Kidney Res Clin Pract > Epub ahead of print
Chung, Liu, Wu, Huang, Tsai, Hsu, Kuo, Chiu, Wu, and Chen: Blood osteoprotegerin is associated with arteriovenous access thrombosis in hemodialysis patients

Abstract

Background

A functioning arteriovenous (AV) access is essential for hemodialysis efficiency and the quality of life in hemodialysis patients. Blood osteoprotegerin (OPG) and soluble receptor activator of nuclear factor kappa B ligand (RANKL) have been linked to cardiovascular diseases and vascular calcification. This study investigated the relationship between blood OPG, RANKL, and the occurrence of AV access thrombosis.

Methods

This prospective cohort study was conducted from August 2016 to August 2021 and included patients undergoing prevalent hemodialysis in two hospital-based hemodialysis units. Cox proportional hazards models and Kaplan-Meier analysis were used to evaluate the association between blood OPG, RANKL, and AV access (AV fistula [AVF] and AV graft [AVG]) outcomes.

Results

A total of 333 hemodialysis patients were enrolled, with an AV access thrombosis rate of 22.2%. Cox regression identified several factors associated with AV access thrombosis: AV access type (AVF vs. AVG; hazard ratio [HR], 0.24; p < 0.001), C-reactive protein (HR, 1.07; p = 0.002), and log-transformed OPG (HR, 5.52; p = 0.005). Subgroup analysis revealed high log-transformed OPG and RANKL were associated with AVF thrombosis (HR, 10.77; p = 0.002 and HR, 3.26; p = 0.009, respectively), while high C-reactive protein increased the risk of AVG thrombosis (HR, 1.31; p < 0.001). Kaplan-Meier analysis showed that patients with AVF in the highest tertile of log OPG (>402 pg/mL) had the highest AVF thrombosis incidence (p = 0.03).

Conclusion

High blood OPG was associated with AV access thrombosis, particularly in the AVF.

Introduction

The prevalence of end-stage kidney disease (ESKD) continues to increase globally owing to improved patient survival, higher prevalence of risk factors for ESKD, and increasing availability of kidney replacement therapy [1]. In patients undergoing hemodialysis (HD), vascular access is recognized as a ‘lifeline’ and provides adequate blood flow for HD treatment. According to the current guidelines, arteriovenous (AV) access, including AV fistulas (AVFs) and prosthetic AV grafts (AVGs), is preferred over central venous catheters in prevalent HD patients due to fewer vascular access-related events (e.g., infections, thrombotic and non-thrombotic complications) [2]. Thrombosis is a leading cause of AV access failure, potentially leading to missed dialysis sessions, hospitalizations, the need for endovascular or surgical thrombectomy, and all-cause mortality [3,4].
Several risk factors for vascular access thrombosis have been identified, including older age, female sex, diabetes, obesity, peripheral vascular disease, atherosclerosis, pre-dialysis hypotension, smoking, the use of an AVG, a distal fistula site, hypoalbuminemia, and elevated inflammatory biomarkers [58]. Recent studies have highlighted the association between vascular calcification and AV access patency [9,10]. Vascular calcification is highly prevalent in patients with ESKD and is a well-known risk factor for cardiovascular events and all-cause mortality in this population [11,12].
Osteoprotegerin (OPG), a member of the tumor necrosis factor (TNF) receptor superfamily, functions as a soluble decoy receptor for the receptor activator of nuclear factor kappa B ligand (RANKL) and regulates osteoclast activation in bone remodeling [13]. Increasing evidence suggests the involvement of the OPG/receptor activator of nuclear factor kappa B (RANK)/RANKL axis in coronary artery disease, atherosclerotic disorders, and vascular calcification [1417]. Some studies have demonstrated elevated OPG concentrations in patients with calcified vessels, suggesting an interacting pathway that increases OPG expression during the development of vascular calcification [18,19]. Additionally, many studies have observed a potential link between the OPG/RANK/RANKL axis and unprovoked venous thromboembolic disease and ischemic stroke [20,21]. A previous experimental study also showed that OPG can regulate platelet adhesion to von Willebrand factor secreted from endothelial cells [22]. However, studies exploring the relationship between blood OPG, soluble RANKL, and AV access outcome are limited. Hence, in this study, we prospectively evaluated the association between AV access thrombosis and clinical factors including OPG and RANKL blood levels in a cohort of stable HD patients.

Methods

Study design and populations

This prospective study was conducted at two hospital-based HD units from August 2016 to January 2017. Patients were included if they 1) were over 20 years of age, 2) had been receiving maintenance HD treatment for at least 90 days, and 3) were using an AVF or AVG as vascular access for HD. The patients who had undergone vascular intervention within 3 months prior to enrollment were excluded. All of the patients received HD treatment three times a week, with each HD session lasting 3.5 to 4 hours, with a blood flow rate of 250 to 300 mL/min and dialysate flow of 500 mL/min. The patients were followed until the occurrence of AV access thrombosis, the end of the study on August 31, 2021, transfer to other HD units or death.
The study protocol was approved by the Institutional Review Board of Kaohsiung Medical University (No. KMUHIRB-E(I)-20160065), and all patients provided signed informed consent.

Demographic, medical, and laboratory data collection

We obtained information including demographics, comorbidities, and laboratory data from the medical records of the dialysis units. Blood samples were collected as soon as possible after enrollment and at the beginning of the week following an overnight fast from the patients via the AV access before the scheduled HD session and stored at –80 °C. Outcomes of the AV access were prospectively collected by reviewing the medical records. The baseline variables examined for correlations with thrombotic events of the AV access included the following: age, sex, smoking status, body mass index (BMI), duration of dialysis treatment, presence of diabetes, presence of hypertension, presence of cardiovascular disease (CVD), type of AV access being used, use of antiplatelet agents, use of warfarin, and levels of hemoglobin, albumin, potassium, calcium × phosphorus products, C-reactive protein (CRP), ferritin, Kt/V, OPG, and RANKL.

The definition of demographics and medical data

Diabetes was defined as a blood glycosylated hemoglobin level above 6.5% or the use of antidiabetic drugs. Hypertension was defined as the current use of antihypertensive medication. The definition of CVD is a patient having coronary artery disease (a history of percutaneous coronary intervention or coronary artery bypass grafting, or diagnosed by a cardiologist) or cerebrovascular disease (a history of cerebrovascular events or diagnosed by a neurologist). Smoking history was defined as current or past cigarette smoking. BMI was calculated as body weight in kilograms divided by the square of height in meters. The use of antiplatelet or warfarin was defined based on the patient’s current use of these drugs at the time of enrollment.

Measurement of osteoprotegerin and RANKL levels

Circulating levels of OPG and RANKL were measured with commercial multiplex enzyme-linked immunosorbent assay kits (MILLIPLEX MAP, Merck Millipore) following the manufacturer’s protocols. In brief, capture microspheres coated with monoclonal antibodies were applied to the wells, followed by standards and plasma samples. After incubation and washing, biotinylated secondary antibodies were added and then incubated with streptavidin-bound fluorescent protein. After washing, microsphere-containing precipitates were resuspended for analysis in a MAGPIX analyzer (Luminex Corp.). Results were processed by Milliplex Analyst software (MilliporeSigma) and reported in pg/mL.

Definition of arteriovenous access thrombosis

Routine monitoring and surveillance protocols for detecting AV dysfunction were conducted according to the KDOQI guidelines. All of the patients were referred for diagnostic angiography and intervention if clinical monitoring detected a sudden cessation of access function. AV access thrombosis was defined as the abrupt occlusion of AV access requiring an intervention. The outcome was defined as the time to the first AV access thrombotic event. We refer patients for vascular intervention only when a thrombotic event causes a complete cessation of blood flow in their AV access.

Statistical analysis

The baseline characteristics of the study patients were compared based on the occurrence of AV access thrombosis. Differences between the two groups were assessed using the chi-square test for categorical variables, the independent t test for continuous variables with approximately normal distribution, and the Mann-Whitney U test for continuous variables with skewed distribution. Data are expressed as percentages for categorical variables or mean ± standard deviation. Potential risk factors for AV access thrombosis were assessed using univariable Cox proportional hazards models. Significant risk factors for AV access thrombosis were selected by forward selection in multivariable Cox proportional hazards analysis. A forward selection procedure sequentially enters variables into the model if they meet the entry criterion. The first variable selected is the one with the largest positive or negative correlation with the dependent variable. The following variable chosen is the one with the largest partial correlation not yet included in the equation. The procedure terminates when no additional variables meet the entry criterion. To evaluate whether distinct variables contributed to AV access thrombosis according to the type of AV access being used, subgroup analysis categorized by AVF or AVG was conducted. The associations between tertiles of log OPG and log RANKL with AVF outcomes were analyzed using Kaplan-Meier curves, and the log-rank test was used to assess differences between the groups. All of the analyses were performed using IBM SPSS version 26 for Windows (IBM Corp.).

Results

Comparisons of baseline characteristics between arteriovenous access outcomes in all patients

A total of 333 patients were included in this cohort study. The mean age of the patients was 59.4 ± 11.5 years, and 174 (52.3%) were male. Of these patients, 290 (87.1%) were using an AVF, and 43 (12.9%) were using an AVG. During a mean follow-up of 5.5 ± 2.1 years, 74 cases of AV access thrombosis occurred, accounting for 22.2% of the total cohort. The clinical characteristics and laboratory data of the study groups, categorized by the occurrence of AV access thrombosis, are summarized in Table 1.
In the patients with AV access thrombosis, the thrombosis rate was higher in those who used an AVG (23 of 43 AVG users, 53.5%) than in those who used an AVF (51 of 290 AVF users, 17.6%). In addition, the patients who experienced an AV access thrombotic event were more likely to have CVD (32.4% vs. 21.2%, p = 0.046), use an AVG (31.1% vs. 7.7%, p < 0.001), use warfarin (8.1% vs. 2.3%, p = 0.03), and have higher levels of hemoglobin (11.0 ± 1.0 g/dL vs. 10.7 ± 1.3 g/dL, p = 0.04), CRP (3.5 ± 4.5 mg/L vs. 2.1 ± 4.2 mg/L, p = 0.02), and OPG (1,168.5 ± 588.9 pg/mLvs. 977.5 ± 442.4 pg/mL, p = 0.01).

Determinants of arteriovenous access outcomes in all patients

Risk factors for AV access thrombosis are presented in Table 2. Multivariable Cox regression model showed that the patients using an AVF had a significantly lower risk of AV access thrombosis than those using an AVG (AVF vs. AVG: adjusted hazard ratio [HR], 0.24; 95% confidence interval [CI], 0.14–0.41; p < 0.001). In addition, the patients with CVD (HR, 2.13; 95% CI, 1.08–4.21; p = 0.03), high CRP levels (HR, 1.07; 95% CI, 1.03–1.11; p = 0.002), high log OPG (HR, 5.52; 95% CI, 1.67–18.22; p = 0.005), and those who used warfarin (HR, 2.61; 95% CI, 1.03–6.63; p = 0.04) were associated with an increased risk of AV access thrombosis.

Comparisons of the clinical characteristics between arteriovenous access outcomes by the type of arteriovenous access

The relationships between risk factors and AV access thrombosis were explored through subgroup analysis, as shown in Table 3. Among the patients using an AVF, there were no significant differences in age, sex, or comorbidities between those with and without AVF thrombosis. However, the patients with AVF thrombosis had higher serum OPG levels than those without AVF thrombosis (1,177.2 ± 658.1 pg/mL vs. 979.7 ± 441.9 pg/mL, p = 0.045). In the patients using an AVG, those with AVG thrombosis had higher levels of hemoglobin (11.2 ± 1.1 g/dL vs. 10.2 ± 1.6 g/dL, p = 0.03) and CRP (4.6 ± 4.4 mg/L vs. 1.6 ± 2.0 mg/L, p = 0.006) compared to those without AVG thrombosis.

Determinants of arteriovenous access outcomes by the type of arteriovenous access

Risk factors for AV access thrombosis categorized by AVF and AVG are presented in Table 4. Multivariable Cox regression model showed that patients with AVF thrombosis had higher levels of log OPG (HR, 10.77; 95% CI, 2.37–48.9; p = 0.002), log RANKL (HR, 3.26, 95% CI, 1.34–7.94, p = 0.009), and BMI (HR, 1.10; 95% CI, 1.02–1.20; p = 0.01) compared to those with AVF patency. In addition, the patients with AVG thrombosis had a higher CRP level (HR, 1.31; 95% CI, 1.15–1.50; p < 0.001), and higher rates of antiplatelet and warfarin therapy than those without AVG thrombosis.

Association between blood osteoprotegerin and RANKL and arteriovenous fistula outcomes

Among the patients using an AVF, those in the highest tertile of log OPG (>402 pg/mL) had a higher cumulative incidence of AVF thrombosis compared to those in the lowest (<211 pg/mL) and intermediate (211–402 pg/mL) tertiles of log OPG (p = 0.03) (Fig. 1A). However, log RANKL levels across tertiles were not associated with AVF thrombotic events (Fig. 1B).

Discussion

This study suggested that higher blood OPG is associated with an increased risk of AV access thrombosis. Additionally, our results revealed that different types of AV access correspond to distinct risk factors for developing thrombotic events. Specifically, in patients using an AVF, elevated blood levels of OPG and RANKL were strongly associated with AVF thrombosis, whereas increased levels of CRP were associated with thrombosis in patients using an AVG.
A key finding of the study is that the patients with higher levels of OPG and RANKL were at a higher risk of developing AVF thrombosis, while these associations were not observed in the patients using AVG. Furthermore, the highest log OPG tertile was linked to an increased risk of an AVF thrombotic event. Most previous studies highlight that blood levels of OPG are associated with arterial calcification, such as coronary arterial calcification, and mortality in HD patients [16,23,24]. Clinical studies link serum OPG levels with AV access dysfunction or thrombosis, but the results have been inconsistent. Kim et al. [25] reported that serum OPG levels were positively correlated with the degree of AVF stenosis using ultrasonography. On the other hand, Morena et al. [26] found no association between OPG and RANKL levels with AVF thrombosis in a study with 128 HD patients. In a prospective study of 727 patients with HD, Lyu et al. [9] investigated markers of vascular calcification and vascular access complications and suggested that OPG was not significantly associated with the risk of an AVF intervention. Instead, they found that other vascular calcification markers, including fetuin-A, osteopontin, and bone morphogenetic protein 7, were associated with an AVF intervention. There are various possible explanations for the link between OPG and AVF thrombosis. As a marker of vascular calcification, higher OPG levels are more likely to be associated with preexisting AV access calcification, which has been suggested to predict AVF failure in HD patients [10,27]. In addition, prior research has shown that OPG is expressed in normal vasculature and is more predominant in advanced atherosclerotic plaques [19], suggesting that circulating OPG may originate from these vascular plaques. The presence of atherosclerosis has been linked to an increased risk of AVF failure [7,8], establishing OPG as a potential biomarker associated with AVF thrombosis [15]. Despite the strong correlation between OPG/RANKL and vascular calcification, there is currently no literature focusing on the direct relationship between OPG and AVF or venous calcification, possibly because AVF calcification is difficult to detect, thus limiting research on this topic. Noteworthy, OPG has been associated with many risk factors that cause vascular calcification and AVF thrombosis, such as old age, diabetes mellitus, and chronic inflammation [5,8,28]. These risk factors may also contribute to eventual AVF thrombosis. Among these risk factors, inflammation, indicated by elevated inflammatory markers and cytokines such as CRP, interleukin-6, and TNF-α, is particularly relevant to AV access thrombosis [29,30]. OPG, belonging to the TNF receptor family, is stimulated by pro-inflammatory agents such as TNF in vascular smooth muscle and endothelial cells [31,32]. Furthermore, emerging evidence has revealed the complex interplay between inflammation and vascular thrombosis [33]. Therefore, OPG levels may link to AVF thrombotic events under inflammatory conditions. However, the association was not observed in patients using AVGs in the present study, which is consistent with Lyu et al. [9], who reported no significant correlation between calcification markers, including OPG, and AVG intervention. Generally, stenosis induced by neointimal hyperplasia at the venous anastomoses is the primary cause of AVG thrombosis. The histology of neointimal hyperplasia comprises myofibroblasts, extracellular matrices, pro-inflammatory cells, neovasculature, and various growth factors and cytokines [30]. Because of the strong correlation of neointimal hyperplasia-induced stenosis with AVG thrombosis, which is less related to vascular calcification, this may partly explain the insignificant association between OPG and AVG thrombosis. Moreover, the small sample size of AVG users in our study may have resulted in reduced statistical power. Further research is needed to investigate this association in AVG users.
In this study, a positive correlation was found between blood RANKL and thrombosis of the AVF. However, the tertiles of blood RANKL were not significantly associated with AVF survival in the Kaplan-Meier analysis. Prior research has suggested the pathogenic effects of the RANKL/OPG/RANK axis in atherosclerosis [15,34], and vascular calcification has been linked to RANKL activity [35]. Nevertheless, the use of serum RANKL as a biomarker for CVD remains controversial. Lieb et al. [36] observed no association between serum RANKL and coronary artery calcification, incident CVD, or mortality in the general population. Similarly, in another cohort study conducted by Spartalis et al. [16] involving 80 HD patients, RANKL levels did not correlate with the presence or progression of vascular calcification in the abdominal aorta and muscular arteries. However, the Bruneck Study, including 909 participants, found that baseline serum RANKL levels strongly predicted CVD [37]. Generally, OPG levels are significantly higher than RANKL levels in circulation, and previous research suggests that OPG is a more stable and reliable indicator of the RANKL/OPG/RANK axis than soluble RANKL [15].
Another important finding in this study is that the patients with elevated CRP levels had a higher risk of developing AV access thrombosis, and the risk was more pronounced among the patients who used an AVG. In general, patients using AV access experience localized and systemic inflammation due to factors such as oxidative stress, wall shear stress, endothelial dysfunction, needle cannulation, AV access surgery, graft material biocompatibility, and uremic status [30,38,39]. Several clinical studies have reported an association between inflammation in HD patients with AV access thrombosis. Chou et al. [29] found that higher serum CRP levels in chronic HD patients were linked to a higher risk of vascular access thrombosis. Notably, compared to AVF users, those with an AVG have been reported to be more likely to have low-grade inflammation at baseline [40], which may lead to an increased risk of AV access thrombosis. These findings are consistent with our study, as suggested by the association of elevated CRP levels with AVG thrombosis. Although the timing of blood sample collection in the present study may not have aligned with that of AV access thrombosis, potentially limiting its ability to reflect the inflammatory status at the time of the thrombosis, our findings still indicated that the HD patients with elevated baseline CRP levels, suggesting chronic inflammation, were at an increased risk of AV access thrombosis, and particularly those with AVG.
The present study has several limitations. First, the small sample size may have decreased the statistical power, particularly in stratified analyses of the patients using AVGs. Second, an observational study may not adequately adjust for all potential confounders. For example, we didn’t have detailed data on AV access vintage, which may have a potential link with AV access thrombosis. Third, the absence of serial measurements of serum OPG and RANKL meant that we could not analyze associations between their fluctuations and the development of AV access thrombosis. Fourth, while we observed an association between higher OPG levels and AVF thrombosis, it is still unclear whether increased OPG contributes directly to the development of a thrombosed AVF or is simply a compensatory response to atherosclerotic disease. In addition, we didn’t perform other imaging studies, such as sonography, to confirm the presence of AV access calcification, despite the significant correlation between OPG and calcification found in previous research. Further investigations are needed to understand the underlying mechanisms of this observation.
In conclusion, our results identified high blood OPG levels associated with AV access thrombosis, particularly in the AVF, suggesting that OPG may be a potential biomarker in clinical use. Further research may be required to investigate the underlying pathophysiological mechanisms for preventing AV access thrombosis.

Notes

Conflicts of interest

All authors have no conflicts of interest to declare.

Funding

The study was funded by grants from the Ministry of Science and Technology, Taiwan (MOST 111-2314-B-037-032-MY3), Kaohsiung Medical University Hospital, Taiwan (KMUH111-1M60, KMUH111-1R73, KMUH111-1M09, KMUH110-0M13, KMUH110-0M73, KMUH110-0M12, and KMUH-DK(C)112001), and Kaohsiung Medical University, Taiwan (KT113P006, KT112P012, NYCUKMU-112-I006, NHRIKMU-111-I003, and NHRIKMU-111-I001). This study is supported partially by the Kaohsiung Medical University Research Center Grant (KMU-TC112B04), KMUH-DK(C)112001, and KMUH-DK(C)113003. The funding sources did not play any role in the design or conduct of the study, collection, management, analysis, interpretation of the data, or preparation, review, or approval of the manuscript.

Acknowledgments

The authors express gratitude to all the patients and healthcare providers who participated in this study, as well as to Kaohsiung Medical University Hospital and Kaohsiung Municipal Siaogang Hospital for their support in conducting this research.

Data sharing statement

The data presented in this study are available from the corresponding author upon reasonable request.

Authors’ contributions

Conceptualization: TLC, YHL, PHW, SCC

Formal analysis: TLC, PHW, SCC

Funding acquisition: PHW

Methodology: MCK, YWC, PHW

Writing–original draft: TLC, PYW, JCH, YCT

Writing–review & editing: YLH, PHW, SCC

All authors read and approved the final manuscript.

Figure 1.

Kaplan-Meier curve of the occurrence of AVF thrombosis in hemodialysis patients.

(A) According to the tertile of log-transformed osteoprotegerin (OPG) levels (log-rank p = 0.03). (B) According to the tertile of log-transformed receptor activator of nuclear factor kappa B ligand (RANKL) levels (log-rank p = 0.43).
AVF, arteriovenous fistula.
j-krcp-24-153f1.jpg
Table 1.
Comparison of clinical characteristics between patients with or without AV access thrombosis
Characteristic Without AV access thrombosis (n = 259) With AV access thrombosis (n = 74) p-value
Age (yr) 59.4 ± 11.5 59.2 ± 11.9 0.91
Male sex 137 (52.9) 37 (50.0) 0.66
Diabetes mellitus 110 (42.5) 31 (41.9) 0.93
Hypertension 194 (74.9) 60 (81.1) 0.27
CVD 55 (21.2) 24 (32.4) 0.046
Smoking history 28 (12.0) 5 (6.8) 0.28
BMI (kg/m2) 23.4 ± 3.8 24.2 ± 3.5 0.10
HD vintage (yr) 6.9 ± 5.5 7.4 ± 6.2 0.51
AV access type <0.001
 AVF 239 (92.3) 51 (68.9)
 AVG 20 (7.7) 23 (31.1)
Laboratory parameters
 Hemoglobin (g/dL) 10.7 ± 1.3 11.0 ± 1.0 0.04
 Albumin (g/dL) 3.9 ± 0.3 3.9 ± 0.3 0.30
 Potassium (meq/L) 4.6 ± 0.6 4.6 ± 0.6 0.85
 Ca × P product (mg2/dL2) 43.9 ± 11.1 4..4 ± 11.0 0.72
 CRP (mg/L) 2.1 ± 4.2 3.5 ± 4.5 0.02
 Ferritin (ng/mL) 472.0 ± 314.5 473.2 ± 397.6 0.98
 Kt/V (Daugirdas) 1.57 ± 0.3 1.57 ± 0.2 0.95
Biomarkers
 OPG (pg/mL) 977.5 ± 442.4 1,168.5 ± 588.9 0.01
 RANKL (pg/mL) 4.24 ± 5.0 5.2 ± 6.2 0.17
Medications
 Antiplatelet 63 (24.3) 23 (31.1) 0.24
 Warfarin 6 (2.3) 6 (8.1) 0.03

Values are presented as mean ± standard deviation or number (%).

AV, arteriovenous; AVF, arteriovenous fistula; AVG, arteriovenous graft; Ca, calcium; CRP, C-reactive protein; OPG, osteoprotegerin; P, phosphorus; RANKL, receptor activator of nuclear factor kappa B ligand.

Table 2.
Determinants of AV access survival in HD patients
Variable Univariable analysis
Multivariable analysis
HR (95% CI) p-value Adjusted HRa (95% CI) p-value
Age (per 1 yr) 1.00 (0.98–1.02) 0.91 - -
Sex (male vs. female) 0.88 (0.56–1.40) 0.88 - -
Diabetes mellitus 0.96 (0.60–1.52) 0.96 - -
Hypertension 1.35 (0.76–2.42) 0.31 - -
CVD 1.68 (1.03–2.73) 0.04 2.13 (1.08–4.21) 0.03
Smoking history 0.62 (0.25–1.53) 0.62 - -
BMI (per 1 kg/m2) 1.05 (0.99–1.12) 0.10 - -
HD vintage (per 1 yr) 1.02 (0.98–1.06) 0.43 - -
AV access type (AVF vs. AVG) 0.23 (0.14–0.39) <0.001 0.24 (0.14–0.41) <0.001
Hemoglobin (per 1g/dL) 1.23 (1.02–1.49) 0.03 - -
Albumin (per 1g/L) 1.60 (0.71–3.61) 0.26 - -
K (per 1 meq/L) 0.93 (0.65–1.32) 0.67 - -
Ca × P product (per 1 mg2/dL2) 1.00 (0.98–1.02) 0.68 - -
CRP (per 1 mg/L) 1.05 (1.01–1.08) 0.01 1.07 (1.03–1.11) 0.002
Ferritin (per 1 ng/mL) 1.00 (1.00–1.00) 0.99 - -
Kt/V (per 1) 0.98 (0.39–2.48) 0.96 - -
log OPG (per 1 pg/mL) 5.07 (1.58–16.23) 0.006 5.52 (1.67–18.22) 0.005
log RANKL (per 1 pg/mL) 1.98 (0.95–4.13) 0.07 - -
Antiplatelet use 1.31 (0.80–2.14) 0.29
Warfarin use 3.17 (1.38–7.32) 0.007 2.61 (1.03–6.63) 0.04

AV, arteriovenous; AVF, arteriovenous fistula; AVG, arteriovenous graft; BMI, body mass index; Ca, calcium; CI, confidence interval; CRP, C-reactive protein; CVD, cardiovascular disease; HR, hazard ratio; HD, hemodialysis; OPG, osteoprotegerin; P, phosphorus; RANKL, receptor activator of nuclear factor kappa B ligand.

aAdjusted for CVD, AV access type, CRP, log OPG, and warfarin use.

Table 3.
Comparison of clinical characteristics between patients with or without AV access thrombosis in different types of AV access (AVF or AVG)
Characteristic AVF (n=290)
AVG (n=43)
Without AVF thrombosis (n = 239) With AVF thrombosis (n = 51) p-value Without AVG thrombosis (n = 20) With AVG thrombosis (n = 23) p-value
Age (yr) 59.4 ± 11.6 58.4 ± 12.3 0.55 59.4 ± 10.5 61.2 ± 11.0 0.58
Male sex 128 (53.6) 29 (56.9) 0.67 9 (45.0) 8 (34.8) 0.49
Diabetes mellitus 103 (43.1) 21 (41.2) 0.80 7 (35.0) 10 (43.5) 0.57
Hypertension 183 (76.6) 42 (82.4) 0.37 11 (55.0) 18 (78.3) 0.10
CVD 51 (21.3) 14 (27.5) 0.34 4 (20.0) 10 (43.5) 0.10
Smoking history 26 (12.0) 4 (8.2) 0.44 2 (10.0) 1 (4.3) 0.59
BMI (kg/m2) 23.4 ± 3.8 24.4 ± 3.5 0.09 23.2 ± 4.0 23.7 ± 3.5 0.67
HD vintage (yr) 6.9 ± 5.5 6.9 ± 6.0 0.98 7.6 ± 6.4 8.6 ± 6.8 0.62
Laboratory parameters
 Hemoglobin (g/dL) 10.7 ± 1.2 10.9 ± 1.0 0.31 10.2 ± 1.6 11.2 ± 1.1 0.03
 Albumin (g/dL) 3.9 ± 0.3 3.9 ± 0.3 0.27 3.9 ± 0.3 3.9 ± 0.3 0.82
 K (meq/L) 4.6 ± 0.6 4.7 ± 0.7 0.33 4.6 ± 0.7 4.3 ± 0.4 0.09
 Ca × P product (mg2/dL2) 43.9 ± 10.8 43.2 ± 11.7 0.70 44.5 ± 14.6 43.8 ± 9.1 0.86
 CRP (mg/L) 2.2 ± 4.3 3.0 ± 4.5 0.22 1.6 ± 2.0 4.6 ± 4.4 0.006
 Ferritin (ng/mL) 465.6 ± 294.0 452.8 ± 236.4 0.77 548.2 ± 503.7 518.4 ± 628.0 0.87
 Kt/V (Daugirdas) 1.6 ± 0.3 1.6 ± 0.2 0.73 1.6 ± 0.3 1.5 ± 0.1 0.63
Biomarkers
 OPG (pg/mL) 979.7 ± 441.9 1,177.2 ± 658.1 0.045 951.0 ± 460.0 1,149.0 ± 407.1 0.14
 RANKL (pg/mL) 4.1 ± 4.8 5.6 ± 7.2 0.16 6.4 ± 7.1 4.4 ± 3.1 0.23
Medications
 Antiplatelet 60 (25.1) 15 (29.4) 0.52 3 (15.0) 8 (34.8) 0.14
 Warfarin 6 (2.5) 2 (3.9) 0.63 0 (0) 4 (17.4) 0.11

Values are presented as mean ± standard deviation or number (%).

AV, arteriovenous; AVF, arteriovenous fistula; AVG, arteriovenous graft; BMI, body mass index; Ca, calcium; CRP, C-reactive protein; CVD, cardiovascular disease; HD, hemodialysis; OPG, osteoprotegerin; P, phosphorus; RANKL, receptor activator of nuclear factor kappa B ligand.

Table 4.
Determinants of AVF and AVG thrombosis in HD patients
Variable AVF (n=290)
AVG (n=43)
Univariable analysis
Multivariable analysis
Univariable analysis
Multivariable analysis
HR (95% CI) p-value Adjusted HRa (95% CI) p-value HR (95% CI) p-value Adjusted HRb (95% CI) p-value
Age (per 1 yr) 0.99 (0.97–1.02) 0.51 - 1.02 (0.98–1.26) 0.46 -
Sex (Male vs. female) 1.11 (0.64–1.92) 0.72 - 0.80 (0.34–1.90) 0.62 -
Diabetes mellitus 0.93 (0.53–1.62) 0.78 - 1.08 (0.47–2.46) 0.86 -
Hypertension 1.37 (0.67–2.82) 0.39 - 1.92 (0.71–5.18) 0.20 -
CVD 1.34 (0.73–2.48) 0.35 - 2.44 (1.07–5.58) 0.04 -
Smoking history 0.68 (0.24–1.88) 0.45 - 0.56 (0.75–4.19) 0.57 -
BMI (per 1 kg/m2) 1.07 (0.99–1.14) 0.08 1.10 (1.02–1.20) 0.01 1.03 (0.92–1.14) 0.66 -
HD vintage (per 1 yr) 1.00 (0.95–1.06) 0.90 - - 1.02 (0.96–1.09) 0.55 -
Hemoglobin (per 1g/dL) 1.14 (0.90–1.44) 0.28 - - 1.34 (1.01–1.78) 0.04 -
Albumin (per 1g/L) 1.80 (0.67–4.86) 0.24 - - 1.38 (0.38–5.08) 0.63 -
K (per 1 meq/L) 1.20 (0.79–1.83) 0.40 - - 0.50 (0.24–1.04) 0.06 -
Ca × P product (per 1 mg2/dL2) 0.99 (0.97–1.02) 0.65 - - 1.00 (0.97–1.03) 0.96 -
CRP (per 1 mg/L) 1.03 (0.99–1.08) 0.19 - - 1.19 (1.08–1.31) <0.001 1.31 (1.15–1.50) <0.001
Ferritin (per 1 ng/mL) 1.00 (1.00–1.00) 0.79 - - 1.00 (1.00–1.00) 0.84 - -
Kt/V (per 1) 1.24 (0.41–3.76) 0.71 - - 0.59 (0.10–3.51) 0.56 - -
log OPG (per 1 pg/mL) 4.26 (1.06–17.17) 0.04 10.77 (2.37–48.9) 0.002 8.98 (0.92–87.33) 0.06 - -
log RANKL (per 1 pg/mL) 2.43 (1.01–5.84) 0.048 3.26 (1.34–7.94) 0.009 0.61 (0.16–2.37) 0.48 - -
Antiplatelet use 1.19 (0.65–2.17) 0.58 - 1.87 (0.79–4.43) 0.15 4.30 (1.40–13.3) 0.01
Warfarin use 1.56 (0.38–6.42) 0.54 - 4.36 (1.41–13.51) 0.01 17.56 (3.30–93.6) 0.001

AVF, Arteriovenous fistula; AVG, Arteriovenous graft; BMI, body mass index; Ca, calcium; CI, confidence interval; CRP, C-reactive protein; CVD, cardiovascular disease; HD, hemodialysis; HR, hazard ratio; OPG, osteoprotegerin; P, phosphorus; RANKL, receptor activator of nuclear factor kappa B ligand.

aAdjusted for BMI, log OPG, and log RANKL.

bAdjusted for CRP, antiplatelet use, and warfarin use.

References

1. Thurlow JS, Joshi M, Yan G, et al. Global epidemiology of end-stage kidney disease and disparities in kidney replacement therapy. Am J Nephrol 2021;52:98–107.
crossref pmid pdf
2. Lok CE, Huber TS, Lee T, et al. KDOQI clinical practice guideline for vascular access: 2019 update. Am J Kidney Dis 2020;75:S1–S164.
crossref pmid
3. MacRae JM, Dipchand C, Oliver M, et al. Arteriovenous access failure, stenosis, and thrombosis. Can J Kidney Health Dis 2016;3:2054358116669126.
crossref pmid pmc pdf
4. Girerd S, Girerd N, Frimat L, et al. Arteriovenous fistula thrombosis is associated with increased all-cause and cardiovascular mortality in haemodialysis patients from the AURORA trial. Clin Kidney J 2019;13:116–122.
crossref pmid pmc pdf
5. Monroy-Cuadros M, Yilmaz S, Salazar-Bañuelos A, Doig C. Risk factors associated with patency loss of hemodialysis vascular access within 6 months. Clin J Am Soc Nephrol 2010;5:1787–1792.
crossref pmid pmc
6. Thomson PC, Mark PB, Robertson M, et al. An Analysis of Vascular Access Thrombosis Events From the Proactive IV irOn Therapy in hemodiALysis Patients Trial. Kidney Int Rep 2022;7:1793–1801.
crossref pmid pmc
7. Smith GE, Gohil R, Chetter IC. Factors affecting the patency of arteriovenous fistulas for dialysis access. J Vasc Surg 2012;55:849–855.
crossref pmid
8. Siddiqui MA, Ashraff S, Carline T. Maturation of arteriovenous fistula: analysis of key factors. Kidney Res Clin Pract 2017;36:318–328.
crossref pmid pmc
9. Lyu B, Banerjee T, Scialla JJ, et al. Vascular calcification markers and hemodialysis vascular access complications. Am J Nephrol 2018;48:330–338.
crossref pmid pdf
10. Georgiadis GS, Georgakarakos EI, Antoniou GA, et al. Correlation of pre-existing radial artery macrocalcifications with late patency of primary radiocephalic fistulas in diabetic hemodialysis patients. J Vasc Surg 2014;60:462–470.
crossref pmid
11. Chen J, Budoff MJ, Reilly MP, et al. Coronary artery calcification and risk of cardiovascular disease and death among patients with chronic kidney disease. JAMA Cardiol 2017;2:635–643.
crossref pmid pmc
12. Zhang A, Wang S, Li H, Yang J, Wu H. Aortic arch calcification and risk of cardiovascular or all-cause and mortality in dialysis patients: a meta-analysis. Sci Rep 2016;6:35375.
crossref pmid pmc pdf
13. Simonet WS, Lacey DL, Dunstan CR, et al. Osteoprotegerin: a novel secreted protein involved in the regulation of bone density. Cell 1997;89:309–319.
crossref pmid
14. Venuraju SM, Yerramasu A, Corder R, Lahiri A. Osteoprotegerin as a predictor of coronary artery disease and cardiovascular mortality and morbidity. J Am Coll Cardiol 2010;55:2049–2061.
crossref pmid
15. Caidahl K, Ueland T, Aukrust P. Osteoprotegerin: a biomarker with many faces. Arterioscler Thromb Vasc Biol 2010;30:1684–1686.
crossref pmid
16. Spartalis M, Kasimatis E, Liakou E, et al. Serum OPG and RANKL levels as risk factors for the development of cardiovascular calcifications in end-stage renal disease patients in hemodialysis. Life (Basel) 2023;13:454.
crossref pmid pmc
17. Abedin M, Omland T, Ueland T, et al. Relation of osteoprotegerin to coronary calcium and aortic plaque (from the Dallas Heart Study). Am J Cardiol 2007;99:513–518.
crossref pmid
18. Kwon A, Choi YS, Choi YW, et al. Serum osteoprotegerin is associated with calcified carotid plaque: a strobe-compliant observational study. Medicine (Baltimore) 2016;95:e3381.
crossref pmid pmc
19. Golledge J, McCann M, Mangan S, Lam A, Karan M. Osteoprotegerin and osteopontin are expressed at high concentrations within symptomatic carotid atherosclerosis. Stroke 2004;35:1636–1641.
crossref pmid
20. Rattazzi M, Faggin E, Galliazzo S, et al. Osteoprotegerin levels are increased in patients with venous thromboembolic disease. J Thromb Haemost 2012;10:1183–1185.
crossref pmid
21. Guldiken B, Guldiken S, Turgut B, et al. Serum osteoprotegerin levels in patients with acute atherothrombotic stroke and lacunar infarct. Thromb Res 2007;120:511–516.
crossref pmid
22. Wohner N, Sebastian S, Muczynski V, et al. Osteoprotegerin modulates platelet adhesion to von Willebrand factor during release from endothelial cells. J Thromb Haemost 2022;20:755–766.
crossref pmid pdf
23. Morena M, Terrier N, Jaussent I, et al. Plasma osteoprotegerin is associated with mortality in hemodialysis patients. J Am Soc Nephrol 2006;17:262–270.
crossref pmid
24. Ozkok A, Caliskan Y, Sakaci T, et al. Osteoprotegerin/RANKL axis and progression of coronary artery calcification in hemodialysis patients. Clin J Am Soc Nephrol 2012;7:965–973.
crossref pmid pmc
25. Kim HR, Kim HK, Oh DJ. Serum osteoprotegerin level is associated with degree of arteriovenous fistula stenosis in patients with hemodialysis. Clin Nephrol 2013;80:322–327.
crossref pmid
26. Morena M, Bosc JY, Jaussent I, et al. The role of mineral metabolism and inflammation on dialysis vascular access failure. J Vasc Access 2006;7:77–82.
crossref pmid pdf
27. Choi SJ, Yoon HE, Kim YS, et al. Pre-existing arterial micro-calcification predicts primary unassisted arteriovenous fistula failure in incident hemodialysis patients. Semin Dial 2015;28:665–669.
crossref pmid
28. Schlieper G, Schurgers L, Brandenburg V, Reutelingsperger C, Floege J. Vascular calcification in chronic kidney disease: an update. Nephrol Dial Transplant 2016;31:31–39.
crossref pmid
29. Chou CY, Kuo HL, Yung YF, Liu YL, Huang CC. C-reactive protein predicts vascular access thrombosis in hemodialysis patients. Blood Purif 2006;24:342–346.
crossref pmid pdf
30. Brahmbhatt A, Remuzzi A, Franzoni M, Misra S. The molecular mechanisms of hemodialysis vascular access failure. Kidney Int 2016;89:303–316.
crossref pmid pmc
31. Collin-Osdoby P, Rothe L, Anderson F, Nelson M, Maloney W, Osdoby P. Receptor activator of NF-kappa B and osteoprotegerin expression by human microvascular endothelial cells, regulation by inflammatory cytokines, and role in human osteoclastogenesis. J Biol Chem 2001;276:20659–20672.
crossref pmid
32. Zhang J, Fu M, Myles D, et al. PDGF induces osteoprotegerin expression in vascular smooth muscle cells by multiple signal pathways. FEBS Lett 2002;521:180–184.
crossref pmid pdf
33. Stark K, Massberg S. Interplay between inflammation and thrombosis in cardiovascular pathology. Nat Rev Cardiol 2021;18:666–682.
crossref pmid pmc pdf
34. Van Campenhout A, Golledge J. Osteoprotegerin, vascular calcification and atherosclerosis. Atherosclerosis 2009;204:321–329.
crossref pmid
35. Panizo S, Cardus A, Encinas M, et al. RANKL increases vascular smooth muscle cell calcification through a RANK-BMP4-dependent pathway. Circ Res 2009;104:1041–1048.
crossref pmid
36. Lieb W, Gona P, Larson MG, et al. Biomarkers of the osteoprotegerin pathway: clinical correlates, subclinical disease, incident cardiovascular disease, and mortality. Arterioscler Thromb Vasc Biol 2010;30:1849–1854.
crossref pmid pmc
37. Kiechl S, Schett G, Schwaiger J, et al. Soluble receptor activator of nuclear factor-kappa B ligand and risk for cardiovascular disease. Circulation 2007;116:385–391.
crossref pmid
38. Lee T, Roy-Chaudhury P. Advances and new frontiers in the pathophysiology of venous neointimal hyperplasia and dialysis access stenosis. Adv Chronic Kidney Dis 2009;16:329–338.
crossref pmid pmc
39. Riella MC, Roy-Chaudhury P. Vascular access in haemodialysis: strengthening the Achilles’ heel. Nat Rev Nephrol 2013;9:348–357.
crossref pmid pdf
40. Banerjee T, Kim SJ, Astor B, Shafi T, Coresh J, Powe NR. Vascular access type, inflammatory markers, and mortality in incident hemodialysis patients: the Choices for Healthy Outcomes in Caring for End-Stage Renal Disease (CHOICE) study. Am J Kidney Dis 2014;64:954–961.
crossref pmid pmc


ABOUT
BROWSE ARTICLES
EDITORIAL POLICY
FOR CONTRIBUTORS
Editorial Office
#301, (Miseung Bldg.) 23, Apgujenog-ro 30-gil, Gangnam-gu, Seoul 06022, Korea
Tel: +82-2-3486-8736    Fax: +82-2-3486-8737    E-mail: registry@ksn.or.kr                

Copyright © 2025 by The Korean Society of Nephrology.

Developed in M2PI

Close layer