Atherosclerosis is a chronic process composing of various stages, in which inflammatory mediators and endothelial dysfunction are involved. Coronary artery disease is one of the leading causes of mortality and morbidity in developed countries. Coronary artery stenosis resulting from atherosclerosis plays a role in the etiology. Risk stratification is widely used for diagnosis, treatment and staging of coronary artery disease and recommended as the first choice in current guidelines[1].
Although coronary angiography-based anatomic classification often overestimates or underestimates the functional significance of lesion(s), it is still commonly used in the conventional percutaneous coronary intervention (PCI) strategies. Fractional flow reserve (FFR), defined as the ratio of maximal hyperemic flow through a stenotic artery [Pd] to normal maximal flow [Pa], is one of the indicators of functional coronary stenosis and. FFR can be easily measured during coronary angiography and an FFR value ≤ 80% shows a functionally critical lesion with >90% accuracy rate[2-5].
The propensity score matching (PSM) method, more effective than traditional regression models and applied to various clinical researches, was described by Rosenbaum[6] and in PSM analysis, the parameters are reclassified using matching, stratification, covariate adjustment and inverse probability weighting methods. The effects of parameters on treatment response or clinical status can be determined more accurately.[7-9] Although FFR is a good diagnostic tool in coronary artery disease, there are no studies investigating the FFR predictors by PSM analysis. In this study, we aimed to investigate FFR predictors after PSM analysis in patients with intermediate coronary lesions.
2. Method
2.1. Patient Characteristics
Study sample was selected from a population of 1100 patients with stable angina pectoris that applied to our medical center between September 2016 and December 2017 and included the patients, who underwent coronary angiography due to suspicion of coronary artery disease and were diagnosed to have intermediate (40-70%) lesion in at least one of the major epicardial arteries. Exclusion criteria involved the history of CABG or a coronary intervention, newly emerging STEMI (<7 days) and existence of an absolute contraindication to adenosine. Ultimately, a total 290 patients were included in the study and a sum of 310 lesions was investigated. The study was carried out following the obtainment of patients’ consent forms as well as the approval of the local ethics committee.
2.2. Definitions
Hypertension was defined as having at least two blood pressure measurements >140/90 mmHg or using antihypertensive drugs, whereas diabetes mellitus was defined as having at least two fasting blood glucose measurements >126 mg/dl or using antidiabetic drugs. Medications, which were used prior to the coronary angiography, were noted. Additionally, hematological indices, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) total cholesterol (TC), triglycerides (TG), and fasting glucose levels were measured for all patients before coronary angiography, and chronic medications were noted.
2.3. Coronary Angiography and Syntax Score
For all cases, coronary angiography (Toshiba Infinix, Toshiba Japan) was performed via femoral artery using the Judkins technique. Coronary angiograms were performed by two invasive cardiologists (UA and OG), who were blinded to the patients’ data. All lesions with >1.5 mm segment length and >50% stenosis were taken into consideration in measurements. Two orthogonal views were taken for assessment. Syntax score was calculated for each patient using the Syntax score calculator as previously defined[10].
2.4. FFR Measurement
FFR procedure was carried out with a 6 Fr guiding catheter. The epicardial arteries, which were >2 mm in segment length and detected to contain lesion, were subjected to FRR procedure and FFR procedure was performed according to current guidelines.
3. Statistics
Continuous variables were expressed as mean ± standard deviation or median (interquartile range) values, whereas categorical variables were presented in percentages. For comparison of continuous variables, the Independent Student T test or the Mann-Whitney U test was used. Moreover, the Chi-square test was used to compare categorical. PSM analysis was performed to reduce the bias rate as the baseline characteristics of the two groups were quite different. A multivariate logistic regression model was used to estimate Propensity scores of the study population. After estimation of the PS of each participant, A 1:1 matched analysis using nearest-neighbor matching method were performed, unmatched patients were excluded from the study. Balance was assessed by standardized difference and c statistics. The variables found to be significant in the univariate analysis (p<0.05) were subjected to multivariate logistic regression