Saphenous Vein Graft Failure after Coronary Artery Bypass Surgery ...circ.ahajournals.org/content/circulationaha/early/2014/09/25/... · Saphenous Vein Graft Failure after Coronary

DOI: 10.1161/CIRCULATIONAHA.113.008193

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Saphenous Vein Graft Failure after Coronary Artery Bypass Surgery:

Insights from PREVENT IV

Running title: Hess et al.; Predictors of VGF after CABG

Connie N. Hess, MD, MHS1; Renato D. Lopes, MD, PhD1; C. Michael Gibson, MD2;

Rebecca Hager, MR1; Daniel M. Wojdyla, MSc1; Brian R. Englum, MD1;

Michael J. Mack, MD3; Robert M. Califf, MD4; Nicholas T. Kouchoukos, MD5;

Eric D. Peterson, MD, MPH1; John H. Alexander, MD, MHS1

1Duke Clinical Research Institute, Duke Medicine, Durham, NC; 2Harvard Medical School,

Harvard University, Boston, MA; 3Baylor Health Care System, Baylor, TX; 4Duke

Translational Medicine Institute, Duke Medicine, Durham, NC; 5Missouri Baptist Medical

Center, St. Louis, MO

Address for Correspondence:

John H. Alexander, MD, MHS

Duke Clinical Research Institute

Duke Medicine

Box 3850

Durham, NC 27710

Tel: 919-668-8955

Fax: 919-668-7085

E-mail: [email protected].

Journal Subject Codes: Cardiovascular (CV) surgery:[39] CV surgery: other, Cardiovascular (CV) surgery:[36] CV surgery: coronary artery disease

Michael J. Mack, MD ; Robert M. Califf, MD ; Nicholas T. Kouchoukoss,, MDMD ;;

Eric D. Peterson, MD, MPH1; John H. Alexander, MD, MHS1

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by guest on June 11, 2018http://circ.ahajournals.org/

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Abstract

Background—Coronary artery bypass grafting (CABG) success is limited by vein graft failure

(VGF). Understanding factors associated with VGF may improve patient outcomes.

Methods and Results—We examined 1828 participants in the PREVENT IV trial undergoing

protocol-mandated follow-up angiography 12–18 months post-CABG or earlier clinically-driven

angiography. Outcomes included patient- and graft-level angiographic VGF ( 75% stenosis or

occlusion). Variables were selected using Fast False Selection Rate methodology. We examined

relationships between variables and VGF in patient- and graft-level models using logistic

regression without and with generalized estimating equations. At 12–18 months post-CABG, 782

of 1828 (42.8%) patients had VGF, and 1096 of 4343 (25.2%) vein grafts had failed.

Demographic and clinical characteristics were similar between patients with and without VGF,

though VGF patients had longer surgical times, worse target artery quality, longer graft length,

and more frequently underwent endoscopic vein harvesting. After multivariable adjustment,

longer surgical duration (odds ratio [OR] per 10-minute increase 1.05, 95% confidence interval

[CI] 1.03–1.07), endoscopic vein harvesting (OR 1.41, 95% CI 1.16–1.71), poor target artery

quality (OR 1.43, 95% CI 1.11–1.84), and postoperative use of clopidogrel or ticlopidine (OR

1.35, 95% CI 1.07–1.69) were associated with patient-level VGF. The predicted likelihood of

VGF in the graft-level model ranged from 12.1–63.6%.

Conclusions—VGF is common and associated with a number of patient and surgical factors.

These findings may help identify patients with risk factors for VGF and inform the development

of interventions to reduce VGF.

Clinical Trial Registration Information—ClinicalTrials.gov. Identifier: NCT00042081.

Key words: coronary disease, coronary artery bypass graft surgery, revascularization

egression without and with generalized estimating equations. At 12–18 months popoststst-C-CABABG,G,, 7782

of 1828 (42.8%) patients had VGF, and 1096 of 4343 (25.2%) vein grafts had faaililededed. f

Demogrg aphic and clinical characteristics were similar between patients with and without VGF,

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Coronary artery bypass grafting (CABG) is one of the most frequently performed surgical

procedures in the United States, with over 400,000 procedures performed annually.1 Although

CABG improves survival and symptoms in selected patients,1-3 surgical success depends on the

continued patency of grafts, and graft failure has been associated with worse outcomes.4,5

Saphenous vein grafts remain the most widely used conduit during CABG, and rates of vein graft

failure (VGF) during the first 12 to 18 months after surgery have been reported to be as high as

25%.6-10

Many studies have examined factors associated with VGF and have inconsistently

reported associations between multiple clinical and surgical characteristics and VGF.11-15 These

previous efforts have been limited by the absence of systematic angiographic follow-up. In

addition, results from these studies may be outdated, given advances in surgical techniques and

adjunctive medical therapies that could impact graft failure. We therefore sought to examine

factors associated with VGF assessed by coronary angiography 12–18 months after CABG using

data from the PRoject of Ex-vivo Vein graft ENgineering via Transfection IV (PREVENT IV)

trial.

Methods

Data source and patient population

We used data from the PREVENT IV trial (ClinicalTrials.gov: NCT00042081), the design and

results of which have been previously described.16 Briefly, PREVENT IV was a phase 3

randomized, double-blind, placebo-controlled trial of ex-vivo vein graft treatment with

edifoligide in patients undergoing primary CABG with 2 planned vein grafts. A total of 3014

patients were enrolled between August 2002 and October 2003 at 107 centers across the U.S., the

previous efforts have been limited by the absence of systematic angiographic fololllolow-ww upupup.. InInIn

addition, results from these studies may be outdated, given advances in surgical techniques and

addjujuuncncnctititivevee mmmeeediciccalalal ttherapies that could impact gggrarar fftft failure. We tthehh reefofoforrere sought to examine t

ffaactttoro s associatatedede wwitiith hh VGVGVGFFF asaassesesssssedede bbyyy corroronnaryyy aaangggioioogrgraapaphyhy 1122–2–18188 mmmononththths s afaffteteter r CACACABGBGBG uuussising

dadatatata fffrororom m thththee e PRPRRojjjecectt ofoff EEx--viviv vovovo VVVeieinnn grgrgrafafafttt ENENENggiginneeerrrinnnggg vvvia aa TrTrTranannsfsfsfececctioonon IIIV V V (P(P(PREREREVEVEENNTNT IIIV)V))

rial.


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first 2400 of whom were scheduled for follow-up angiography between 12–18 months after

CABG. The PREVENT IV protocol was approved by institutional review boards of all

participating sites and all enrolled patients provided written informed consent.

We included patients in the angiographic cohort who were scheduled to undergo follow-

up angiography 12–18 months after the index CABG (n=2400). Patients in the angiographic

cohort who had VGF documented during earlier angiography for clinical indications in place of

(n=64) or in addition to (n=107) routine protocol angiography were included. We excluded

patients who did not undergo angiographic follow-up (n=477), who received only arterial grafts

(n=4), or who died prior to their 12–18 month repeat angiogram (n=91). Our final analysis

population consisted of 1828 patients enrolled at 100 sites (Figure 1).

Definitions and outcomes

VGF was defined as 75% stenosis or occlusion detected at follow-up angiography 12–18

months after CABG or earlier angiography performed for clinical indications. All angiograms

were analyzed at a core laboratory (PERFUSE Angiographic Core Laboratory, Boston, MA). For

grafts with multiple distal anastomoses (m-SVG), failure of any component was considered

VGF.17 Outcomes for our analyses were defined as failure of 1 or more vein grafts (patient-level

angiographic VGF) and graft-level angiographic VGF.

Statistical analysis

Baseline patient and procedure characteristics were examined according to patient-level absence

or presence of VGF at 12–18 months post-CABG. Continuous variables were summarized using

medians and interquartile ranges (IQR), while categorical variables were presented as

frequencies and percentages. Comparisons within continuous and categorical variable groups

were performed using Wilcoxon 2-sample test and Chi-square test, respectively.

population consisted of 1828 patients enrolled at 100 sites (Figure 1).

Definitions and outcomes

VGVGGFFF wwawas s dededefiffineed dd aasas 75% stenosis or occlusion n n dededettected at followoww-upp ananangiography 12–18

mmonntnths after CCABABA G G ooror eeeararrlliliererer aangnggioioogrgrapapphy pppeeerforrrmmmed fofoor r ccclininnicicaaal iindnddiiiff ccacattiononnss.. AAlllll aangngn ioii ggrgramammss s

weweererer aaananan lylylyzezezedd atatt aaa ccororre lalaboborarar tototoryryry (((PEPEERFRFRFUUSUSEEE AnAnAngigiiogoggraaaphphphicic CCCoorore ee LaLaL bbborrarattororory,y,y BBososostttonnn, MMMA)A)A). FFoF r

grafts with mumuultlttipipiplelele ddisisi tatat l anananasaa tototomomomosess sss (m(m(m-S-SSVGVGVG),),) fffaiaiailulurerere ooof f f ananany y y cococompmpmponononenenent t t wawawasss cococonsnsnsidi ered


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We analyzed surgical features at both the patient- and graft-levels. When describing

patient-level characteristics, we used the “worst” status to describe procedure characteristics for

patients with multiple vein grafts. The following hierarchies (worst status listed first) were used:

target artery quality= poor, fair, good; graft quality= poor, fair, good; distal connection

technique= non-suture, suture; graft length= longest measurement; graft source= arm vein, lesser

saphenous vein, greater saphenous vein; vein harvest technique= endoscopic, open; and m-SVG

use= yes, no.

We developed patient- and graft-level models to determine factors associated with VGF.

For the main analysis, patient-level variables were created by assessing graft-level data for each

patient and, for patients with multiple grafts, determining the worst status for each characteristic

among all grafts. We also performed a secondary analysis to examine graft-level variables

associated with VGF. For both models, variables associated with VGF were selected using Fast

False Selection Rate (Fast FSR).18 Fast FSR is a conservative variable selection method that

accounts for the percentage of variables incorrectly identified as associated with the outcome of

interest. Logistic regression models were then fit using the chosen variables to estimate the

association of each factor with VGF and odds ratios (OR) with associated 95% confidence

intervals (CI) were reported. For graft-level analyses, in order to account for the correlation

among multiple grafts within the same patient, generalized estimating equations were used to fit

a generalized linear logistic model that allows for an exchangeable correlation matrix between

grafts within a single patient.

The following candidate variables were chosen based on clinical judgment and

considered for inclusion in both patient- and graft-level models: age, female sex, weight, race,

smoking status, chronic lung disease, hypertension, dyslipidemia, prior myocardial infarction,

patient and, for patients with multiple grafts, determining the worst status for eacachhh chchc arararaccacteteteriririststic

among all grafts. We also performed a secondary analysis to examine y graft-level variables

asssosoociciciatatatededed wwwiitith VGVGVGF.F For both models, variablees ss assssociated withh VVVGFFF wwwere e selected using Fast

FFalsssee Selectioon n RaRaRatee (((FaFaaststst FFFSRSRSR).).18181 FFFasastt FFFSRRR isss a cccoonnseeervrvvatativivi eee vavaaririabablele seeelececcttitionon mmmetetthohoh d thththatatt

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nterest. Logigig stststicicic rrregegegrereesssssioon n n momom dededelsls wwwererere e thththenenen fffititt uuusisiingnn ttthehehe ccchohohosesesen n vavavariririababableleles ss totoo eeestststimimmataa e the


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prior percutaneous coronary intervention, prior cancer, history of liver disease, peripheral artery

disease, cerebrovascular disease, prior congestive heart failure, current New York Heart

Association class, diabetes (no history, non-insulin therapy, insulin therapy), renal failure, atrial

fibrillation/flutter, ejection fraction, type of CABG procedure (emergent/salvage, urgent,

elective), use of cardiopulmonary bypass (CPB), CPB time, aortic cross-clamp time, surgical

time, graft source (greater saphenous, lesser saphenous), vein harvest technique (endoscopic,

open), graft quality, maximum stenosis of target vessel (<75%, 75%), target artery quality,

proximal anastomosis connection technique (suture, non-suture), graft length, and use of m-

SVG. For both patient- and graft-level models, linear splines were used to determine appropriate

knot points for the following non-linear variables (see Online supplement for knot points): aortic

cross-clamp time, ejection fraction, graft length (patient-level model only), and CPB time (graft-

level model only). Significant (p<0.1) levels were then included as candidate variables (see

Online supplement). We hypothesized that chronic use of certain medications might be

associated with VGF. In PREVENT IV, data regarding medication use were collected at the

discrete time points at baseline, discharge, 30 days, and 1 year. We chose to examine 30-day

medication use as covariates, as these were thought to best represent chronic postoperative use

following the initial surgery. However, since medication use at 30 days is a post-baseline

variable, it was included in models as a sensitivity analyses. Rates of missingness for data in our

models were 1.5%, and no imputation was performed for missing data. Multivariable models

were derived from complete cases. For the Fast FSR method, the desired false selection rate was

set to 0.05. All analyses were performed at the Duke Clinical Research Institute using SAS

version 9.2 (SAS Institute, Cary, NC).

knot points for the following non-linear variables (see Online supplement for knnooot pppoioiintntnts)s)s)::: aoaoa rrtic

cross-clamp time, ejection fraction, graft length (patient-level model only), and CPB time (graft-

eeveveelll mmomodededel l l ooonlyyy)).). SSignificant (p<0.1) levels wererre ee tthhen included aaass caandndndiididate variables (see

OOOnllilinen supplememeenentt). WeWeWe hhhypypypototothehesisis zzezedd thhhat ccchhrroniiic useee ooof f cccerrtrtaiainnn mmemedididicaaatiionononss s mimighghght t t bebebe

asssososociciciatata eded wwwiitith h VGVGVGF.F. Inn n PRPREVEVEVENENENT T T IVIVV, dadadattata rrreeegagaardddininngg g mememeddidicacacatitiiononn uuusesee wwwerereee cocoollllececectteted d attt tthehee

discrete time e popopoininntststs aat t t babab seeelilil nenn , , dididiscscchahah rgrgrge,e,e, 3330 0 0 dadad ysysys,,, anana d d d 111 yeyeyeararr.. WeWeWe ccchohohosesese tttooo exexxamamamininine e e 30-day


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Results

Patient and procedure characteristics

Among a total of 1828 patients included in our study, 782 (42.8%) had VGF at 12–18 months

after CABG. At the graft-level, 1096 (25.2%) of the 4343 grafts placed during the index CABG

had failed at 12–18 months after CABD. Demographic characteristics and comorbid conditions

were similar between patients with and without VGF with the exception of cerebrovascular

disease, which was more prevalent among patients with VGF (Table 1).

Patient-level CABG procedure characteristics among patients with and without VGF are

shown in Table 2. Compared with patients without VGF, those with VGF had longer surgical

and cross-clamp times and worse target artery quality. Patients with VGF also more frequently

underwent endoscopic versus open vein graft harvest and had slightly longer graft length than

patients without VGF. At 30 days after the index CABG, patients with subsequent VGF were

more frequently taking clopidogrel or ticlopidine (26.1% vs. 19.2%, p<0.001) and had similar

use of warfarin (9.1% vs. 8.5%, p=0.66) and statins (74.6% vs. 74.9%, p=0.88) than patients who

did not have subsequent VGF.

Factors associated with VGF

We first examined patient-level factors associated with VGF at 12–18 months after CABG.

Longer duration of surgery (OR per 10-minute increase 1.05; 95% CI 1.03–1.07; p<0.01),

endoscopic vein graft harvest technique (OR 1.44; 95% CI 1.19–1.75; p<0.01), and poor target

artery quality (OR 1.45; 95% CI 1.13–1.87; p<0.01) were significantly associated with VGF.

Adding medications continued at 30 days after CABG to the variable selection model revealed

that the use of clopidogrel or ticlopidine was significantly associated with VGF (OR 1.35; 95%

CI 1.07–1.69; p=0.01); addition of clopidogrel or ticlopidine to the model did not substantially

and cross-clamp times and worse target artery quality. Patients with VGF also momooreee ffrereequququenenentltly y

underwent endoscopic versus open vein graft harvest and had slightly longer graft length than

paatitiienenentststs wwwititithohohoutt VVVGGF. At 30 days after the index x x CACABG, patientss wwitth h h sususubsequent VGF were

mmorrere frequentltly y taakikinngg ccclololopipipidododogrgrelele ooor titicccloppidddine (2226.1%1%1% vvsss. 1919..22%%,%, pp<0<0<0.00010101))) anandd d hahahadd d siiimimmilalal rr r

ususe ee ofofof wwwararfafafarirrin n ((9(9..11%% % vsvss. 8.8 5%5%5%, p=p=p=0.00.66666) ) anananddd stststatata ininnss (7(774.4.6%6%6% vvvsss.. 77474.99.9%,%,%, pp=0=0.8.8.88)8)8) tthahahannn papaatiienentstss wwwhoh

did not have sssubububseseequququenenent tt VGVGVGF.FF


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change the relationship between the other significant predictors and VGF (Table 3). Goodness of

fit of the model as measured by the Hosmer-Lemeshow statistic indicated that the model fits the

data well (p = 0.85). The c-statistic for the model was 0.61.

Next, we assessed the relationship of graft-level variables with VGF (Table 4). Factors

that were significantly associated with per-graft VGF (Table 4) included fair or poor target

artery quality (OR 1.31; 95% CI 1.11–1.56; p<0.01 and OR 2.34; 95% CI 1.89–2.91; p<0.01,

respectively), longer duration of surgery (OR per 10-minute increase 1.04; 95% CI 1.02–1.05;

p<0.01), endoscopic vein harvest technique (OR 1.37; 95% CI 1.16–1.62; p<0.01), and history of

cerebrovascular disease (OR 1.39; 95% CI 1.06–1.81; p=0.02). After including 30-day

medication use, clopidogrel or ticlopidine use was again associated with VGF (OR 1.30; 95% CI

1.07–1.58; p<0.01).

Distribution of predicted VGF risk

We examined the distribution of predicted VGF risk using the full (including 30-day medication

use) graft-level model of VGF. Predicted probability of VGF at 12–18 months post-CABG

ranged from a low of 12.1% to a high of 63.6%. The median predicted risk of VGF among our

patient cohort was 23.4% (interquartile range 19.5% to 29.2%) (Figure 2).

Discussion

In this analysis from PREVENT IV which included over 1800 patients, more than 4300

implanted vein grafts, and systematic 12–18 month angiographic follow-up, we found that longer

duration of surgery, endoscopic vein graft harvesting, poor target artery quality, and the use of

clopidogrel or ticlopidine at 30 days post-CABG were factors associated with VGF in both per-

patient- and per-graft-level models. The broad range of predicted VGF using our per-graft-level

medication use, clopidogrel or ticlopidine use was again associated with VGF (OOOR R 11.303030;;; 959595%% % CI

1.07–1.58; p<0.01).

DiDistststririribububutititionono of f prprprede icted VGF risk

WeWe eexamined d ththhee dddiststrir bububutititiononn oof f prprpreedediicctteed VGVGVGF rriisskk uussisinngng tthhee ffuuulll (i(incnccluudidinngng 330-0-dadaday y y mmemedididicacaatiiiono

ususe)e)e) gggrarar ftft-l-llevevevelel mmmoododelell oof f VGVGGF.F.F. PPPrererediddictcttededd ppprrrobobbababa iililittty y y oofof VVVGFGFGF aaat t 12122–1–1– 88 mmomontntnthshshs pppososost-t-t-CAAABBGBG

anged from a a a loloow w w ofofo 1112.22 1%%% ttto o a a a hihih ghghg ooof f f 636363.6.6.6%.%.% ThThThe e e memeedididiananan ppprereredidd ctctctededed rrrisisisk k k ofoff VVVGFGFGF aaamom ng our


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model (12.1–63.6%) suggests that VGF is prevalent and hence, these data may be clinically

useful to inform efforts to reduce VGF.

Interest in understanding factors associated with VGF after CABG has been

longstanding, but prior efforts have been limited.15 Previous studies have consistently reported 1

year VGF rates of 10–20%, with another 5–10% of vein grafts failing between 1–5 years after

CABG.10,19-24 These studies have identified patient characteristics, including younger age,11,12

female sex,12,13 prior heart failure or low ejection fraction,12,13 and increased serum

cholesterol,11,25 as predictors of VGF. Surgical factors, including temperature of graft solution,25

multiple distal anastamoses,13,26 poor distal vessel,13,26 target artery stenosis,12 and endoscopic

harvest technique,26,27 have also been identified as predictive of VGF. Importantly, these

analyses were based on data from patients undergoing CABG several decades ago, prior to the

widespread use of antiplatelet therapy and the introduction of newer surgical CABG

techniques.28-30 Some prior reports were also based on single-center studies, reducing the

generalizability of their results, or analyzed data at either the patient- or graft-level, which may

account for some of the inconsistency in previous findings. Furthermore, a number of prior

studies examined patients undergoing clinically-driven coronary angiography, which may under

or overestimate the rate and influence of factors associated with VGF.

Our study extends knowledge in the field in several ways. First, this analysis represents

one of the largest analyses of factors associated with VGF to date and includes data from over

100 sites. Second, our study included patients undergoing angiography for clinical reasons as

well as relatively complete, protocol-mandated follow-up angiography, allowing for a more

unbiased assessment of VGF and the factors associated with it. Third, our analysis was based on

data representing more contemporary practice and was strengthened by the detailed clinical and

harvest technique,26,27 have also been identified as predictive of VGF. Importanttlylyly, ththt eseseseee

analyses were based on data from patients undergoing CABG several decades ago, prior to the

wiwidededespspsprereadadad uusse ooofff ana tiplatelet therapy and the intntntrorodduction of newwwer ssurururggigical CABG

eechhhnin ques.28-28 3030 SSSoommee prprrioioiorrr rerereppoportrts ss wwewerere alsooo bbbaseeedd onn ssiiningglglee--cecenntnterer sstutuuddieies,s,s, rrrededucuccininngg thtt ee e

gegennenerararalilil zazabibibilililityty ooof f f ththeeiir reresusultltlts,s, ooorrr anaanalallyzyzyzededed datatata a aaat eeitttheheherrr thththe papap ttitienennt-t-t ooor grgrg afafaft-t-lelel veveel,l,l, wwhhhicchch mmmayayy

account for sosoomemem ooof f f ththhee inncococonsnn isisstetetencncncy y ininin ppprereevvvioioioususs fffininndidingngngs.s.s. FFFurururthththerrrmomomorerere, , a a a nunun mbmbmbererer ooof f prior


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procedural data that were collected for PREVENT IV. Finally, whereas prior studies have

assessed VGF at either the graft- or patient-level, we examined both, as each provides useful and

potentially different information. We found that the factors associated with VGF in patient-and

graft-level models were almost identical.

We found a number of surgical factors that were associated with VGF. Pathologic studies

have demonstrated that atherosclerosis is the main etiology of late (more than 12 months) VGF,

whereas early (less than 1 month) and subacute (up to 12 months) graft failure is due to

thrombosis, surgical technical errors, and intimal hyperplasia.31 Intraoperative processes of vein

graft harvesting, graft manipulation, and graft implantation can all lead to endothelial

dysfunction, inflammation, and ultimately thrombosis and graft occlusion.15 Accordingly, there

is mechanistic feasibility to explain our study results. Longer duration of surgery may reflect

technical difficulty, thus contributing to risk of VGF. Endoscopic vein graft harvesting, though

less invasive than open vein graft harvesting, can damage vein graft endothelium, causing

inflammation and thrombosis with early graft failure or increased intimal hyperplasia and

subacute VGF. Observational data regarding the benefits of endoscopic vein harvesting are

mixed, with some studies reporting associations of this technique with VGF and worse

outcomes,26,27,32 while others have not confirmed these findings.33,34 Definitively determining

whether endoscopic graft harvesting is associated with VGF will require a prospective

randomized clinical study. The Randomized Endo-Vein Graft Prospective (REGROUP) Trial

(ClinicalTrials.gov: NCT01850082) which is currently under development will provide

important insight into this topic.

We also found that poor target artery quality was associated with VGF. In PREVENT IV,

assessments of target artery quality were based on qualitative surgeon judgment and not

dysfunction, inflammation, and ultimately thrombosis and graft occlusion.15 Acccooordidid ngngnglylyly, , thththerere

s mechanistic feasibility to explain our study results. Longer duration of surgery may reflect

eechchhnininiccacalll dididiffffffiicululltytyty, , thus contributing to risk of VVVGFGF. Endoscopic c vev inn gggrraraft harvesting, though

eessss iinvasive ththaann oopepenn veveveininin gggrraraftft hhhaararvvvessstinggg, ccan ddaamamaaggege vvveieiin n gggraafaft t enenndoooththeleeliiuium,m, ccauaua ssis ngngng

nnflflflamamammamam titiiononon aanndd ttthrhromomombobosiisss wiwiwiththth eeeararlylyl gggrararaft fafafailillururre e ooor iiincncncrereasasaseedd ininintitit mmamal l hyhyypepeperprpplalalassisia aanand d d

ubacute VGFGFF. ObObObseseservrvvatata iooonananal l l dadadatatata rrregege ararardididingngng ttthhhe e bebebenenen fiitststs ooof f f enenendododoscccopopopicicic vvveieiein n n hahaharvrvrvesesestititingn are


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systematic classification. However, this qualitative rating likely incorporates the elements of

smaller vessel diameter that might reflect challenging surgical anatomy and poor distal run-off,

which has been previously associated with VGF.7

Two of the factors significantly associated with VGF in our analyses were not related to

the surgical procedure. The first was a clinical history of cerebrovascular disease, which was

associated with VGF in the graft-level model. Cerebrovascular disease may represent a marker of

both more advanced vascular disease and also poor target vessel distal run-off. We also found

that use of clopidogrel or ticlopidine at 30 days was associated with an increased risk of VGF.

Given the pathologic contribution of thrombosis to early VGF, antiplatelet therapy would be

expected to reduce VGF, and randomized data support the use of aspirin to reduce graft

failure.35,36 In this study, since use of antiplatelet therapy was not randomized, we hypothesize

that the relationship between antiplatelet therapy and VGF is likely due to confounding. Data to

support the use of clopidogrel to improve early venous graft patency after CABG are limited,29,37

and clopidogrel is more frequently prescribed to patients with acute coronary syndrome, patients

undergoing off-pump CABG, or patients with extensive coronary artery disease.38,39

In our study, the majority of VGF events were clinically silent. Only 7.1% of the patients

with VGF had VGF identified during early repeat angiography for clinical indications. However,

studies have demonstrated that VGF identified either during clinically-driven or routine follow-

up angiography is associated with significant morbidity.4,5,10,40,41 Thus, reducing overall VGF

after CABG is an important goal that may improve patient outcomes and the durability of CABG

surgery.

Research efforts to date have focused on a multifaceted approach to prevent VGF,

including modifications in patient behavior, especially smoking cessation, and exploration of

expected to reduce VGF, and randomized data support the use of aspirin to reduuccce gggraaftftft

failure.35,36 In this study, since use of antiplatelet therapy was notf randomized, we hypothesize

hhatatt ttthehehe rrelelelatatatioionsshihihipp between antiplatelet therapyyy aannnd VGF is likelelly y duuee e ttoto confounding. Data to

uuppppport the usse e oofo clolopipp dododoggrgrelelel ttoo iiimpmpmprooovve eaaarllyy veenenoouss s ggrgrafafft ppapateteennccy y afafa teeer CACACABGBGG arrere lllimimmitititededed,229,2 37

anndd d clclclopopopididogogogrerell iiis mmorore e frfreqequuuennntltltly y y pprpreesscrcrcribibibeeded tttooo ppapatitienenntstss wwwiith hh acaccututteee cocoororonanaryryry sssynynyndrdrdromomme, ppatattieienntnts

undergoing ooffffff-p-ppumumump p p CACAC BGBGBG,,, ororr pppatattieii ntntnts s wiwiwiththth eeextxtxtenene sisis veee cccororo onononararary yy arararteteeryryry dddisisiseaeasesese...383838,393939


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optimal postoperative antiplatelet regimens, as a large proportion of CABG patients are resistant

to aspirin.15 Given the wide range of predicted VGF risk of our model, these data might help to

identify patients at higher risk for VGF who might be considered for CABG with non-vein graft

conduits and who should be followed more closely for post-CABG VGF events. However, some

of the factors associated with VGF in our study are non-modifiable, suggesting that the greatest

use of our data may be to help direct further research into strategies to prevent VGF. The high

rate of VGF also emphasizes the importance of investigational surgical techniques to reduce vein

graft injury, such as external vein graft support through either stenting or fibrin glue, exploration

of novel gene-based molecular therapies to reduce VGF, and the development of synthetic, non-

vein graft conduits.15

Limitations

This is a retrospective, post-hoc analysis. We assessed VGF at routine angiography 12–18

months after CABG, and the predictors of VGF may change over time. We were not able to

assess VGF in patients who died prior to angiography or who did not return for protocol-

mandated angiography and have excluded these patients from the analysis. We chose to study

VGF and did not include arterial conduits in our analysis. The factors associated with arterial

graft failure may differ.19,20,42 Some other factors that have previously been associated with vein

graft patency were not collected in PREVENT IV.11,28,30,35 PREVENT IV only included patients

undergoing first-time CABG, and the vein graft handling techniques and pressurized delivery

system used in PREVENT IV were unique to the trial. Although our models fit the data well

(Hosmer-Lemeshow p=0.85), there was low discriminatory power (C-statistic 0.61). We also

included use of clopidogrel and ticlopidine in sensitivity analyses, though these were post-

baseline variables that might be associated with non-VGF factors. We were not able to account

vein graft conduits.15

Limitations

Thhisisis iiisss aa rereretrtrtrooospepeectctctivive, post-hoc analysis. We asssssesese ssed VGF at rououutinee aaanngngiography 12–18

mmonntnths after CCABABA G,G, aaandndd ttthehehe pppreredddicicicttotorrs oof VGVGVGF mamamayy chchhaananggge ooveveer ttimimee. WWWe e wewwerere nnnototot aablblb eee totoo r

asssesesesssss VVVGFGFF iiinn papapatiiienenttss wwwhoh dddieieddd prprpriioior r totoo aaannnggigiogogograraaphphhy y orrr wwwhohoho dddididd nnnototo rrretetururu n nn fofoor r r prprprotototoccolol--

mandated angngngioioiogrgrgrapapaphyhyhy aaanddd hhhavava e e e exexe clclc ududdededd ttthehehesesee pppaaatitiienene tstss fffrororom m m thththe ee anananalalalysysysisisis.. WeWeWe ccchohohosesee to study


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for clustering by specific surgeon, as these data were not available. Finally, it should be

recognized that both the study timeframe and identification of VGF based on routine

angiography impacted the selection of collected data elements, and strategies to reduce VGF

have evolved since the time of this study15; all of these factors may limit the generalizability of

our results.

Conclusions

VGF is common and associated with both patient and surgical factors including, poor target

artery quality, longer duration of surgery, use of endoscopic vein harvesting, use of clopidogrel

or ticlopidine, and cerebrovascular disease. These data may be useful in identifying patients with

risk factors for VGF and to inform the development of strategies to prevent VGF. Further

investigation of VGF should be pursued in contemporary datasets.

Funding Sources: PREVENT IV was funded by Corgentech, Inc, San Francisco, CA. Dr. Hess

and Ms. Hager are supported by the National Institutes of Health (CNH: grant 5T32HL069749-

09, RH: grant T32HL079896). Dr. Alexander is supported in part by grant U01-HL088953 from

the National Institutes of Health Cardiothoracic Surgical Trials Network. The authors are solely

responsible for the design and conduct of this study, study analyses the drafting and editing of

the manuscript, and its final contents.

Conflict of Interest Disclosures: Dr. Lopes reports institutional research funding from Bristol-

Myers Squibb and GlaxoSmithKline; consulting for AstraZeneca, Bayer, Boehringer Ingelheim,

Bristol-Myers Squibb, and Pfizer. Dr. Califf’s disclosures are available at

https://www.dcri.org/about-us/conflict-of-interest/COI-Califf_Jan-Mar2013.pdf. Dr. Peterson

reports research funding from Eli Lilly & Company, Ortho-McNeil-Janssen Pharmaceuticals,

Inc., Society of Thoracic Surgeons, American Heart Association, American College of

Cardiology (all significant); consulting for AstraZeneca, Boehringer Ingelheim, Genentech,

or ticlopidine, and cerebrovascular disease. These data may be useful in identifyyininnggg paaatititienenentststs wwith

isk factors for VGF and to inform the development of strategies to prevent VGF. Further

nnveveestststigigigatatatioioionn off VVVGGGF should be pursued in contemememppporary datasetts.s.s

FuFuundndndinng SoSoururu cecees:: PRPRREEVVENENNTT T IVIV wwwasass ffununddededdd byby CCCororgegegentnteecchhh,, Innnc,, Sanann FFFraranncncisisi coco,, CCACA.. DDrDr. HeHeHess

and d MsMs. HaHager r ara e e susuppporrtet d d byby tthehe Nattioionanall InInststitutteses oof f HeHealalthh ((CNCNH:H ggrarantnt 55TT32HHL0L0696974749-9-

09, RH: grg ananntt t T3T3T32H2H2HL0L0L079797 8989896)6)6). DrDrDr. AlAA exexexanandededer rr isiss ssupupuppopportrttededed iinnn papap rrt bbby yy grgrgrananantt t U0U0U01-1-1 HLHLHL0808088953 frommm


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Johnson & Johnson, Ortho-McNeil-Janssen Pharmaceuticals, Inc., Pfizer, Sanofi-Aventis, and

WebMD (all modest). Dr. Alexander reports consulting for Sohmalution and Moerae Matrix (all

modest). The remaining authors have no conflicts to disclose.

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36. CoC llaborative overview of randomised trials of antiplatelet therapy-y -III: Reduction in venoushhroroombmbmbososisisis aannnd pppuululmmonary embolism by antiplaateteteleet prophylaxis amaa ononngg g sus rgical and medical

papaatitieeentts. BMBMMJJJ. 1919994949 ;3;3080808:2:2235353 -2-2464646...JJ

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saphenous vein bypass grafts to coronary arteries. J Thorac Cardiovasc Surg. 1993;105:605-612. 42. Desai ND, Cohen EA, Naylor CD, Fremes SE. A randomized comparison of radial-artery and saphenous-vein coronary bypass grafts. N Engl J Med. 2004;351:2302-2309. Table 1. Baseline patient characteristics according to presence or absence of VGF.

Characteristic With VGF (n=782)

Without VGF(n=1046) P Value

Age, median (IQR), yrs 63.0 (55.0–69.0) 63.0 (55.0–70.0) 0.62 Female sex 158 (20.2) 184 (17.6) 0.16 Weight, median (IQR), kg 88.7 (77.0–100.0) 88.0 (78.0–100.0) 0.57 Race: White 701 (89.6) 954 (91.2) 0.26 AF/flutter 54 (6.9) 60 (5.7) 0.31 Cancer 72 (9.2) 77 (7.4) 0.15 Prior CHF 52 (6.6%) 69 (6.6%) 0.96 Cerebrovascular disease 90 (11.5%) 88 (8.4%) 0.03 Diabetes mellitus 0.07

No diabetes 489 (62.5%) 678 (64.9%) Diabetes, no current treatment 14 (1.8%) 23 (2.2%) Diabetes, insulin treatment 85 (10.9%) 77 (7.4%) Diabetes, non-insulin treatment 194 (24.8%) 267 (25.6%)

EF, median (IQR), % 50.0 (40.0–60.0) 52.5 (43.0–60.0) 0.30 Hypercholesterolemia 169 (21.6) 254 (24.3) 0.18 Hypertension 574 (73.4) 760 (72.7) 0.72 History of liver disease 16 (2.0) 17 (1.6) 0.50 Chronic lung disease 101 (12.9) 146 (14.0) 0.52 NYHA class 0.95

I 312 (40.4) 427 (41.1) II 271 (35.1) 353 (33.9) III 131 (17.0) 177 (17.0) IV 58 (7.5) 83 (8.0)

PAD 87 (11.1) 114 (10.9) 0.88 History of renal failure 6 (0.8) 17 (1.6) 0.10 Smoking status 0.62

Never 257 (32.9) 339 (32.4) Former 345 (44.1) 483 (46.2) Current 180 (23.0) 224 (21.4)

Prior MI 343 (43.9) 432 (41.3) 0.27 Prior PCI 220 (28.1) 279 (26.7) 0.49 Data presented as no. (%), unless otherwise indicated. AF indicates atrial fibrillation; CHF, congestive heart failure; EF, ejection fraction; IQR, interquartile range; MI, myocardial infarction; NYHA, New York Heart Association; PAD, peripheral artery disease; PCI, percutaneous coronary intervention; VGF, vein graft failure.

Cerebrovascular disease 90 (11.5%) 88 (8.4%) 0.0.0.03030 Diabetes mellitus 0.0.0 0707

No diabetes 489 (62.5%) 678 (64.9%) ) Diabetes, no current treatment 14 (1.8%) 23 (2.2%) DiDiababetess, , insusulilin n treatment 85 (1010.9.9%) 7777 ((7.4%) DiDiDi bababetettesese , noon-n-n iininsulin treatment 194 (2(2(244..8%) 262677 7 ((2(25.6%)

EFEFF, mem dian (((IQIQIQR)R)R),, % % 50500 0.0.0 ((4040.00––60.0..0)0)0) 5552.2.2 55 (4(4(43.0–0–606060 0.0.0) ) ) 000.30303 HHyppepercholestererololeemmiaia 1669 ((211.6))) 2525544 (2(2244.4.3)3) 000.118 8HyHyHyppepertensiononn 5774 ((733.4)4)) 766600 0 (7(772..7)7) 00.772 HiHistststororryyy ofofof llliviviverer dddissseaeassse 161616 (((2..0)0)0 1717 (((1.1.6)6)6) 000.5500 0Chroronin c luunggg ddisi eaasese 101011 (1(( 2.9)9)) 14146 (1(1( 4.4 0)0)) 00.52 2NYHA classsss 0.95

II 313122 (4(400 4)4) 424277 (4(411 1)1)


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Table 2. Baseline procedural characteristics at the patient-level according to presence or absence of VGF.

Characteristic With VGF (n=782)

Without VGF (n=1046) P Value

Angiographic classification Per protocol angiography only 655 (83.8) 1002 (95.8) Early angiography only 64 (8.2) 0 (0.0) Early and per protocol angiographies 63 (8.1) 44 (4.2)

Maximum stenosis of any target vessel 75% 790 (72.3) 2317 (71.5) 0.61 Endoscopic vein harvest technique 468 (60.1) 531 (50.9) <0.001 Any use of composite graft 286 (36.6) 344 (32.9) 0.10 Longest graft length, median (IQR), cm 17.0 (14.3–19.3) 16.0 (14.0–19.0) 0.02 Any proximal (non-suture) 21 (2.7) 19 (1.8) 0.21 Any distal (non-suture) 23 (2.9) 27 (2.6) 0.65 Graft source* 0.32

Arm vein 0 (0.0) 2 (0.2) Lesser saphenous 12 (1.5) 22 (2.1) Greater saphenous 770 (98.5) 1022 (97.7)

Worst target artery quality <0.01 Good 308 (39.4) 484 (46.3) Fair 281 (36.0) 363 (34.7) Poor 192 (24.6) 198 (18.9)

Worst graft quality 0.12 Good 537 (68.7) 764 (73.1) Fair 206 (26.3) 237 (22.7) Poor 39 (5.0) 44 (4.2)

Use of cardiopulmonary bypass 617 (78.9) 825 (78.9) 0.99 Pump time, median (IQR), min 95.0 (62.0–123.0) 86.0 (51.0–111.0) <.0001 Cross-clamp time, median (IQR), min 60.0 (33.0–78.0) 53.0 (30.0–72.0) 0.01 Surgical time, median (IQR), min 240.0 (201.0–284.0) 221.0 (186.0–261.0) <.0001 Type of procedure 0.66

Emergent/salvage 20 (2.6) 32 (3.1) Urgent 373 (47.7) 480 (45.9) Elective 389 (49.7) 533 (51.0)

Data presented as no. (%), unless otherwise indicated. IQR indicates interquartile range; VGF, vein graft failure. * For patients with multiple graft sources, the “worst” source according to the following hierarchy was used (worst status listed first): arm vein, lesser saphenous vein, greater saphenous vein

Arm vein 0 (0.0) 2 (0.2.2)) ) Lesser saphenous 12 (1.5) 22 (2.2 1)1)1) Greater saphenous 770 (98.5) 1022 (97.7)

Worst target artery quality <0.0GoGoGoododod 33308 (39.4) 484 (46.3) FFaFairi 22281 (3(3( 6.6.0)0 36363 (((3434.7.7) ) PPoor 11922 2 ((2(24.4.6))) 11989898 ((18188.9.9.9) ) )

WWWorrsrst graft quququaliityyy 000.1GoGoGoododod 5353537 7 7 (6(6(68.8.8.7)7)7) 77646464 (((737373.1.1.1))) FaFaFairirir 202020666 (2(2(266.6.3)3)3) 222373737 (((222222 7.7.7))) Poor 39393 (((5.55 0)0)0) 44444 (((4.44 2)2)2)


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Table 3. Factors associated with patient-level VGF.

Variable Chi-Square OR 95% CI P Value Without 30-day medications*

Duration of surgery (per 10-min increase) 34.66 1.05 1.03–1.07 <0.0001 Endoscopic harvest technique (vs. open) 14.07 1.44 1.19–1.75 <0.0001 Worst target artery quality (vs. good)

Fair Poor

3.72 8.35

1.24 1.45

1.00–1.53 1.13–1.87

0.05

<0.01 Including 30-day medications

Duration of surgery (per 10-min increase) 32.51 1.05 1.03–1.07 <0.0001 Endoscopic harvest technique (vs. open) 12.16 1.41 1.16–1.71 <0.001 Worst target artery quality (vs. good)

Fair Poor

3.13 7.55

1.22 1.43

0.98–1.51 1.11–1.84

0.08

<0.01 Clopidogrel or ticlopidine use 6.62 1.35 1.07–1.69 0.01

CI indicates confidence interval; OR, odds ratio. *1817 patients with non-missing covariates were included in the “without 30-day medications” model, and 1812 patients were included in the “30-day medications” model.

Table 4. Factors associated with graft-level VGF.

Variable Chi-Square OR 95% CI P Value Without 30-day medications*

Duration of surgery (per 10-min increase) 27.3 1.04 1.02–1.05 <0.0001 Endoscopic harvest technique (vs. open) 14.03 1.37 1.16–1.62 <0.001 Target artery quality (vs. good)

Fair Poor

9.85 59.19

1.31 2.34

1.11–1.56 1.89–2.91

<0.01

<0.0001 History of cerebrovascular disease 5.82 1.39 1.06–1.81 0.02

Including 30-day medications Duration of surgery (per 10-min increase) 25.30 1.03 1.02–1.05 <0.0001 Endoscopic harvest technique (vs. open) 12.17 1.35 1.14–1.59 <0.001 Target artery quality (vs. good)

Fair Poor

9.35 58.29

1.31 2.34

1.10–1.55 1.88–2.91

<0.01

<0.0001 History of cerebrovascular disease 4.92 1.35 1.04–1.77 0.03 Clopidogrel or ticlopidine use 7.10 1.30 1.07–1.58 <0.01

CI indicates confidence interval; OR, odds ratio. *4288 grafts over 1813 patients with non-missing covariates were included in the “without 30-day medications” model, and 4279 grafts over 1808 patients were included in the “30-day medications” model.

CI indicates confidence interval; OR, odds ratio. 1817 patients with non-missing covariates were included in the “without 30-day medications” mmmododdeel, anand dd 18181811212

patients were included in the “30-day medications” model.

TaTaablblblee e 4.4 FaFaactctctorss asassos ciated with graft-level VGGFF..

VVaV rririable CChhii-Squququararare OOOR 99595%% CICICI PP VVaaluPWiWiWiththhououo t t 3030-d-d-dayay mmedediciccatattioonsss*

DuDuD raratititionon oof ff surgrgerery ((p(pere 1100-0- imimin n iincrcreaeasese))) 27272 .33.3 111 0.0.044 1.1.020202–11–1.00555 <0<00 0.0.000000Enddoscopopicicic hharararvevev ststs tteccchnhnhniqiqueueue ((vsvsv . opopo enenen))) 14141 .0.0333 1.1.373737 11.1.116–6–6 1.1.1.626262 <0.00001TaTargrgetet aartrtereryy ququalalitityy (v(vss ggooood)d)


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Figure Legends:

Figure 1. Flowchart of patient selection for the final analysis population.

Figure 2. Distribution of predicted VGF risk. Shown is the distribution of predicted risk of VGF

using the full (including 30-day medication use) graft-level VGF model among the patient

cohort. Listed above each bar is the observed probability of VGF. IQR, interquartile range; VGF,

vein graft failure.


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AlexanderEnglum, Michael Mack, Robert Califf, Nicholas T. Kouchoukos, Eric D. Peterson and John H.

Connie N. Hess, Renato D. Lopes, C. Michael Gibson, Rebecca Hager, Daniel M. Wojdyla, Brian R.PREVENT IV

Saphenous Vein Graft Failure after Coronary Artery Bypass Surgery: Insights from

Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright © 2014 American Heart Association, Inc. All rights reserved.

is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231Circulation published online September 26, 2014;Circulation.

http://circ.ahajournals.org/content/early/2014/09/25/CIRCULATIONAHA.113.008193World Wide Web at:

The online version of this article, along with updated information and services, is located on the

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SUPPLEMENTAL MATERIAL

Knot point selection for non-linear variables encountered during model variable selection

Patient-level model

The following variables were found to be non-linear: aorta cross-clamp time (acctime),

pre-operative ejection fraction (ef), and longest graft length (pglen). Each one was split

into 3 linear pieces with the cutoff points chosen appropriately. The definition for each

spline follows:

We entered each variable if it was significant (<0.1) in a logistic regression model including only

the other levels of the variable. The variables included in our model were acctime_low,

acctime_mid, ef_mid, ef_high, and pglen_mid. Variables were allowed to enter the model

separately.

Graft-level model

The following variables were found to be non-linear: aorta cross-clamp time (acctime),

pre-operative ejection fraction (ef), and time on bypass pump in minutes (pumptime).

Acctime and ef were split into 3 linear pieces with 2 cutoffs, while pumptime was split

into 2 linear pieces with 1 cutoff. The definition for each spline follows:

We entered each variable if it was significant (<0.1) in a logistic regression model

including only the other levels of the variable. Variables included in our model were

acctime_low, acctime_mid, ef_low, ef_mid, ef_high, and pumptime_high. Variables were

allowed to enter the model separately.

7373

Summary

배경

관상동맥우회술(coronary artery bypass grafting, CABG)의

성공은 복재정맥의 이식 실패(vein graft failure, VGF)에 의해

제한된다. VGF와 관련된 요인들을 이해하면 환자의 임상 결과

를 향상시킬 수 있을 것이다.

방법 및 결과

PREVENT IV(Project of Ex Vivo Vein Graft Engineering

via Transfection IV) 연구에 참여한 1,828명의 환자를 대상으

로 분석을 진행하였다. 이 연구에서는 프로토콜상 의무적으로

CABG 12-18개월 이후 추적 혈관조영술을 시행하거나, 그 이

전에 임상증상이 발생하게 되는 경우 추적 혈관조영술을 시행

하게 되어 있었다. 임상 결과는 환자- 및 이식편- 수준의 VGF

(≥75% 협착 또는 폐색)가 포함되었다. 변수는 빠른 거짓 선택

평가 방법론(Fast False Selection Rate methodology)을 사

용하여 선택하였다. 연구자들은 일반화 추정 방정식을 포함 또

는 제외하는 로지스틱 회귀 분석을 사용하여 환자- 및 이식편-

수준의 모델에서 변수들과 VGF 사이의 관계를 조사하였다.

CABG 12-18개월 후 782/1,828명(42.8%)의 환자에서 VGF가

발생하였고, 1,096/4,343(25.2%)의 이식편에서 VGF가 발생하

였다. 인구 통계학적 및 임상적 특성 등은 VGF가 발생한 환자

나 그렇지 않은 환자에서 차이가 없었다. 다만, VGF 환자들은

외과적 수술 시간이 더 길었고, 목표 혈관의 상태가 좋지 않았

던 경우가 많았으며, 이식 복재정맥의 길이가 더욱 긴 경우가 많

았고, 내시경 정맥 수확을 한 경우가 많았다. 다변량 조정 후, 긴

수술 시간(10분 증가 시마다 OR, 1.05; 95% CI, 1.03-1.07), 내

시경 정맥 수확(OR, 1.41; 95% CI, 1.16-1.71), 적절치 않은 목

표 혈관 상태(OR, 1.43; 95% CI, 1.11-1.84)와 clopidogrel 또는

ticlopidine의 수술 후 사용(OR, 1.35; 95% CI, 1.07-1.69)은 환

자-수준 VGF와 관련 있었다. 이식편-수준 VGF 모델의 예측

가능성은 12.1-63.6%였다.

결론

VGF는 CABG 후 흔히 발생하며, 환자 및 수술적 요인과 관련

이 있다. 이러한 연구 결과는 VGF 위험인자를 가진 환자들을

식별하는 데 도움이 되고, VGF를 줄이기 위한 중재적 방법을

개발하는 데 중요한 정보를 제공해 줄 것으로 보인다.

관상동맥우회술 후 이식한 복재정맥의 재협착이나 폐쇄는 흔하며, 환자 및 수술적 요인과 관련이 있다

: PREVENT IV 연구로부터의 견해

나 승 운 교수 고려대학교 구로병원 순환기내과

Coronary Artery Disease

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