India has the second-highest prevalence of diabetes in the world, with 77 million individuals living with diabetes; this number is estimated to reach >130 million by 2045. [1] Diabetes is associated with a high risk of major cardiovascular risk factors, such as hypertension, hypercholesterolemia, and high triglyceride levels, among Indians. [2] In clinic-based studies, the prevalence of coronary artery disease (CAD) was ~11%–30%, while the prevalence in community-based studies was ~9%–15% among patients with diabetes,[3] and many will require percutaneous coronary intervention (PCI).

Over the years, fraction flow reserve (FFR) has emerged as a reliable physiologic index for the assessment of severity of angiographic intermediate lesions, guiding PCI in multivessel coronary lesions. [4] Currently, FFR is the gold standard invasive diagnostic test in guiding revascularization in patients with CAD.   Recent times a cut-off FFR value of 0.80 has been generally used to decide on PCI for intermediate coronary lesions.

Optical coherence tomography (OCT) is a novel and safe imaging modality with higher resolution and is proved to be useful in optimizing PCI procedure. The 2018 European Society of Cardiology and the European Association for Cardio-Thoracic Surgery (ESC/EACTS) guidelines on myocardial revascularization recommend OCT for selected patients to optimize stent implantation with the same class of recommendation and level of evidence as IVUS. Furthermore, guidelines recommend that IVUS and/or OCT should be considered to detect stent-related mechanical problems leading to restenosis (Recommendation Class II a, Level of evidence C). [8]

Optical coherence tomography can be used for optimizing PCI using MLD (Morphology [M], Length [L], and Diameter [D]) and  MAX  (Medial dissection [M], Apposition [A], and eXpansion [X]) algorithm for pre- and post-PCI, respectively. This algorithm helps in delivering optimal results and guides treatment decisions. [9]

Multiple intravascular imaging studies have shown that vulnerable plaque characteristics are more prevalent in DM patients compared to non-DM patients. The PROSPECT Registry demonstrated an ~12 % future unanticipated major adverse cardiovascular events (MACE) in non-culprit lesions (NCL) with insulin-dependent DM which is identified as an independent predictor of NCL MACE. [10] According to a meta-analysis study of 139,774 patients with T2DM, those who underwent PCI had significantly more in-hospital mortality (RR: 2.57; 95% CI: 1.95–3.38; p=0 .00001) and MACEs (RR: 1.38; 95% CI: 1.10–1.73; p =0 .005) versus patients without DM. In addition, majority of the short and long-term adverse clinical outcomes were also significantly higher in the DM group as compared to the non-DM group. Stent thrombosis was significantly higher in the DM compared to the non-DM group during the short-term follow-up period (RR 1.59; 95% CI: 1.16–2.18; p = 0.004).[10] A pooled analysis of 6 randomized trials has shown that diabetes and hypertension (p<0.01 for both) predicted TLF between 30 days and 1 year post PCI, while between 1 and 5 years, diabetes (HR 1.40, 95% CI 1.13–1.73, p=0.002), prior coronary artery bypass grafting (HR 2.52, 95% CI 1.92–3.30, p<0.0001), and prior PCI (HR 1.29, 95% CI 1.02–1.64, p=0.04) predicted TLF post PCI.[11] In diabetic patients, the TLF was found to be about 10% at one year post index PCI. [12,13]

With the help of OCT, it is easy to detect high-risk vulnerable plaques that are common in patients with DM. The introduction of OCT has helped in understanding the plaque morphology and the mechanisms of plaque rupture that may help optimizing treatment of coronary lesions. [14,15] Due to these characteristics, OCT is being frequently used to evaluate lesion morphology; however, the predictive value of this modality with regard to future clinical outcomes is not well studied in Indian settings.

The present Registry proposes to evaluate the feasibility and potential benefits of using OCT and FFR on the outcomes of PCI in diabetic patients. The lesions undergoing PCI will be guided by the MLD-MAX algorithm of OCT use. The intermediate lesions will undergo FFR measurements and   lesions with FFR value≤0.80 will be selected for PCI. As far as possible complete revascularization will be ensured in each case.

References

1.      International Diabetes Federation. IDF Diabetes Atlas, 9th edn. Brussels, Belgium: International Diabetes Federation, 2019.

2.      Gupta A, Gupta R, Sharma KK, et al. Prevalence of diabetes and cardiovascular risk factors in middle-class urban participants in India. BMJ Open Diabetes Res Care. 2014;2(1):e000048.

3.      Pradeepa R, Mohan V. Prevalence of type 2 diabetes and its complications in India and economic costs to the nation. Eur J Clin Nutr. 2017;71(7):816-824.

4.      Bishop AH, Samady H. Fractional flow reserve: critical review of an important physiologic adjunct to angiography. Am Heart J. 2004 May;147(5):792-802.

5.      Kern MJ, Lerman A, Bech JW, et al. American Heart Association Committee on Diagnostic and Interventional Cardiac Catheterization, Council on Clinical Cardiology. Physiological assessment of coronary artery disease in the cardiac catheterization laboratory: a scientific statement from the American Heart Association Committee on Diagnostic and Interventional Cardiac Catheterization, Council on Clinical Cardiology. Circulation. 2006 Sep 19;114(12):1321-41.

6.      Thomson VS, Varghese MJ, Chacko ST, Coronary artery disease management and cost implications with fractional flow reserve guided coronary intervention in Indian patients with stable ischemic coronary artery disease. Catheter Cardiovasc Interv. 2020 Apr 15. doi: 10.1002/ccd.28897

7.      Van Belle E, Cosenza A, Baptista SB, et al. Usefulness of Routine Fractional Flow Reserve for Clinical Management of Coronary Artery Disease in Patients With Diabetes. JAMA Cardiol. 2020;5(3):272–281.

8.      Neumann FJ, Sousa-Uva M, Ahlsson A, et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. Eur Heart J. 2019;40(2):87–165.

9.      Shlofmitz, E. et al. Algorithmic Approach for OCT Guided Stent Implantation During PCI. Intervent Cardiol Clin 7 (2018) 329-344.

10.  Stone GW, Maehara A, Lansky AJ, de Bruyne B, Cristea E, Mintz GS, Mehran R, McPherson J, Farhat N, Marso SP, et al. A prospective natural-history study of coronary atherosclerosis. N Engl J Med. 2011;364(3):226–35.

11.  Zhuo X, Zhang C, Feng J, Ouyang S, Niu P, Dai Z. In-hospital, short-term and long-term adverse clinical outcomes observed in patients with type 2 diabetes mellitus vs non-diabetes mellitus following percutaneous coronary intervention: A meta-analysis including 139,774 patients. Medicine (Baltimore). 2019;98(8):e14669.

12.  Franzone A, Pilgrim T, Heg D, et al. Clinical outcomes according to diabetic status in patients treated with biodegradable polymer sirolimus-eluting stents versus durable polymer everolimus-eluting stents: prespecified subgroup analysis of the BIOSCIENCE trial. Circ Cardiovasc Interv. 2015 Jun;8(6):e002319

13.  Kornowski R, Roguin A, Danenberg H, et al. BIOFLOW-III satellite-One-year clinical outcomes of diabetic patients treated with a biodegradable polymer sirolimus-eluting stent and comprehensive medical surveillance. Cardiovasc Revasc Med. 2017 Jul-Aug;18(5):338-343.

14.  Fujii K, Kawasaki D, Masutani M, et al. OCT assessment of thin-cap fibroatheroma distribution in native coronary arteries. J Am Coll Cardiol Imaging. 2010;3(2):168–75.

15.  Jang IK, Tearney GJ, MacNeill B et al. In vivo characterization of coronar atherosclerotic plaque by use of optical coherence tomography. Circulation. 2005;111(12):1551–5.