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Research Article
Originally Published 19 September 2022
Free Accessfeatured article

Prognostic Value of Measuring Fractional Flow Reserve After Percutaneous Coronary Intervention in Patients With Complex Coronary Artery Disease: Insights From the FAME 3 Trial

Zsolt Piroth, MD, PhD https://orcid.org/0000-0001-9256-1267, Hisao Otsuki, MD, Frederik M. Zimmermann, MD, Tamás Ferenci, PhD https://orcid.org/0000-0001-6791-3080, Danielle C.J. Keulards, MD, PhD, Alan C. Yeung, MD, Nico H.J. Pijls, MD, PhD, Bernard De Bruyne, MD, PhD https://orcid.org/0000-0001-6567-168X, and William F. Fearon, MD https://orcid.org/0000-0003-1799-1368 [email protected] on behalf of the FAME 3 InvestigatorsAuthor Info & Affiliations
Circulation: Cardiovascular Interventions
Volume 15, Number 11
https://doi.org/10.1161/CIRCINTERVENTIONS.122.012542
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Abstract

Background:

We evaluate the prognostic value of measuring fractional flow reserve (FFR) after percutaneous coronary intervention (post-PCI FFR) and intravascular imaging in patients undergoing PCI for 3-vessel coronary artery disease in the FAME 3 trial (Fractional Flow Reserve versus Angiography for Multivessel Evaluation).

Methods:

The FAME 3 trial is a multicenter, international, randomized study comparing FFR-guided PCI with coronary artery bypass grafting in patients with multivessel coronary artery disease. PCI was not noninferior with respect to the primary end point of death, myocardial infarction, stroke, or repeat revascularization at 1 year. Post-PCI FFR data were acquired on a patient and vessel-related basis. Intravascular imaging guidance was tracked. The primary end point is a comparison of target vessel failure (TVF) defined as a composite of cardiac death, target vessel myocardial infarction, and target vessel revascularization at 1 year based on post-PCI FFR values. Cox regression with robust SEs was used for analysis.

Results:

Of the 757 patients randomized to PCI, 461 (61%) had post-PCI FFR measurement and 11.1% had intravascular imaging performed. The median post-PCI FFR was 0.89 [IQR‚ 0.85–0.94]. On a vessel-level, post-PCI FFR was found to be a significant predictor of TVF univariately (hazard ratio=0.67 [95% CI‚ 0.48–0.93] for 0.1 unit increase, P=0.0165). On a patient-level, the single lowest post-PCI FFR value was also found to be a significant predictor of TVF univariately (hazard ratio=0.65 [95% CI‚ 0.48–0.89] for 0.1 unit increase, P=0.0074). Post-PCI FFR was an independent predictor of TVF in multivariable analysis adjusted for key clinical parameters. Outcomes were similar between patients who had intravascular imaging guidance and those who did not.

Conclusions:

Post-PCI FFR measurement was a significant predictor of TVF on a vessel and patient level and an independent predictor of outcomes in a population with complex 3-vessel coronary artery disease eligible for coronary artery bypass grafting. The limited use of intravascular imaging did not affect outcomes.

Registration:

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02100722.

Graphical Abstract

What is Known

•
Measuring post-percutaneous coronary intervention fractional flow reserve has been shown to correlate with outcomes in most studies of patients with less complex coronary disease.
•
The impact of intravascular imaging in patients with complex coronary disease undergoing percutaneous coronary intervention remains poorly studied.

What the Study Adds

•
We found that post-percutaneous coronary intervention fractional flow reserve measurement was a significant predictor of target vessel failure on a vessel and patient level.
•
Post-percutaneous coronary intervention fractional flow reserve was an independent predictor of outcomes in a population with complex coronary disease eligible for coronary artery bypass grafting.
•
The limited use of intravascular imaging did not affect outcomes.
Measuring fractional flow reserve (FFR) is a guideline-directed method for assessing the functional relevance of an epicardial stenosis and determining the need for coronary revascularization. Assessing FFR immediately after percutaneous coronary intervention (PCI) (post-PCI FFR) has been shown to have prognostic value; however, the results of the published studies are mixed.1–6 The prognostic value of post-PCI FFR has not been extensively studied in patients with complex 3-vessel coronary artery disease (CAD) eligible for coronary artery bypass grafting (CABG). The impact of intravascular imaging (intravascular ultrasound [IVUS] or optical coherence tomography [OCT]) in this setting is also poorly understood. Therefore, we sought to evaluate the prognostic value of post-PCI FFR and intravascular imaging in patients undergoing PCI for 3-vessel CAD in the FAME 3 trial (Fractional Flow Reserve versus Angiography for Multivessel Evaluation).

Methods

The rationale and design7 as well as the primary results of the FAME 3 trial8 have been published. In brief, the FAME 3 trial is a multicenter, international, randomized study comparing FFR-guided PCI with current generation drug-eluting stents with CABG in patients with angiographically defined 3-vessel CAD not involving the left main. Patients could have chronic or acute coronary syndrome, and only recent ST-segment–elevation myocardial infarction, cardiogenic shock, and severe left ventricular dysfunction (EF<30%) were exclusion criteria. PCI was not shown to be noninferior with respect to the primary end point of death, myocardial infarction (MI), stroke, or repeat revascularization at 1 year. Investigators were requested to measure post-PCI FFR and IVUS/OCT guidance was tracked. Patients were followed-up at discharge, 1, 6, and 12 months for clinical events that were adjudicated by a Clinical Events Committee whose members were unaware of the patient allocation.
The data that support the findings of this study are available from the corresponding author upon reasonable request. The study was approved by each site’s institutional review committee and the subjects gave informed consent.

End Points

The primary end point of the present analysis is a comparison of target vessel failure (TVF) defined as a composite of cardiac death, target vessel MI, and target vessel revascularization (TVR) at 1 year. In the present analysis, we did not count periprocedural MI. We performed a vessel-level analysis to study the value of post-PCI FFR to predict TVF. If FFR was measured both in the main vessel and its side branch (eg, in the left anterior descending [LAD] and the diagonal) after PCI, only the value of the main vessel FFR was used in the analysis. In the vessel-level analysis, death of the patient was assigned to all vessels. A patient-level analysis was also performed. In patients with multiple vessels with post-PCI FFR measurement, the lowest of these post-PCI FFR values was utilized. In the patient-level analysis, outcome on any vessel was assigned to the patient, with its time being the smallest of all vessels of the given outcome. The third aim was to study the impact of the use of intravascular imaging (IVUS or OCT) on the occurrence of the composite of cardiac death, MI, and repeat revascularization.

Statistical Analysis

Continuous variables are presented as mean±SD; categorical data are presented as numbers and percentages. Comparisons between continuous variables were performed using Student t test. Comparisons between categorical variables were evaluated using Pearson χ2. The predictors of post-PCI FFR were investigated by deriving the regression coefficients in a multiple linear regression model. The covariates were selected based on clinical relevance and information according to the previous studies, and were the following: sex, diabetes, LAD location, baseline FFR, minimum stent diameter, and total stent length. Time to TVF was multivariable modeled on vessel-level with Cox proportional hazards model using key clinical variables as covariates. Robust SEs with the Huber-White method were used with clusters set to patients to correct for the dependence of observations coming from the same patient. For patient-level analysis, this reduces to “sandwich” covariance matrix estimation. Cox models are characterized by the c-index (equivalent to the area under the receiver operating characteristic curve in the univariate dichotomous case). Linearity was checked with spline-expansion, followed by an F-test.9 Patients without events were censored at 1 year (365 days). A P value of <0.05 was considered statistically significant. Statistical analyses were performed using JMP statistical software (JMP Statistical Discovery LLC, Cary, NC) and R statistical environment version 4.2.1 (R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria).

Results

Post-PCI FFR

Of the 1500 patients in the FAME 3 trial, 757 were randomized to the FFR-guided PCI arm. Of these, 461 (61%) had post-PCI FFR measurement: 197 (42.7%) had 1, 194 (42.1%) had 2, and 70 (15.2%) had 3-vessel FFR assessment immediately after PCI. Of note, all values in this analysis are the final FFR after which no further intervention was performed. Of the studied vessels, 382 (48.1%) were in the LAD artery, 193 (24.2%) were in the left circumflex, and 220 (27.6%) were in the right coronary artery (Figure S1). Baseline characteristics of those who underwent post-PCI FFR with those who did not are summarized in Table 1. These 2 populations were similar, with only previous PCI occurring slightly more frequently among those who had no post-PCI FFR measurement. The distribution of post-PCI FFR values is shown in Figure S2; the median FFR was 0.89 (IQR 0.85–0.94). Of note, 72 vessels (9.1%) had a post-PCI FFR of 0.80 or less. The median post-PCI FFR in the LAD was 0.87 (IQR 0.83–0.90), whereas in non-LAD vessels it was 0.92 (IQR 0.88–0.96). Figure S3 shows the distribution of the single lowest post-PCI FFR of the patients; the median value was 0.86 (IQR 0.83–0.90). On multiple regression analysis, male sex, LAD location, minimum stent diameter, and total stent length were found as significant predictors of post-PCI FFR (Table 2). Of note, pre-PCI FFR and diabetes were not significant predictors.
Table 1. Baseline Characteristics of the Patients With and Without Post-PCI FFR
CharacteristicPCI (n=757)
Post PCI FFR (−); N=296Post PCI FFR (+); N=461P value
Age, years65.3±8.865.1±8.50.85
Male sex, no. (%)247 (83.4)369 (80.0)0.24
White/Caucasian, no. (%)272 (91.9)439 (95.2)0.06
Body mass index, kg/m228.7±4.628.6±4.50.95
Diabetes, no. (%)85 (28.7)129 (28.0)0.83
 Insulin dependent24 (8.1)31 (6.7)0.47
 Noninsulin dependent61 (20.6)98 (21.3)0.83
Hypertension, no. (%)215 (72.9)323 (70.1)0.40
Dyslipidemia, no. (%)211 (71.5)310 (67.3)0.21
Smoking status, no. (%)
 Current tobacco user61 (20.7)84 (18.2)0.42
 Previous tobacco user111 (37.6)185 (40.1)0.47
Family history of CAD, no. (%)97 (32.9)149 (32.3)0.87
Previous MI, no. (%)93 (31.5)159 (34.5)0.40
Previous PCI, no. (%)49 (16.6)49 (10.6)0.02
History of TIA/CVA, no. (%)25 (8.5)24 (5.2)0.08
Renal disease (MDRD<60 mL/min/1.73 m2); no. (%)17 (5.8)20 (4.3)0.38
Noninvasive test for ischemia126 (42.7)185 (40.1)0.48
Ejection fraction≤50%, no. (%)44 (14.9)93 (20.3)0.06
Hospitalized with NSTEMI, no. (%)69 (23.3)128 (27.8)0.17
Values are expressed as mean±SD or n (%). The body-mass index is the weight in kilograms divided by the height in meters squared. CAD indicates coronary artery disease; CVA, cerebrovascular accident; FFR, fractional flow reserve; MDRD, modification of diet in renal disease; MI, myocardial infarction; NSTEMI, non–ST-segment–elevation myocardial infarction; PCI, percutaneous coronary intervention; and TIA, transient ischemic attack.
Table 2. Predictors of Post-PCI FFR
VariablePartial regression coefficient95% CIP value
Male sex−0.012−0.018 to −0.006<0.001
Diabetes0.004−0.002 to 0.0100.15
LAD−0.024−0.029 to −0.019<0.001
Baseline FFR0.025−0.012 to 0.0620.18
Minimum stent diameter0.0200.009 to 0.031<0.001
Total stent length−0.0004−0.0006 to −0.00010.006
FFR indicates fractional flow reserve; LAD, left anterior descending coronary artery; and PCI, percutaneous coronary intervention.
In this analysis, follow-up at 1 year was complete in 100%. On a vessel-level, post-PCI FFR was found to be univariately a significant predictor of TVF (hazard ratio=0.67 [95% CI‚ 0.48–0.93] for 0.1 unit increase, P=0.0165, c=0.60) (Table 3). Results of the ROC-analysis are shown in (Figure S4), with 0.88 being the best post-PCI FFR cut-off according to the Youden-index to predict TVF. At this cutoff value, post-PCI FFR was a significant predictor of TVF (Figure 1). Of note‚ the hazard ratios of all components of TVF (cardiac death‚ target vessel MI‚ and TVR) were <1 and the difference in cardiac death was statistically significant (Table 3). There was a progressive and significant decrease in TVF rates as post-PCI FFR values increased (Figure S5). When evaluating the change in FFR from pre-PCI to post-PCI, the TVF rate was significantly higher in vessels with a % change in FFR≤15% compared with >15% (Figure S6).
Table 3. Univariate Association of Post-PCI FFR on Different Outcomes at Vessel-Level or Patient-Level
TypeOutcomeHR95% CIP valuec-indexLinearity
Vessel-levelTVF (cardiac death, TVMI, TVR)0.670.48–0.930.0170.600.226
Cardiac death0.810.66–0.980.0290.620.187
TVMI0.720.45–1.160.180.610.135
Cardiac death+TVMI0.750.55–1.040.0850.610.405
TVR0.640.41–1.000.0510.570.074
Patient-levelTVF (cardiac death, TVMI, TVR)0.650.48–0.890.0070.630.383
Cardiac death0.890.70–1.140.360.600.031
TVMI0.720.50–1.050.0850.640.502
Cardiac death+TVMI0.770.56–1.040.0840.630.559
TVR0.600.42–0.860.0050.640.223
P values were calculated with Wald test. c-index characterizes the goodness of the model (it is equivalent to the area under the receiver operating characteristic curve in the univariate dichotomous case). A linearity P>0.05 indicates that there was no significant deviation from linearity. Robust covariance matrix estimation was used with clusters set to patients. Analyses pertain to 0.1 increase in post-PCI FFR. FFR indicates fractional flow reserve; HR, hazard ratio; PCI, percutaneous coronary intervention; TVF, target vessel failure; TVMI, target vessel myocardial infarction; and TVR, target vessel revascularization.
Figure 1. Kaplan-Meier curves for target vessel failure rates based on post-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) (vessel-level).
P values pertain to testing the difference of the dichotomized predictor, using robust covariance matrix estimation with the clusters set to the patients. TVF indicates target vessel failure.
On a patient-level, the single lowest post-PCI FFR value was found to be a univariately significant predictor of TVF (hazard ratio=0.65 [95% CI‚ 0.48–0.89] for 0.1 unit increase, P=0.0074, c=0.63) (Table 3), where the target vessel included any vessel with a post-PCI FFR measurement. Results of the ROC analysis are shown in (Figure S4), with 0.85 being the best single lowest patient-level post-PCI FFR cut-off according to the Youden-index to predict the primary end point. At this cutoff value, post-PCI FFR was a significant predictor of TVF (Figure 2). Of note‚ the hazard ratios of all components were <1 and the difference in TVR was statistically significant (Table 3). When comparing the cardiac death, all MI, and repeat revascularization rate at 1 year in patients who had post-PCI FFR measured with those who did not, there was no significant difference (log-rank P=0.15; Figure 3).
Figure 2. Kaplan-Meier curves for target vessel failure rates based on post-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) (patient-level).
P values pertain to testing the difference of the dichotomized predictor, using robust covariance matrix estimation with the clusters set to the patients. TVF indicates target vessel failure.
Figure 3. Outcomes of patients who had post-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) measured compared with those who did not during PCI.
We used uni- and multivariable Cox proportional hazard models to determine the independent predictors of the composite of cardiac death‚ target vessel MI, and TVR on a vessel-level. On univariable analysis, Caucasian race, previous MI, history of TIA/CVA, renal disease, and NSTEMI were found to be significant predictors in addition to the single lowest post-PCI FFR (Table 4). On multivariable analysis, only renal disease (hazard ratio‚ 5.71 [95% CI‚ 1.91–17.1]; P=0.002) and post-PCI FFR as a continuous variable (hazard ratio per 0.1 increase 0.67 [95% CI, 0.49–0.91]; P=0.03) emerged as significant predictors. A supplemental analysis applying a LASSO-regularization to the Cox proportional hazards model found similar results (Supplemental Material and Table S1).
Table 4. Univariable Cox Proportional Hazard Models for a Composite of Cardiac Death‚ TVMI, and TVR (Vessel-Level)
CovariateHRCIP valuec-index
Age (per 1 increase)1.020.98–1.060.270.55
Male sex0.440.13–1.440.170.55
White/Caucasian0.200.08–0.530.0010.56
Body mass index (per 1 increase)0.960.88–1.040.310.56
Diabetes1.860.90–3.870.090.57
Hypertension1.420.61–3.310.420.53
Dyslipidemia1.740.75–4.060.200.56
Current tobacco user0.740.28–1.920.530.52
Previous myocardial infarction0.270.09–0.760.010.62
Previous PCI0.990.30–3.240.980.50
History of TIA/CVA3.841.53–9.640.0040.56
Renal disease6.202.55–15.0<0.0010.58
Ejection fraction ≤50%0.780.30–2.050.610.52
Hospitalized with NSTEMI0.340.12–0.980.0460.59
Number of stents (per 1 increase)1.130.74–1.730.580.53
Total length of stents placed (per 10 mm increase)1.040.88–1.220.660.52
Single lowest post-PCI FFR (per 0.1 increase)0.670.49–0.910.0110.60
P values were calculated with Wald test. c-index characterizes the goodness of the model (it is equivalent to the area under the receiver operating characteristic curve in the univariate dichotomous case). Robust covariance matrix estimation was used with clusters set to patients. Variables with P<0.05 by the univariable analyses were included in the multivariable analysis. Single lowest post-PCI FFR as a continuous was analyzed. CVA indicates cerebrovascular accident; FFR, fractional flow reserve; HR, hazard ratio; NSTEMI, non–ST-segment–elevation myocardial infarction; PCI, percutaneous coronary intervention; TIA, transient ischemic attack; TVMI, target vessel myocardial infarction; and TVR, target vessel revascularization.
Since the LAD was found to be a significant, independent predictor of post-PCI FFR, with a median value 0.05 units lower than in non-LAD vessels, we also studied LAD versus non-LAD territories separately. In the LAD, by ROC analysis, the AUC was 0.56 (95% CI‚ 0.41–0.71), whereas in non-LAD vessels, the AUC was 0.62 (95% CI‚ 0.44–0.80; Figure S4).

Intravascular Imaging

Of the 757 patients randomized to FFR-guided PCI in the FAME 3 trial, 11 underwent CABG and information on intravascular imaging is missing in another 6. Of the remaining 740, overall 82 patients (11.1%) had intravascular imaging guidance during PCI (56 patients had IVUS, 21 had OCT, and 5 had both). The baseline characteristics of those undergoing intravascular imaging compared to those not having IVUS or OCT are listed in Table S2. As shown, males, patients with Type 1 diabetes, and those with a noninvasive test for ischemia before PCI were found significantly more frequently in the intravascular imaging-guided group, whereas the percentage of Caucasians in the nonimaging-guided group was significantly higher. In patients in whom intravascular imaging-guided PCI was performed, the PCI procedure was longer and more often staged and resulted in more stents and a greater total length of stents (Table 5). The rate of cardiac death, all MI, or repeat revascularization was similar between patients who had intravascular imaging guidance and those who did not (log-rank P=0.21; Figure 4).
Table 5. Procedural Characteristics of Patients With or Without Intravascular Imaging
CharacteristicPCI (n=740)
No imaging; N=658Imaging-guided; N=82P value
Time to procedure, d8.6±10.88.5±9.40.89
Procedure duration, min91.6±35.0115.7±60.8<0.001
Length of hospital stay, d4.4±4.43.7±3.70.17
Number of lesions4.3±1.34.1±1.30.19
≥1 chronic total occlusion, no. (%)137 (20.9)19 (23.2)0.63
≥1 bifurcation lesion, no. (%)448 (68.2)64 (78.1)0.07
SYNTAX score, mean25.8±7.126.3±6.70.60
 Low (0–22); no. (%)216 (33.5)19 (24.7) 
 Intermediate (23–32); no. (%)312 (48.5)47 (61.0) 
 High (>32); no. (%)116 (18.0)11 (14.3) 
PCI
 Staged procedure, no. (%)130 (19.8)34 (41.5)<0.001
 Number of stents3.6±1.84.4±2.1<0.001
 Total length of stents placed, mm; median (IQR)79 (52–114)94 (61–151.5)<0.001
Values are expressed as mean±SD, n (%), or median (IQR). IQR indicates interquartile range; PCI, percutaneous coronary intervention; and SYNTAX‚ Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery.
Figure 4. Outcomes of patients with or without intravascular imaging used during percutaneous coronary intervention.
HR indicates hazard ratio; and MI‚ myocardial infarction.

Discussion

The main finding of this study is that a low post-PCI FFR in patients with complex CAD is predictive of adverse cardiac events at 1 year. On a vessel level, low post-PCI FFR was associated with a significantly higher rate of TVF, as well as cardiac death alone. This was also seen on a patient level, where the lowest post-PCI FFR was associated with a significantly higher rate of TVF, as well as TVR alone. On multivariable analysis, only renal disease and post-PCI FFR as a continuous variable were found to be independent predictors of TVF. Moreover, in patients who had FFR measured after PCI, there was a numerically lower rate of adverse outcomes compared with those patients who did not, although it did not reach statistical significance. Interestingly, the use of intravascular imaging (IVUS/OCT) was not associated with any improvement in outcome.
Some previous reports on the prognostic value of post-PCI FFR have had conflicting results1–6; however, Rimac performed a study-level meta-analysis showing that post-PCI FFR is inversely related to major adverse cardiac events‚10 while Johnson published a patient-level meta-analysis and demonstrated a continuous inverse relationship between the two.11 Both meta-analyses involved patients undergoing PCI with both bare metal stents as well as drug-eluting stents. Given the higher clinical event rates after bare metal stent implantation and their subsequent omission from clinical practice, these analyses are less relevant to our present-day challenges. Our analysis of the post-PCI FFR values in the FAME and FAME 2 studies12 and a number of other more recent studies13–19 demonstrate the prognostic value of post-PCI FFR in the drug-eluting stents era; however, these studies did not include many patients with complex 3-vessel CAD eligible for CABG. The current study adds to the literature by demonstrating the prognostic value of post-PCI FFR on both a vessel and patient level in subjects with complex coronary disease. We also found that post-PCI FFR was a significant predictor of cardiac death alone and was an independent predictor of adverse outcomes.
Although patients were not randomized to post-PCI FFR measurement, there were no major differences in baseline characteristics between those who did and did not have post-PCI FFR measurement performed. However, there was a trend toward improved outcomes in patients who had the measurement. Unfortunately, we do not have data regarding whether these patients had further intervention performed, such as postdilation of stents, although the number and length of stented region in the post-PCI FFR group was greater (data not shown). Interestingly, the use of intravascular imaging (IVUS/OCT) did not appear to have any benefit on 1-year outcomes, if anything there was a signal toward harm. In addition, intravascular imaging resulted in a longer procedure, more stents, and longer total stented length. Of course, this analysis is limited by the fact that patients were not randomized to intravascular imaging guidance and only 11% of patients received it.
We showed that post-PCI FFR values are influenced by factors like male sex and LAD vessel location, possibly due to the larger myocardial mass subtended by the LAD. However, emerging evidence supports that this difference is partially related to hydrostatic pressure differences caused by the fact that in a supine patient, the LAD courses superiorly to the aortic root where the guiding catheter measures aortic pressure.20 Also, total stent length was related to post-PCI FFR, possibly because a longer stented segment signifies more diffuse CAD. Of note, pre-PCI FFR was not a predictor of post-PCI FFR. In the post-PCI FFR substudy of the FAME and FAME 2 trials,12 we found a statistically significant but weak correlation between the two.
Limitations of this study include that even though post-PCI FFR measurement was recommended per protocol, it was only performed in 61% of the patients undergoing FFR-guided PCI and we do not have granular data regarding pressure pullback curves. We compared baseline characteristics in those with and without post-PCI FFR assessment and found no relevant difference, but selection bias or other unmeasured confounding variables cannot be ruled out as a cause for the differences in outcomes. Furthermore, post-PCI FFR was made available to the physicians treating the patients. However, all patients had angiographically successful PCI, and the vast majority had a nonsignificant post-PCI FFR. As for intravascular imaging, only a small minority underwent IVUS or OCT assessment. Unfortunately, we do not have more granular data regarding the results of intravascular imaging.
In conclusion, we found that post-PCI FFR measurement was a significant predictor of TVF on a vessel and patient level. Post-PCI FFR was an independent predictor of outcomes in a population with complex 3-vessel CAD eligible for CABG. The limited use of intravascular imaging did not affect outcomes.

ARTICLE INFORMATION

Supplemental Material

Supplemental Statistical Analysis
Tables S1–S2
Figures S1–S6
References 21–24

Footnote

Nonstandard Abbreviations and Acronyms

CABG
coronary artery bypass grafting
CAD
coronary artery disease
DES
drug-eluting stent
FAME
Fractional Flow Reserve Versus Angiography for Multivessel Evaluation
FFR
fractional flow reserve
IVUS
intravascular ultrasound
LAD
left anterior descending
LCx
left circumflex
MI
myocardial infarction
OCT
optical coherence tomography
PCI
percutaneous coronary intervention
RCA
right coronary artery
TVF
target vessel failure
TVMI
target vessel myocardial infarction
TVR
target vessel revascularization

Supplemental Material

File (circcvint-2022-012542-t-s01.pdf)
File (circcvint-2022-012542-t-s02.pdf)
File (circinterventions_circcvint-2022-012542-t_supp2.pdf)

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Published In

Go to Circulation: Cardiovascular Interventions
Circulation: Cardiovascular Interventions
Volume 15 • Number 11 • November 2022
Pages: 884 - 891
PubMed: 36121706

Copyright

© 2022 American Heart Association, Inc.

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History

Received: 3 September 2022
Accepted: 13 September 2022
Published online: 19 September 2022
Published in print: November 2022

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Keywords

  1. coronary artery disease
  2. fractional flow reserve
  3. optical coherence tomography
  4. percutaneous coronary intervention
  5. stent

Subjects

  1. Percutaneous Coronary Intervention
  2. Revascularization

Authors

Affiliations

Zsolt Piroth, MD, PhD https://orcid.org/0000-0001-9256-1267
Gottsegen National Cardiovascular Center, Budapest‚ Hungary (Z.P.).
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Hisao Otsuki, MD
Division of Cardiovascular Medicine and Stanford Cardiovascular Institute, Stanford University, CA (H.O., A.C.Y., W.F.F.).
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Frederik M. Zimmermann, MD
Catharina Hospital, Eindhoven, the Netherlands (F.M.Z., D.C.J.K.‚ N.H.J.P.).
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Tamás Ferenci, PhD https://orcid.org/0000-0001-6791-3080
Physiological Controls Research Center, Obuda University and Department of Statistics, Corvinus University of Budapest, Hungary (T.F.).
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Danielle C.J. Keulards, MD, PhD
Catharina Hospital, Eindhoven, the Netherlands (F.M.Z., D.C.J.K.‚ N.H.J.P.).
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Alan C. Yeung, MD
Division of Cardiovascular Medicine and Stanford Cardiovascular Institute, Stanford University, CA (H.O., A.C.Y., W.F.F.).
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Nico H.J. Pijls, MD, PhD
Physiological Controls Research Center, Obuda University and Department of Statistics, Corvinus University of Budapest, Hungary (T.F.).
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Bernard De Bruyne, MD, PhD https://orcid.org/0000-0001-6567-168X
Cardiovascular Center Aalst, Aalst, Belgium and Lausanne University Centre Hospital, Switzerland (B.D.B.).
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William F. Fearon, MD https://orcid.org/0000-0003-1799-1368 [email protected]
Division of Cardiovascular Medicine and Stanford Cardiovascular Institute, Stanford University, CA (H.O., A.C.Y., W.F.F.).
Stanford University School of Medicine, Stanford Cardiovascular Institute, and VA Palo Alto Health Care System, CA (W.F.F.).
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on behalf of the FAME 3 Investigators
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Notes

Supplemental Material is available at Supplemental Material.
For Sources of Funding and Disclosures, see page 891.
This work was presented as a late breaking trial abstract at TCT Connect, September 16–19, 2022.
Correspondence to: William F. Fearon, MD, Professor of Medicine, Director of Interventional Cardiology, Stanford University School of Medicine, 300 Pasteur Dr, H2103, Stanford, CA 94305. Email [email protected]

Disclosures

Disclosures Dr Fearon receives research funding from Abbott, Medtronic, and Boston Scientific‚ and has a consulting relationship with Siemens and CathWorks‚ and stock options with HeartFlow. Dr Pijls receives research funding from Abbott, has consulting relationships with Abbott and Opsens, and stock or stock options with ASML, General Electric, HeartFlow, Hexacath, and Philips. Dr De Bruyne has stock or stock options with Edwards LifeSciences, General Electric, HeartFlow, Philips‚ and Siemens. Dr Piroth receives speaker’s fee from Abbott, Boston Scientific and OpSens. The other authors report no conflicts.

Sources of Funding

FAME 3 was an investigator-initiated study funded by research grants from Medtronic, Inc‚ and Abbott Vascular, Inc‚ and sponsored by Stanford University. This substudy was not funded.

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Prognostic Value of Measuring Fractional Flow Reserve After Percutaneous Coronary Intervention in Patients With Complex Coronary Artery Disease: Insights From the FAME 3 Trial
Circulation: Cardiovascular Interventions
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