1000097.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Wells G, Shea B, O'Connell D, Peterson J, Welch V, Losos M, Tugwell P: The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Ottawa Hospital Research Institute.
  10. Swiglo BA, Murad MH, Schunemann HJ, Kunz R, Vigersky RA, Guyatt GH, Montori VM: A case for clarity, consistency, and helpfulness: state-of-the-art clinical practice guidelines in endocrinology using the grading of recommendations, assessment, development, and evaluation system. J Clin Endocrinol Metab. 2008, 93 (3): 666-673.View ArticlePubMedGoogle Scholar
  11. DerSimonian R, Laird N: Meta-analysis in clinical trials. Control Clin Trials. 1986, 7 (3): 177-188. 10.1016/0197-2456(86)90046-2.View ArticlePubMedGoogle Scholar
  12. Egger M, Davey Smith G, Schneider M, Minder Minder C: Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997, 315 (7109): 629-634. 10.1136/bmj.315.7109.629.View ArticlePubMedPubMed CentralGoogle Scholar
  13. Acarturk E, Cayli M, Akpinar O, Attila G, Demir M: Relation between age and gender differences in plasma triglyceride concentrations and coronary artery disease in Southern Turkey. Clin Chim Acta. 2004, 339 (1-2): 123-128. 10.1016/j.cccn.2003.10.001.View ArticlePubMedGoogle Scholar
  14. Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM: Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA. 2007, 298 (3): 309-316. 10.1001/jama.298.3.309.View ArticlePubMedGoogle Scholar
  15. Barrett-Connor E, Khaw KT: Borderline fasting hypertriglyceridemia: absence of excess risk of all-cause and cardiovascular disease mortality in healthy men without hypercholesterolemia. Prev Med. 1987, 16 (1): 1-8. 10.1016/0091-7435(87)90001-6.View ArticlePubMedGoogle Scholar
  16. Bass KM, Newschaffer CJ, Klag MJ, Bush TL: Plasma lipoprotein levels as predictors of cardiovascular death in women. Arch Intern Med. 1993, 153 (19): 2209-2216. 10.1001/archinte.1993.00410190045006.View ArticlePubMedGoogle Scholar
  17. Bonaventure A, Kurth T, Pico F, Barberger-Gateau P, Ritchie K, Stapf C, Tzourio C: Triglycerides and risk of hemorrhagic stroke vs. ischemic vascular events: the three-city study. Atherosclerosis. 2010, 210 (1): 243-248. 10.1016/j.atherosclerosis.2009.10.043.View ArticlePubMedGoogle Scholar
  18. Carlson LA, Rosenhamer G: Reduction of mortality in the Stockholm ischaemic heart disease secondary prevention study by combined treatment with clofibrate and nicotinic acid. Acta Med Scand. 1988, 223 (5): 405-418.View ArticlePubMedGoogle Scholar
  19. Chan WB, Tong PC, Chow CC, So WY, Ng MC, Ma RC, Osaki R, Cockram CS, Chan JC: Triglyceride predicts cardiovascular mortality and its relationship with glycaemia and obesity in Chinese type 2 diabetic patients. Diabetes Metab Res Rev. 2005, 21 (2): 183-188. 10.1002/dmrr.497.View ArticlePubMedGoogle Scholar
  20. Chester M, Chen L, Kaski JC: Identification of patients at high risk for adverse coronary events while awaiting routine coronary angioplasty. Br Heart J. 1995, 73 (3): 216-222. 10.1136/hrt.73.3.216.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Czernichow S, Bruckert E, Bertrais S, Galan P, Hercberg S, Oppert JM: Hypertriglyceridemic waist and 7.5-year prospective risk of cardiovascular disease in asymptomatic middle-aged men. Int J Obes (Lond). 2007, 31 (5): 791-796.Google Scholar
  22. Drexel H, Aczel S, Marte T, Benzer W, Langer P, Moll W, Saely CH: Is atherosclerosis in diabetes and impaired fasting glucose driven by elevated LDL cholesterol or by decreased HDL cholesterol?. Diabetes Care. 2005, 28 (1): 101-107. 10.2337/diacare.28.1.101.View ArticlePubMedGoogle Scholar
  23. Eberly LE, Stamler J, Neaton JD: Relation of triglyceride levels, fasting and nonfasting, to fatal and nonfatal coronary heart disease. Arch Intern Med. 2003, 163 (9): 1077-1083. 10.1001/archinte.163.9.1077.View ArticlePubMedGoogle Scholar
  24. Egger M, Smith GD, Pfluger D, Altpeter E, Elwood PC: Triglyceride as a risk factor for ischaemic heart disease in British men: effect of adjusting for measurement error. Atherosclerosis. 1999, 143 (2): 275-284. 10.1016/S0021-9150(98)00300-1.View ArticlePubMedGoogle Scholar
  25. Ellingsen I, Hjermann I, Abdelnoor M, Hjerkinn EM, Tonstad S: Dietary and antismoking advice and ischemic heart disease mortality in men with normal or high fasting triacylglycerol concentrations: a 23-y follow-up study. Am J Clin Nutr. 2003, 78 (5): 935-940.PubMedGoogle Scholar
  26. Gaziano JM, Hennekens CH, O'Donnell CJ, Breslow JL, Buring JE: Fasting triglycerides, high-density lipoprotein, and risk of myocardial infarction. Circulation. 1997, 96 (8): 2520-2525.View ArticlePubMedGoogle Scholar
  27. Goldberg RJ, Urowitz MB, Ibanez D, Nikpour M, Gladman DD: Risk factors for development of coronary artery disease in women with systemic lupus erythematosus. J Rheumatol. 2009, 36 (11): 2454-2461. 10.3899/jrheum.090011.View ArticlePubMedGoogle Scholar
  28. Habib AN, Baird BC, Leypoldt JK, Cheung AK, Goldfarb-Rumyantzev AS: The association of lipid levels with mortality in patients on chronic peritoneal dialysis. Nephrol Dial Transplant. 2006, 21 (10): 2881-2892. 10.1093/ndt/gfl272.View ArticlePubMedGoogle Scholar
  29. Haim M, Benderly M, Brunner D, Behar S, Graff E, Reicher-Reiss H, Goldbourt U: Elevated serum triglyceride levels and long-term mortality in patients with coronary heart disease: the Bezafibrate Infarction Prevention (BIP) registry. Circulation. 1999, 100 (5): 475-482.View ArticlePubMedGoogle Scholar
  30. Hoogeveen RC, Gambhir JK, Gambhir DS, Kimball KT, Ghazzaly K, Gaubatz JW, Vaduganathan M, Rao RS, Koschinsky M, Morrisett JD: Evaluation of Lp[a] and other independent risk factors for CHD in Asian Indians and their USA counterparts. J Lipid Res. 2001, 42 (4): 631-638.PubMedGoogle Scholar
  31. Jonsdottir LS, Sigfusson N, Guonason V, Sigvaldason H, Thorgeirsson G: Do lipids, blood pressure, diabetes, and smoking confer equal risk of myocardial infarction in women as in men? The Reykjavik study. J Cardiovasc Risk. 2002, 9 (2): 67-76. 10.1097/00043798-200204000-00001.View ArticlePubMedGoogle Scholar
  32. Lamarche B, Despres JP, Moorjani S, Cantin B, Dagenais GR, Lupien PJ: Prevalence of dyslipidemic phenotypes in ischemic heart disease (prospective results from the Quebec Cardiovascular study). Am J Cardiol. 1995, 75 (17): 1189-1195. 10.1016/S0002-9149(99)80760-7.View ArticlePubMedGoogle Scholar
  33. Lloret Linares C, Pelletier AL, Czernichow S, Vergnaud AC, Bonnefont-Rousselot D, Levy P, Ruszniewski P, Bruckert E: Acute pancreatitis in a cohort of 129 patients referred for severe hypertriglyceridemia. Pancreas. 2008, 37 (1): 12-13.Google Scholar
  34. Lu W, Resnick HE, Jablonski KA, Jones KL, Jain AK, Howard WMJ, Robbins DC, Howard BV: Non-HDL cholesterol as a predictor of cardiovascular disease in type 2 diabetes: The strong heart study. Diabetes Care. 2003, 26 (1): 16-23. 10.2337/diacare.26.1.16.View ArticlePubMedGoogle Scholar
  35. Malone DC, Boudreau DM, Nichols GA, Raebel MA, Fishman PA, Feldstein AC, Ben-Joseph RH, Okamoto LJ, Boscoe AN, Magid DJ: Association of cardiometabolic risk factors and prevalent cardiovascular events. Metab Syndr Relat Disord. 2009, 7 (6): 585-593. 10.1089/met.2009.0033.View ArticlePubMedGoogle Scholar
  36. Mazza A, Tikhonoff V, Schiavon L, Casiglia E: Triglycerides + high-density-lipoprotein-cholesterol dyslipidaemia, a coronary risk factor in elderly women: the CArdiovascular STudy in the ELderly. Intern Med J. 2005, 35 (10): 604-610. 10.1111/j.1445-5994.2005.00940.x.View ArticlePubMedGoogle Scholar
  37. Mora S, Rifai N, Buring JE, Ridker PM: Fasting compared with nonfasting lipids and apolipoproteins for predicting incident cardiovascular events. Circulation. 2008, 118 (10): 993-1001. 10.1161/CIRCULATIONAHA.108.777334.View ArticlePubMedPubMed CentralGoogle Scholar
  38. Noda H, Maruyama K, Iso H, Dohi S, Terai T, Fujioka S, Goto K, Horie S, Nakano S, Hirobe K: Prediction of myocardial infarction using coronary risk scores among Japanese male workers: 3M study. J Atheroscler Thromb. 2010, 17 (5): 452-459. 10.5551/jat.3277.View ArticlePubMedGoogle Scholar
  39. Rubins HB, Robins SJ, Collins D, Fye CL, Anderson JW, Elam MB, Faas FH, Linares E, Schaefer EJ, Schectman G: Gemfibrozil for the secondary prevention of coronary heart disease in men with low levels of high-density lipoprotein cholesterol. Veterans Affairs High-Density Lipoprotein Cholesterol Intervention Trial Study Group. N Engl J Med. 1999, 341 (6): 410-418. 10.1056/NEJM199908053410604.View ArticlePubMedGoogle Scholar
  40. Samuelsson O, Hedner T, Persson B, Andersson O, Berglund G, Wilhelmesen L: The role of diabetes mellitus and hypertriglyceridaemia as coronary risk factors in treated hypertension: 15 years of follow-up of antihypertensive treatment in middle-aged men in the Primary Prevention Trial in Goteborg, Sweden. J Intern Med. 1994, 235 (3): 217-227. 10.1111/j.1365-2796.1994.tb01063.x.View ArticlePubMedGoogle Scholar
  41. Schupf N, Costa R, Luchsinger J, Tang MX, Lee JH, Mayeux R: Relationship between plasma lipids and all-cause mortality in nondemented elderly. J Am Geriatr Soc. 2005, 53 (2): 219-226. 10.1111/j.1532-5415.2005.53106.x.View ArticlePubMedGoogle Scholar
  42. Sprecher DL, Pearce GL, Park EM, Pashkow FJ, Hoogwerf BJ: Preoperative triglycerides predict post-coronary artery bypass graft survival in diabetic patients: a sex analysis. Diabetes Care. 2000, 23 (11): 1648-1653. 10.2337/diacare.23.11.1648.View ArticlePubMedGoogle Scholar
  43. Tanko LB, Bagger YZ, Qin G, Alexandersen P, Larsen PJ, Christiansen C: Enlarged waist combined with elevated triglycerides is a strong predictor of accelerated atherogenesis and related cardiovascular mortality in postmenopausal women. Circulation. 2005, 111 (15): 1883-1890. 10.1161/01.CIR.0000161801.65408.8D.View ArticlePubMedGoogle Scholar
  44. Tsai SP, Wen CP, Chan HT, Chiang PH, Tsai MK, Cheng TY: The effects of pre-disease risk factors within metabolic syndrome on all-cause and cardiovascular disease mortality. Diabetes Res Clin Pract. 2008, 82 (1): 148-156. 10.1016/j.diabres.2008.07.016.View ArticlePubMedGoogle Scholar
  45. Upmeier E, Lavonius S, Lehtonen A, Viitanen M, Isoaho H, Arve S: Serum lipids and their association with mortality in the elderly: A prospective cohort study. Aging Clin Exp Res. 2009, 21 (6): 424-430.View ArticlePubMedGoogle Scholar
  46. Valdivielso P, Sanchez-Chaparro MA, Calvo-Bonacho E, Cabrera-Sierra M, Sainz-Gutierrez JC, Fernandez-Labandera C, Fernandez-Meseguer A, Quevedo-Aguado L, Moraga MR, Galvez-Moraleda A: Association of moderate and severe hypertriglyceridemia with obesity, diabetes mellitus and vascular disease in the Spanish working population: results of the ICARIA study. Atherosclerosis. 2009, 207 (2): 573-578. 10.1016/j.atherosclerosis.2009.05.024.View ArticlePubMedGoogle Scholar
  47. Weir CJ, Sattar N, Walters MR, Lees KR: Low triglyceride, not low cholesterol concentration, independently predicts poor outcome following acute stroke. Cerebrovasc Dis. 2003, 16 (1): 76-82. 10.1159/000070119.View ArticlePubMedGoogle Scholar
  48. Furukawa TA, Watanabe N, Omori IM, Montori VM, Guyatt GH: Association between unreported outcomes and effect size estimates in Cochrane meta-analyses. JAMA. 2007, 297 (5): 468-470.View ArticlePubMedGoogle Scholar
  49. Labreuche J, Deplanque D, Touboul PJ, Bruckert E, Amarenco P: Association between change in plasma triglyceride levels and risk of stroke and carotid atherosclerosis: systematic review and meta-regression analysis. Atherosclerosis. 2010, 212 (1): 9-15. 10.1016/j.atherosclerosis.2010.02.011.View ArticlePubMedGoogle Scholar
  50. Gandhi GY, Murad MH, Fujiyoshi A, Mullan RJ, Flynn DN, Elamin MB, Swiglo BA, Isley WL, Guyatt GH, Montori VM: Patient-important outcomes in registered diabetes trials. JAMA. 2008, 299 (21): 2543-2549. 10.1001/jama.299.21.2543.View ArticlePubMedGoogle Scholar
  51. Bruckert E, Labreuche J, Deplanque D, Touboul PJ, Amarenco P: Fibrates effect on cardiovascular risk is greater in patients with high triglyceride levels or atherogenic dyslipidemia profile: a systematic review and meta-analysis. J Cardiovasc Pharmacol. 2011, 57 (2): 267-272. 10.1097/FJC.0b013e318202709f.View ArticlePubMedGoogle Scholar
  52. Loomba RS, Arora R: Prevention of cardiovascular disease utilizing fibrates-a pooled meta-analysis. Am J Ther. 2010, 17 (6): e182-e188. 10.1097/MJT.0b013e3181dcf72b.View ArticlePubMedGoogle Scholar
  53. Jun M, Foote C, Lv J, Neal B, Patel A, Nicholls SJ, Grobbee DE, Cass A, Chalmers J, Perkovic V: Effects of fibrates on cardiovascular outcomes: a systematic review and meta-analysis. Lancet. 2010, 375 (9729): 1875-1884. 10.1016/S0140-6736(10)60656-3.View ArticlePubMedGoogle Scholar
  54. Lee M, Saver JL, Towfighi A, Chow J, Ovbiagele B: Efficacy of fibrates for cardiovascular risk reduction in persons with atherogenic dyslipidemia: A meta-analysis. Atherosclerosis. 2011Google Scholar
  55. Bruckert E, Labreuche J, Amarenco P: Meta-analysis of the effect of nicotinic acid alone or in combination on cardiovascular events and atherosclerosis. Atherosclerosis. 2010, 210 (2): 353-361. 10.1016/j.atherosclerosis.2009.12.023.View ArticlePubMedGoogle Scholar
  56. Duggal JK, Singh M, Attri N, Singh PP, Ahmed N, Pahwa S, Molnar J, Singh S, Khosla S, Arora R: Effect of niacin therapy on cardiovascular outcomes in patients with coronary artery disease. J Cardiovasc Pharmacol Ther. 2010, 15 (2): 158-166. 10.1177/1074248410361337.View ArticlePubMedGoogle Scholar
  57. Chew EY, Ambrosius WT, Davis MD, Danis RP, Gangaputra S, Greven CM, Hubbard L, Esser BA, Lovato JF, Perdue LH: Effects of medical therapies on retinopathy progression in type 2 diabetes. N Engl J Med. 2010, 363 (3): 233-244.View ArticlePubMedGoogle Scholar
  58. AIM-HIGH Investigators: The role of niacin in raising high-density lipoprotein cholesterol to reduce cardiovascular events in patients with atherosclerotic cardiovascular disease and optimally treated low-density lipoprotein cholesterol Rationale and study design. The Atherothrombosis Intervention in Metabolic syndrome with low HDL/high triglycerides: Impact on Global Health outcomes (AIM-HIGH). Am Heart J. 2011, 161 (3): 471-477. e472View ArticleGoogle Scholar
  59. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6823/12/2/prepub

Copyright

© Murad et al; licensee BioMed Central Ltd. 2012

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement