A lower eGFR_{cystatin C}/eGFR_creatinine ratio is associated with greater cardiovascular risk (higher Framingham Risk Score) in Chinese patients with newly diagnosed type 2 diabetes mellitus

Abstract

Background

Cardiovascular disease (CVD) is the leading cause of mortality in type 2 diabetes mellitus (T2DM) patients. Shrunken pore syndrome (SPS) is defined as eGFR_{cystatin C}/eGFR_creatinine ratio <0.70 and predicts high CVD mortality. The Framingham Risk Score (FRS) is used to estimate an individual’s 10-year CVD risk. This study investigated the association between FRS and eGFR_{cystatin C}/eGFR_creatinine ratio in T2DM patients.

Methods

Patients aged 18-80 years who were newly diagnosed with T2DM were included in this retrospective study. Ordinal logistic regression analysis was used to investigate the association between risk factors of T2DM and FRS. A Generalized Linear Model was used to calculate odds ratios (OR) and 95% confidence intervals (CI).

Results

There were 270 patients included in the study. Only 27 patients (10%) met the diagnostic criteria of SPS. Ordinal logistic regression analysis showed that SPS was not correlated with FRS risk (OR = 1.99, 95%CI = 0.94–4.23, p = 0.07), whereas eGFR_{cystatin C}/eGFR_creatinine (OR = 0.86, 95%CI = 0.77–0.97, p = 0.01) showed a significant negative association with FRS risk. Compared with eGFR_{cystatin C}/eGFR_creatinine>0.85, eGFR_{cystatin C}/eGFR_creatinine≤0.85 increased FRS risk (OR = 1.95, 95%CI = 1.18–3.21, p < 0.01). After adjustment for confounding factors, increased eGFR_{cystatin C}/eGFR_creatinine ratio was associated with decreased FRS risk when considered as a continuous variable (OR = 0.87, 95%CI = 0.77–0.99, p = 0.03). The FRS risk in patients with eGFR_{cystatin C}/eGFR_creatinine≤0.85 is 1.86 times higher than that in patients with eGFR_{cystatin C}/eGFR_creatinine>0.85 (OR = 1.86, 95%CI = 1.08–3.21, p = 0.03).

Conclusions

In the current study, no significant association between SPS and FRS was identified. However, lower eGFR_{cystatin C}/eGFR_creatinine and eGFR_{cystatin C}/eGFR_creatinine≤0.85 were associated with a significantly increased CVD risk in T2DM.

Keywords:

• Type 2 diabetes mellitus
• framingham risk score
• shrunken pore syndrome
• eGFR

Introduction

The prevalence of type 2 diabetes mellitus (T2DM) is increasing worldwide, and is projected to increase to 578 million by 2030 [1]. T2DM is a tremendous global public health concern and financial burden. Cardiovascular disease (CVD) and chronic kidney disease (CKD) are the common comorbidities of T2DM. Approximately 32.2% of patients with T2DM sufferred from CVD, including myocardial infarction, heart failure, coronary heart disease, and atherosclerosis [2]. CVD is the leading cause of mortality in patients with T2DM, accounting for 52% of all cases in the worldwide [3]. CKD increases the risk of adverse clinical outcomes, particularly CVD.

The Framingham Risk Score (FRS) is a simplified and commonly used clinical algorithm for estimating an individual’s 10-year CVD risk. According to the National Cholesterol Education Program Adult Treatment Panel (NCEP-ATP)-III guidelines, the FRS incorporates age, sex, smoking habits, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and systolic blood pressure (SBP) [4].

Shrunken pore syndrome (SPS) is characterized by a difference in renal filtration between cystatin C and creatinine, leading to a decreased ratio of estimated glomerular filtration rates (eGFR) based upon cystatin C to eGFR based upon creatinine [5]. Renal impairment measured by serum creatinine and cystatin C is associated with an increased risk of CVD morbidity and mortality [6, 7]. Schöttker et al. found that the cystatin C-based CKD equation showed potentially better clinical utility for FRS than creatinine-based equations in diabetes [8]. Recent studies have indicated that a lower eGFR_{cystatin C}/eGFR_creatinine ratio is associated with increased mortality and poor prognosis in general population cohorts and several clinical settings [9–13]. Whether SPS is associated with an increased risk of CVD in T2DM patients remains unclear. Based on the above, our study aimed to investigate the association between FRS and eGFR_{cystatin C}/eGFR_creatinine ratio in patients with newly diagnosed T2DM.

Methods

Study design and population

This retrospective study was conducted in the Department of Endocrinology of the Third Affiliated Hospital of Soochow University. Patients aged between 18 and 80 years with newly diagnosed T2DM were admitted between March 2011 and December 2012. The exclusion criteria were as follows: (1) complicated with heart disease, malignancy, and severe infection; (2) missing data for cystatin C or creatinine; (3) missing data for calculation of FRS; and (4) presence of proteinuria or renal dysfunction to exclude patients with diabetic kidney disease.

Data collection

Demographic data, medical history, and laboratory examinations were obtained from the electronic medical records. SBP, diastolic blood pressure (DBP), hemoglobin, albumin, globulin, fasting plasma glucose (FPG), serum creatinine, blood urea nitrogen (BUN), cystatin C, uric acid, glycated hemoglobin (HbA1c), TC, triglyceride, HDL-C, low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (apo-A1), and apolipoprotein B (apo-B) were included. Body mass index (BMI) (kg/m²) was equal to body weight divided by the square of height. The serum cystatin C and creatinine levels were measured by a laboratory technician blinded to patients’ information. The latex-enhanced immunoturbidimetric method and the Cystatin C Kit (Meikang Biotech, China) were used to measure serum cystatin C. The serum creatinine levels were measured by enzymatic creatinine-2 reagents (Siemens Healthcare Diagnostics Inc., Germany) using the enzyme method. The eGFR was calculated from creatine and cystatin C levels using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [14] (Table 1). SPS is a condition when eGFR_{cystatin C} is less than or equal to 70% of eGFR_creatinine [9]. Absolute 10-year CVD risk percentage was calculated according to the FRS scores. Individuals with FRS scores of <10% are considered to have a low 10-year risk of CVD, while those with FRS scores of 10% −20% and >20% are considered to have intermediate and high CVD risks, respectively [4].

Table 1. Formulas for estimating glomerular filtration rate.

	Gender	Creatinine (mg/dL)	cystatin C (mg/L)	Formula
CKD-EPI eGFRcreatinine	female	≤0.7		144×(sCr/0.7)^–0.329×0.993^age
	female	>0.7		144×(sCr/0.7)^–1.209×0.993^age
	male	≤0.9		144×(sCr/0.7)^–0.411×0.993^age
	male	>0.9		144×(sCr/0.7)^–1.209×0.993^age
CKD-EPI eGFRcystatin C	female		≤0.8	133×(cystatin C/0.8)^-0.499×0.996^age×0.932
	female		>0.8	133×(cystatin C/0.8)^-1.328×0.996^age×0.932
	male		≤0.8	133×(cystatin C/0.8)^-0.499×0.996^age
	male		>0.8	133×(cystatin C/0.8)^-1.328×0.996^age

Statistical analyses

Normality tests of continuous variables were performed using the Kolmogorov–Smirnov test. Normally distributed variables presented as mean ± standard deviation (SD) were compared using an unpaired t-test, while non-normally distributed variables presented as median (interquartile range, IQR) were compared using the Mann–Whitney U-test. Categorical variables, presented as frequencies (percentages), were compared using Pearson’s chi-square test. The association between risk factors of T2DM and the FRS risk was to be analyzed by ordinal logistic regression if the proportional odds assumption was satisfied. A Generalized Linear Model was used to calculate odds ratios (OR) and 95% confidence intervals (CI). All statistical analyses were performed using SPSS 24.0 software. A 2-sided P value less than 0.05 was regarded as statistically significant.

Results

This study included 270 patients, most of whom were male (60.7%). The clinical characteristics at baseline are shown in Table 2. Only 27 patients (10%) met the diagnostic criteria of SPS. Patients were divided into 2 groups: Group A, eGFR_{cystatin C}/eGFR_creatinine ≤0.85 (89 patients, 33% of patients, lowest tertile), and Group B, eGFR_{cystatin C}/eGFR_creatinine >0.85 (181 patients, 67% of patients, upper 2 tertiles). The median age of onset was 54 years. The average age of the patients in group A was higher than that of those in group B (p < 0.01). One-third of the patients had a family history of DM. There was a higher proportion of patients complicated with hypertension in group A (p < 0.01). However, there were no significant differences in SBP and DBP between the 2 groups. Compared with group B, a significantly higher BMI (p < 0.01), uric acid (p < 0.01), and triglycerides (p = 0.03) were found in group A. Patients in group A showed a higher level of cystatin C (p < 0.01) and a lower level of eGFR_{cystatin C} (p < 0.01), while no significant difference was detected in creatinine (p = 0.43) and eGFR_creatinine (p = 0.75). More patients in group A were at intermediate (36.0%) and high risk (14.6%) of CVD in the light of the FRS categorization than in group B (p = 0.03).

Table 2. Baseline characteristics of patients with type 2 diabetes.

Variables	Total (n = 270)	Group A (n = 89)	Group B (n = 181)	P-value
Male (n, %)	164 (60.7%)	59 (66.3%)	105 (58.0%)	0.19
Age (years)	54 (44, 62)	58 (47, 64)	51 (42, 59)	<0.01
Hypertension (n, %)	120 (44.4%)	51 (57.3%)	69 (38.1%)	<0.01
Smoking habit (n, %)	62 (23%)	24 (27.0%)	38 (21.0%)	0.27
Drinking habit (n, %)	37 (13.7%)	13 (14.6%)	24 (13.3%)	0.76
Diabetes family history (n, %)	90 (33.3%)	24 (27.0%)	66 (36.5%)	0.12
CVD family history (n, %)	18 (6.7%)	9 (10.1%)	9 (5.0%)	0.11
BMI (kg/m^2)	24.46 (22.59, 26.81)	25.39 (23.11, 27.43)	24.11 (22.45, 26.50)	<0.01
SBP (mmHg)	137.76 ± 15.42	139.69 ± 16.53	136.90 ± 14.68	0.16
DBP (mmHg)	85 (79, 91)	85 (80, 93)	84 (78, 91)	0.20
Albumin (g/L)	37.90 ± 3.35	37.55 ± 3.08	38.11 ± 3.46	0.20
Globulin (g/L)	26.40 (23.20, 28.86)	26.00 (23.18, 28.80)	26.55 (23.40, 28.90)	0.54
FPG (mmol/L)	8.99 (7.13, 11.36)	8.38 (6.95, 11.14)	9.32 (7.42, 11.49)	0.09
BUN (mmol/L)	4.80 (3.95, 5.75)	4.82 (4.15, 5.59)	4.85 (3.87, 5.81)	0.99
Serum creatinine (μmol/L)	77.60 (67.38, 87.20)	76.30 (64.55, 87.45)	78.00 (67.30, 87.15)	0.43
Cystatin C (mg/L)	0.95 (0.80, 1.08)	1.11 (1.01, 1.30)	0.85 (0.72, 0.98)	<0.01
eGFRcystatin C (ml/min/1.73m^2)	86.35 ± 22.96	66.12 ± 15.41	96.54 ± 19.74	<0.01
eGFRcreatinine (ml/min/1.73m^2)	89.35 ± 16.98	90.29 ± 18.96	89.58 ± 16.82	0.75
eGFRcystatin C/eGFRcreatinine	0.97 (0.80, 1.12)	0.76 (0.67, 0.80)	1.05 (0.97, 1.17)	<0.01
Uric acid (μmol/L)	256.95 (205.35, 309.18)	285.20 (218.20, 338.50)	242.70 (199.85, 296.30)	<0.01
CRP (mg/L)	3.70 (3.20, 4.10)	3.70 (3.10, 4.05)	3.7 (3.20, 4.20)	0.63
Cholesterol (mmol/L)	4.99 (4.35, 5.57)	4.98 (4.20, 5.60)	4.86 (3.29, 5.57)	0.68
Triglyceride (mmol/L)	2.35 (1.60, 3.58)	2.67 (1.67, 4.56)	2.29 (1.57, 3.12)	0.03
HDL-C (mmol/L)	1.05 (0.88, 1.19)	1.03 (0.88, 1.16)	1.04 (0.87, 1.20)	0.43
LDL-C (mmol/L)	2.49 (2.08, 2.93)	2.52 (2.06, 2.83)	2.44 (2.07, 2.93)	0.73
apo-A1 (g/L)	1.21 ± 0.15	1.21 ± 0.14	1.20 ± 0.15	0.42
apo-B (g/L)	1.02 (0.87, 1.22)	1.06 (0.89, 1.30)	1.00 (0.84, 1.17)	0.06
HbA1c (%)	10.6 (8.5, 12.1)	10.5 (8.4, 11.9)	10.9 (8.5, 12.2)	0.46
FRS				0.03
Low risk (n, %)	163 (60.4%)	44 (49.4%)	119 (65.7%)
Intermediate risk (n, %)	79 (29.3%)	32 (36.0%)	47 (26.0%)
High risk (n, %)	28 (10.4%)	13 (14.6%)	15 (8.3%)

Ordinal logistic regression analysis showed that hypertension (OR = 2.86, 95%CI = 1.75–4.67, p < 0.01), drinking habit (OR = 2.57, 95%CI = 1.33–4.98, p < 0.01), BUN (OR = 1.50, 95%CI = 1.23–1.83, p < 0.01), serum creatinine (OR = 1.04, 95%CI = 1.02–1.06, p < 0.01), cystatin C (OR = 13.77, 95%CI = 4.71–40.28, p < 0.01), eGFR_{cystatin C} (OR = 0.97, 95%CI = 0.96–0.98, p < 0.01), eGFR_creatinine (OR = 0.97, 95%CI = 0.96–0.98, p < 0.01), LDL-C (OR = 1.60, 95%CI = 1.14–2.25, p < 0.01), and HbA1c (OR = 1.12, 95%CI = 1.01–1.24, p = 0.03) were associated with FRS risk (Table 3). Although SPS was not correlated with FRS risk (OR = 1.99, 95%CI = 0.94–4.23, p = 0.07), eGFR_{cystatin C}/eGFR_creatinine (per 0.1unit increase, OR = 0.86, 95%CI = 0.77–0.97, p = 0.01) showed a significant negative association with FRS risk. Compared with eGFR_{cystatin C}/eGFR_creatinine>0.85, eGFR_{cystatin C}/eGFR_creatinine≤0.85 increased FRS risk (OR = 1.95, 95%CI = 1.18–3.21, p < 0.01). We further stratified patients into 4 groups by eGFR_{cystatin C}/eGFR_creatinine ratio: ≤0.70, 0.71–0.85, 0.86-0.99, and ≥1.00 (Figure 1). Compared with patients with eGFR_{cystatin C}/eGFR_creatinine ≥1.00, patients with eGFR_{cystatin C}/eGFR_creatinine ratio of ≤0.70 showed the highest FRS risk (OR = 2.88, 95%CI= 1.28–6.44, p = 0.01), those with eGFR_{cystatin C}/eGFR_creatinine ratio of 0.71–0.85 showed a still significant but not as high FRS risk (OR = 2.21, 95%CI = 1.20–4.07, p = 0.01), and those with eGFR_{cystatin C}/eGFR_creatinine ratio of 0.86-0.99 showed a borderline FRS risk (OR = 1.79, 95%CI = 0.95–3.38, p = 0.07).

Figure 1. The association between FRS and eGFR_{cystatin C}/eGFR_creatinine ratio at 4 ranges in univariate analysis.

Table 3. Association between baseline characteristics of T2DM and Framingham risk score (univariate Ordinal logistic regression analysis).

Variables	FRS
	Univariate analysis
	OR (95% CI)	P-value
Gender (male vs. female)	10.48 (5.36, 20.49)	<0.01
Age (years)	1.11 (1.08, 1.14)	<0.01
Hypertension	2.86 (1.75, 4.67)	<0.01
Smoking habit	6.41 (3.60, 11.44)	<0.01
Drinking habit	2.57 (1.33, 4.98)	<0.01
Diabetes family history	0.74 (0.44, 1.23)	0.24
CVD family history	0.45 (0.15, 1.37)	0.16
BMI (kg/m^2)	0.98 (0.91, 1.05)	0.55
SBP (mmHg)	1.02 (1.01, 1.04)	<0.01
DBP (mmHg)	0.99 (0.97, 1.02)	0.60
Albumin (g/L)	0.95 (0.88, 1.02)	0.15
Globulin (g/L)	0.97 (0.92, 1.03)	0.29
FPG (mmol/L)	1.02 (0.95, 1.10)	0.52
BUN (mmol/L)	1.50 (1.23, 1.83)	<0.01
Serum creatinine (μmol/L)	1.04 (1.02, 1.06)	<0.01
Cystatin C (mg/L)	13.77 (4.71, 40.28)	<0.01
eGFRcystatin C (ml/min/1.73m^2)	0.97 (0.96, 0.98)	<0.01
eGFRcreatinine (ml/min/1.73m^2)	0.97 (0.96, 0.98)	<0.01
eGFRcystatin C/eGFRcreatinine (per 0.1unit)	0.86 (0.77, 0.97)	0.01
Shrunken pore syndrome	1.99 (0.94, 4.23)	0.07
eGFRcystatin C/eGFRcreatinine (≤0.85 vs. >0.85)	1.95 (1.18, 3.21)	<0.01
Uric acid (μmol/L)	1.00 (1.00, 1.00)	0.76
CRP (mg/L)	0.89 (0.77, 1.03)	0.12
Cholesterol (mmol/L)	1.27 (1.06, 1.53)	0.01
Triglyceride (mmol/L)	1.06 (0.96, 1.16)	0.24
HDL-C (mmol/L)	0.26 (0.09, 0.79)	0.02
LDL-C (mmol/L)	1.60 (1.14, 2.25)	<0.01
apo-A1 (g/L)	1.15 (0.23, 5.73)	0.87
apo-B (g/L)	1.74 (1.00, 3.05)	0.05
HbA1c (%)	1.12 (1.01, 1.24)	0.03

As shown in Tables 4 and 5, hypertension, drinking habit, LDL-C, HbA1c, and BUN were associated with FRS risk in the multivariate ordinal logistic regression analysis. After adjusting for these confounding factors, increased eGFR_{cystatin C}/eGFR_creatinine ratio was associated with decreased FRS risk when considered as a continuous variable (per 0.1unit, OR = 0.87, 95%CI = 0.77–0.99, p = 0.03). The FRS risk in patients with eGFR_{cystatin C}/eGFR_creatinine≤0.85 is 1.86 times higher than that in patients with eGFR_{cystatin C}/eGFR_creatinine>0.85 (OR = 1.86, 95%CI = 1.08–3.21, p = 0.03).

Table 4. Association between continuous eGFR_{cystatin C}/eGFR_creatinine and Framingham risk score (multivariate Ordinal logistic regression analysis).

Variables	FRS
	Multivariate analysis
	OR (95% CI)	P-value
Hypertension	3.23 (1.89, 5.52)	<0.01
Drinking habit	3.24 (1.60, 6.59)	<0.01
LDL-C (mmol/L)	1.74 (1.20, 2.51)	<0.01
HbA1c (%)	1.12 (1.01, 1.26)	0.04
BUN (mmol/L)	1.54 (1.24, 1.90)	<0.01
eGFRcystatin C/eGFRcreatinine (per 0.1unit)	0.87 (0.77, 0.99)	0.03

Table 5. Association between eGFR_{cystatin C}/eGFR_creatinine≤0.85 and Framingham risk score (multivariate Ordinal logistic regression analysis).

Variables	FRS
	Multivariate analysis
	OR (95% CI)	P-value
Hypertension	3.18 (1.86, 5.44)	<0.01
Drinking habit	3.31 (1.63, 6.73)	<0.01
LDL-C (mmol/L)	1.72 (1.19, 2.48)	<0.01
HbA1c (%)	1.13 (1.01, 1.26)	0.04
BUN (mmol/L)	1.52 (1.23, 1.87)	<0.01
eGFRcystatin C/eGFRcreatinine (≤0.85 vs. >0.85)	1.86 (1.08, 3.21)	0.03

Discussion

In the present study, a significant relationship between renal function and different FRS categories among patients with T2DM was identified. Moreover, lower eGFR_{cystatin C}/eGFR_creatinine makes patients more susceptible to intermediate and high risks of CVD. The eGFR_{cystatin C}/eGFR_creatinine ratio could provide a predictive value for CVD risk in Chinese T2DM patients.

Our study demonstrated an inverse adjusted association between eGFR and FRS according to logistic regression analysis (eGFR_{cystatin C}: OR = 0.97, 95%CI = 0.96–0.98, p < 0.01; eGFR_creatinine: OR = 0.97, 95%CI = 0.96–0.98, p < 0.01). Previous studies have indicated an association between renal function and FRS in healthy and general population [15–17]. Consistent with our study, Khaloo et al. also confirmed an inverse association in patients with T2DM. However, a loss of correlation between eGFR and FRS was observed in patients with moderate to severe CKD [18]. These findings indicate that slowing the progression of diabetic kidney disease may reduce the chances of developing CVD events. A collaborative meta-analysis revealed that the inclusion of creatinine-based eGFR and albuminuria significantly improved the discrimination of CVD events in the general population, especially in individuals with diabetes and CKD [19]. Nevertheless, the addition of eGFR and albuminuria to the FRS formula did not substantially improve CVD risk prediction in patients with T2DM or CKD [18,20]. Future studies should investigate risk equations that include unique comorbidities associated with CKD to predict CVD events in T2DM patients.

This is the first study to explore the association between SPS and FRS in patients with T2DM. Increased levels of cystatin C and/or decreased levels of creatinine result in a lower eGFR_{cystatin C}/eGFR_creatinine ratio. The result indicated the eGFR_{cystatin C}/eGFR_creatinine ratio was valuable in predicting future CVD events. Serum creatinine is the most widely used endogenous filtration marker and is freely filtered across glomeruli [21,22]. It is influenced by muscle mass, dietary protein, and secretion by renal tubular epithelial cells, and extrarenal clearance [21,23]. Cystatin C is produced by nucleated cells, freely filtered across glomeruli, completely reabsorbed and metabolized by renal tubular epithelial cells [24]. Compared with creatinine, cystatin C is less affected by non-renal confounders; therefore, the eGFR calculated by cystatin C alone or in combination with creatinine is more dependable [25]. Possible mechanisms of SPS include decreased pore size in the filtration barrier, dysfunction of endothelial cell fenestrae, and thickness of the glomerular basement membrane [9,26,27]. An inverse correlation between glomerular basement membrane thickness and the eGFR_{cystatin C}/eGFR_creatinine ratio in kidney biopsies of diabetic kidney disease provides a basis for the latter mechanism [27]. SPS indicates renal function impairment and is associated with high mortality because of the accumulation of atherosclerosis-promoting proteins [11]. A high increase in morbidity and mortality has been observed in patients with SPS during long-term follow-up [28]. In 2781 patients measured GFR using iohexolclearance, patients with SPS showed a significantly higher all-cause mortality than those with cancer, CVD, diabetes, and CKD [29]. Furthermore, in individuals with normal measured GFR, there was a marked increase in all-cause mortality in individuals with SPS [29]. Although we did not detect a significant association between SPS and FRS, we found that a lower eGFR_{cystatin C}/eGFR_creatinine ratio was significantly related to intermediate and high CVD risk. Moreover, the increase in FRS categorization was inversely proportional to the eGFR_{cystatin C}/eGFR_creatinine starting at a ratio of 0.85 (OR = 1.86, 95%CI = 1.08–3.21, p = 0.03). We speculated that patients with a lower eGFR_{cystatin C}/eGFR_creatinine ratio might have a poor prognosis that supported by statistical association. These results will be useful for enabling early interventional strategies to prevent CVD and improve prognosis. The cutoff value of eGFR_{cystatin C}/eGFR_creatinine≤0.7 regarded as the definition of SPS, was obtained from patients undergoing cardiac surgery [28] and coronary artery bypass grafting [30]. Different eGFR_{cystatin C}/eGFR_creatinine ratio cutoff values are needed in various clinical settings to identify CVD risk. Thus, future studies with larger sample sizes are needed to determine suitable cutoff values for different patient populations.

Our study has some limitations. First, the FRS is only an estimation algorithm to predict CVD risk and is an imprecise tool in the young population. Second, other potential CVD risk factors may have been ignored. Finally, this was a cross-sectional study with a small sample size, the applicability of our results to other T2DM clinics may not be guaranteed. We were unable to clarify the causal relationship between the eGFR_{cystatin C}/eGFR_creatinine ratio and CVD events. A prospective multicenter study with long-term follow-up is needed to address the direction of causation.

Conclusions

This study evaluated the association between eGFR_{cystatin C}/eGFR_creatinine and FRS to estimate the 10-year CVD risk in patients with T2DM in China for the first time. Although we found no significant association between SPS and FRS, we concluded that lower eGFR_{cystatin C}/eGFR_creatinine and eGFR_{cystatin C}/eGFR_creatinine≤0.85 were associated with significantly increased CVD risk. The results provide valuable information for designing interventional strategies to prevent CVD in patients with T2DM.

Declarations

Ethics approval and consent to participate

The study was approved by the Ethics Committee of the Third Affiliated Hospital of Soochow University, China (registration number:27/2013), and conformed to the principles of the Declaration of Helsinki. Written informed consent was obtained from all the patients.

Authors’ contributions

Yan Yang: Methodology, Formal Analysis, Writing-Original Draft Preparation, Funding Acquisition; Bixia Yang: Resources, Data Curation, Formal Analysis, Investigation; Shizhu Zhao: Resources, Data Curation, Writing–Review & Editing; Shusu Liu: Software, Investigation, Data Curation; Hua Zhou: Validation, Visualization; Min Yang: Conceptualization, Funding Acquisition, Project Administration; Ning Xu: Conceptualization, Supervision.

Consent for publication

Not applicable.

Acknowledgements

Not applicable.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data and materials

Data used to support the findings of this study are available from the corresponding author upon request.

Additional information

Funding

This study was supported by the Changzhou Science and Technology Youth Talent Support Program (Grant No. KY20221408), Funding from Young Talent Development Plan of Changzhou Health Commission (Grant No. CZQM2023002) and Changzhou Key Medical Discipline (Grant No. CZXK202204).