The estimated glomerular filtration rate (eGFR) was estimated according to the Kidney Disease-Epidemiology Collaboration (CKD-EPI) formula16 and those patients whose eGFR were less than 60mL/min/1.73m2 were defined as CKD. Of all the 6749 patients who received coronary angiography (CAG) due to angina-like chest pain, the consecutive data of 521 CKD patients at The People's Hospital of Suzhou New District (date range: January 2017 and November 2019) and 457 CKD patients at the Zhong Da Hospital Affiliated to Southeast University (date range: May 2016 and December 2016) who did not undergo dialysis were analyzed. The exclusion criteria comprised of hepatic failure, evidence of an active infection or systemic inflammatory disease, valvular disease, cardiomyopathy, myocarditis, thyroid dysfunction, cancer, acute renal insufficiency, a history of kidney transplant or previous CAD. Of all the 978 CKD patients, 70 patients had acute coronary syndromes.

Medical histories were obtained by reviewing the patients’ electronic medical records and included the age, sex, body mass index (BMI), history of smoking, alcohol-intake, hypertension, and diabetes mellitus. Hypertension was diagnosed as a repeated blood pressure measurement>140/90mmHg or based on antihypertensive drug medication. Diabetes mellitus was diagnosed as repeated fasting serum glucose levels>7.0mmol/L, a random plasma glucose level>11.1mmol/L, or on hypoglycemic medication.

Before CAG, patients’ fasting blood samples were obtained from the antecubital vein after fasting for 8h. The complete blood count was analyzed by the automated hematology analysis system (Beckman LH750, Beckman Coulter, Brea, CA, USA; Sysmex DI-60, Sysmex Corporation, Kobe, Japan). Laboratory indices including hemoglobin, uric acid, triglyceride (TC), total cholesterol (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), lipoprotein (a) [Lp(a)], serum creatinine (Scr), prealbumin, and albumin levels were tested with a biochemistry analyzer (Beckman AU680, Beckman Coulter; Roche Cobas 8000, Roche, Basel, Switzerland). Plasma fibrinogen levels were measured using the Clauss’ method (Beckman ACL-TOP700, Beckman Coulter; C3510, Mairui, Beijing, China).

The CAG was performed using an X-ray system according to the standard Judkins technique (Philips UNIQ Clarity FD10, Philips, Amsterdam, Netherlands; Siemens ARTIS Icono Biplane, Munich, Germany) and all patients had signed the informed consent form. At least two different plane images were obtained for the main coronary artery, including the left main coronary artery (LM), the left anterior descending coronary artery (LAD), the left circumflex coronary artery (LCX), and the right coronary artery (RCA). CAD was defined as the presence of obstructive stenosis>50% of the lumen diameter in any of aforesaid four main coronary arteries. Patients with a stenosis≥50% in diameter in the LM was diagnosed as LM coronary artery stenosis (LMCA). Simultaneous stenosis (≥50%) of the LAD, LCX, and RCA, with or without LM involvement, was diagnosed as three-vessel coronary artery disease (TVD). LMCA and TVD were defined as severe coronary artery stenosis (CAS).

The Gensini Score (GS) was calculated for patients diagnosed with CAD (n=759) to evaluate the severity of CAS.17 Each coronary artery had a coefficient that corresponded to the lesion's position, such as 5 for LM; 2.5 for proximal LAD and proximal LCX; 1.5 for the midportion LAD; 1 for the RCA, the distal segment of the LAD, the mid-distal region of the LCX, the posterolateral artery, and the obtuse marginal artery; and 0.5 for other segments. These coefficients were multiplied by 1, 2, 4, 8, 16, and 32, and were associated with 0–25%, 26–50%, 51–75%, 76–90%, 91–99%, and 100% stenosis, respectively. The total score for each patient was calculated. The lower GS group (n=378) was defined as a GS between 1 and 30, and the higher GS group (n=381) was defined as a GS>30 according to the median of the subjects diagnosed with CAD in the study.

The statistical analyses were conducted with the SPSS 25.0 software package (IBM Corporation, Armonk, NY, USA). Normally distributed variables were expressed as means±standard deviations and compared using Student's t-test. Non-normal variables were presented as medians with interquartile ranges, and the Mann–Whitney U-test was used. The categorical variables were presented as numbers and percentages and were compared using Fisher's exact tests or chi-squared tests. The Kruskal–Wallis rank test and chi-squared test were used to compare continuous variables and categorical variables related to FAR quartiles, as appropriate. Correlation analysis between FAR and GS was performed using Spearman's correlation coefficient. Multivariate logistic regression analysis was used to determine the relationship between FAR levels and the presence and severity of CAD. A P-value<0.05 was considered as statistically significant.

A total of 978 CKD patients who had undergone CAG were divided into one of two groups: the CAD group (n=759) and the non-CAD group (n=219). As shown in Table 1, the mean age of all patients was 73.6 years, and the mean eGFR value was 50.4mL/min/1.73m2. Patients with CAD were older than patients without CAD (P<0.001), and they were more likely to be males, smokers, or had a history of hypertension and diabetes mellitus (P<0.001). Moreover, the FAR levels were significantly higher in the CAD group than in the non-CAD group (P<0.001). In contrast, the levels of eGFR in the CAD group were significantly lower than those in the non-CAD group (P<0.001). Serum levels of uric acid, lipoprotein (a) (Lp[a]) and fibrinogen were higher in patients with CAD than in non-CAD patients (P<0.05), while patients with CAD had lower HDL-C, prealbumin, and albumin levels (P<0.05). There were no significant differences of BMI, systolic blood pressure, diastolic blood pressure, hemoglobin, TG, TC, LDL-C, and the presence of alcohol-intake between the two groups (P>0.05).

In the correlation analysis, FAR was negatively associated with eGFR (r=−0.195, P<0.001). Then the study subjects were further grouped based on FAR quartile distributions (Quartile 1: 0.045–0.082; Quartile 2: 0.083–0.096; Quartile 3: 0.097–0.111; Quartile 4: 0.112–0.212). As shown in Fig. 1A, patients with lower FAR levels had higher levels of eGFR (53.3 [interquartile range, 45.3–57.4] vs. 51.8 [44.3–55.8] vs. 49.8 [41.1–55.8] vs. 47.9 [40.3–53.7]mL/min/1.73m2, Ptrend<0.001).

Fig. 1.

The eGFR and the presence of CAD among FAR quartiles. Quartiles for total patients (n=978): Quartile 1: 0.045–0.082; Quartile 2: 0.083–0.096; Quartile 3: 0.097–0.111; Quartile 4: 0.112–0.212. Data were reported as the percent or median (interquartile range). eGFR, estimated glomerular filtration rate; FAR, fibrinogen-to-albumin ratio; CAD, coronary artery disease.

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As shown in Fig. 1B, the percent of CAD was significantly higher in the groups with higher FAR levels, with 65.2%, 72.7%, 85.3% and 87.3% in the FAR quartile 1–4, respectively (Ptrend<0.001). In the multivariate logistic regression analysis shown in Table 2, FAR (at the 0.01 level, adjusted OR=1.191, 95% CI 1.100–1.290, P<0.001) and higher FAR quartiles (quartile 3 vs. quartile 1 [adjusted OR=3.059, 95% CI 1.859–5.032, P<0.001]; quartile 4 vs. quartile 1 [adjusted OR=2.670, 95% CI 1.605–4.441, P<0.001]) were significantly positively associated with the prevalence of CAD after adjusting for related factors, such as age, sex, BMI, smoking, alcohol-intake, hypertension, systolic blood pressure, diastolic blood pressure, diabetes mellitus, eGFR, uric acid, TG, TC, HDL-C, LDL-C, hemoglobin, prealbumin, and Lp(a). Moreover, age, male, and a history of smoking, hypertension, and diabetes mellitus had a positive association with the presence of CAD (P<0.05).

To explore the association between FAR levels and the severity of CAD, 759 patients diagnosed with CAD were grouped according to FAR quartile distributions (Quartile 1: 0.045–0.085; Quartile 2: 0.086–0.099; Quartile 3: 0.100–0.114; Quartile 4: 0.115–0.212). As shown in Fig. 2A and B, those subjects with higher FAR levels showed higher percent of LMCA (5.1% vs. 7.7% vs. 7.7% vs. 13.4% in the FAR quartile 1–4 groups respectively, Ptrend<0.01) and TVD (31.1% vs. 38.5% vs. 44.8% vs. 57.8% in the FAR quartile 1–4 groups respectively, Ptrend<0.001). Moreover, FAR was positively associated with GS (r=0.232, P<0.001). Fig. 2C shows that the GS values were increased with the increase of FAR quartile distributions (23.00 [interquartile range, 10.00–43.00] vs. 25.00 [12.00–52.25] vs. 34.5 [15.0–54.25] vs. 38.00 [22.00–74.00], Ptrend<0.001).

Fig. 2.

The presence of LMCA, TVD and higher GS among FAR quartiles. Quartiles for CAD patients (n=759): Quartile 1: 0.045–0.085; Quartile 2: 0.086–0.099; Quartile 3: 0.100–0.114; Quartile 4: 0.115–0.212. Data were reported as the percent or median (interquartile range). Higher GS: GS>30; lower GS: GS 1–30; FAR: fibrinogen-to-albumin ratio; CAD: coronary artery disease; LMCA: left main coronary artery stenosis; TVD: three-vessel coronary artery disease; GS: Gensini score.

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To examine the role of FAR in the severity of CAD, multivariate regression analysis was performed in our study. As shown in Table 2, after adjusting for abovementioned confounders, FAR (at the 0.01 level) was significantly positively associated with the prevalence of LMCA (adjusted OR=1.177, 95% CI 1.067–1.299, P=0.001) and TVD (adjusted OR=1.154, 95% CI 1.076–1.238, P<0.001). Likewise, FAR quartiles were independently associated with the prevalence of LMCA (quartile 4 vs. quartile 1 [adjusted OR=3.274, 95% CI 1.406–7.627, P=0.006]) and TVD (quartile 3 vs. quartile 1 [adjusted OR=1.701, 95% CI 1.072–2.699, P=0.024]; quartile 4 vs. quartile 1 [adjusted OR=2.777, 95% CI 1.723–4.475, P<0.001]).

Moreover, we further divided the subjects into two groups according to the median of GS: the lower GS group (GS 1–30, n=378) and the higher GS group (GS>30, n=381). As shown in Fig. 2D, the percent of higher GS patients was significantly higher in the groups with higher FAR levels, which were 39.8%, 44.0%, 56.2% and 61.0% in the FAR quartile 1–4 groups respectively (Ptrend<0.001). In the multivariate logistic regression analysis, FAR (at the 0.01 level, adjusted OR=1.152, 95% CI 1.073–1.238, P<0.001) and higher FAR quartiles (quartile 3 vs. quartile 1 [adjusted OR=2.141, 95% CI 1.353–3.385, P=0.001]; quartile 4 vs. quartile 1 [adjusted OR=2.260, 95% CI 1.399–3.652, P=0.001]) were also independently associated with the prevalence of higher GS.