Skip to main content
Download PDF

Diabetes does not impact the diagnostic performance of contrast-based fractional flow reserve: insights from the CONTRAST study

Cardiovascular Diabetology volume 16, Article number: 7 (2017) Cite this article

Abstract

Background

Adenosine-free coronary pressure wire metrics have been proposed to test the functional significance of coronary artery lesions, but it is unexplored whether their diagnostic performance might be altered in patients with diabetes.

Methods

We performed a post-hoc analysis of the CONTRAST study, which prospectively enrolled an international cohort of patients undergoing routine fractional flow reserve (FFR) assessment for standard indications. Paired, repeated measurements of all physiology metrics (Pd/Pa, iFR, contrast-based FFR, and FFR) were made. A central core laboratory analyzed blinded pressure tracings in a standardized fashion.

Results

Of 763 subjects enrolled at 12 international centers, 219 (29%) had diabetes. The two groups were well-balanced for age, clinical presentation (stable or unstable), coronary vessel studied, volume and type of intracoronary contrast, and volume of intracoronary adenosine. A binary threshold of cFFR ≤ 0.83 produced an accuracy superior to both Pd/Pa and iFR when compared with FFR ≤ 0.80 in the absence of significant interaction with diabetes status; indeed, accuracy in subgroups of patients with or without diabetes was similar for cFFR (86.7 vs 85.4% respectively; p = 0.76), iFR (84.2 vs 80.0%, p = 0.29) and Pd/Pa (81.3 vs 78.9%, p = 0.55). There was no significant heterogeneity between patients with or without diabetes in terms of sensitivity and specificity of all metrics. The area under the receiver operating characteristic (ROC) curve was largest for cFFR compared with Pd/Pa and iFR which were equivalent (cFFR 0.961 and 0.928; Pd/Pa 0.916 and 0.870; iFR 0.911 and 0.861 in diabetic and non-diabetic patients respectively).

Conclusions

cFFR provides superior diagnostic performance compared with Pd/Pa or iFR for predicting FFR irrespective of diabetes (clinicaltrials.gov identifier NCT02184117).

Background

Due to its multi-test validation and cost-effective improvement in clinical outcomes demonstrated by multiple randomized trials as well as observational data, physiological assessment of coronary stenoses by fractional flow reserve (FFR) has emerged as the gold standard for making revascularization decisions on stable lesions [1,2,3,4,5]. Importantly, FFR requires hyperemia, but that does add a small cost and risk [1, 6, 7]. Therefore, the CONTRAST (Can cONTrast Injection Better Approximate FFR compAred to Pure reSTing Physiology?) study recently investigated whether contrast medium could provide an easy alternative and inexpensive tool for assessing FFR (namely contrast FFR, cFFR). It demonstrated that cFFR was superior to resting measurements (rest distal pressure [Pd]/aortic pressure [Pa], and the instantaneous wave-free ratio [iFR]) in terms of diagnostic performance to predict FFR [8].

Diabetes mellitus increases cardiovascular risk, which has been attributed mainly to its detrimental effects on vascular function [9,10,11,12,13]. Before contributing to the development of structural vascular changes or significant coronary artery disease (CAD), diabetes impairs endothelial function leading to microvascular dysfunction [12,13,14,15,16,17,18]. Even in diabetic patients without additional cardiac risk factors, endothelial dysfunction has been demonstrated and explained by associated autonomic dysfunction, chronic hyperglycemia, and insulin resistance.

Diabetes does not seem to significantly impact FFR accuracy or its interpretation [4, 19,20,21,22], although it can produce coexisting epicardial lesions (quantified by FFR) and microvascular dysfunction (often quantified by measures of hyperemic resistance). Because of potential alterations in microvascular reactivity, cFFR might perform differently in diabetic patients. Thus the aim of this study was to explore whether diabetes might impact the diagnostic ability of cFFR compared with Pd/Pa or iFR versus adenosine-derived FFR ≤ 0.80.

Methods

Study population

We explored the impact of diabetes in a post-hoc analysis of the CONTRAST study (clinicaltrials.gov identifier NCT02184117). The design and results of this study have been previously published [8]. Briefly summarized, CONTRAST was an investigator-initiated, prospective diagnostic accuracy study that enrolled a multicenter, international cohort of patients undergoing routine FFR assessment for standard indications. Patients were recruited from 12 centers between June 2014 and April 2015. Subsequent care proceeded as per routine from the clinical FFR measurement without further study-related follow-up. Each subject gave informed consent as approved by the local institutional review board of that participating center. Subjects were excluded in case of prior coronary bypass surgery, known severe cardiomyopathy (LV ejection fraction <30%) or LV hypertrophy (septal wall thickness >13 mm), contraindication to adenosine, or renal insufficiency such that an additional 12–20 ml of contrast would, in the opinion of the operator, pose an unwarranted risk. In cases of multivessel disease, only the first lesion studied using FFR was included. Culprit lesions for an acute infarction were excluded, but non-culprit lesions were permitted. Standard demographic, clinical, and catheterization parameters were collected for each subject.

Measurements and core lab analysis

The physiology protocol and core lab analysis used for the study has been previously described [8]. Briefly, an initial period of at least 1 min provided a stable assessment of resting physiology without further contrast injection. Next, a manual or injector-based IC bolus of contrast medium was given as per local practice for diagnostic angiography. The volume and type of IC contrast medium were not mandated but varied among sites and even among subjects at a single site but with a strong recommendation for 6–10 ml. A second IC bolus of contrast medium was injected using the same technique when conditions had returned to baseline (after approximately 1 min). Next, after the return of baseline conditions, a manual IC bolus of adenosine was administered (dose at operators’ discretion but with a strong recommendation for 100–200 μg). A second, identical bolus of IC adenosine was given after 1 min.

A subsequent period of at least 1 min provided a second assessment of resting physiology before starting an adenosine infusion at a standard rate of 140 μg/kg/min via either a central or wide bore peripheral IV. The duration of the infusion was approximately 2 min, but could be prolonged or abbreviated as necessary. After stopping IV adenosine and waiting approximately 2 min for conditions to return to baseline, a second, identical IV adenosine infusion was performed. At the end of the procedure, an optional but recommended drift check was performed by bringing the pressure sensor back to the guide catheter at the same location as equalization.

All pressure tracings were sent to the Cardiovascular Research Foundation physiology core lab for standardized and centralized review. The core lab carried out its post-hoc analysis without knowledge of the locally determined Pd/Pa value, IC substance (contrast medium or adenosine), enrolling site, or subject/lesion characteristics.

Statistical analysis and endpoints

The primary endpoint was accuracy against FFR ≤ 0.80 and compared using a McNemar test between metrics. Secondary endpoints included the area under the receiver operating characteristic (ROC) curve (compared using the DeLong method), sensitivity, and specificity. All the analyses were performed in diabetic and non-diabetic patients. Based on previous evidence [8], the binary thresholds were as follows: FFR ≤ 0.80; cFFR ≤ 0.83; Pd/Pa < 0.92 and iFR < 0.90.

Continuous variables are presented as mean ± standard deviation and were compared with independent samples Student t test. Categorical variables are expressed as count and percentages and were compared with Chi square or Fisher exact tests as appropriate. A Cox proportional model was used for univariate and multivariate analysis to explore the role of diabetes in predicting the cFFR disagreement with FFR. Applicable tests were two-tailed, and p < 0.05 was considered statistically significant. Analyses were performed in SPSS, version 23.0 (SPSS Inc., Chicago, IL, USA) and MedCalc version 12.5 (MedCalc Software, Ostend, Belgium).

Results

Of 763 subjects, 219 (29%) were diabetic. Compared with non-diabetic patients, those with diabetes were more frequently women, had a higher body mass index, and more frequently had hypertension or dyslipidemia (Table 1). The 2 groups were well-balanced for clinical presentation (stable or unstable), coronary vessel studied, volume and type of intracoronary contrast, and volume of intracoronary adenosine (Table 1).

Table 1 Baseline characteristics in patients with or without diabetes
Full size table

As reported previously, a binary threshold of cFFR ≤ 0.83 produced an accuracy of 85.8%, superior to both Pd/Pa 78.5% and iFR 79.9% (McNemar p < 0.001 versus both resting metrics), when compared with FFR ≤ 0.8 [8]. In this substudy, there was no significant interaction between diabetes and accuracy; indeed, accuracy in subgroups of patients with or without diabetes was similar for cFFR (86.7 vs 85.4% respectively; p = 0.76), iFR (84.2 vs 80.0% respectively; p = 0.29) and Pd/Pa (81.3 vs 78.9% respectively; p = 0.55) (Fig. 1). Overall, sensitivity was similar among the 3 metrics when comparing non-diabetics and diabetics, respectively (cFFR 78.6 vs 74.7%, p = 0.61; iFR 88.8 vs 77.2%, p = 0.05; Pd/Pa 78.8 vs 74.6%, p = 0.57), but cFFR improved specificity compared with iFR or Pd/Pa and there was no significant interaction with diabetes status (cFFR 95.6 vs 95.3%, p = 0.85; iFR 78.9 vs 78.6%, p = 0.89; Pd/Pa 84.0 vs 82.9%, p = 0.96) (Fig. 1).

Fig. 1
figure1

Diagnostic performance of cFFR, iFR and Pd/Pa in patients with or without diabetes. Accuracy, specificity, and sensitivity of each metric are reported for patients with (red bars) and without (blue bars) diabetes, demonstrating absence of heterogeneity in these subgroups

Full size image

The area under the ROC curve was largest for cFFR compared with Pd/Pa and iFR which were equivalent in both diabetic (0.961 cFFR, 0.916 Pd/Pa, 0.911 iFR; DeLong p = 0.003 for cFFR vs iFR, p < 0.0001 for cFFR vs Pd/Pa and p = 0.66 for iFR vs Pd/Pa; Fig. 2) and non-diabetic patients (0.928 cFFR, 0.870 Pd/Pa, 0.861 iFR; DeLong p < 0.0001 for cFFR vs iFR, p < 0.0001 for cFFR vs Pd/Pa and p = 0.13 for iFR vs Pd/Pa; Fig. 2). There were no significant differences when ROC curves in diabetic and non-diabetic patients were compared (cFFR 0.961 vs 0.928, DeLong p = 0.08; Pd/Pa 0.916 vs 0.870, DeLong p = 0.09; iFR 0.911 vs 0.861, DeLong p = 0.08).

Fig. 2
figure2

Diagnostic performance expressed by the area under the ROC curve for each metric in patients with or without diabetes. In patients with or without diabetes, contrast FFR (red line) has the largest area under the ROC curve, while iFR (blue line) and Pd/Pa (black line) have equivalent areas

Full size image

As a physiologic explanation for the superior diagnostic performance of cFFR compared to resting physiology (either Pd/Pa or iFR), Fig. 3 shows that the modest hyperemia induced by cFFR determines a more linear and less scattered relationship versus FFR compared to that of resting physiology, irrespective of diabetes status. Indeed, compared with Pd/Pa and iFR, the correlation of cFFR with FFR was superior in both diabetic (r = 0.92 and ICC = 0.85 for cFFR; r = 0.84 and ICC = 0.64 for iFR; r = 0.87 and ICC = 0.37 for Pd/Pa) or non-diabetic patients (r = 0.93 and ICC = 0.84 for cFFR; r = 0.80 and ICC = 0.56 for iFR; r = 0.85 and ICC = 0.38 for Pd/Pa; Fig. 3).

Fig. 3
figure3

Scatterplots of each metric with FFR in patients with or without diabetes. Resting physiology (either Pd/Pa or iFR) displays a less linear and more scattered relationship with FFR than does modest hyperemia (contrast FFR) in both diabetic (red dots) and non-diabetic patients (blue dots), as shown visually by the raw data and its local regression (thick blue line with dashed 95% confidence intervals) and quantified by correlation coefficients (r from Pearson, ICC from intraclass correlation)

Full size image

Diabetes did not predict agreement/disagreement between cFFR and FFR (p = 0.66) in a univariate analysis. Also when diabetes was forced into a multivariable model, it did not significantly influence the accuracy of cFFR (adjusted p = 0.71) (Table 2).

Table 2 Predictors of cFFR disagreement with FFR
Full size table

Discussion

This sub-analysis of the CONTRAST study shows that there is no significant interaction between diabetes and the diagnostic performance of cFFR, therefore, the findings of the main analysis can be extended to patients with diabetes. Contrast FFR provides superior diagnostic performance compared with resting metrics (iFR and Pd/Pa) irrespective of diabetic status.

The CONTRAST study is the largest study to investigate the diagnostic performance of cFFR and the present sub-analysis is the first to explore the impact of diabetes on cFFR performance compared with resting methods [23,24,25].

Diabetes mellitus is a well-known risk factor for cardiovascular disease [9,10,11]. The presence of diabetes accelerates the natural course of atherosclerosis, involving both proximal epicardial and distal small vessel coronary arteries with greater plaque ulceration and thrombosis and microvascular disease. Patients with diabetes have a variety of structural and functional microvascular coronary abnormalities [12,13,14,15,16,17,18] that may translate into a reduction of hyperemic blood flow due to an impairment of microcirculatory vasodilation.

Some studies investigated the accuracy of FFR in diabetic patients. Yanagisawa et al. compared FFR performance in 96 and 149 patients with or without diabetes respectively and observed that there was no significant difference, although within diabetic patients, those with a poor glycemic control (glycated hemoglobin >7%) had a lower FFR specificity [19]. Domínguez-Franco et al. found that deferring PCI in diabetic patients (29% of all patients) with a moderately severe coronary artery stenosis based on the FFR value was as safe as in patients without diabetes [20]. Sahinarslan et al. analyzed 122 patients (29.5% with diabetes) with intermediate coronary lesions and observed that there was no difference between the FFR values in patients with or without diabetes who had been paired according to reference vessel diameter and degree of luminal narrowing of coronary lesions [21]. Reith et al. evaluated FFR in 266 intermediate grade lesions of 224 patients (113 non-diabetics and 111 diabetics) with stable CAD, also exploring the role of adequate glycemic control (defined as glycated hemoglobin <7%). They found that FFR accuracy was not affected by diabetic status and its glycemic control [22]. In the FAME-2 trial, the FFR guided PCI was superior to medical therapy for the primary end point (composite of death from any cause, nonfatal myocardial infarction, or urgent revascularization within 2 years) in patients with or without diabetes (28 and 72% respectively) with an absence of significant interaction between the two sub-groups interaction p = 0.50) [4].

Interestingly, some data have questioned the accuracy of FFR is some cases. Although FFR and coronary flow velocity reserve (CFVR) have an equivalent diagnostic accuracy for inducible myocardial ischemia, it has been shown that they provide discordant results in 30–40% of cases, which was suggested to have a significant impact on clinical outcomes, particularly when FFR is normal and CFVR abnormal that generally indicates predominant microvascular involvement in coronary artery disease [26, 27]. Therefore it cannot be excluded that the accuracy of FFR, and thus also of cFFR, may be affected in case of microvascular disease as occurs in patients with diabetes. Indeed, a recent study has showed that in patients with diabetes, particularly those with previous MI, FFR-based deferred revascularization was associated with poor medium-term outcomes suggesting that the combining of FFR with imaging techniques may be useful to guide our treatment strategy in these patients with high-risk, fast-progressing disease [28]. Comparing FFR-guided deferred revascularization in patients with and without diabetes, Kennedy et al. also showed that those with diabetes were associated with a significantly higher rate of target lesion failure [29]. Accordingly, a recent study by Liu et al. showed that a higher FFR was associated with lower rates of death, myocardial infarction and revascularization among non-diabetic patients with deferred PCI, but in diabetic patients with deferred revascularization, FFR was not able to differentiate the risk of cardiovascular events [30].

Whether intravascular imaging, may impact on this higher failure rate remains unexplored, but the COMBINE study, the first prospective multicenter combining FFR and optical coherence tomography, will contribute to clarify this issue investigating the hypothesis that adding the study of plaque morphology to FFR in intermediate lesions may better predict events in patients with diabetes [31].

Although few data exist on the clinical value of FFR in diabetic patients, the impact of diabetes and any potentially associated microvascular dysfunction was previously unknown for cFFR performance. Indeed, whether the submaximal vasodilatation induced by contrast medium compared with adenosine might affect the accuracy of cFFR measurement in patients with diabetes had never been explored before. Our novel results found no significant heterogeneity between subgroups stratified by diabetes, and that the overall results of the CONTRAST study can be extended to all patients irrespective of diabetic status. Therefore, cFFR has been proven accurate and superior to resting metrics in patients with diabetes as well as in those without diabetes.

Limitations

This is an unplanned post-hoc analysis of the CONTRAST study, which was not designed or powered to investigate the diabetic subgroup specifically. Therefore, our exploratory analysis should be considered hypothesis-generating and needs to be confirmed in further trials. Additionally, our sub-analysis shares the limitations of the main study [8], namely the short-acting nature of contrast-induced hyperemia and lack of clinical data regarding contrast-induced nephropathy. Finally, being cFFR measured during submaximal hyperemia, it shares the same FFR limitations related to hyperemia in the setting of microvascular dysfunction.

Clinical relevance and conclusions

When performing physiological lesion assessment, some operators prefer to avoid adenosine due to rare side effects and minimal but nonzero added time and expense. Moreover, adenosine is still expensive or unavailable in some areas of the world, and sporadic patients have contraindications.

Contrast FFR provides superior diagnostic performance than Pd/Pa or iFR for predicting FFR irrespective of diabetes. Although FFR remains the reference standard for diagnostic certainty, for clinical scenarios or healthcare systems in which adenosine is contraindicated or prohibitively expensive, cFFR may represent a simple alternative technique to adenosine-FFR for invasive coronary physiological assessment in diabetic as well as non-diabetic patients.

Abbreviations

CAD:

coronary artery disease

cFFR:

contrast-based fractional flow reserve

ECG:

electrocardiogram

FFR:

fractional flow reserve

IC:

intracoronary

iFR:

instantaneous wave-free ratio

IQR:

interquartile range

IV:

intravenous(ly)

Pd/Pa:

resting ratio of distal coronary pressure to aortic pressure

ROC:

receiver operating characteristic curve

References

  1. 1.

    Pijls NH, De Bruyne B, Peels K, Van Der Voort PH, Bonnier HJ, Bartunek JKJJ, Koolen JJ. Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses. N Engl J Med. 1996;334:1703–8.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Zimmermann FM, Ferrara A, Johnson NP, van Nunen LX, Escaned J, Albertsson P, Erbel R, Legrand V, Gwon HC, Remkes WS, Stella PR, van Schaardenburgh P, Bech GJ, De Bruyne B, Pijls NH. Deferral vs performance of percutaneous coronary intervention of functionally non-significant coronary stenosis: 15-year follow-up of the defer trial. Eur Heart J. 2015;36:3182–8.

    Article  PubMed  Google Scholar 

  3. 3.

    van Nunen LX, Zimmermann FM, Tonino PA, Barbato E, Baumbach A, Engstrom T, Klauss V, MacCarthy PA, Manoharan G, Oldroyd KG, Ver Lee PN, Van’t Veer M, Fearon WF, De Bruyne B, Pijls NH. Fractional flow reserve versus angiography for guidance of pci in patients with multivessel coronary artery disease (fame): 5-year follow-up of a randomised controlled trial. Lancet. 2015;386:1853–60.

    Article  PubMed  Google Scholar 

  4. 4.

    De Bruyne B, Fearon WF, Pijls NH, Barbato E, Tonino P, Piroth Z, Jagic N, Mobius-Winckler S, Rioufol G, Witt N, Kala P, MacCarthy P, Engstrom T, Oldroyd K, Mavromatis K, Manoharan G, Verlee P, Frobert O, Curzen N, Johnson JB, Limacher A, Nuesch E, Juni P. Fractional flow reserve-guided pci for stable coronary artery disease. N Engl J Med. 2014;371:1208–17.

    Article  PubMed  Google Scholar 

  5. 5.

    Johnson NP, Gould KL, Di Carli MF, Taqueti VR. Invasive ffr and noninvasive cfr in the evaluation of ischemia: what is the future? J Am Coll Cardiol. 2016;67:2772–88.

    Article  PubMed  Google Scholar 

  6. 6.

    Pijls NH, van Son JA, Kirkeeide RL, De Bruyne B, Gould KL. Experimental basis of determining maximum coronary, myocardial, and collateral blood flow by pressure measurements for assessing functional stenosis severity before and after percutaneous transluminal coronary angioplasty. Circulation. 1993;87:1354–67.

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Johnson NP, Toth GG, Lai D, Zhu H, Acar G, Agostoni P, Appelman Y, Arslan F, Barbato E, Chen SL, Di Serafino L, Dominguez-Franco AJ, Dupouy P, Esen AM, Esen OB, Hamilos M, Iwasaki K, Jensen LO, Jimenez-Navarro MF, Katritsis DG, Kocaman SA, Koo BK, Lopez-Palop R, Lorin JD, Miller LH, Muller O, Nam CW, Oud N, Puymirat E, Rieber J, Rioufol G, Rodes-Cabau J, Sedlis SP, Takeishi Y, Tonino PA, Van Belle E, Verna E, Werner GS, Fearon WF, Pijls NH, De Bruyne B, Gould KL. Prognostic value of fractional flow reserve: linking physiologic severity to clinical outcomes. J Am Coll Cardiol. 2014;64:1641–54.

    Article  PubMed  Google Scholar 

  8. 8.

    Johnson NP, Jeremias A, Zimmermann FM, Adjedj J, Witt N, Hennigan B, Koo BK, Maehara A, Matsumura M, Barbato E, Esposito G, Trimarco B, Rioufol G, Park SJ, Yang HM, Baptista SB, Chrysant GS, Leone AM, Berry C, De Bruyne B, Gould KL, Kirkeeide RL, Oldroyd KG, Pijls NH, Fearon WF. Continuum of vasodilator stress from rest to contrast medium to adenosine hyperemia for fractional flow reserve assessment. JACC Cardiovasc Interv. 2016;9:757–67.

    Article  PubMed  Google Scholar 

  9. 9.

    Beckman JA, Creager MA, Libby P. Diabetes and atherosclerosis: epidemiology, pathophysiology, and management. JAMA. 2002;287:2570–81.

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Schramm TK, Gislason GH, Kober L, Rasmussen S, Rasmussen JN, Abildstrom SZ, Hansen ML, Folke F, Buch P, Madsen M, Vaag A, Torp-Pedersen C. Diabetes patients requiring glucose-lowering therapy and nondiabetics with a prior myocardial infarction carry the same cardiovascular risk: a population study of 3.3 million people. Circulation. 2008;117:1945–54.

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Gargiulo G, Windecker S, da Costa BR, Feres F, Hong MK, Gilard M, Kim HS, Colombo A, Bhatt DL, Kim BK, Morice MC, Park KW, Chieffo A, Palmerini T, Stone GW, Valgimigli M. Short term versus long term dual antiplatelet therapy after implantation of drug eluting stent in patients with or without diabetes: systematic review and meta-analysis of individual participant data from randomised trials. BMJ. 2016;355:i5483.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Marciano C, Galderisi M, Gargiulo P, Acampa W, D’Amore C, Esposito R, Capasso E, Savarese G, Casaretti L, Lo Iudice F, Esposito G, Rengo G, Leosco D, Cuocolo A, Perrone-Filardi P. Effects of type 2 diabetes mellitus on coronary microvascular function and myocardial perfusion in patients without obstructive coronary artery disease. Eur J Nucl Med Mol Imaging. 2012;39:1199–206.

    Article  PubMed  Google Scholar 

  13. 13.

    Picchi A, Capobianco S, Qiu T, Focardi M, Zou X, Cao JM, Zhang C. Coronary microvascular dysfunction in diabetes mellitus: a review. World J Cardiol. 2010;2:377–90.

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Yokoyama I, Momomura S, Ohtake T, Yonekura K, Nishikawa J, Sasaki Y, Omata M. Reduced myocardial flow reserve in non-insulin-dependent diabetes mellitus. J Am Coll Cardiol. 1997;30:1472–7.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Pitkanen OP, Nuutila P, Raitakari OT, Ronnemaa T, Koskinen PJ, Iida H, Lehtimaki TJ, Laine HK, Takala T, Viikari JS, Knuuti J. Coronary flow reserve is reduced in young men with iddm. Diabetes. 1998;47:248–54.

    CAS  Article  PubMed  Google Scholar 

  16. 16.

    Nitenberg A, Valensi P, Sachs R, Dali M, Aptecar E, Attali JR. Impairment of coronary vascular reserve and ach-induced coronary vasodilation in diabetic patients with angiographically normal coronary arteries and normal left ventricular systolic function. Diabetes. 1993;42:1017–25.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Di Carli MF, Janisse J, Grunberger G, Ager J. Role of chronic hyperglycemia in the pathogenesis of coronary microvascular dysfunction in diabetes. J Am Coll Cardiol. 2003;41:1387–93.

    Article  PubMed  Google Scholar 

  18. 18.

    Camici PG, Crea F. Coronary microvascular dysfunction. N Engl J Med. 2007;356:830–40.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Yanagisawa H, Chikamori T, Tanaka N, Usui Y, Takazawa K, Yamashina A. Application of pressure-derived myocardial fractional flow reserve in assessing the functional severity of coronary artery stenosis in patients with diabetes mellitus. Circ J. 2004;68:993–8.

    Article  PubMed  Google Scholar 

  20. 20.

    Dominguez-Franco AJ, Jimenez-Navarro MF, Munoz-Garcia AJ, Alonso-Briales JH, Hernandez-Garcia JM, de Teresa Galvan E. Long-term prognosis in diabetic patients in whom revascularization is deferred following fractional flow reserve assessment. Rev Esp Cardiol. 2008;61:352–9. doi:10.1016/S1885-5857(08)60144-9.

    Article  PubMed  Google Scholar 

  21. 21.

    Sahinarslan A, Kocaman SA, Olgun H, Kunak T, Kiziltunc E, Ozdemir M, Timurkaynak T. The reliability of fractional flow reserve measurement in patients with diabetes mellitus. Coron Artery Dis. 2009;20:317–21.

    Article  PubMed  Google Scholar 

  22. 22.

    Reith S, Battermann S, Hellmich M, Marx N, Burgmaier M. Impact of type 2 diabetes mellitus and glucose control on fractional flow reserve measurements in intermediate grade coronary lesions. Clin Res Cardiol. 2014;103:191–201.

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Kanaji Y, Murai T, Lee T, Matsuda J, Usui E, Araki M, Niida T, Ichijyo S, Hamaya R, Yonetsu T, Kimura S, Kakuta T. Efficacy of pressure parameters obtained during contrast medium-induced submaximal hyperemia in the functional assessment of intermediate coronary stenosis in comparison with instantaneous wave-free ratio. Int J Cardiol. 2016;208:128–36.

    Article  PubMed  Google Scholar 

  24. 24.

    Leone AM, Scalone G, De Maria GL, Tagliaferro F, Gardi A, Clemente F, Basile E, Cialdella P, De Caterina AR, Porto I, Aurigemma C, Burzotta F, Niccoli G, Trani C, Rebuzzi AG, Crea F. Efficacy of contrast medium induced pd/pa ratio in predicting functional significance of intermediate coronary artery stenosis assessed by fractional flow reserve: insights from the rinasci study. EuroIntervention. 2015;11:421–7.

    Article  PubMed  Google Scholar 

  25. 25.

    De Bruyne B, Pijls NH, Barbato E, Bartunek J, Bech JW, Wijns W, Heyndrickx GR. Intracoronary and intravenous adenosine 5’-triphosphate, adenosine, papaverine, and contrast medium to assess fractional flow reserve in humans. Circulation. 2003;107:1877–83.

    Article  PubMed  Google Scholar 

  26. 26.

    van de Hoef TP, van Lavieren MA, Damman P, Delewi R, Piek MA, Chamuleau SA, Voskuil M, Henriques JP, Koch KT, de Winter RJ, Spaan JA, Siebes M, Tijssen JG, Meuwissen M, Piek JJ. Physiological basis and long-term clinical outcome of discordance between fractional flow reserve and coronary flow velocity reserve in coronary stenoses of intermediate severity. Circ Cardiovasc Interv. 2014;7:301–11.

    Article  PubMed  Google Scholar 

  27. 27.

    Lee JM, Jung JH, Hwang D, Park J, Fan Y, Na SH, Doh JH, Nam CW, Shin ES, Koo BK. Coronary flow reserve and microcirculatory resistance in patients with intermediate coronary stenosis. J Am Coll Cardiol. 2016;67:1158–69.

    Article  PubMed  Google Scholar 

  28. 28.

    Kennedy MW, Hermanides RS, Kaplan E, Hemradj V, Fabris E, Koopmans PC, Dambrink JE, Gosselink AT, Van’t Hof AW, Ottervanger JP, Roolvink V, Remkes WS, van der Sluis A, Suryapranata H, Kedhi E. Fractional flow reserve-guided deferred versus complete revascularization in patients with diabetes mellitus. Am J Cardiol. 2016;118:1293–9.

    Article  PubMed  Google Scholar 

  29. 29.

    Kennedy MW, Kaplan E, Hermanides RS, Fabris E, Hemradj V, Koopmans PC, Dambrink JH, Marcel Gosselink AT, Van’t Hof AW, Ottervanger JP, Roolvink V, Remkes WS, van der Sluis A, Suryapranata H, Kedhi E. Clinical outcomes of deferred revascularisation using fractional flow reserve in patients with and without diabetes mellitus. Cardiovasc Diabetol. 2016;15:100.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Liu Z, Matsuzawa Y, Herrmann J, Li J, Lennon RJ, Crusan DJ, Kwon TG, Zhang M, Sun T, Yang S, Gulati R, Bell MR, Lerman LO, Lerman A. Relation between fractional flow reserve value of coronary lesions with deferred revascularization and cardiovascular outcomes in non-diabetic and diabetic patients. Int J Cardiol. 2016;219:56–62.

    Article  PubMed  Google Scholar 

  31. 31.

    Kennedy MW, Fabris E, Ijsselmuiden AJ, Nef H, Reith S, Escaned J, Alfonso F, van Royen N, Wojakowski W, Witkowski A, Indolfi C, Ottervanger JP, Suryapranata H, Kedhi E. Combined optical coherence tomography morphologic and fractional flow reserve hemodynamic assessment of non- culprit lesions to better predict adverse event outcomes in diabetes mellitus patients: combine (oct-ffr) prospective study. Rationale and design. Cardiovasc Diabetol. 2016;15:144.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Authors’ contributions

GG, GE, BT NPJ, and WFF conceived and designed the study. GG performed all analyses, interpreted the results, and drafted the manuscript. GE, BT NPJ, and WFF interpreted the results, and revised critically the manuscript. All authors participated in data collection, revised critically the manuscript. All authors read and approved the final manuscript.

Acknowledgements

The authors thank all the centers and personal participating at the data collection.

Competing interests

Dr. Gargiulo is supported by a research grant from Cardiopath PhD program. Dr. Johnson has received internal funding from the Weatherhead PET Center for Preventing and Reversing Atherosclerosis; and significant institutional research support from St. Jude Medical (for this study [NCT02184117]) and Volcano/Philips Corporation (for NCT02328820), makers of intracoronary pressure and flow sensors. Dr. Jeremias has served as a consultant and member of the Speakers’ Bureau for Volcano/Philips Corporation. Dr. Barbato has received institutional consultancy fees and research support from St. Jude Medical. Dr. Fearon has received institutional research support from St. Jude Medical and Medtronic; has received honoraria from Medtronic; and has served as a consultant to HeartFlow. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Availability of data and material

The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Consent for publication

All authors have read and approved the submission of the manuscript; the manuscript has not been published and is not being considered for publication elsewhere, in whole or in part, in any language, except as an abstract.

Ethics approval and consent to participate

The study was approved by the local institutional review board of all participating centers. All participants gave their written informed consent before data collection.

Funding

The present sub-analysis did not receive financial support.

Author information

Affiliations

  1. Department of Advanced Biomedical Sciences, University of Naples Frederico II, Naples, Italy

    Giuseppe Gargiulo, Eugenio Stabile, Marco Ferrone, Emanuele Barbato, Bruno Trimarco & Giovanni Esposito

  2. Cardiovascular Center, OLV Clinic, Aalst, Belgium

    Emanuele Barbato & Julien Adjedj

  3. Department of Cardiology, Catharina Hospital, Eindhoven, The Netherlands

    Frederik M. Zimmermann

  4. West of Scotland Heart and Lung Centre, Golden Jubilee National Hospital, Clydebank, Scotland, UK

    Barry Hennigan

  5. British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, Scotland, UK

    Barry Hennigan

  6. Cardiovascular Research Foundation (CRF), New York, NY, USA

    Mitsuaki Matsumura & Allen Jeremias

  7. Division of Cardiology, Department of Medicine, Weatherhead PET Center, McGovern Medical School at UTHealth and Memorial Hermann Hospital, Houston, TX, USA

    Nils P. Johnson

  8. Stanford University Medical Center, Stanford, USA

    William F. Fearon

  9. The Palo Alto VA Health Care Systems, Palo Alto, CA, USA

    William F. Fearon

  10. Division of Cardiovascular Medicine, Stony Brook University Medical Center, Stony Brook, NY, USA

    Allen Jeremias

  11. Division of Cardiology-Department of Advanced Biomedical Sciences, Federico II University of Naples, Via Pansini 5, 80131, Naples, Italy

    Giovanni Esposito

Authors
  1. Giuseppe Gargiulo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eugenio Stabile
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marco Ferrone
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Emanuele Barbato
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Frederik M. Zimmermann
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Julien Adjedj
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Barry Hennigan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mitsuaki Matsumura
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nils P. Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. William F. Fearon
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Allen Jeremias
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Bruno Trimarco
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Giovanni Esposito
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

On behalf of the CONTRST Study Investigators

Corresponding author

Correspondence to Giovanni Esposito.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gargiulo, G., Stabile, E., Ferrone, M. et al. Diabetes does not impact the diagnostic performance of contrast-based fractional flow reserve: insights from the CONTRAST study. Cardiovasc Diabetol 16, 7 (2017). https://doi.org/10.1186/s12933-016-0494-2

Download citation

Keywords

  • Diabetes
  • Coronary lesion
  • Fractional flow reserve
  • Hyperemia
  • Contrast medium
  • Adenosine
  • Resting metrics
  • Instantaneous wave-free ratio

Cardiovascular Diabetology

ISSN: 1475-2840