Kidney Res Clin Pract > Volume 42(2); 2023 > Article
Kim, Kim, Ro, Chang, Lee, Chung, and Jung: Serum calcification propensity and its association with biochemical parameters and bone mineral density in hemodialysis patients

Abstract

Background

T50 is a novel serum-based marker that assesses the propensity for calcification in serum. A shorter T50 indicates a greater propensity to calcify and has been associated with cardiovascular disease and mortality among patients with chronic kidney disease. The factors associated with T50 and the correlation between T50 and bone mineral density (BMD) are unknown in hemodialysis (HD) patients.

Methods

This cross-sectional study included 184 patients undergoing HD. Individuals were grouped into tertiles of T50 to compare the demographic and disease indicators of the tertiles. Linear regression was used to evaluate the association between T50 and hip and spinal BMD in a multivariate model.

Results

Mineral and inflammatory parameters, including serum phosphate (r = –0.156, p = 0.04), albumin (r = 0.289, p < 0.001), and high-sensitivity C-reactive protein (r = –0.224, p = 0.003) levels, were associated with T50. We found a weak association between T50 and BMD in the total hip area in the unadjusted model (β = 0.030, p = 0.04) but did not find a statistically significant association with the total hip (β = 0.017, p = 0.12), femoral neck (β = –0.001, p = 0.96), or spinal BMD (β = 0.019, p = 0.33) in multivariable-adjusted models.

Conclusion

T50 was moderately associated with mineral and inflammatory parameters but did not conclusively establish an association with BMD in HD patients. Broad-scale future studies should determine whether T50 can provide insights into BMD beyond traditional risk factors in this population.

Introduction

Chronic kidney disease (CKD)-mineral bone disease (MBD) is a common complication of CKD that is associated with morbidity and mortality. Several studies have suggested an interconnection between vascular calcification, impaired bone and mineral metabolism, and increased mortality [13]. Recent studies have found that bone mineral density (BMD) measurement in patients with advanced CKD predicts the risk of fracture, which can be expected to provide nephrologists with skeletal fragility and targeted fracture prevention strategies [46].
T50 has been proposed as a potential novel serum-based marker for assessing calcification propensity [7]. With the initiation of calcium and phosphate precipitation in the serum, primary calciprotein particles (CPP) are formed that are rich in calcium and phosphate and contain small amounts of protein, including albumin and fetuin-A [7]. Over time, these primary CPPs are converted into larger secondary CPPs with different calcium, phosphate, and protein content. CPP maturation time (T50) is a measurement of the in vitro conversion time from primary CPP to secondary CPP in the serum [7]. The balance of calcification enhancing and inhibitory factors in each serum sample is a critical factor in determining transformation time [8]. The shorter the T50, the greater the tendency for calcification. A shorter T50 has been reported to be associated with increased risk of cardiovascular disease (CVD) and all-cause mortality in CKD patients [8,9].
Although vascular calcification and bone health are intercorrelated and are known risk factors for predicting cardiovascular events (CVE) in dialysis patients, the association between T50 and BMD in dialysis patients with a high CVE risk is not well understood. As renal function decreases in CKD patients, mineral parameters are perturbed and related to bone and vascular health, which is an important pathophysiology of CKD-MBD [10]. T50 also tends to accompany mineral parameters in serum in the CKD environment, indicating the tendency for vascular calcification [11].
In the past, routine BMD evaluation was not recommended in CKD patients [12], but fractures can be predicted by measuring BMD in non-dialysis-dependent CKD (CKD-ND) patients [13] and end-stage kidney disease (ESKD) patients on hemodialysis (HD) [6]. In addition, as osteoporosis treatments for patients with impaired renal function have been developed, BMD measurement is being actively performed. However, in the pathophysiology of CKD-MBD, it is difficult to reflect bone quality because the bone density of the trabecular bone may be overestimated [12,14]. A recent study reported that CKD showed a correlation with low BMD measured at the hip, but not with BMD measured at the spine [13]. Until now, osteopenia and osteoporosis have been diagnosed using the same cut-off values as in the general population [14], but follow-up studies on bone health are needed in ESKD patients.
Therefore, in this study, we aimed to provide the first analysis of the clinical and biochemical parameters of T50 in patients undergoing HD. We also examined the relationships between T50, BMD from the various sites, and mineral and inflammatory parameters, to evaluate the potential of T50 as a predictor of the CKD-MBD association in HD patients.

Methods

Study design and setting

This study was based on maintenance HD patients from a single center in Korea. We investigated the associations between T50, BMD, and biochemical parameters using a cross-sectional design.

Study population

A total of 184 patients who visited our HD unit at the Gachon University Gil Medical Center between March 2020 and February 2021 were analyzed. Patients were enrolled in the study if they 1) had been on HD for at least 3 months, 2) agreed to participate in the study with written informed consent, and 3) were free of any complications that could affect serum T50 and other biochemical parameters such as an indwelling catheter, any underlying malignancy, active liver disease, current infection, or previous parathyroidectomy.
This study adheres to the Declaration of Helsinki and was approved by the Institutional Review Board at the Gachon University Gil Medical Center (No. GBIRB2020-342). Written informed consent was obtained from all participants.

Clinical and laboratory parameters

All demographic and clinical data, comorbidities, laboratory values, and medications were collected at the time of enrollment from participants’ medical records by a well-trained study coordinator. The following baseline demographic and clinical characteristics were collected: age, sex, body mass index, smoking, and HD duration. Data on comorbidities, including hypertension (HTN), diabetes mellitus (DM), CVD such as angina pectoris, myocardial infarction, heart failure (HF), transient ischemic attack (TIA), stroke, and peripheral arterial disease, were also collected. Angina pectoris and myocardial infarction were defined as the presence of coronary artery disease as documented by angiography, an acute coronary syndrome, angina requiring percutaneous coronary intervention, or coronary artery bypass grafting surgery. Stroke and TIA were defined as cases where magnetic resonance imaging was performed on patients with suspected symptoms that were diagnosed by a neurologist. Systolic HF was defined as left ventricular ejection fraction of <40%, and diastolic HF was defined as E/é of >15. All blood samples were obtained prior to a mid-week HD session after overnight fasting and microcentrifugation for measurements. Serum was separated from blood samples within 1 hour of collection and stored at −70°C until analysis. Laboratory data included the single-pool Kt/V (spKtV), hemoglobin, albumin, protein, calcium, phosphorus, 25-hydroxyvitamin D, 1,25-dihydroxyvitamin D, parathyroid hormone, alkaline phosphatase (ALP), total cholesterol, triglyceride (TG), and high-sensitivity C-reactive protein (hsCRP). Medication data included the use of renin-angiotensin-aldosterone system blockers, calcium channel blockers, β-blockers, phosphate binders, statin, vitamin D analogues, and cinacalcet.

Determination of the serum calcification propensity (T50)

T50 was determined using a nephelometer (Nephelostar; BMG Labtech, Offenburg, Germany), which measures the time-point transformation from primary to secondary CPP, as described in a previous study [7]. To this end, patient serum (80 μL) was first exposed to NaCl solution (20 μL), followed by high and supersaturated concentrations of calcium (50 μL) and phosphate (50 μL) solutions. The experiment was performed in triplicate in a 96-well plate. The Nephelostar was operated and controlled using Galaxy software. Nonlinear regression curves were calculated for the determination of T50. The analytical coefficients of variation of standards precipitated at 120, 240, and 360 minutes were 9.8%, 8.7%, and 8.4%, respectively.

Measurement of bone mineral density and abdominal aortic calcification score

The BMD was estimated using a dual-energy X-ray absorptiometry system (Hologic, Marlborough, MA, USA). The BMD of the total hip, femoral neck, and lumbar spine (L1–L4) were measured at baseline, and the results were expressed as density (g/cm2) and T-scores (standard deviation [SD] from the average BMD value in a healthy young population).
Plain X-ray images of the lateral lumbar spine from all subjects were studied to calculate semiquantitative abdominal aortic calcification (AAC) scores, as described by Kauppila et al. [15]. The AAC score was graded on a 0 to 3 scale at each segment (L1–L4) of the lumbar vertebrae based on the severity of calcification as follows: 0, no aortic calcific deposits; 1, small scattered calcific deposits less than 1/3 of the longitudinal wall of the aorta; 2, 1/3 or more but less than 2/3; and 3, 2/3 or more. The anterior and posterior wall scores were separately graded and summed, resulting in a total score of 0 to 24. All X-ray images were analyzed by two independent observers having no knowledge of the clinical history of each subject, and consensus was reached on the interpretation of all radiographs.

Statistical analyses

Continuous variables were tested for normality using the Shapiro-Wilk test before further statistical analysis. Variables without a normal distribution were either transformed into a logarithmic scale and then subjected to parametric tests or analyzed using a non-parametric test. Values with a normal distribution are expressed as mean ± SD, while those without a normal distribution are presented as median and interquartile range. Comparisons between the groups were performed using the chi-square test, Student t test, or analysis of variance with Tukey multiple comparison test as appropriate. Correlation between two continuous variables was analyzed using Pearson correlation test. Variables that do not show a normal distribution were analyzed by converting them to logarithmic values. Independent variables associated with T50 were identified using multiple stepwise linear regression analysis. All statistical analyses were conducted using R software, version 3.5.3 with packages (The Comprehensive R Archive Network; http://cran.r-project.org). For all statistical analyses, statistical significance was set at p < 0.05.

Results

Characteristics of the study population

Participant demographics and clinical characteristics stratified by tertiles of T50 concentration are shown in Table 1. The mean T50 was 296 ± 85 minutes. Ninety-six participants (52.2%) were men, mean age was 61 ± 12 years, mean dialysis duration was approximately 107 months, and there was a high prevalence of comorbidities such as DM (47.3%), HTN (58.7%), and previous CVD (40.8%). Descending tertiles of serum T50 were associated with lower serum albumin (3.9 ± 0.4, 4.0 ± 0.3, 4.1 ± 0.3; p < 0.001) and TG (85.4 ± 68.8, 106.2 ± 74.6, 113.6 ± 72.8; p = 0.03) levels as well as higher serum hsCRP (0.2 [0.1–0.5], 0.2 [0.0–0.3], 0.1 [0.0–0.3]; p = 0.03), phosphate (5.6 ± 1.8, 5.3 ± 1.3, 5.0 ± 1.0; p = 0.02), and ALP (125.4 ± 95.7, 98.3 ± 41.2, 102.0 ± 37.5; p = 0.045) concentrations (Table 1).

Correlation between serum T50 and related parameters

T50 showed a significant correlation with the total hip T-score (r = 0.158, p = 0.038) (Table 2). However, there was no significant correlation between the T50 and AAC scores on plain radiographs (r = 0.064, p = 0.401) (Table 2). With respect to medication use, there was no significant correlation between the descending tertiles of serum T50 and medications for CKD-MBD, including phosphate binders, vitamin D analogues, and cinacalcet. Serum T50 was positively correlated with serum albumin concentration (r = 0.289, p < 0.001) (Fig. 1). In addition, it was inversely correlated with serum hsCRP (r = –0.224, p = 0.003) and phosphate (r = –0.156, p = 0.040) concentrations (Fig. 1).

Association between bone mineral density and related parameters

We compared the mean T-score of BMD according to the sites at which it was assessed (Fig. 2). The mean T-score for BMD measured at the femur neck was relatively lower than that for the BMD assessed at the total hip or lumbar spine (–1.9 ± 1.2, –1.6 ± 1.3, and –1.1 ± 1.8, respectively). There was a significant difference between the three groups (p < 0.001). In the multiple comparison test by Tukey method, there were also significant differences between femur neck and L spine (p < 0.001) and between total hip and L spine (p = 0.001), but the difference between femur neck and total hip was not significant (p = 0.26).
BMD showed an inverse correlation with age and the spKtV (lumbar: r = –0.310, p < 0.001; femoral neck: r = –0.403, p < 0.001; total hip: r = –0.440, p < 0.001) and a positive correlation with albumin (lumbar: r = 0.094, p = 0.218; femoral neck: r = 0.201, p = 0.008; total hip: r = 0.219, p = 0.004). Only the L spine BMD showed an inverse correlation with ALP (r = –0.225, p = 0.003). Femoral neck (r = –0.267, p < 0.001) and total hip BMD (r = –0.176, p = 0.021) also showed an inverse relationship with AAC scores (Table 2).

Evaluating the usefulness of T50 as a predictor of bone mineral density

We used linear regression to evaluate the cross-sectional association between T50 and femoral neck, hip, and spinal BMD. We found no statistically significant associations between T50 and femoral neck or lumbar spine BMD in either the unadjusted models (femoral neck: β = 0.005, p = 0.708; lumbar spine: β = 0.032, p = 0.101) or in the adjusted models (femoral neck: β = –0.001, p = 0.956; lumbar spine: β = 0.019, p = 0.331) (Table 3) for variables including age, sex, smoking, HD duration, spKtV, inflammatory and mineral parameters (albumin and ALP), and medications (phosphate binders, vitamin D analogues, and cinacalcet).
We found a weak association between T50 and BMD in the total hip area in the unadjusted model (β = 0.030, p = 0.043) but did not find a statistically significant association in the multivariate-adjusted models (β = 0.017, p = 0.188) (Table 3).

Discussion

In this cross-sectional study of HD patients, T50 was associated with mineral and inflammatory parameters but not with AAC score or BMD.
CKD-MBD is a common complication of CKD and is associated with morbidity and mortality. The interconnection between vascular calcification and bone health has been reported as a significant inverse relationship between vascular calcification and bone fragility (low BMD) [1618]. Impaired bone metabolism, particularly low bone turnover, may promote vascular calcification [1]. Several factors have been suggested as possible links between bone and soft tissue calcification; however, the key elements of the cross-talk mechanism are yet to be elucidated [1].
Reduced serum T50 is associated with a lack of inhibitors and abundant promoters of vascular calcification [19]. Therefore, it is assumed that the action of these factors and the effect of T50 on the overall tendency of serum calcification will be in the same direction.
The main determinants of T50 in this study were inflammatory (serum albumin and hsCRP), mineral (serum phosphate), and the bone turnover marker (ALP). Only the values measured in the BMD total hip joint area showed a weak correlation in the unadjusted model, but there was no association with BMD measured in all regions in the multivariable-adjusted models. This finding is consistent with epidemiological data in advanced CKD-ND cohorts, where reduced T50 has been correlated with increased phosphate, decreased albumin, and CPP-associated fetuin-A concentration [8]. These results are also consistent with those of a dialysis cohort in which low BMD was related to mineral deposition in arterial walls and soft tissues [20,21].
Recently, an association between T50 and BMD was reported in 150 non-CKD participants from an elderly male cohort [22]. Subjects with a shorter T50 were likely to be older, and there was a nonlinear trend with a higher prevalence of diabetes, but T50 did not show any association with total hip or spine BMD. Moreover, there was no correlation with mineral parameters such as calcium and phosphate. The lack of association between T50 and BMD were consistent with our results, but the association between T50 and serum albumin from this and previous studies [8,9] could not be assessed.
A lower T50 was significantly associated with the severity and progression of coronary artery calcification in patients with CKD-ND; however, T50 was not associated with the incidence of coronary artery calcification [11]. In the present study, T50 was not associated with vascular calcification. The difference between these results is that although the range of our measurements using simple plain radiographs is limited, their correlation could be shown in their measurement methods using electron beam computed tomography. In addition, the fact that T50 is not related to the incidence of vascular calcification but correlates with its progression is thought to reflect a dynamic change in the progression of vascular calcification once it has occurred. This finding suggests that a significantly longer observation period is required to observe an association between T50 and vascular calcification.
The propensity for serum calcification reflects the degree of activity of numerous humoral and cellular factors that affect the formation and growth of calcified crystals in blood vessels [7]. Calcification mechanisms require functional and direct measurements targeting calcium phosphate precipitation more comprehensively rather than focusing on the individual molecular components of the calcification process, as their developmental processes are multifactorial [8]. In this regard, it is considered that the contribution of T50 could be large, and in the case of CKD patients, the results of a study comparing reduced T50 and cardiovascular complications and death have been reported [8,9]. In patients with ESKD, an association between lower T50, CVE, and mortality was reported in the EVOLVE (Effect of Cinacalcet on Cardiovascular Disease in Patients Undergoing Dialysis) study cohort [23]. However, in ESKD patients, dialysis itself and medications to maintain mineral parameters in the target range associated with CKD-MBD may affect T50. Therefore, further studies are needed to evaluate its value as a predictor of clinical prognosis in patients with ESKD.
The T-score of BMD showed slightly different results depending on the measurement location, with the lowest values at the femur neck, the highest values at the lumbar spine, and a moderate level at the total hip. When studying the relationship between BMD and vascular calcification, there is currently no consensus as to which specific bone location should be the representative for BMD measurement [24]. This uncertainty is due to heterogeneity between the population and bone sites selected for BMD measurements in previous studies [16,25]. Depending on the severity of atherosclerosis, calcium deposition in the intima can affect the measurement of the spinal BMD. Our findings are consistent with those of previous studies that reported that peripheral BMD was lower than central BMD [26,27]. Lumbar BMD may be relatively overestimated in patients with ESKD with severe AAC. Therefore, peripheral BMD measurements may be more appropriate than central BMD measurements in these patients.
Osteoporosis causes both cortical and trabecular bone loss, whereas CKD-MBD results in primarily cortical bone loss [10,28]. In a recent study on the relationship between vascular calcification and BMD in CKD patients [29], cortical or trabecular bone loss was observed in CKD patients, but not all patients showed a simultaneous loss. In particular, the cortical bone loss did not show an association with vascular calcification, unlike trabecular bone loss [29]. Vascular calcifications are strongly associated with CKD-MBD [10,30]; however, the correlation between cortical bone and vascular calcification is not yet clear. In this respect, in this study, it is insufficient to explain the weak association between T50 and BMD in the femur and the lack of association in the lumbar region. To evaluate the relationship between the pathophysiology of vascular calcification and bone density in HD patients with both MBD and osteoporosis components, consensus through follow-up studies on quantitative BMD measurement methods and sites according to pathophysiology is required.
This study has some limitations. First, a causal relationship could not be confirmed by conducting a cross-sectional study. However, we performed correlation analyses with various mineral parameters; in particular, we evaluated BMD in a relatively large number of HD patients, described its distribution, and analyzed its association with T50. Second, we were unable to control the dialysis protocol and medications that affected T50 measurements. However, considering that the characteristics of dialysis patients are always affected by medication as well as dialysis itself, we need to carefully consider the evaluation value of T50 in future.
In summary, for the first time in Korea, we have provided a stable measurement method for T50 and applied it to clinical research. T50 was correlated with mineral and inflammatory parameters but not with AAC. BMD was correlated with T50 in the case of total hip but was not correlated with BMD measured at other sites (femoral neck and lumbar spine). To evaluate the value of T50 as a predictor of CKD-MBD diagnosis and treatment in ESKD patients, a study on its association with hard outcomes, including fracture, CVE, and mortality, should be prioritized. In addition, to confirm the association between T50 and dynamic changes such as vascular calcification or BMD changes, a large-scale study that includes a larger number of patients and a longer observation period is needed.

Notes

Conflicts of interest

All authors have no conflicts of interest to declare.

Funding

This work was supported by Gachon University Gil Medical Center (grant No. FRD2020-12 to JYJ) and by a National Research Foundation of Korea grant funded by the Korean government (No. 2019R1F1A1057630 to JYJ).

Data sharing statement

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

Authors’ contributions

Conceptualization: JYJ

Data curation, Formal analysis: HK, JYJ

Investigation: AJK, HR, JHC, HHL, WC

Methodology, Funding acquisition, Supervision: JYJ

Writing–original draft: HK, JYJ

Writing–review & editing: all authors

All authors read and approved the final manuscript.

Figure 1.

Association of serum T50 with mineral and inflammatory markers in hemodialysis patients.

Bivariate correlation analysis of serum T50 with (A) albumin, (B) phosphate, (C) calcium, (D) hsCRP, (E) AAC, and (F) BMD total hip. Serum T50 was positively correlated with serum albumin concentration (r = 0.289, p < 0.001) and inversely correlated with serum hsCRP (r = –0.224, p = 0.003) and phosphate (r = –0.156) concentrations.
AAC, abdominal aortic calcification; BMD, bone mineral density; hsCRP, high-sensitivity C-reactive protein.
j-krcp-22-059f1.jpg
Figure 2.

T-scores at the sites of BMD measurement.

The mean T-score for BMD measured at the femur neck was relatively lower than that for the BMD assessed at the total hip or lumbar spine (–1.9 ± 1.2, –1.6 ± 1.3, and –1.1 ± 1.8, respectively; p < 0.001). In the multiple comparison test by Tukey method, there were also significant differences between femur neck and lumbar spine (p < 0.001) and between total hip and lumbar spine (p = 0.001), but the difference between femur neck and total hip was not significant (p = 0.27). The thick line within the box represents the median, the upper and lower boundaries of the box represent the interquartile range, the solid square inside the box represents the mean, the upper and lower whiskers represent the maximum and minimum values, respectively, and the gray dots in each group represent individual data.
BMD, bone mineral density.
j-krcp-22-059f2.jpg
Table 1.
Baseline characteristics of the study group according to tertiles of serum T50
Characteristic Total T50
p-value
T1 T2 T3
No. of patients 184 61 62 61
T50 (min) 296.3 ± 85.3 204.1 ± 39.0 290.9 ± 25.3 394.1 ± 40.3
Age (yr) 61.1 ± 12.3 61.8 ± 12.5 58.7 ± 13.1 62.8 ± 10.9 0.65
Male sex 96 (52.2) 33 (54.1) 32 (51.6) 31 (50.8) 0.93
HD duration (mo) 107 (64–139) 120 (71–147) 92 (69–139) 104 (52–127) 0.10
BMI (kg/cm2) 23.5 ± 3.8 23.1 ± 3.9 23.8 ± 3.8 23.5 ± 3.8 0.56
Smoking 28 (15.2) 10 (16.4) 9 (14.5) 9 (14.8) 0.95
Diabetes mellitus 87 (47.3) 25 (41.0) 29 (46.8) 33 (54.1) 0.35
Hypertension 108 (58.7) 36 (59.0) 37 (59.7) 35 (57.4) 0.97
CVD 75 (40.8) 27 (44.3) 21 (33.9) 27 (44.3) 0.40
spKtV 1.6 (1.4–1.8) 1.6 (1.4–1.9) 1.6 (1.4–1.8) 1.6 (1.4–1.8) 0.96
RAS blockade 79 (42.9) 26 (42.6) 28 (45.2) 25 (41.0) 0.90
CCB 81 (44.0) 29 (47.5) 28 (45.2) 24 (39.3) 0.64
β-blocker 80 (43.5) 29 (47.5) 28 (45.2) 23 (37.7) 0.52
Phosphate binder 131 (71.2) 44 (72.1) 42 (67.7) 45 (73.8) 0.75
Statin 71 (38.6) 24 (39.3) 22 (35.5) 25 (41.0) 0.81
Vitamin D analogues 123 (66.8) 41 (67.2) 37 (59.7) 45 (73.8) 0.25
Cinacalcet 17 (9.2) 8 (13.1) 5 (8.1) 4 (6.6) 0.42
Hemoglobin (g/dL) 10.8 ± 1.3 10.7 ± 1.3 10.7 ± 1.2 11.1 ± 1.2 0.07
Albumin (g/dL) 4.0 ± 0.3 3.9 ± 0.4 4.0 ± 0.3 4.1 ± 0.3 <0.001
Cholesterol (mg/dL) 137.0 ± 34.5 128.7 ± 28.6 141.9 ± 37.6 140.2 ± 35.6 0.07
Triglyceride (mg/dL) 101.9 ± 72.7 85.4 ± 68.8 106.2 ± 74.6 113.6 ± 72.8 0.03
hsCRP (mg/dL) 0.1 (0.0–0.4) 0.2 (0.1–0.5) 0.2 (0.0–0.3) 0.1 (0.0–0.3) 0.03
Calcium (mg/dL) 8.2 ± 0.9 8.3 ± 0.9 8.2 ± 1.0 8.2 ± 0.9 0.70
Phosphate (mg/dL) 5.3 ± 1.4 5.6 ± 1.8 5.3 ± 1.3 5.0 ± 1.0 0.02
VD25 (ng/mL) 17.2 ± 9.8 17.4 ± 10.4 17.9 ± 10.1 16.4 ± 8.9 0.61
VD1,25 (pg/mL) 5.9 ± 7.1 5.7 ± 7.4 5.7 ± 7.0 6.4 ± 7.1 0.61
PTH (pg/mL) 564.2 ± 380.9 649.1 ± 501.2 504.2 ± 293.5 541.7 ± 306.9 0.12
ALP (U/L) 108.5 ± 64.6 125.4 ± 95.7 98.3 ± 41.2 102.0 ± 37.5 0.045
BMD (g/cm2)
 Lumbar spine 1.034 ± 0.214 0.998 ± 0.218 1.045 ± 0.205 1.059 ± 0.217 0.13
 Femoral neck 0.713 ± 0.145 0.693 ± 0.159 0.729 ± 0.147 0.715 ± 0.129 0.42
 Total hip 0.749 ± 0.164 0.717 ± 0.165 0.753 ± 0.185 0.775 ± 0.135 0.06
AAC 4.0 (0.0–12.0) 4.0 (0.0–10.5) 3.5 (0.0–8.0) 5.0 (0.0–11.0) 0.54

Data are expressed as number only, mean ± standard deviation, number (%), or median (interquartile range).

AAC, abdominal aortic calcification; ALP, alkaline phosphatase; BMD, bone mineral density; BMI, body mass index; CCB, calcium channel blocker; CVD, cardiovascular disease; HD, hemodialysis; hsCRP, highly selective C-reactive protein; PTH, parathyroid hormone; RAS, renin-angiotensin-aldosterone; spKtV, single-pool Kt/V; T1, 1st tertile; T2, 2nd tertile; T3, 3rd tertile; VD1,25, 1,25-dihydroxyvitamin D.

Table 2.
Cross-sectional correlation analyses between serum T50 and BMD and other variables
Variable Age spKtV Albumin hsCRPa Calcium Phosphate PTH ALP BMD_LS BMD_FN BMD_TH AACa T50
Age 1.000
spKtV 0.226* 1.000
Albumin –0.245* –0.015 1.000
hsCRPa 0.025 –0.120 –0.205* 1.000
Calcium 0.020 0.037 0.242* –0.107 1.000
Phosphate –0.350* –0.213* 0.191* 0.097 0.063 1.000
PTH –0.193* –0.215* 0.113 0.010 0.193* 0.342* 1.000
ALP 0.089 –0.029 0.058 0.011 0.085 –0.032 0.339* 1.000
BMD_LS –0.180* –0.310* 0.094 0.056 –0.026 0.105 –0.069 –0.225* 1.000
BMD_FN –0.513* –0.403* 0.201* –0.003 0.028 0.132 0.011 –0.019 0.599* 1.000
BMD_TH –0.353* –0.440* 0.219* 0.053 0.044 0.061 –0.005 –0.103 0.599* 0.800* 1.000
AACa 0.443* –0.009 –0.126 0.089 0.063 –0.051 –0.072 0.126 0.024 –0.267* –0.176* 1.000
T50 0.042 –0.006 0.289* –0.224* –0.005 –0.156* –0.081 –0.156* 0.123 0.034 0.158* 0.064 1.000

AAC, abdominal aortic calcification; ALP, alkaline phosphatase; BMD, bone mineral density; FN, femoral neck; hsCRP, highly selective C-reactive protein; LS, lumbar spine; PTH, parathyroid hormone; spKtV, single-pool Kt/V; TH, total hip.

aData for hsCRP and AAC were log-transformed.

*p < 0.05.

Table 3.
Linear regression of the association between T50 (every 100 minutes increase) and BMD (g/cm2)
BMD β (95% confidence interval) p-value
Spine L1–L4
 Crude 0.03 (–0.01 to 0.07) 0.10
 Model 1 0.03 (–0.002 to 0.07) 0.07
 Model 2 0.02 (–0.02 to 0.06) 0.32
 Model 3 0.02 (–0.02 to 0.06) 0.33
Femur neck
 Crude 0.01 (–0.02 to 0.03) 0.71
 Model 1 0.01 (–0.01 to 0.03) 0.42
 Model 2 –0.001 (–0.02 to 0.02) 0.94
 Model 3 –0.001 (–0.02 to 0.02) 0.96
Total hip
 Crude 0.03 (0.001 to 0.06) 0.04
 Model 1 0.03 (0.01 to 0.06) 0.01
 Model 2 0.02 (–0.01 to 0.04) 0.19
 Model 3 0.02 (–0.01 to 0.04) 0.19

Model 1: adjusted for age, sex, and smoking. Model 2: model 1 + adjustment for hemodialysis duration (mo), single-pool Kt/V, albumin, and alkaline phosphatase. Model 3: model 2 + adjustment for phosphate binders, vitamin D receptor activators, and cinacalcet.

BMD, bone mineral density.

References

1. Cannata-Andia JB, Roman-Garcia P, Hruska K. The connections between vascular calcification and bone health. Nephrol Dial Transplant 2011;26:3429–3436.
crossref pmid pmc
2. Aleksova J, Kurniawan S, Vucak-Dzumhur M, et al. Aortic vascular calcification is inversely associated with the trabecular bone score in patients receiving dialysis. Bone 2018;113:118–123.
crossref pmid
3. Kim H, Lee J, Lee KB, et al. Low bone mineral density is associated with coronary arterial calcification progression and incident cardiovascular events in patients with chronic kidney disease. Clin Kidney J 2021;15:119–127.
crossref pmid pmc pdf
4. Naylor KL, Garg AX, Zou G, et al. Comparison of fracture risk prediction among individuals with reduced and normal kidney function. Clin J Am Soc Nephrol 2015;10:646–653.
crossref pmid pmc
5. Yenchek RH, Ix JH, Shlipak MG, et al. Bone mineral density and fracture risk in older individuals with CKD. Clin J Am Soc Nephrol 2012;7:1130–1136.
crossref pmid pmc
6. Iimori S, Mori Y, Akita W, et al. Diagnostic usefulness of bone mineral density and biochemical markers of bone turnover in predicting fracture in CKD stage 5D patients: a single-center cohort study. Nephrol Dial Transplant 2012;27:345–351.
crossref pmid
7. Pasch A, Farese S, Gräber S, et al. Nanoparticle-based test measures overall propensity for calcification in serum. J Am Soc Nephrol 2012;23:1744–1752.
crossref pmid pmc
8. Smith ER, Ford ML, Tomlinson LA, et al. Serum calcification propensity predicts all-cause mortality in predialysis CKD. J Am Soc Nephrol 2014;25:339–348.
crossref pmid
9. Dahle DO, Åsberg A, Hartmann A, et al. Serum calcification propensity is a strong and independent determinant of cardiac and all-cause mortality in kidney transplant recipients. Am J Transplant 2016;16:204–212.
crossref pmid pdf
10. Moe S, Drüeke T, Cunningham J, et al. Definition, evaluation, and classification of renal osteodystrophy: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 2006;69:1945–1953.
crossref pmid
11. Bundy JD, Cai X, Scialla JJ, et al. Serum calcification propensity and coronary artery calcification among patients with CKD: the CRIC (Chronic Renal Insufficiency Cohort) study. Am J Kidney Dis 2019;73:806–814.
crossref pmid pmc
12. Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group. KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD). Kidney Int Suppl 2009;113:S1–S130.
13. Bezerra de Carvalho KS, Vasco RF, Custodio MR, Jorgetti V, Moysés RM, Elias RM. Chronic kidney disease is associated with low BMD at the hip but not at the spine. Osteoporos Int 2019;30:1015–1023.
crossref pmid pdf
14. Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Update Work Group. KDIGO 2017 clinical practice guideline update for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD). Kidney Int Suppl (2011) 2017 7:1–59.
crossref pmid pmc
15. Kauppila LI, Polak JF, Cupples LA, Hannan MT, Kiel DP, Wilson PW. New indices to classify location, severity and progression of calcific lesions in the abdominal aorta: a 25-year follow-up study. Atherosclerosis 1997;132:245–250.
crossref pmid
16. Frye MA, Melton LJ 3rd, Bryant SC, et al. Osteoporosis and calcification of the aorta. Bone Miner 1992;19:185–194.
crossref pmid
17. Naves M, Rodríguez-García M, Díaz-López JB, Gómez-Alonso C, Cannata-Andía JB. Progression of vascular calcifications is associated with greater bone loss and increased bone fractures. Osteoporos Int 2008;19:1161–1166.
crossref pmid pdf
18. Szulc P, Samelson EJ, Sornay-Rendu E, Chapurlat R, Kiel DP. Severity of aortic calcification is positively associated with vertebral fracture in older men: a densitometry study in the STRAMBO cohort. Osteoporos Int 2013;24:1177–1184.
crossref pmid pdf
19. Shanahan CM, Crouthamel MH, Kapustin A, Giachelli CM. Arterial calcification in chronic kidney disease: key roles for calcium and phosphate. Circ Res 2011;109:697–711.
crossref pmid pmc
20. London GM, Marchais SJ, Guérin AP, Boutouyrie P, Métivier F, de Vernejoul MC. Association of bone activity, calcium load, aortic stiffness, and calcifications in ESRD. J Am Soc Nephrol 2008;19:1827–1835.
crossref pmid pmc
21. Toussaint ND, Lau KK, Strauss BJ, Polkinghorne KR, Kerr PG. Relationship between vascular calcification, arterial stiffness and bone mineral density in a cross-sectional study of prevalent Australian haemodialysis patients. Nephrology (Carlton) 2009;14:105–112.
crossref pmid
22. Bullen AL, Anderson CA, Hooker ER, et al. Correlates of T50 and relationships with bone mineral density in community-living older men: the osteoporotic fractures in men (MrOS) study. Osteoporos Int 2019;30:1529–1531.
crossref pmid pmc pdf
23. Pasch A, Block GA, Bachtler M, et al. Blood calcification propensity, cardiovascular events, and survival in patients receiving hemodialysis in the EVOLVE trial. Clin J Am Soc Nephrol 2017;12:315–322.
crossref pmid
24. Iseri K, Dai L, Chen Z, et al. Bone mineral density and mortality in end-stage renal disease patients. Clin Kidney J 2020;13:307–321.
crossref pmid pmc pdf
25. Banks LM, Lees B, MacSweeney JE, Stevenson JC. Effect of degenerative spinal and aortic calcification on bone density measurements in post-menopausal women: links between osteoporosis and cardiovascular disease? Eur J Clin Invest 1994;24:813–817.
crossref pmid
26. Chen Z, Qureshi AR, Brismar TB, et al. Differences in association of lower bone mineral density with higher coronary calcification in female and male end-stage renal disease patients. BMC Nephrol 2019;20:59.
crossref pmid pmc pdf
27. Lee SM, Lee HW, Son YK, Kim SE, An WS. Abdominal aortic calcification score among several vascular calcification scores of plain radiograph is the most reliable predictor of severe coronary artery calcification in dialysis patients. Ren Fail 2017;39:729–735.
crossref pmid pmc pdf
28. Kim CS, Bae EH, Ma SK, et al. Chronic kidney disease-mineral bone disorder in Korean patients: a report from the KoreaN Cohort Study for Outcomes in Patients With Chronic Kidney Disease (KNOW-CKD). J Korean Med Sci 2017;32:240–248.
crossref pmid pdf
29. Costa LR, Carvalho AB, Bittencourt AL, Rochitte CE, Canziani ME. Cortical unlike trabecular bone loss is not associated with vascular calcification progression in CKD patients. BMC Nephrol 2020;21:121.
crossref pmid pmc pdf
30. Ott SM. Therapy for patients with CKD and low bone mineral density. Nat Rev Nephrol 2013;9:681–692.
crossref pmid pdf


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