Table Of ContentPapaetal.CardiovascularDiabetology2013,12:20 CARDIO
http://www.cardiab.com/content/12/1/20 VASCULAR
DIABETOLOGY
ORIGINAL INVESTIGATION Open Access
Macrovascular complication phenotypes in type 2
diabetic patients
Giuseppe Papa*, Claudia Degano, Maria P Iurato, Carmelo Licciardello, Raffaella Maiorana
and Concetta Finocchiaro
Abstract
Background: Macrovasculardiseases(MVD)intype2diabetesmellitus(T2DM)areoftenconsideredalltogether,
withoutdiscriminatingtheareasinvolved.TheaimofourstudywastoanalyseMVDprevalenceinalargepopulation
ofT2DMpatientsbydividingthecasesintosubgroupsaccordingtoMVDsites(NMVD,noMVD;NSCS,non-significant
carotidstenosis;CBVD,cerebrovasculardisease;CAD,coronaryarterydisease;PAD,peripheralarterydisease;PVD,
polyvasculardisease)andstudyingtheanthropometric,clinicalandlaboratoryparametersineachgroup.
Methods:Adiabeticoutpatientcohort(n=1199)wasretrospectivelystudied.Demographic,clinicalandlaboratory
parameterswereincludedinanalyses.Athoroughcardiovascularhistoryasdocumentedbypreviousmedicalrecords
(includingmedicalandhospitalrecords)andvascularlaboratorystudies(includingstandardisedelectrocardiogram,
echocardiogram,provocativetestsforcardiacischaemia,ankle/brachialindex,duplexultrasonographyofthecarotid
andlowerlimbsand,inselectedcases,computedtomographyangiography,carotidandperipheralarteriographyand
evaluationoftranscutaneousoxygenpressure),wascollectedforallofthepatients.Standardisedprocedureswere
usedtoassessmicrovascularcomplicationsaswellasmetabolicsyndrome(Mets).
Results:TheunadjustedMVDprevalencewas46.4%amongtheparticipants.ThemajorityofpatientswithMVDwere
inthePVDgroup.Inthemultivariateanalysis,age,malesexanddiabetesdurationwereindependentriskfactorsfor
PADandPVD(P<0.01).AlowHDL-CvaluewasanindependentriskfactorintheCADandPVDgroups(P=0.03).Very
highfrequenciesofMetSwereobservedinthePADandPVDgroups(94.9and95.7%respectively).ThemostMetS
diagnosticcriteriawererecordedamongmembersoftheCADgroup(allorall-1criteriawerepresentin73%of
patients).TheaverageageintheCADgroup(64.5y)wascomparabletothatoftheNMVDgroup.Microvascular
complicationsweremorefrequentinthePADandPVDpatients.
Conclusion:PhenotypicheterogeneityisassociatedwithdifferentmacrovascularcomplicationsinT2DMpatients.These
findingsmighthaveclinicalimplicationsfordevelopingdiagnosticandtherapeuticstrategiestargetingtype2diabetes.
Keywords:Type2diabetesmellitus,Macrovasculardisease,Cardiovascularriskfactors,Metabolicsyndrome
Background describing cardiovascular disease in diabetic patients, the
Cardiovascularcomplicationsaretheleadingcauseofmor- patient population is lumped together as a heterogeneous
bidity and mortality among patients with type 2 diabetes, group with CVD, without separation into subgroups ac-
andcardiovasculardisease(CVD)riskis2-to8-foldhigher cording to the macrovascular disease type. Furthermore
inthediabetic populationthan it isinnon-diabeticindivi- multiplevascularsitesareoftensimultaneouslyinvolvedin
dualsofasimilarage,sexandethnicity[1,2].Furthermore, type 2 diabetic patients, which contributes to the highest
macrovascularcomplicationsarethelargestcontributorto cardiovascular risk in this population. To the best of our
thedirectandindirectcostsofdiabetes[3].However,when knowledge, no extensive clinical studies of type 2 diabetic
subjects have stratified patients according to their macro-
vascularcomplications.Theaimofourretrospectivestudy
*Correspondence:[email protected] was to evaluate macrovascular disease in a large cohort of
UnitofMetabolicandEndocrineDiseases,“CentroCatanesediMedicinae type 2 diabetic adults by dividing the subjects into several
Chirurgia”Clinic,viaBattello48,Catania95126,Italy
©2013Papaetal.;licenseeBioMedCentralLtd.ThisisanOpenAccessarticledistributedunderthetermsoftheCreative
CommonsAttributionLicense(http://creativecommons.org/licenses/by/2.0),whichpermitsunrestricteduse,distribution,and
reproductioninanymedium,providedtheoriginalworkisproperlycited.
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subgroups according to the vascular areas that were in- pressure ≥130/85 mmHg or receiving blood pressure re-
volved. We also studied differences between these sub- ductiontreatment.
groups in their anthropometric, clinical and laboratory
characteristics,aswellastheirMetSprevalence/severity. Macrovascularcomplicationevaluation
A thorough cardiovascular history, as documented by pre-
Methods vious medical records (including medical and hospital
Subjects records)andvascularlaboratorystudies(includingstandar-
In this observational, cross-sectional survey, we studied dised electrocardiogram, echocardiogram, ankle/brachial
1199 subjects with type 2 diabetes who had been referred index, duplex ultrasonography (DUS) of the carotid and
to us by general practitioners or other specialists for dia- lower limbs and provocative tests for cardiac ischaemia),
betes management and/or chronic complication assess- wascollectedforallofthepatients.
ment between January 1, 2008 and January 1, 2011. The
subjects were divided into 6 subgroups: NMVD, no Non-significantcarotidstenosis(NSSC)diagnosis
macrovascular disease; NSCS, non-significant carotid ste- Asymptomatic patients with 50-69% carotid stenosis in
nosis; CBVD, cerebrovascular disease; CAD, coronary any section as detected by DUS were diagnosed with
artery disease; PAD, peripheral artery disease; and PVD, NSSC.
polyvasculardisease.Thedatawerecollectedfromadiag-
nosticDay-Hospitalinourcentreandwereretrospectively Cerebrovasculardisease(CBVD)diagnosis
analysed. The exclusion criteria were as follows: acute ill- Patients with a history of TIA, previous stroke (as con-
nesses, advanced renal disease (creatinine clearance ≤15 firmed by CT/MRI brain scan), or previous significant/
ml/min or dialysis), chronic active hepatitis (liver transa- symptomatic carotid stenosis (patients had undergone
minases ≥2 times higher than the normal range and/or surgical or endoluminal interventions) were diagnosed
positive viral hepatitis B or C serology), or glucocorticoid withCBVD. However,asymptomaticpatientswithsignifi-
therapy.Thelocalethicscommitteeapprovedthestudy. cant stenosis (≥70% in any section as detected by DUS
and confirmed by computed tomography angiography
Clinicalandlaboratorymeasurements (CTA)) were also included in this group. Patients who
Body weight was measured in light clothing without were undergoing interventional procedures were sent di-
shoes to the nearest half kilogram. Height was measured rectlyforacarotidarteriography.
to the nearest half centimetre. Body mass index (BMI)
was calculated as the weight (kg) divided by height2 (m). Coronaryarterydisease(CAD)diagnosis
Waist circumference (WC,tothenearest half centimetre) Weincludedinthisgroupallofthepatientswithprevious
was measured in the standing position at the umbilicus. acute coronary sindromes (ACS) diagnoses (STEMI,
Arterial blood pressure was taken with a standard mer- NSTEMI,unstableangina)whetherornottheyhadendo-
curybloodpressuremeter.Threebloodpressurereadings luminal or surgical revascularisation procedures. We also
wereobtainedat1minintervals,andthesystolicanddia- included those patients with ischaemic heart disease and
stolic pressure readings were averaged and used for the stableangina.Allofthepatientsweresubjectedtocardiac
analysis.Venousbloodwasdrawninthemorningatward examination, ECG and echocardiogram to confirm the
admission after a 10–12 h overnight fast. All of the bio- previous diagnosis. Patients with ECG abnormalities or
chemicalparameterswereevaluatedwithstandardlabora- symptoms that were suggestive of ischaemia and/or with
tory procedures. All of the patients were tested for viral provocativetestssuspectedformyocardialischaemiawere
hepatitis B and C. LDL cholesterol was calculated by the sent for a coronary angiography to confirm the diagnosis
Friedewald formula except when the serum triglyceride orendoluminaltreatment.
concentration was >400 mg/dL. HbA was measured by
1c
high-performance liquid chromatography (HPLC); the Peripheralarterydisease(PAD)diagnosis
uppernormalitylimit forthelaboratorywas5.9%.Adaily Patientswhohadendoluminalorsurgicalrevascularisation
glycaemic profile with 6 finger-prick tests (One Touch interventional procedures, had previous amputations, or
Ultra, LifeScan, Milpitas, California, USA) was also ob- had been diagnosed withischaemic ulcers were diagnosed
tained from all of the patients. Metabolic Syndrome with PAD. All of the symptomatic patients (Fontaine’s
(MetS) was diagnosed using the AHA-NHLBI criteria [4], classificationstageII-IV)whowereconfirmedbyABIand
by the presence of diabetes and ≥2 of the following com- DUS were diagnosed with PAD. Asymptomatic patients
ponents: 1) WC >102 cm in men and >88 cm in women; with an ABI <0.9 who had significant stenosis or occlu-
2) triglycerides >1.7 mmol/L (150 mg/dL) or fibrate/fish sionsasdeterminedbyDUS(andconfirmedbyperipheral
oil users; 3) HDL <1.0 mmol/L (40 mg/dL) in men and CTA) were also included in the PAD group. Patients with
<1.29 mmol/L (50 mg/dL) in women; and 4) blood suspected critical limb ischaemia were evaluated by
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transcutaneuos oxygen pressure (TcPO2); if the results Results
were <30 mmHg, then the patients were referred to angi- Clinical and biochemical patient characteristics are pre-
ographytoperformendoluminalprocedures. sented in Table 1. In total, 643 (53.6%) patients had no
evidenceofmacrovasculardisease,andtheremaining556
Polyvasculardisease(PVD)diagnosis (46.4%) had MVD (see Figure 1, panel A). There were
When two or more ofthe above conditions were present 12.4% of the MVD patients who were classified as NSCS,
atthesame time,thepatientswerediagnosedwithPVD. 14.6%asCBVD,16%asCAD,10.6%asPAD,and46.4%as
PVD(Figure1,panelB).
Nomacrovasculardisease(NMVD)diagnosis
Patients who did not meet the criteria above were not Univariateanalyses
consideredtohavecardiovascular disease. Macrovasculardisease,anthropometricandclinicaldata
PatientswithCBVD,PADandPVDwereolderthanwere
Microvascularcomplicationevaluations patientsintheothergroups.CADpatientsweresimilarin
Microvascular complications were evaluated using fundus age to those without complications and to those in the
oculi and/or fluorescence angiography to assess retino- NSCSgroup.MalepatientsweremorenumerousinCAD,
pathy, urinary albumin excretion and eGFR calculation to PADandPVDgroups,whereasfemalepatientsweremore
assess nephropathy, and the 10g monofilament test and numerousintheothergroups.
vibration perception threshold analysis to assess peri- Diabetes duration was significantly greater in the PAD
pheral neuropathy. Microalbuminuria was defined as uri- andPVDpatients.BMIwassignificantlylowerinthePVD
naryalbuminexcretionbetween30and299mg/dayonat groupcomparedtotheNMVDandCADgroups.
least 2 of3 occasions.TheeGFRwascalculatedusing the
MDRDformula [estimated GFR (mL/m/1.73m2) = 186 × Macrovasculardiseaseandmetabolicparameters
creatinine(mg/dl)-1.154×age(yy)-0.203×0.742(iffemale)× We found no differences in the metabolic parameters
1.210 (if of black ethnicity)] [5]. Diabetic retinopathy was among the 6 subgroups. The HbA1c levels, FPG levels,
defined as any diabetes-linked retinal injury. Diabeticper- post-prandialglucoselevels,andΔpre-postprandialplasma
ipheral neuropathy was diagnosed based on neuropathic glucose levels were comparable among all of the groups.
symptoms,insensitivitytoa10gmonofilamentandanab- All of the data were outsideofthe normal ranges because
normalvibrationperceptionthreshold. thepatientshadpoorglycaemiccontrolatthisfirstobser-
vationinourcentre.
Statisticalanalysis
ThedataweretestedfornormalcyusingtheKolmogorov- Macrovasculardiseaseandlipoproteinprofile
Smirnovtest,whichindicatedanon-Gaussiandistribution The extensive use of statins across all of the groups
for all continuous variables; therefore, the results were strongly influenced the lipid profile in our patients. The
reported as a median value and an interquartile range total cholesterol levels were higher in patients without
(IQR, 25th-75th quartiles). Univariate analysis was per- complicationsorwithNSCScomparedwithCADorPVD
formed with the non-parametric Kruskal-Wallis test and patients, and the LDL-C values followed the same trend.
Dunn’s multiple comparison post-hoc test to compare HDL-C was significantly lower in the CAD and PVD
each of the continuous variables of interest among the patients compared to those in the NMVD and CBVD
macrovascular groups. The qualitative variable data were groups.Nosignificantdifferencesinthetriglyceridevalues
expressed as frequencies, and the groups were compared werefoundamongthegroups.
using the chi-square test. Multivariate logistic regression
analysiswasusedtodeterminewhethertraditionalcardio- MacrovasculardiseaseandMetS
vascular risk factors (sex, age, smoking status, diabetes As expected, metabolic syndrome prevalence was signifi-
duration, WC, SBP, DBP, LDL-C, HDL-C, triglyceride cantly greater in patients who belonged to the macrovas-
levels, HbA1c, FPG, use of antihypertensive and lipid- cular groups than in patients who did not have
lowering drugs and the presence of AHA/NHLBI-defined complications.Thehighestprevalencewasrecordedinthe
metabolicsyndrome)wereassociatedwithprevalentCVD PAD(94.9%)andPVD(95.7%)patients.Thesimultaneous
(dependentvariable,MVD; referencegroup,NMVD),and presence of 3 or 4 diagnostic MetS criteria (indicating
theresultswereexpressedas oddsratios(ORs)±95%CI. MetS severity) was more frequent in CAD patients (73%)
TheORswerecalculatedusingexponentiallogisticregres- (Figure2).
sion coefficients. A p-value of less than 0.05 was consid-
ered to be statistically significant. All of the analyses were Macrovasculardiseaseandmicrovascularcomplications
performed with SPSS version 17 (Chicago, IL, USA) and Microvascularcomplications(diabeticretinopathy,diabetic
Prismsoftware(GraphPad,USA). nephropathy and diabetic neuropathy) were significantly
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Table1Clinicalandmetabolicpatientvariables(allofthepatientsandgroupedaccordingtomacro-vascularinvolvement) ttpap
Variables All NMVD(I) NSCS(II) CBVD(III) CAD(IV) PAD(V) PVD(VI) pthdeifgferoreunpcseasamong ://wwaeta
wl.
NASegpxea%(tyiMeyn)ts(%) 1641799.5(958–75) 6644353.3(5(55–3.762)) 663969.1((55.97–)71) 873137((66.68–)79) 865958.4((75.54–)75) 567912((46.59–)76) 2675138.2(6(72–1.758)) _*IIV≠*≠*IIIV,V*,,VVII******,II≠III**,VI***III≠IV***, .cardiab.com/cCardiovascular
DM2duration(yy) 12(6–20) 10(5–18) 10(5–15.5) 12.5(7–20) 14(6–20) 20(10–30) 20(10–28.3) IIV≠≠VV,VII*****,II≠V,VI***,III≠VI*, ontenDiabe
Weight(Kg) 80(69.5-92.7) 81(71.1-94.4) 80.1(67.3-93.8) 74.6(65.1-85.5) 85.7(74.4-98.6) 75.2(67–90) 76.5(65.4-87.8) I≠III,VI**,III≠IV***,IV≠VI** t/12/1tology
BMI(Kg/m2) 31.1(27.6-35.5) 31.5(28.1-36.4) 31.5(26.5-36.6) 29.7(27.1-33.6) 32.2(27.6-37) 30.3(26.3-34.9) 30(26.3-33.8) I≠VI**,IV≠VI* /22
00
1
WC(cm) 105(97–118) 106(97–120) 105.5(94.3-119) 102(96–110.5) 110(98–120) 103(98–115.8) 104(97–116) ns 3
,
1
Smokinghistory% 27.3 26.9 20.3 14.8 25.8 33.9 32.6 *** 2:2
0
SBP(mmHg) 130(120–140) 130(120–140) 130(120–140) 130(120–140) 130(120–140) 130(120–145) 130(120–140) ns
DBP(mmHg) 80(70–80) 80(70–80) 80(70–80) 70(70–80) 80(70–80) 70(70–80) 80(70–80) ns
TC(mg/dl) 178(151–210) 183(157–212) 201(175–221) 176(153–204) 162(132–193) 179(156–212) 165(135–196) I≠IV,VI***,II≠IV,VI***
HDL-C(mg/dl) 45(38–55) 47(39–57) 49(39–58) 47(41–60) 42(35–50) 45(39–55) 43(35–52) I≠IV*,I≠VI***,III≠IV,VI*
LDL-C(mg/dl) 102(77–131) 105(83–133) 121(99–144) 101(76–129) 82(64–116) 102(74–130) 91(70–123) I≠IV,VI***,II≠IV,VI***
TG(mg/dl) 124(91–166) 123(91–161) 125(96–173) 117(82–149) 126(94–184) 123(90–170) 130(91–176) ns
HbA1c(%) 8.1(7–9.5) 8.1(7.1-9.7) 8(6.9-10.2) 8.2(6.8-9.5) 8.1(7.2-9.5) 7.7(6.8-9) 8(7–9.3) ns
FPG(mg/dl) 174(139–224) 174(138–230) 177(148–232) 169(138–213) 182(142–222) 177(140–218) 174(137–219) ns
2h-BG(mg/dl) 201(160–265) 203(160–270) 219(174–286) 195(160–232) 205(160–270) 200(167–239) 200(155–254) ns
ΔBG(prandial) 34(−6-76) 35(−3-79) 44(14–81) 39(−8-88) 38(−1-61) 31(−22-58) 22(−16-69) ns
MetS% 88 83.1 91.3 88.9 89 94.9 95.7 ***
3-4MetSfactors% 61 55.7 62.3 64.2 73 69.5 66.7 ***
eGFR 84(65–101) 89(74–106) 87(61–100) 79(65–99) 82(57–103) 66(49–88) 68(50–88) I≠III*,V,VI***,II≠V*,II≠VI**,IV≠VI*
Albuminuria% 25.9 24.3 21.9 25.3 31.8 33.3 27.2 ns
DR% 37.3 28.6 33.3 40.7 38.2 78 49.2 ***
DN% 49.7 39.0 42.0 53.1 43.8 88.1 70.5 ***
Statinusers% 65 55.4 69.6 70.4 76.4 81.4 78.7 ***
AHuser% 80.4 72.3 79.7 85.2 91 96.6 91.9 ***
OHAusers% 38.3 43.2 49.3 42 39.3 20.3 25.6 ***
OHA+BIusers% 13.6 16.5 11.6 8.6 10.1 10.1 10.5 ***
P
MDIusers% 48.1 48.1 39.1 49.4 50.6 69.3 63.9 *** ag
e
Dataaremedians(IQR,25th–75thquartiles)orproportions;aKruskal-Wallisone-wayANOVAwithDunn’smultiplecomparisonpost-hoctestandχ2-test;ns,notsignificant;*p<0.05,**p≤0.01,***p≤0.001;2h-BG,2h 4
glycaemiaaftermeals;ΔBG,Δpost-preprandialglycaemia;DR,Diabeticretinopathy;DN,DiabeticNeuropathy;eGFRwasexpressedasmL/min/1.73m2. of
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Figure1PanelA:Macrovascularcomplicationprevalenceinourpopulation.PanelB:Macrovascularsubgroupprevalenceinpatients
withmacrovascularcomplications.Thedataarefrequencies.
moreprevalentinPADandPVDsubjectsthanintheother In this analysis, in all of the macrovascular groups except
subjects. fortheCADandNSCSgroups,agewassignificantlyasso-
ciated with macrovascular disease. Male sex and diabetes
durationweresignificantlyassociatedonlyinthePADand
MultivariateAnalysis PVD groups. Reduced HDL-C was independently asso-
Multivariatelogisticregressionanalysiswasusedtodeter- ciatedinthe CADand PVD groups. Statin utilisationwas
mine whether traditional cardiovascular risk factors (sex, independently associated in all of the macrovascular
age, smoking status, diabetes duration, WC, SBP, DBP, groups with the exception of the NCSC group. MetS
LDL-C levels, HDL-C levels, triglyceride levels, HbA1c diagnosiswasindependentlyassociatedwithonlythePVD
levels, FPG levels, use of antihypertensive and lipid- group. In the logistic regression model, the inclusion of
lowering drugs and the presence of AHA/NHLBI-defined logarithmicallytransformed values of HDL-C,LDL-Cand
metabolicsyndrome)wereassociatedwithprevalentCVD triglycerides did not change the results. Similarly, when
(dependent variable, MVD; reference group, NMVD),and excluding MetS, logistic model coefficients were almost
thedatawereexpressedasoddsratios(ORs)(seeTable2). unchanged(datanotshown).
Figure2MetSprevalence(whitecolumns)and“severity”(blackcolumns)(presenceof3or4AHA/NHLBIclassificationcriteria)inthe
subgroups.Thedataarefrequencies.*,significantatp≤0.001fromChi-Squaretest.
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Table2Multivariablelogisticregressionanalyses t/12/1tology
NSCS CBVD CAD PAD PVD /22
00
1
OR 95%CI p OR 95%CI p OR 95%CI p OR 95%CI p OR 95%CI p 3
,
Gender(male) 1.03 0.54–1.96 0.94 1.35 0.70–2.61 0.37 1.53 0.85–2.74 0.16 2.90 1.37–6.12 0.005 2.39 1.53–3.73 0.0001 12
:2
Age 1.03 1.0–1.06 0.09 1.10 1.06–1.14 <0.0001 1.02 0.99–1.04 0.28 1.09 1.05–1.14 <0.0001 1.11 1.08–1.14 <0.0001 0
WC 0.99 0.97–1.01 0.36 0.97 0.95–0.99 0.01 0.99 0.98–1.01 0.45 0.98 0.96–1.00 0.07 0.99 0.97–1.00 0.04
Diabetesduration 0.98 0.94–1.01 0.17 0.99 0.96–1.02 0.68 1.01 0.98–1.04 0.60 1.05 1.02–1.08 0.004 1.04 1.02–1.06 0.0001
SmokingHistory(yes) 1.81 0.52–6.38 0.35 1.44 0.35–5.9 0.62 0.70 0.26–1–90 0.49 2.02 0.63–6.43 0.24 0.85 0.42–1.73 0.65
SBP 1.02 0.99–1.04 0.18 1.01 0.98–1.03 0.46 0.97 0.94–0.99 0.007 1.03 1.01–1.06 0.01 0.99 0.98–1.01 0.73
DBP 0.98 0.94–1.02 0.41 0.99 0.95–1.04 0.84 1.05 1.01–1.10 0.009 0.95 0.91–0.99 0.03 1.01 0.98–1.04 0.75
AHuser(yes) 0.96 0.45–2.02 0.91 1.25 0.53–2.94 0.61 2.93 1.19–7.23 0.02 8.4 1.02–68.4 0.04 1,55 0.83–2.89 0.17
HDL-C 0.99 0.97–1.02 0.66 0.99 0.97–1.02 0.74 0.97 0.95–0.99 0.03 0.97 0.95–1.00 0.06 0.98 0.97–0.99 0.03
LDL-C 1.00 0.99–1.01 0.16 1.00 0.99–1.01 0.41 0.99 0.98–0.99 0.02 1.00 0.99–1.01 0.66 1.00 0.99–1.00 0.09
Triglycerides 1.00 0.99–1.00 0.45 0.99 0.99–1.00 0.18 1.00 0.99–1.00 0.70 1.00 0.99–1.01 0.65 1.00 0.99–1.00 0.48
Statinusers(yes) 1.51 0.80–2.85 0.21 4.11 1.94–8.60 0.0002 2.31 1.24–4.30 0.009 4.92 1.99–12.10 0.0006 3.42 2.13–5.47 <0.0001
HbA1c 0.94 0.76–1.15 0.53 1.08 0.87–1.34 0.48 0.93 0.76–1.13 0.45 0.78 0.60–1.03 0.09 0.98 0.84–1.13 0.75
FPG 1.00 0.99–1.01 0.26 0.99 0.99–1.00 0.35 1.00 0.99–1.01 0.33 1.00 1.00–1.01 0.51 1.00 0.99–1.00 0.95
MetS(yes) 1.29 0.47–3.57 0.62 1.33 0.43–4.12 0.62 1.10 0.37–3.27 0.86 1.81 0.34–9.73 0.49 2.30 1.01–5.29 0.04
Relationship(ORs)amongselectedvariablesandthemacro-vasculargroups(Dependentvariable,macrovasculargroups;referencegroup,NMCV).Valuesinboldaresignificant.
P
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Discussion target,wetestedthehypothesisthatdifferentmacrovascu-
Thefirstgoalofourstudywastoassesstheprevalenceof lar involvement types might correspond to different phe-
different macroangiopathic conditions in our patients. notypes. By analysing the anthropometric and clinical
Ourstudydemonstratesthat46.4%ofourpatientpopula- characteristics of subgroups of patients, we found that
tionhasmacrovasculardisease.ItiswellknownthatCVD PADand PVD patients wereolder, had had diabetesfor a
prevalence, incidence, and mortality are strikingly greater longerperiodoftime,weremorelikelytohavebeensmo-
in the diabetic than in the non-diabetic population. kers and had a lower weight, BMI and WC than did the
According to the World Health Organization, CVD patients in the other groups. A multivariate analysis de-
prevalenceindiabeticpatientsrangesfrom26to36%[6]. monstrated that age, male sex, diabetes duration and the
The significantly higher prevalence of macrovascular use of statins were the most important independent PAD
complications in our patients is likely linked to patient andPVDriskfactors.Itisnoteworthythatthesamechar-
characteristics (average age, diabetes duration, poor gly- acteristics were not found to be independent risk factors
caemic control over time) and due to our inclusion of intheCADgroupandthattheaveragepatientageinthis
NSCS patients. As expected, almost half of our patients group was comparable to that of the population without
hadpolydistrectualinvolvement. macrovascular complications. The question arises of
Advanced atherosclerotic vascular changes are often whether a genetically determined predisposition alone
preceded by impairment of endothelium-dependent may explain the early onset of cardiac involvement in the
vasodilation, vascular smooth muscle dysfunction and CADgroup.Inrecent years, manygenetic risk factorsfor
increased arterial stiffness. Today all of these factors are both diabetes and coronary artery disease have been
recognizedaspredictorsofvasculardysfunctioninT2DM discovered through genome-wide association studies.
patients [7]. Atherosclerotic disease usually causes sys- Genetic aspects of diabetes, diabetic macrovascular com-
temicinvolvement,whichismorefrequentinthediabetic plications and CAD may share mechanisms, leading to a
population [8]. Moreover, atherosclerosis in diabetic common effector hypothesis. However, only a few genetic
patients is different from that in non-diabetic subjects risk factors could be identified that modulate the risk for
because both pathologic studies and angiographic reports both conditions. Polymorphisms in theTCF7L2 and near
in individuals with coronary heart disease and PAD have the CDKNZA/B genes may be of great importance for
shown that diabetic patients have more blood vessels CAD development because these genes modulate both
involved, with a more diffuse atherosclerotic lesion distri- conditions and are not necessarily related to hyperinsuli-
bution[9,10]. naemiaorhyperglycaemia[13].
Genetic studies have also shown that different macro- The complexinteractions betweengenetic and environ-
vascular phenotypes (as CAD and CBVD) and T2DM mental factors on cardiometabolic risk were analyzed by
share a major linkage at the chromosome12q24 locus. In twin studies indicating that some cardiometabolic risk
thisregard,thegeneofproteasomemodulator9(PSMD9) factors had strongheritability (as weight, waistcircumfer-
islinkedtomacrovascularpathologyofT2DM[11]. ence,SBP,DBP)whileothersweresubstantiallyinfluenced
Estimated twentyyears incidence of different cardiovas- byenvironmentalfactors[14].
cular complication phenotypes (ischaemic heart, myo- Byanalysingglico-metabolicparameters(HbA1c,fasting
cardial infarction, heart failure, cerebrovascular disease, glucose,postprandialglucoseandΔpost-preprandialblood
amputation of lower limbs) was evaluated in a Mexican glucose)wefoundnodifferencesamongthesixsubgroups.
diabetic population by a simulation model indicating that Despite a clear association between diabetes and athero-
a large portion of this diabetic population is at risk of sclerotic vascular disease, the underlying mechanism
myocardial infarction and cerebrovascolar disease in sub- responsible for the two diseases is not fully understood.
sequentyears[12].Alsoinourstudy,amongpatientswith The relative importance of “non-glycaemic” risk factors
macrovascular-isolated events, the majority of patients and hyperglycemia “per sè” has always been debated [15].
wereplacedintheCAD(16%)andCBVD(14.6%)groups. Results on the causal relationship between hyperglycemia
PAD, CAD and CBVD risk factors are similar and are and macroangiopathy have been contradictory. Plenty of
also typical atherosclerosis risk factors. These risk factors evidencesuggestasignificativerelationshipbetweenHbA1c
include smoking, dyslipidaemia, diabetes and hyperten- levels,post-prandialhyperglycemia,andriskofCVevents
sion. However, specific risk factors, such as genetic back- and adverse outcomes especially in overweight and obese
ground, could be more important for the development of patients [16,17] . However, recently three major studies,
macro-vascular disease at certain sites.To the bestof our ACCORD [18], ADVANCE [19] and VADT [20] eva-
knowledge, no study has compared the anthropometric, luated the impact of attaining euglycemia (ACCORD) or
clinical and laboratory features in type 2 diabetic patients near-euglycemia(ADVANCEandVADT)inpatientswith
by stratifying patients according to the type of macrovas- long-lasting diabetes and high cardio-vascular risk. None
cular involvement. For this reason, as a second study of these studies, either individually or on pooled analysis,
Papaetal.CardiovascularDiabetology2013,12:20 Page8of9
http://www.cardiab.com/content/12/1/20
demonstratedanyreductioninallcauseorcardiovascular calculating the eGFR in the CAD,PADandPVD groups.
mortality, although a meta-analysis revealed a 15-17% Diabetic neuropathy was more frequent in the PAD and
reductioninthe incidence ofnon-fatalmyocardialinfarc- PVD groups, and diabetic retinopathy was strikingly
tion in those patients exposed to tight glucose control present in the PAD group. As expected, patients in the
[21].Ahighermortalitywasobservedintheintensiveglu- CAD, PAD and PVD groups were the largest statin and
cose control arm of ACCORD, leading to the premature antihypertensive drug users, and those in the PAD and
termination of the glucose-lowering component of this PVD groups were more frequently treated with multiple
study. The weak association between glycemic control insulin injections.
and macro-vascular disease observed in UKPDS [22] has
been confirmed and amplified by these recent interven- Strengthsandlimitations
tion studies. Accordingly, our data show that glycated Macrovascular complication phenotyping in type 2 dia-
hemoglobin, post-prandial and fasting glucose were similar betic patients has not yet been reported. Such phenotyp-
in each subgroup considered. However, the relationship ing may have diagnostic and therapeutic implications in
between hyperglycemia and macrovascular complications type 2 diabetes management. An additional strength of
is made even more complex by the potential role of epi- our study is the large number of patients who were stu-
genetic mechanisms, as the metabolic memory, by which died in a single clinical centre, with each diagnostic
a prior exposure to hyperglycemia predisposes diabetic examination being performed bya single operator. How-
patientstothecontinuingdevelopmentofvasculardiseases ever, we recognise that there are some limitations to our
despite a subsequent good glycemic control [23]. Further- study. First, the retrospective cross-sectional design pre-
more,inourstudy,referralbias(diabeticpatientswithpoor cluded the establishment of causal or temporal relations
metabolic control referred to us for the first time) did not among macrovascular events and other features in our
allow to clarify the causal or temporal relationship among diabetic population. In addition, this study mainly
macrovasculareventsandglycemiccontrolovertime. included older diabetic subjects who had unsatisfactory
By analysing the lipid profile, we found a clear differ- glycaemic control, who may not have been representa-
ence in HDL-C among the groups, which was lower in tive ofthegeneraldiabetic population.
CAD, PAD, and PVD patients. These data are in accord-
ance with other scientific evidence that support the im- Conclusion
portance of this macroangiopathy-associated risk factor. Ourstudyshowsthatnearlyhalfofdiabeticpatients,espe-
Inamultivariateanalysis,wealsoconfirmedthatreduced cially those who are elderly and male with a long disease
HDL-C values are independent CAD and PVD risk fac- duration,havepolydistrectualatheroscleroticinvolvement.
tors (the association was borderline significant for the The characterization of different phenotypes may have
PAD group). The importance of HDL-C as “target the- aclinicalsignificancefortheeveryday clinician.
rapy” is now emerging from recent cardiovascular trials Firstly, different factors were associated with isolated
of CETP (cholesteryl ester transfer protein) inhibitors, coronaryarterydisease,likeameanagecomparabletothat
such as Anacetrapib [24] and Evacetrapib [25]. This new of patients without macro-vascular complications and a
pharmacologicalgroupisverypromising for cardiovascu- high frequency of severe metabolic syndrome. These data
lar risk reduction either when administered alone or in raise the interesting hypothesis that coronary artery dis-
conjunctionwithconventionaltherapy. ease, metabolic syndrome and diabetes may be genetically
Many reports have suggested that metabolic syndrome linked in some individuals. Further studies may clarify
mayprecede/predictvasculardisease.Ithasbeenreported whether this is because of genetic background and/or be-
that insulin resistance and metabolic syndrome increase cause coronary heart disease might be the first event in
theriskofnewcardiovasculareventsalsoinpatientswith- polydistrectualatheroscleroticinvolvement.
outknowndiabetesbutwithmanifestarterialdisease[26]. Secondly,lowHDL-CvaluesareamarkerofPAD,CAD
Intype2diabetes,metabolicsyndromeishighlyprevalent and PVD, confirming the importance of HDL-C as a
andoftenprecedeshyperglycaemiaonset[27,28].Further- potential therapeutic target. Alternatively, lifestyle modifi-
more, insulin resistance and metabolic syndrome predict cationstrategiestopreventa lowHDL-cholesterolshould
atherosclerosis in type 2 diabetic patients [29]. Our find- beimplemented.
ings support the clinical relevance of MetS component
detection, which may be a simple, quick tool to stratify Abbreviations
ABI:Ankle-brachialindex;ACS:Acutecoronarysyndrome;BMI:Bodymass
diabeticpatientsaccordingtotheexpectedmacrovascular
index;CAD:Coronaryarterydisease;CAS:Carotidarterystenting;
complicationseverity(asapolydistrectualdisease). CBVD:Cerebrovasculardisease;CEA:Carotidendarterectomy;CLI:Critical
Microvascular complications were not equally present limbischaemia;CT:Computedtomography;CTA:Computedtomography
angiography;CVD:Cardiovasculardisease;DBP:Diastolicbloodpressure;
in the various groups. We found more diabetic nephro-
DUS:Duplexultrasonography;eGFR:Estimatedglomerularfiltrationrate;
pathy, as assessed by micro/macroalbuminuria or by FPG:Fastingplasmaglucose;MVD:Macrovasculardisease;MDIs:Multiple
Papaetal.CardiovascularDiabetology2013,12:20 Page9of9
http://www.cardiab.com/content/12/1/20
dailyinjections;MetS:Metabolicsyndrome;NMVD:Nomacrovasculardisease; 13. SousaAG,SelvaticiL,KriegerJE,PereiraAC:Associationbetweengeneticsof
NSCS:Non-significantcarotidstenosis;PAD:Peripheralarterydiseases; diabetes,coronaryarterydisease,andmacrovascularcomplications:
PTA:Percutaneoustransluminalangioplasty;PVD:Polyvasculardisease; exploringacommongroundhypothesis.RevDiabetStud2011,8(2):230–244.
SBP:Systolicbloodpressure;TcPO2:Transcutaneuosoxygenpressure; 14. JermendyG,HorvathT,LittvayL,SteinbachR,JermendyAL,TarnokiAD,
T2DM:Type2diabetesmellitus;TIA:Transientischaemicattack;WC:Waist TarnokiDL,MetnekiJ,OsztovitsJ:Effectofgeneticandenvironmental
circumference. influencesoncardiometabolicriskfactors:atwinstudy.Cardiovasc
Diabetol2011,10:96.doi:10.1186/1475-2840-10-96.
15. MilicevicZ,RazI,BeattieBD,CampaigneBN,SarwatS,GromniakE,
Competinginterests
KowalskaI,GalicE,TanM,HanefeldM:NaturalHistoryofCardiovascular
Noneoftheauthorshasanyconflictofinterest.
DiseaseinPazientswithdiabetes.DiabetesCare2008,31(2):S155–S160.
doi:10.2337/dc08-s240.
Authors’contributions 16. Temelkova-KurktschievTS,KoehlerC,HenkelE,LeonhardtW,FueckerK,
GPparticipatedintheoveralldesign,datacollection,statisticalanalysis,data HanefeldM:Postchallengeplasmaglucoseandglycemicspikesaremore
interpretation,writingandcriticalreviewofthemanuscript.CD,MPI,CL,RM stronglyassociatedwithatherosclerosisthanfastingglucoseorHbA1c
participatedindatacollection,datainterpretationandcriticallyrevisedthe level.DiabetesCare2000,23:1830–1934.
manuscriptbeforefinalapproval.CFsupervisedthedesignandconduction 17. AnderssonC,vanGaalL,CatersonID,WeekeP,JamesWP,CoutinhoW,
ofthestudy,participatedindatainterpretationandcriticallyrevisedthe FinerN,SharmaAM,MaggioriAP,Torp-PedersenC:Relationshipbetween
manuscriptbeforefinalapproval.Allauthorsreadandapprovedthefinal HbA1clevelsandriskofcardiovascularadverseoutcomesandall-cause
manuscript. mortalityinoverweightandobesecardiovascularhigh-riskwomenand
menwithtype2diabetes.Diabetologia2012,55(9):2348–2355.
Acknowledgments doi:10.1007/s00125-012-2584-3.
WethankDr.V.Pezzinoforcriticalreviewofthemanuscript.WethankDr.F. 18. ActiontoControlCardiovascularRiskinDiabetes(ACCORD)StudyGroup,
Palermoforhisadviceonthestatisticalanalysis. GersteinHC,MillerME,ByingtonRP,GoffDCJr,BiggerJT,etal:Effectsof
intensiveglucoseloweringintype2diabetes.NEnglJMed2008,
Received:6December2012Accepted:16January2013 358(24):2545–2559.
Published:18January2013 19. ADVANCECollaborativeGroup,PatelA,MacMahonS,ChalmersJ,NealB,
BillotL,etal:Intensivebloodglucoseandvascularoutcomesinpatients
withtype2diabetes.NEnglJMed2008,358(24):2560–2572.
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