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05 June 2024: Clinical Research  

Serum Lipoprotein(a) Levels as a Predictor of Aortic Stiffness in Patients on Long-Term Peritoneal Dialysis

Po-Yu Huang ORCID logo12BCDEF, Bang-Gee Hsu345ABCDEFG, Yu-Li Lin345ABCG, Chi-Chong Tang34B, Hung-Hsiang Liou6AD, Jen-Pi Tsai135ABCDFG*

DOI: 10.12659/MSM.944348

Med Sci Monit 2024; 30:e944348

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Abstract

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BACKGROUND: Lipoprotein (a) [Lp(a)] is associated with atherosclerosis and cardiovascular mortality in patients with kidney failure. Aortic stiffness (AS), measured primarily by carotid–femoral pulse wave velocity (cfPWV), reflects vascular aging and precedes end-organ failure. This study aimed to evaluate the association between serum Lp(a) levels and cfPWV in patients undergoing peritoneal dialysis (PD).

MATERIAL AND METHODS: In this cross-sectional study, which included 148 patients with long-term PD for end-stage kidney failure, cfPWV was measured using a cuff-based method. AS was defined as a cfPWV exceeding 10 m/s, and an enzyme-linked immunosorbent assay was used to determine serum Lp(a) levels. Univariate and multivariate regression analyses were performed to identify the clinical correlates of AS.

RESULTS: There were 32 (21.6%) patients diagnosed with AS. Based on the multivariate logistic regression analysis, the odds ratio for AS was 1.007 (95% confidence interval, 1.003-1.011; P=0.001) for every 1 mg/L increase in Lp(a) levels. Multivariate linear regression analysis showed that Lp(a) (P<0.001), age (P=0.003), waist circumference (P=0.008), systolic blood pressure (P=0.010), and diabetes mellitus (P<0.001) were positively associated with cfPWV. The area under the receiver operating characteristic curve for Lp(a) in differentiating AS from non-AS was 0.770 (95% confidence interval, 0.694-0.835; P<0.0001).

CONCLUSIONS: Serum Lp(a) level was independently associated with cfPWV and AS in patients with PD.

Keywords: Peritoneal Dialysis, Vascular Stiffness, Lipoprotein(a)

Introduction

Cardiovascular (CV) disease is the primary cause of mortality among patients with kidney failure, including those undergoing maintenance peritoneal dialysis (PD) [1,2]. According to a population-based study in Taiwan, myocardial infarction, cerebrovascular accidents, cardiac dysrhythmias, and heart failure were common reasons for hospital admission in patients undergoing maintenance dialysis treatment, and in-hospital mortality rates were around 10% [3]. PD-specific risk factors for CV complications include dextrose-rich dialysis solution preparations, diminished residual kidney function, ultrafiltration failure with the resultant volume overload, chronic inflammation, protein-energy wasting, vascular calcification, and vitamin D deficiency [4,5]. A recent systematic review and meta-analysis of observational studies focusing on patients undergoing PD revealed that older age, presence of diabetes mellitus (DM), history of comorbid CV conditions, anemia, and higher levels of serum alkaline phosphatase, but not serum albumin, were significantly associated with the increased likelihood of CV death [6].

Aortic stiffness (AS), which results from chronic injury to vessel walls under the influence of aging, high blood pressure, calcium deposition, uremia, inflammation, and hyperglycemia, is closely associated with the degree of atherosclerosis and end-organ dysfunction [7,8]. Carotid–femoral pulse wave velocity (cfPWV) is the criterion standard tonometry-based approach to determining AS severity, and it is calculated from the arterial pressure waveforms and propagation time [9,10]. Studies have proved that higher cfPWV is a marker of increased CV disease-related morbidity and death [11]. Notably, AS was reported to independently predict adverse CV outcomes in patients with coronary heart disease and those with chronic kidney disease [12,13].

Lipoprotein (a) [Lp(a)], produced by hepatocytes, comprises a lipid core enriched in cholesterol esters and triglycerides in addition to apolipoprotein B100 linked to apolipoprotein(a) via a single disulfide bond [14]. Lp(a) is closely associated with vasculopathy: as a molecule structurally similar to plasminogen, Lp(a) can inhibit plasminogen activation and subsequent fibrinolysis, predisposing patients to thrombotic complications [15,16]. Lp(a) also contains oxidized phospholipids that can induce the expression of proinflammatory cytokines, thereby promoting inflammation and contributing to the formation of atherosclerotic plaques [17]. Furthermore, Lp(a) can induce vascular calcification, likely through inflammatory response [18,19]. Serum levels of Lp(a) are higher in patients with chronic kidney disease, nephrotic syndrome, and end-stage kidney disease than in those without renal insufficiency [20,21]. Furthermore, higher serum Lp(a) levels are associated with a greater risk of myocardial infarction, ischemic stroke, valvular heart disease, and heart failure [20,22]. Importantly, in a retrospective cohort study of patients undergoing chronic PD, elevated Lp(a) levels were independently associated with death attributed to CV conditions [23].

Several studies have evaluated the association between Lp(a) and arterial stiffness [24]. For example, a cross-sectional study on elderly diabetic participants revealed that Lp(a) concentrations were positively associated with aortic pulse wave velocity after adjustment for confounders such as glycemic status, age, fibrinogen levels, and lipid-lowering treatments [25]. In patients with hypertension, older age and higher levels of Lp(a) and C-reactive protein were independently associated with increased AS augmentation index, an indicator of AS [26]. Our previously published work enrolling patients on PD from Hualien Tzu Chi Hospital concluded that carotid-ankle vascular index (CAVI), an alternative method of AS determination from the aorta to the tibial arteries, was positively linked with serum Lp(a) after adjusting other lipid parameters and inflammatory biomarkers in 86 PD participants [27]. However, cfPWV is considered the reference standard for AS measures [8,10]. Therefore, this study included more participants to evaluate the association between serum Lp(a) and AS measuring by cfPWV in patients with long-term PD from Dalin Tzu Chi Hospital and Hualien Tzu Chi Hospital.

Material and Methods

ETHICS AND STUDY SUBJECTS:

This was a cross-sectional study including 148 patients who were receiving maintenance PD due to end-stage kidney failure for more than 3 months in Dalin Tzu Chi Hospital and Hualien Tzu Chi Hospital in Taiwan and between February 1, 2020 and May 31, 2021. The study was reviewed and approved by the Institutional Review Board of the Protection of Human Subjects in Dalin Tzu Chi Hospital and Hualien Tzu Chi Hospital (IRB108-219-A). A written informed consent was provided to each study participant. There were no incentives or compensation given to the patients for their participation. Patients with active infectious disease, heart failure, acute coronary syndrome, cerebrovascular disease, malignant tumor, or history of limb amputation were excluded from the study.

Data on indicators of solute clearance, including weekly and peritoneal fractional urea clearance index (Kt/V) and overall and peritoneal creatinine clearance, were collected from the medical records. In the present study, DM was defined as a fasting plasma glucose concentration of ≥126 mg/dL or the use of antidiabetic medications. Hypertension was defined as a systolic blood pressure (SBP) of ≥140 mmHg, diastolic blood pressure (DBP) of ≥90 mmHg, and the use of chronic antihypertensive agents in the 2 weeks prior to study inclusion. Data on the ongoing use of angiotensin receptor, beta-, and calcium channel blockers as well as statins were also retrieved from the medical records.

ANTHROPOMETRIC ANALYSES:

In all patients, height, waist circumference, and weight were measured 3 times with the patient in casual clothing and stockings. The height, which was checked with patients standing erect, was the distance from the sole of the foot to the top of the head (H910, Nagata Scale Co., Ltd, Tainan City, Taiwan). When participants were standing upright, the waist circumference was measured at the midpoint between the inferior margin of the ribs and the superior border of the iliac crest. The body weight was determined by the results of a digital scale (FM-200, Hostart Co., Ltd, New Taipei City, Taiwan). The results were averaged and rounded to the nearest half-centimeter and half-kilogram, as appropriate. Body mass index was calculated as weight/height2 (kg/m2).

BIOCHEMICAL TESTS:

In all patients, a 5-mL blood sample was collected before the daytime exchange of PD solution after an 8-h fasting period. After using 0.5 mL of the collected sample for complete blood count (Sysmex SP-1000i; Sysmex American, Mundelein, IL, USA), the remaining blood sample was centrifuged at 3000 g for 10 min, and the separated serum was stored at 4°C for biochemical tests. An autoanalyzer (Siemens Advia 1,800; Siemens Healthcare, Henkestr, Germany) was used to measure the serum levels of total cholesterol, triglycerides, fasting glucose, albumin, blood urea nitrogen, creatinine, total calcium, and phosphorus. Enzyme-linked immunosorbent assays were used to determine the levels of intact parathyroid hormone (catalog no. NM59041; IBL International, Hamburg, Germany) and Lp(a) (catalog no. ab212165; Abcam, Cambridge, MA, USA). The intra- and inter-assay coefficients of variation were 3.6% and 2.8% for iPTH, respectively; the intra- and inter-assay coefficients of variation were and 1.8% and 2.0% for Lp(a), respectively.

MEASUREMENT OF CFPWV:

As a marker of AS, cfPWV was determined using volumetric displacement data acquired with a SphygmoCor XCEL cuff device (AtCor Medical, Sydney, NSW, Australia) [28]. Briefly, patients were asked to remain in a supine position without disturbance in an environment with constant 26°C temperature. After a 10-min rest period, data were collected to determine cfPWV. First, an appropriately sized cuff was placed in the left upper arm, brachial SBP and DBP were recorded, and the cuff was reinflated within 5 s to a pressure below DBP. Next, with the SphygmoCor XCEL device, applanation tonometry was used to measure carotid pulses and a thigh cuff was used to plot femoral artery waveforms. The pulse wave travel length was determined by subtracting the distance between carotid pulse and sternal notch from the distance between the sternal notch and femoral cuff site [29]. Data on the distances and transit times were eventually utilized to calculate cfPWV. For each participant, the recorded cfPWV value was averaged over 2 consecutive measurements. The calibration process strictly adhered to the operator’s manual of the SphygmoCor XCEL device. To optimize the accuracy of the study results, the tonometer, cuffs, and air lines used in the study were all validated with SphygmoCor XCEL. After each measurement of cfPWV, the quality control indicator based on the variability of pulse wave velocity was displayed. Based on the 2018 European Society of Cardiology and the European Society of Hypertension guidelines, a cfPWV cutoff value of 10 m/s was used to define AS in the present study [30].

STATISTICAL ANALYSES:

For continuous variables, which were presented as means±standard deviation, the Kolmogorov-Smirnov test was used to determine normality of distribution. Continuous variables with normal distribution were compared using Student’s t test. Non-normally distributed variables were presented as medians with interquartile ranges and compared using the Mann-Whitney U test. For linear regression analyses, non-normally distributed variables were logarithmically transformed. Categorical variables were presented as numbers with percentages and compared using the chi-square test. Multivariate logistic regression analysis to identify factors associated with AS was performed by adjusting for the following clinical variables, which exhibited significant differences between the patients with and without AS: age, waist circumference, SBP, fasting plasma glucose, serum Lp(a) level, weekly Kt/V, and diagnosis of DM. Simple and multivariate regression analyses were further used to determine variables associated with cfPWV as a readout of AS. The optimal cutoff serum Lp(a) level that distinguished between patients with and without AS was determined using the area under the receiver operating characteristic curve. The association of log-transformed Lp(a) [log-Lp(a)] with ordinal and continuous clinical variables was evaluated using Spearman’s rank correlation coefficient analysis. All analyses were performed using IBM SPSS Statistics for Windows version 19.0 (IBM, Armonk, NY, USA). The receiver operating characteristic curve was performed using MedCalc Software for Windows version 22.019 (MedCalc Software Ltd, Ostend, Belgium). Statistical significance was defined as a P value of <0.05.

Results

ASSOCIATION OF CLINICAL CHARACTERISTICS WITH AS IN PATIENTS ON MAINTENANCE PD:

The detailed clinical characteristics of the 148 patients on maintenance PD included in the study cohort are presented in Table 1. The study cohort included 61 and 87 patients who were receiving automated and continuous ambulatory PD, respectively. In the overall cohort, the mean age was 58.61 years and the median vintage of PD therapy at recruitment was 48.54 (21.03–81.42) months. Additionally, AS was present in 32 (21.6%) patients, whereas 59 (39.9%) and 107 (72.3%) patients had DM and hypertension, respectively. Compared with the patients without AS, those with AS had higher serum levels of Lp(a) (P<0.001), greater small solute clearance indicated by higher weekly Kt/V (P=0.045), larger waist circumference (P=0.009), higher SBP (P=0.041), higher fasting serum glucose levels (P=0.014), and a higher rate of DM (P=0.003). In contrast, PD vintage; PD modality; body mass index; DBP; hemoglobin level; solute removal indicated by weekly creatinine clearance; sex; hypertension; and serum levels of lipids, albumin, blood urea nitrogen, creatinine, calcium, phosphorus, and intact parathyroid hormone were not significantly different between the patients with and without AS. The rates of patients on antihypertensive and lipid-lowering medications were not significantly different between the 2 study groups.

SERUM LP(A) LEVELS ARE INDEPENDENTLY ASSOCIATED WITH AS:

Multivariate logistic regression analysis (adopted factors: age, DM, SBP, waist circumference, fasting glucose, weekly Kt/V, and Lp(a)) indicated that a high serum Lp(a) level was the only independent variable associated with the increased likelihood of AS (odds ratio [OR], 1.007 for every 1 mg/L increase; 95% confidence interval [CI], 1.003–1.011; P<0.001) (Table 2).

LINEAR REGRESSION ANALYSIS OF CFPWV AND CLINICAL VARIABLES:

Simple linear regression analysis to determine the relationship of cfPWV with clinical variables revealed that cfPWV was positively associated with DM (r=0.404; P<0.001), age (r=0.295; P<0.001), waist circumference (r=0.306; P<0.001), SBP (r=0.281; P=0.001), total cholesterol (r=0.216; P=0.008), log-transformed glucose (log-glucose, r=0.322; P<0.001), and log-Lp(a) (r=0.396; P<0.001) (Table 3). Multivariate, forward, stepwise linear regression analysis performed after adjusting for these variables indicated that the following variables were independently associated with higher cfPWV: diagnosis of DM (β=0.317; adjusted R2 change=0.158; P<0.001), older age (β=0.198; adjusted R2 change=0.028; P=0.003), waist circumference (β=0.178; adjusted R2 change=0.025; P=0.008), SBP (β=0.174; adjusted R2 change=0.024; P=0.010), and Lp(a) (β=0.342; adjusted R2 change=0.170; P<0.001).

OPTIMAL CUTOFF LP(A) LEVEL FOR THE PREDICTION OF AS:

The area under the receiver operating characteristic curve analysis (Figure 1) indicated that the ideal cutoff Lp(a) level in predicting the presence of AS in patients on PD was 102.73 mg/L (area under the curve, 0.770; 95% CI, 0.694–0.835; P<0.0001 with a sensitivity of 93.75% (95% CI, 0.854–1.021), specificity of 50.00% (95% CI, 0.409–0.590), positive predictive value of 34.09% (95% CI, 0.242–0.440), and negative predictive value of 96.67% (95% CI, 0.924–1.012).

ASSOCIATION OF LOG-LP(A) WITH CLINICAL VARIABLES:

As shown in Table 4, Spearman’s rank correlation coefficient analysis to determine the association between log-Lp(a) with clinical variables revealed its positive association with total cholesterol (ρ=0.321; P<0.001), blood urea nitrogen (ρ=0.234; P=0.004), and cfPWV (ρ=0.398; P<0.001), and negative association with serum albumin (ρ=−0.194; P=0.018).

Discussion

In this cross-sectional study, our analyses revealed that Lp(a), diabetes, advanced age, large waist circumference, and high SBP were independent predictors of AS in patients on maintenance PD. We also found that serum log-Lp(a) was an independent predictor of hypercholesterolemia, hypoalbuminemia, azotemia, and increased cfPWV.

AS reflects the altered compliance of significant blood vessels, which leads to severe end-organ damage (including left ventricular hypertrophy, albuminuria, and cerebral ischemia) and clinically overt CV complications [31]. The utility of increased pulse wave velocity as a critical biomarker to predict incident major CV events was shown in the Framingham Heart Study with a median follow-up period of 7.8 years [32]. In accordance with a systematic review including patients with end-stage kidney disease, cfPWV is a precise indicator in the prediction of CV events and related deaths [33]. Hemodynamic alterations, which are related to fluid balance, activation of neurohumoral factors, and shear stress secondary to fluctuations in blood pressures, as well as intrinsic vasculopathy resulting from aging, diminished elastin content relative to collagen, acute and chronic inflammation, formation of advanced glycation end products, vascular smooth muscle cell migration, and endothelial dysfunction are central pathogenic processes that contribute to vascular stiffening [7,34]. Patients with kidney failure are exceedingly vulnerable to the development of atherosclerotic lesions related to the complex interplay among inflammation, oxidative stress, uremic molecules, and impaired calcium–phosphorus homeostasis [35,36].

Various mechanisms underlie the effect of Lp(a) on the initiation and progression of atherosclerosis. In a study using endothelial cell cultures, the expression levels of adhesion molecules such as E-selectin and vascular cell adhesion molecule-1 were enhanced by Lp(a), which indicating its role as a trigger for the recruitment of inflammatory cells [37]. Lp(a) exhibits increased binding affinity for fibronectin and collagen fibers within the extracellular matrix of arterial walls, which can accelerate the development of atheromas [38,39]. In addition, Lp(a) is involved in chemotaxis and the production of cytokines, including interleukins 6 and 1β and tumor necrosis factor-α, thus establishing a proinflammatory milieu within the blood vessel wall [40,41]. Oxidized Lp(a) induces the growth and migration of vascular smooth muscle cells [42,43], whereas Lp(a) leads to endothelial dysfunction and vasodilation through the reduction of endothelial nitric oxide production [44,45]. Furthermore, Lp(a) exerts its prothrombotic property by inhibiting tissue factor pathway inhibitor and by altering the microstructure of fibrin clots [46]. The thrombogenicity of Lp(a) also promotes vasculopathy, leading to thromboembolic complications [47]. Therefore, the potential association of Lp(a) levels with AS, as evidenced by the good utility of Lp(a) in predicting AS in patients on PD in the present study, might be explained by the role of Lp(a) in atherogenesis.

The aforementioned cross-sectional studies have proven the positive association between serum Lp(a) and parameters of AS in various populations, including the elderly, diabetic individuals, hypertensive patients, and people with kidney failure [24–27]. In these investigations, the participants were mainly middle-aged or elderly, and the AS could be noninvasively assessed by pulse wave velocities, augmentation indices, and CAVI [48].

We also noted that serum Lp(a) concentrations were negatively associated with serum albumin levels. A cross-sectional study with a small cohort of patients on long-term PD reported that albumin was negatively associated with Lp(a); as a possible explanation of the observed association, the authors suggested that protein malnutrition reflected by hypoalbuminemia would stimulate the hepatic synthesis of Lp(a) and other lipids with atherogenic potential [49]. Additionally, albumin can be considered a negative acute phase reactant; thus, hypoalbuminemia is positively associated with inflammation [50]. However, the exact mechanism underlying the link between low serum albumin and high serum Lp(a) levels observed in the present study remains to be determined.

Large waist circumference independently predicted increased cfPWV in patients on PD in the present study. In a Korean study, brachial-ankle pulse wave velocity was positively associated with waist circumference and visceral fat area [51]. A study in the USA including elderly patients found that the degree of abdominal visceral adiposity independently predicted AS estimated by aortic pulse wave velocity [52]. Insulin resistance, endothelial dysfunction, and inflammatory processes are potential mechanisms of vasculopathy resulting from central obesity.

Our findings should be interpreted with consideration of its limitations. First, the relatively small cohort size restricts the generalizability of our findings to larger populations. Second, this was a cross-sectional study and demonstrating the causative role of Lp(a) in vasculopathy and adverse outcomes in patients on PD is challenging. In fact, we did not have serial measurements of cfPWV and Lp(a) on these patients. Third, we did not evaluate the degree of vascular calcifications through the histology or imaging studies in these participants. Fourth, we only checked iPTH and Lp(a) once, and small errors are inevitably present. Fifth, the optimal cutoff cfPWV in defining AS in patients with kidney failure has not been established; however, a cfPWV exceeding 10 m/s is acceptable to determine AS according to the European Society of Cardiology and the European Society of Hypertension practice guidelines. Sixth, we did not perform concomitant measurements of serum oxidized Lp(a) levels, which might also act as a critical driver of AS.

Conclusions

In patients with end-stage kidney disease on long-term PD, serum Lp(a) levels were independently associated with cfPWV as evidenced by the multivariate analysis. The high discrimination capability of Lp(a) in underlying AS (area under the curve: 0.770) makes Lp(a) an ideal biomarker for the prediction of CV complications. Based on the results of previous research and the current investigation, there is a close relationship between Lp(a) and AS among various populations, including patients on PD. Future studies should elucidate the molecular mechanisms underlying the role of Lp(a) in vascular stiffening by using cell lines and animal models. Longitudinal studies with continuous monitoring of Lp(a) levels should evaluate the causal relationship between the biomarkers and adverse CV outcomes.

References

1. Jankowski J, Floege J, Fliser D, Cardiovascular disease in chronic kidney disease: Pathophysiological insights and therapeutic options: Circulation, 2021; 143(11); 1157-72

2. Van Biesen W, Verbeke F, Vanholder R, Cardiovascular disease in haemodialysis and peritoneal dialysis: Arguments pro peritoneal dialysis: Nephrol Dial Transplant, 2007; 22(1); 53-58

3. Lee CC, Hsu CC, Lin MH, Hospitalization in patients with dialysis in Taiwan: A nationwide population-based observational study: J Formos Med Assoc, 2022; 121(Suppl 1); S39-S46

4. Chiu YW, Mehrotra R, Can we reduce the cardiovascular risk in peritoneal dialysis patients?: Indian J Nephrol, 2010; 20(2); 59-67

5. Krediet RT, Balafa O, Cardiovascular risk in the peritoneal dialysis patient: Nat Rev Nephrol, 2010; 6(8); 451-60

6. Zhang J, Lu X, Li H, Wang S, Risk factors for mortality in patients undergoing peritoneal dialysis: A systematic review and meta-analysis: Ren Fail, 2021; 43(1); 743-53

7. Shirwany NA, Zou MH, Arterial stiffness: A brief review: Acta Pharmacol Sin, 2010; 31(10); 1267-76

8. Tsai JP, Hsu BG, Arterial stiffness: A brief review: Tzu Chi Med J, 2020; 33(2); 115-21

9. Millasseau SC, Stewart AD, Patel SJ, Evaluation of carotid-femoral pulse wave velocity: Influence of timing algorithm and heart rate: Hypertension, 2005; 45(2); 222-26

10. Wilkinson IB, Mäki-Petäjä KM, Mitchell GF, Uses of arterial stiffness in clinical practice: Arterioscler Thromb Vasc Biol, 2020; 40(5); 1063-67

11. Cavalcante JL, Lima JA, Redheuil A, Aortic stiffness: Current understanding and future directions: J Am Coll Cardiol, 2011; 57(14); 1511-22

12. Angoff R, Mosarla RC, Tsao CW, Aortic stiffness: Epidemiology, risk factors, and relevant biomarkers: Front Cardiovasc Med, 2021; 8; 709396

13. Bonarjee VVS, Arterial Stiffness: A prognostic marker in coronary heart disease. Available methods and clinical application: Front Cardiovasc Med, 2018; 5; 64

14. Maranhão RC, Carvalho PO, Strunz CC, Lipoprotein (a): Structure, pathophysiology and clinical implications: Arq Bras Cardiol, 2014; 103(1); 76-84

15. Hancock MA, Boffa MB, Marcovina SM, Inhibition of plasminogen activation by lipoprotein(a): Critical domains in apolipoprotein(a) and mechanism of inhibition on fibrin and degraded fibrin surfaces: J Biol Chem, 2003; 278(26); 23260-69

16. Loscalzo J, Weinfeld M, Fless GM, Lipoprotein(a), fibrin binding, and plasminogen activation: Arteriosclerosis, 1990; 10(2); 240-45

17. Reyes-Soffer G, Ginsberg HN, Berglund L, Lipoprotein(a): A genetically determined, causal, and prevalent risk factor for atherosclerotic cardiovascular disease: A scientific statement from the American Heart Association: Arterioscler Thromb Vasc Biol, 2022; 42(1); e48-e60

18. Rogers MA, Atkins SK, Zheng KH, Lipoprotein(a) induces vesicular cardiovascular calcification revealed with single-extracellular vesicle analysis: Front Cardiovasc Med, 2022; 9; 778919

19. Singh SS, van der Toorn JE, Sijbrands EJG, Lipoprotein(a) is associated with a larger systemic burden of arterial calcification: Eur Heart J Cardiovasc Imaging, 2023; 24(8); 1102-9

20. Kronenberg F, Mora S, Stroes ESG, Lipoprotein(a) in atherosclerotic cardiovascular disease and aortic stenosis: A European Atherosclerosis Society consensus statement: Eur Heart J, 2022; 43(39); 3925-46

21. Kronenberg F, Utermann G, Dieplinger H, Lipoprotein(a) in renal disease: Am J Kidney Dis, 1996; 27(1); 1-25

22. Wilson DP, Jacobson TA, Jones PH, Use of lipoprotein(a) in clinical practice: A biomarker whose time has come. A scientific statement from the National Lipid Association: J Clin Lipidol, 2019; 13(3); 374-92

23. Zhong Z, Peng F, Shi D, Serum lipoprotein(a) and risk of mortality in patients on peritoneal dialysis: J Clin Lipidol, 2020; 14(2); 252-59

24. Sorokin A, Kotani K, Lipoprotein(a) and arterial stiffness parameters: Pulse (Basel), 2015; 3(2); 148-52

25. Wakabayashi I, Masuda H, Lipoprotein (a) as a determinant of arterial stiffness in elderly patients with type 2 diabetes mellitus: Clin Chim Acta, 2006; 373(1–2); 127-31

26. Brosolo G, Da Porto A, Bulfone L, Plasma lipoprotein(a) levels as determinants of arterial stiffening in hypertension: Biomedicines, 2021; 9(11); 1510

27. Tsai JP, Wang CH, Lin YL, Elevated lipoprotein(a) levels measured by cardio-ankle vascular index are associated with arterial stiffness in patients undergoing peritoneal dialysis: Rev Cardiovasc Med, 2023; 24(11); 322

28. Butlin M, Qasem A, Large artery stiffness assessment using SphygmoCor technology: Pulse (Basel), 2017; 4(4); 180-92

29. Avolio A, Zuo J, Tan I, Pathway for elimination of distance measurement in studies of pulse wave velocity: Hypertension, 2018; 71(5); 819-21

30. Williams B, Mancia G, Spiering W, 2018 ESC/ESH Guidelines for the management of arterial hypertension: Eur Heart J, 2018; 39(33); 3021-104

31. Vasan RS, Short MI, Niiranen TJ, Interrelations between arterial stiffness, target organ damage, and cardiovascular disease outcomes: J Am Heart Assoc, 2019; 8(14); e012141

32. Mitchell GF, Hwang SJ, Vasan RS, Arterial stiffness and cardiovascular events: The Framingham Heart Study: Circulation, 2010; 121(4); 505-11

33. Sequí-Domínguez I, Cavero-Redondo I, Álvarez-Bueno C, Accuracy of pulse wave velocity predicting cardiovascular and all-cause mortality. A systematic review and meta-analysis: J Clin Med, 2020; 9(7); 2080

34. Zieman SJ, Melenovsky V, Kass DA, Mechanisms, pathophysiology, and therapy of arterial stiffness: Arterioscler Thromb Vasc Biol, 2005; 25(5); 932-43

35. Cai Q, Mukku VK, Ahmad M, Coronary artery disease in patients with chronic kidney disease: A clinical update: Curr Cardiol Rev, 2013; 9(4); 331-39

36. Valdivielso JM, Rodríguez-Puyol D, Pascual J, Atherosclerosis in chronic kidney disease: More, less, or just different?: Arterioscler Thromb Vasc Biol, 2019; 39(10); 1938-66

37. Allen S, Khan S, Tam Sp, Expression of adhesion molecules by lp(a): A potential novel mechanism for its atherogenicity: FASEB J, 1998; 12(15); 1765-76

38. Ehnholm C, Jauhiainen M, Metso J, Interaction of lipoprotein(a) with fibronectin and its potential role in atherogenesis: Eur Heart J, 1990; 11(Suppl E); 190-95

39. Khalil MF, Wagner WD, Goldberg IJ, Molecular interactions leading to lipoprotein retention and the initiation of atherosclerosis: Arterioscler Thromb Vasc Biol, 2004; 24(12); 2211-18

40. Dzobo KE, Kraaijenhof JM, Stroes ESG, Nurmohamed NS, Kroon J, Lipoprotein(a): An underestimated inflammatory mastermind: Atherosclerosis, 2022; 349; 101-9

41. Lampsas S, Xenou M, Oikonomou E, Lipoprotein(a) in atherosclerotic diseases: From pathophysiology to diagnosis and treatment: Molecules, 2023; 28(3); 969

42. Komai N, Morishita R, Yamada S, Mitogenic activity of oxidized lipoprotein (a) on human vascular smooth muscle cells: Hypertension, 2002; 40(3); 310-14

43. Liu J, Ren Y, Kang L, Oxidized low-density lipoprotein increases the proliferation and migration of human coronary artery smooth muscle cells through the upregulation of osteopontin: Int J Mol Med, 2014; 33(5); 1341-47

44. Cominacini L, Rigoni A, Pasini AF, The binding of oxidized low density lipoprotein (ox-LDL) to ox-LDL receptor-1 reduces the intracellular concentration of nitric oxide in endothelial cells through an increased production of superoxide: J Biol Chem, 2001; 276(17); 13750-55

45. Schlaich MP, John S, Langenfeld MR, Does lipoprotein(a) impair endothelial function?: J Am Coll Cardiol, 1998; 31(2); 359-65

46. Boffa MB, Koschinsky ML, Lipoprotein (a): Truly a direct prothrombotic factor in cardiovascular disease?: J Lipid Res, 2016; 57(5); 745-57

47. Scipione CA, Koschinsky ML, Boffa MB, Lipoprotein(a) in clinical practice: New perspectives from basic and translational science: Crit Rev Clin Lab Sci, 2018; 55(1); 33-54

48. Townsend RR, Wilkinson IB, Schiffrin EL, Recommendations for improving and standardizing vascular research on arterial stiffness: A scientific statement from the American Heart Association: Hypertension, 2015; 66(3); 698-722

49. Ross EA, Shah GM, Kashyap ML, Elevated plasma lipoprotein(a) levels and hypoalbuminemia in peritoneal dialysis patients: Int J Artif Organs, 1995; 18(12); 751-56

50. Gremese E, Bruno D, Varriano V, Serum albumin levels: A biomarker to be repurposed in different disease settings in clinical practice: J Clin Med, 2023; 12(18); 6017

51. Kim HL, Ahn DW, Kim SH, Association between body fat parameters and arterial stiffness: Sci Rep, 2021; 11(1); 20536

52. Sutton-Tyrrell K, Newman A, Simonsick EM, Aortic stiffness is associated with visceral adiposity in older adults enrolled in the study of health, aging, and body composition: Hypertension, 2001; 38(3); 429-33

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17 Jan 2024 : Review article   3,694,697

Vaccination Guidelines for Pregnant Women: Addressing COVID-19 and the Omicron Variant

DOI :10.12659/MSM.942799

Med Sci Monit 2024; 30:e942799

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14 Dec 2022 : Clinical Research   1,585,228

Prevalence and Variability of Allergen-Specific Immunoglobulin E in Patients with Elevated Tryptase Levels

DOI :10.12659/MSM.937990

Med Sci Monit 2022; 28:e937990

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16 May 2023 : Clinical Research   690,866

Electrophysiological Testing for an Auditory Processing Disorder and Reading Performance in 54 School Stude...

DOI :10.12659/MSM.940387

Med Sci Monit 2023; 29:e940387

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01 Jan 2022 : Editorial   50,699

Editorial: Current Status of Oral Antiviral Drug Treatments for SARS-CoV-2 Infection in Non-Hospitalized Pa...

DOI :10.12659/MSM.935952

Med Sci Monit 2022; 28:e935952

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750