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Impact of a Single Hemodialysis Session on Oxidative Stress-Inducing and Oxidative Damage Biomarkers in End-Stage Kidney Disease Patients

  † These authors contributed equally to this work.

Submitted:

01 April 2026

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02 April 2026

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Abstract
Oxidative stress (OS) is elevated in patients with end-stage kidney disease undergoing maintenance dialysis and contributes to increased cardiovascular risk. While kidney dysfunction and dialysis can generate OS, the acute effects of a single dialysis session remain unclear due to variability in study design and biomarkers used. In this observational study, blood samples from 68 hemodialysis patients were collected before and after a single session. Plasma levels of the reactive oxygen species marker superoxide (O2•−) and OS-damage markers lipid hydroperoxides (LOOH), protein-bound malondialdehyde (PrMDA), protein-bound thiobarbituric acid reactive substances (PrTBARS), and protein carbonyls (PrCO) were measured. LOOH increased significantly by 50% post-dialysis, whereas PrMDA and PrTBARS decreased modestly by ~10%. No significant changes were observed in O2•− or PrCO. Dialysis vintage correlated positively with LOOH, PrMDA, and PrTBARS, but not with O2•− or PrCO. Patients undergoing low-flux hemodialysis exhibited a greater post-dialysis increase in LOOH than those treated with high-flux hemodialysis. No significant associations were found between OS markers and comorbidities or medication. The post-dialysis rise in LOOH, an early-formed and least accumulating lipid peroxidation marker, highlights its sensitivity to acute dialysis-related oxidative changes. The rising tendency of PrMDA and PrTBARS with dialysis vintage suggests cumulative OS over time.
Keywords: 
chronic kidney disease
;  
hemodialysis
;  
lipid peroxidation
;  
oxidative stress
;  
reactive oxygen species
Subject: 
Medicine and Pharmacology  -   Urology and Nephrology

1. Introduction

Oxidative stress (OS) has emerged as an important risk factor for chronic kidney disease (CKD) and especially for patients on maintenance hemodialysis (HD). Reactive oxygen species (ROS) are generated under physiological conditions due to aerobic metabolism. However, occurs when their production exceeds their neutralization by endogenous antioxidant defenses[1]. Consequently, DNA, lipids and proteins undergo oxidative damage, impairing cellular and organismal function [2].
The major free radicals (FR) are superoxide (O2•−) and hydroxyl radical (•OH). Hydroxyl radical is highly reactive and directly attacks and damages biomolecules, whereas O2•− contributes indirectly through secondary reactions generating more toxic species such as •OH and peroxynitrite (ONOO-) [3,4]. Lipids, especially polyunsaturated fatty acids, are susceptible to peroxidation, forming lipid hydroperoxides (LOOH, an early lipid peroxidation marker), which are degraded to aldehydic byproducts such as malondialdehyde (MDA), considered among the most biotoxic late markers of lipid peroxidation. Malondialdehyde is extremely reactive and readily binds to proteins covalently, thereby altering their structure and functionality [3]. Proteins are also prone to oxidative modifications, one of them being carbonylation, which is almost irreversible modification. Accumulation of carbonylated proteins can lead to cellular dysfunction [5].
Patients with end-stage kidney disease exhibit reduced life expectancy, mainly due to cardiovascular disease (CVD), in which OS has a critical role [6,7,8,9,10,11,12]. Extracorporeal circulation during hemodialysis can further increase OS, as determined thus far, through factors such as filter membrane bio-incompatibility, antioxidant loss and anticoagulation[13,14,15].
The heterogeneity in methodology and design of previous studies as well as the non-specificity of the evaluated OS markers, have produced contradictory findings across studies. Specifically, blood O2•- levels have been assessed by chemiluminescence (CL) of the non-specific probe lucigenin [16], which can also lead to overestimation due to redox cycling [17,18]. Many other studies have focused on the damage ROS cause on biomolecules such as lipids (using as markers of their peroxidation free MDA and thiobarbituric acid reactive substances (TBARS) [19,20,21,22,23,24,25,26,27,28,29,30], and glutathione (GSH) (measuring also its oxidized form, GSSG) [19,21,22,24,26,29]. Moreover, other studies have measured the activity of ROS key antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase, xanthine oxidase) [19,22,23,24,26,31], as well as natural antioxidants’ cumulative levels by the total antioxidant capacity (TAC) [25,27,31,32]. Even disease non-specific oxidized LDLs have been evaluated in patients on dialysis (by ELISA [31,32]).
The present study aims to provide more reliable conclusions regarding the relationship between dialysis and OS by employing specific methodologies and clinical markers that demonstrate its presence, directly through the identification of specific FR and indirectly by detecting oxidative modifications in blood plasma lipids and proteins. O2•− levels are specifically measured before and after a single dialysis session, along with LOOH, MDA, TBARS in their protein-bound form (PrMDA, PrTBARS) and protein carbonyls (PrCO). Evaluation of OS markers is also conducted in relation to dialysis vintage, modality (low-flux conventional HD, high-flux conventional HD and pre-dilution HDF), comorbidities and medication.

2. Materials and Methods

2.1. Study Design and Patients

An observational pre-post dialysis study was conducted in 68 patients aged 25 to 86 years from the Hemodialysis Unit of the University Hospital of Patras, Greece, to assess changes in the levels of oxidative stress markers before and after a dialysis session. Demographic and clinical characteristics are shown in Table 1. Eligible participants were ESKD patients (> 18 years) receiving regular hemodialysis (three times a week, 3-4 h/session) for at least 3 months. Exclusion criteria included systemic infection within 30 days prior to participation and active malignancy or malignancy within the previous 5 years. Patients were separated in three groups according to dialysis modality, i.e., those that received hemodialysis with low flux dialyzer (Fresenius-FX-10 polysulfone membrane, effective surface area of 1.8 m2, ultrafiltration coefficient of 14 ml/h x mmHg), hemodialysis with high flux dialyzer (Fresenius-FX-80 polysulfone membrane, effective surface area of 1.8 m2, ultrafiltration coefficient of 59 ml/h x mmHg) and pre-dilution hemodialfiltration (Fresenius-FX-80). All patients received an adequate dialysis dose as confirmed with a single-pool Kt/V of over 1.2 confirmed in a maximum of two weeks interval before the collection of blood samples for the analyses used in this study. Dialysate flow was set to a standard of 500 ml/min and replacement fluid volume for pre-dilution HDF was set to 20 L. All patients received anti-coagulation with a standard dose of 4000 IU of enoxaparine. All participants provided written consent. The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University Hospital of Patras (No.316/04.09.2025).

2.2. Methods

Blood was collected into heparinized tubes immediately before the initiation and after the end of the second weekly dialysis session, as a more representative patient’s state-condition and to avoid long interdialytic interval.

2.2.1. O2•− Quantification

O2•− was measured using hydroethidine (HE) as a probe at 25 μM final concentration, added in heparinized tubes before blood collection. Samples were incubated 15 min at room temperature (RT) and centrifuged to isolate plasma. 0.1 ml blood plasma was used for O2•− quantification via measurement of 2-hydroxyethidium (2-OН-Е+) by High-Performance Thin Layer Chromatography [33].

2.2.2. OS Markers Quantification

For the quantification of the OS markers LOOH, PrMDA, PrTBARS and PrCO, blood was centrifuged and plasma was protected from artificial oxidation by addition of the antioxidants BHA/BHT at final 1/1 mM (using stock solution 200/200 mM in 100% EtOH). 0.25 ml plasma was subjected to a fractionation protocol to isolate proteins and total lipids [34]. Protein fraction was analyzed for the determination of PrMDA, PrTBARS and PrCO, while lipid fraction was analyzed for the measurement of LOOH [34,35].
For all assays, samples were measured in triplicate using three different dilutions, and the mean was calculated.

2.3. Statistical Analysis

Statistical analysis was performed using the IBM SPSS Statistics 26 with the significance level set at 0.05. Paired T-tests or Wilcoxon Signed-Rank tests were used to evaluate OS markers levels pre-post hemodialysis.
Differences in OS markers among three dialysis modalities were evaluated using one-way ANOVA or the Kruskal-Wallis test, depending on data distribution and homogeneity of variances (assessed by Levene’s test). Post-hoc Tukey analysis was performed to identify differences between groups. Analyses were based on both the pre-dialysis values of OS markers and their intradialytic changes (Δ = Pre – Post dialysis).
Spearman’s rank correlation was used for associations between dialysis vintage or patient’s age and each OS marker.
Robust linear regression (MM-estimation; R v.4.5.1, lmrob() function) was performed to assess whether the relationship between dialysis vintage and OS markers differs by dialysis modality.
Associations of OS markers with gender, comorbidities and medication were assessed with Mann-Whitney U test.

3. Results

3.1. OS Biomarkers Levels Before and After a Single Dialysis Session

Direct and indirect OS markers were assessed (Figure 1) in 68 hemodialysis patients (48 males, 20 females) with a mean age 62.4 ± 14.6 years. The duration of hemodialysis ranged from 0.4 to 24.6 with a mean 6.9 ± 5.5 years. Among participants, 47 were undergoing conventional hemodialysis (HD) and 21 were receiving pre-dilution hemodiafiltration (HDF).
O2•− was used for direct OS assessment and the OS indirect markers LOOH, PrMDA, PrTBARS and PrCO were measured in blood plasma obtained before and after the dialysis session. O2•− levels were slightly elevated post-dialysis (22.86 ± 8.34 vs. 24.79 ± 10.2 pmoles O2•−/mg protein), indicating a statistically non-significant change. However, the LOOH OS marker significantly increased (by 1.5-fold, or 50%) after the dialysis session (0.054 ± 0.025 vs. 0.081 ± 0.042 nmoles Cum-OOH equivalent/mg protein), while the PrMDA and PrTBARS OS markers exhibited a modest but significant decrease (by 1.1-fold, or ~10%) post dialysis (PrMDA: 4.7 ± 1.98 vs. 4.21 ± 1.87 pmoles MDA/mg protein; PrTBARS: 8.97 ± 2.74 vs. 8.12 ± 2.59 pmoles MDA/mg protein). Finally, the OS marker PrCO remained unchanged during dialysis (1.31 ± 0.43 and 1.33 ± 0.51 nmoles carbonyls/mg protein).

3.2. Impact of Dialysis Modalities on OS Biomarkers

To investigate the potential impact of dialysis modalities on OS burden, OS biomarkers’ levels were compared among patients undergoing low-flux conventional HD (N=30), high-flux conventional HD (N=17) and pre-dilution HDF (N=21). Comparisons were performed both on pre-dialysis values and on intradialytic changes (Δ = value before dialysis – value after dialysis), to account for both baseline oxidative stress status and the effect of the dialysis itself. Detailed data are presented in Table 2 and Table 3. No significant differences were observed among the three modalities for O2•−, PrMDA, PrTBARS or PrCO, either at baseline or in Δ values. However, LOOH levels differed significantly among modalities, but only when comparisons were performed on Δ values. Post-hoc Tukey analysis revealed a significant difference between low-flux and high-flux HD (mean difference= -0.038, P = 0.021), with low-flux HD inducing a greater increase in LOOH post-dialysis than high-flux HD.

3.3. Associations Between OS Biomarkers and Dialysis Vintage

In order to assess whether dialysis vintage correlates with the pre-dialysis levels of OS markers, Spearman’s rank correlation analyses were performed (Figure 2). A significant positive correlation was between dialysis vintage and LOOH (r=0.458, P = 0.005; panel B), PrMDA (r= 0.298, P = 0.018; panel C) and PrTBARS (r=0.272, P = 0.025; panel D). However, no significant correlation was observed between dialysis vintage and O2•− (r= -0.126, P = 0.47; panel A) or PrCO (r= -0.112, P = 0.356; panel E).
The same correlation analysis was applied to assess the relationship between patients’ age and OS markers, where none of the measured OS markers showed a significant correlation with age. Detailed correlation coefficients are presented in Table 4.
Furthermore, Robust Linear Regression analyses showed that the pre-dialysis levels of each OS marker in relation to dialysis vintage, did not differ significantly among patients undergoing low-flux HD, high-flux HD or pre-dilution HDF (Supplemental Table S1).

3.4. Additional Analyses

Finally, analyses were conducted to search for possible associations between the OS markers and patient’s clinical characteristics, specifically underlying conditions and medication. However, no significant differences were observed between OS markers and comorbidities such as Hypertension, CVD, CHD, PAD and Diabetes (Supplemental Table S2). Similarly, no significant associations were found between OS parameters and the use of medications including statins, alfacalcidol, paricalcitol, ACEis, ARBs, CaChBl, B blockers, Levocarnitine and Cholecalciferol (Supplemental Table S3). In addition, demographic characteristics such as gender were examined for potential associations with the oxidation markers but revealed no significant differences between males and females for any of the investigated OS markers (Supplemental Table S4).

4. Discussion

In the present study, we evaluated five specific OS markers, including free radicals (O2•−) and oxidative modifications (LOOH, PrMDA, PrTBARS and PrCO) in blood plasma from patients on maintenance dialysis before and after a single session. Our findings indicate that dialysis affects lipid and protein oxidation markers differently. O2•- levels were slightly but not significantly increased following dialysis.
The most pronounced change among indirect OS markers was observed with LOOH levels, which increased by 1.5-fold or 50% after dialysis (Figure 1). Ιn plasma LOOH are present in oxidized lipoproteins, oxidized phospholipids and oxidized free fatty acids bounded to albumin. The marked accumulation of LOOH post-dialysis may reflect not only increased OS but also a relative deficiency in plasma antioxidant defense, particularly of glutathione peroxidase 3 (GPx3). GPx3 is primarily expressed in the kidney and secreted into plasma, catalyzing the reduction of soluble lipid peroxides, and low levels of GPx3 have been reported in CKD patients[36]. This is in agreement with the suggested RO• and ROO• increased production after one dialysis session due to impaired scavenging activity for these radicals[37]. Other contributing factors may include the low concentration of GSH in plasma or its partial loss during dialysis [21,22,23,38].
Furthermore, PrMDA and PrTBARS levels showed a slight but significant decrease after dialysis by 1.1-fold, or ~10% (Figure 1). These markers reflect the total aldehydic content bound to proteins that result from lipid peroxidation, and provide a more accurate indication of the protein-related oxidative damage [39]. In contrast, free ΜDA and TBARS levels (i) do not represent the total levels produced by OS nor (ii) the fraction causing oxidative damage. Also, we could suggest that the dialysis session duration may be too short for the generation of the late products of lipid peroxidation MDA and TBARS and their reaction with proteins, let alone considering their possible diffusion through the dialyzer.
PrCO levels remained unchanged during one dialysis session and this aligns with previous studies [22,23,31], and with the fact that the PrCO represent long term and mostly cumulative oxidative modifications [5].
Additionally, we compared low-flux HD, high-flux HD and pre-dilution HDF to assess potential differences in their impact on OS markers. No significant differences were observed among the dialysis modalities for O2•-, PrMDA, PrTBARS, or PrCO, regarding pre-dialysis levels of OS markers (Table 2) or intradialytic changes (Δ) during a single session (Table 3). However, significant differences in LOOH levels were detected among the three dialysis modalities, but only when analyzing the Δ values, indicating that the dialysis modality influenced the extent of LOOH change rather than baseline levels. According to Post-hoc Tukey analysis low-flux HD induced a greater increase in LOOH levels after dialysis compared to high-flux HD, suggesting that the improved clearance of pro-oxidant molecules by high-flux membranes may be account for the milder change in LOOH levels [40]. Although HDF has been associated with lower OS, inflammation and greater antioxidant retention [31,41,42] versus conventional HD, no significant differences were observed in our study. Longitudinal measurements across multiple dialysis sessions may provide a more appropriate approach to reveal modality-related differences.
Next, we investigated whether dialysis vintage correlates with OS markers (Figure 2). Spearman’s rank analysis showed significant positive correlation between dialysis vintage and LOOH, PrMDA, PrTBARS, whereas no correlations were observed with O2•- or PrCO. Although these associations do not imply causal relationship, the increase of several OS markers with dialysis vintage highlights the necessity of OS management, given its contribution to complications like CVDs, amyloidosis, inflammation and immune dysfunction [43]. Using the same analysis, no correlations were found between patient age and any OS marker (Table 4). Our findings suggest that OS markers are primarily influenced by CKD and dialysis-related factors, rather than age. Therefore, OS management strategies should be considered equally important across all age groups of HD patients.
Using robust linear regression with an interaction term, we tested whether the effect of dialysis vintage on OS markers differed by dialysis modality. No significant differences were found among patients receiving low-flux HD, high-flux HD or pre-dilution HDF, suggesting that the increase in OS markers with dialysis vintage is a long-term cumulative phenomenon driven mainly by CKD-related factors and chronic exposure to dialysis treatment (Supplemental Table S1).
Moreover, OS markers were analyzed for potential associations with patients’ comorbidities, medication and gender (Supplemental Tables S2-S4). Τhe comorbidities examined included hypertension, CAD, CVD, PAD and diabetes, which are common in HD patients and closely related to OS. Τhe medication included statin, alfacalcidol, paricalcitol, ACEi, ARBs, CaChBl, B-blocker, Levocarnitine, Vit B supplement. No statistically significant associations were observed. However, limited statistical power from small subgroups and adherence to medication may have influenced the lack of significant findings.
Concluding, the findings of our study show that during hemodialysis LOOH increased by 50%, as well as vs dialysis vintage (Figure 2). This suggests that LOOH represent a sensitive marker for the evaluation of OS during the short time frame of an HD session, as they are formed early during lipid peroxidation. In contrast, O2•- levels were unchanged during the short period of hemodialysis. This FR is predominantly generated intracellularly, in mitochondria, and is efficiently scavenged via its dismutation by H2O co-assisted by SOD [44]. Its presence does not necessarily reflect acute oxidative damage during an HD session. Rather, its indirect impact is mostly mediated through oxidative modifications on serum lipids and proteins. Furthermore, and in accordance with an increased LOOH-associated OS tendency are the levels of the also lipid peroxidation markers PrMDA and PrTBARS vs dialysis vintage (Figure 2), although they slightly decreased (by ~10%) during one hemodialysis session. On the other hand, the effect of hemodialysis on OS-associated protein damage is unchanged both after dialysis session as well as vintage. However, as we only measured the changes of oxidative stress markers before and after a single dialysis session, we cannot assess individual variability or long-term trends.
This study investigates the effect of a single dialysis session on OS, complementing previous research on OS during maintenance dialysis. Although limited by the sample size (68 subjects) and the absence of longitudinal measurements, our findings highlight the importance of monitoring OS in dialysis patients. Future studies with larger cohorts and repeated measurements over time, potentially including supplementation with dietary antioxidants are needed to better elucidate the long-term effects of dialysis and to evaluate targeted therapeutic interventions.

Supplementary Materials

The following supporting information can be downloaded at: Preprints.org, Table S1: Associations between dialysis parameters (modality, vintage) and OS markers using robust linear regression, Table S2: Underlying medical conditions and OS markers in dialysis patients, Table S3: Medication and OS markers in dialysis patients, Table S4: Gender and OS markers in dialysis patients.

Author Contributions

AV: formal analysis, investigation, data visualization, statistical analysis, original draft writing, review, editing. EM: formal analysis, review, editing. EK: formal analysis, review, editing. PP: formal analysis, review, editing. MS: formal analysis, review, editing. MP, EP, DG: Design of clinical study, methodology, review, editing. CG: conceptualization, data curation, formal analysis, original draft writing, review, editing.

Funding

This work was financially supported by the “Andreas Mentzelopoulos Foundation” by University of Patras, Greece (PhD Personal Fellowship, Grand number 33720000).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University Hospital of Patras (No.316/04.09.2025).

Data Availability Statement

The data underlying this article will be shared on reasonable request to the corresponding author.

Acknowledgments

Τhe study was institutionally supported by the Biology Department of the University of Patras, Greece (Section of Genetics, Cell and Developmental Biology). The authors thank the staff of the Hemodialysis Unit of the University Hospital of Patras for their assistance with patient recruitment and sample collection.

Conflicts of Interest

The authors declare no financial or personal relationships that could be considered as a potential conflict of interest.

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Figure 1. Effect of a single session of hemodialysis on ROS and OS markers in 68 patients. Data are presented as mean ± standard deviation (SD). Statistical analysis showed a significant increase for LOOH levels (by 1.5-fold, or 50%), while a significant decrease was observed for PrMDA (by 1.1-fold, or ~10%) and PrTBARS (by 1.1-fold, or ~10%) levels. O2•− and PrCO levels showed no significant difference.
Figure 1. Effect of a single session of hemodialysis on ROS and OS markers in 68 patients. Data are presented as mean ± standard deviation (SD). Statistical analysis showed a significant increase for LOOH levels (by 1.5-fold, or 50%), while a significant decrease was observed for PrMDA (by 1.1-fold, or ~10%) and PrTBARS (by 1.1-fold, or ~10%) levels. O2•− and PrCO levels showed no significant difference.
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Figure 2. Spearman’s rank correlation tests between OS markers and dialysis vintage. Significant positive correlations were observed for markers such as LOOH (r= 0.458, P = 0.005; panel B), PrMDA (r=0.298, P = 0.018; panel C) and PrTBARS (r=0.272, P = 0.025; panel D). No significant correlations were found for O2•− (r=-0.126, P = 0.47; panel A) and PrCO (r=-0.112, P = 0.356; panel E).
Figure 2. Spearman’s rank correlation tests between OS markers and dialysis vintage. Significant positive correlations were observed for markers such as LOOH (r= 0.458, P = 0.005; panel B), PrMDA (r=0.298, P = 0.018; panel C) and PrTBARS (r=0.272, P = 0.025; panel D). No significant correlations were found for O2•− (r=-0.126, P = 0.47; panel A) and PrCO (r=-0.112, P = 0.356; panel E).
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Table 1. Demographic and clinical characteristics of study population.
Table 1. Demographic and clinical characteristics of study population.
HD patients
Age (years) Mean (± SD) 25 to 86
62.4 (± 14.6)
Dialysis vintage (years) Mean (± SD) 0.1 to 24.6
6.9 (± 5.5)
N
Gender
Male 48
Female 20
Medical status
Type of dialysis Low-flux HD 30
High-flux HD 17
Pre-dilution HDF 21
Medical conditions
Hypertension 32
Coronary artery disease
(CAD)		 14
Cardiovascular disease
(CVD)		 31
Peripheral artery disease
(PAD)		 21
Diabetes 24
Medication
Statin 22
Alfacalcidol 8
Paricalcitol 9
Angiotensin-converting
enzyme inhibitors (ACEi)		 3
Angiotensin receptor
blockers (ARBs)		 9
Calcium channel
blockers (CaChBl)		 19
B blockers 38
Levocarnitine 12
Cholecalciferol 17
Table 2. Comparison of three dialysis modalities based on pre-dialysis value of each OS marker a table.
Table 2. Comparison of three dialysis modalities based on pre-dialysis value of each OS marker a table.
Oxidative stress markers Modality of
dialysis		 Pre-dialysis values P value
O2•− Low-flux HD 22.03 (±9.16) 0.929
High-flux HD 23.456 (±6.8)
Pre-dilution HDF 23.09 (±11.22)
LOOH Low-flux HD 0.045 (±0.027) 0.067
High-flux HD 0.067 (±0.023)
Pre-dilution HDF 0.059 (±0.022)
PrMDA Low-flux HD 3.474 (±1.21) 0.458
High-flux HD 4.04 (±0.99)
Pre-dilution HDF 3.6 (±0.88)
PrTBARS Low-flux HD 7.643 (±2.41) 0.725
High-flux HD 8.144 (±1.33)
Pre-dilution HDF 7.547 (±2.48)
PrCO Low-flux HD 1.134 (±0.52) 0.850
High-flux HD 1.143 (±0.26)
Pre-dilution HDF 1.07 (±0.33)
Νotes: values are presented as mean ± standard deviation (SD). Abbreviations: HD, hemodialysis; HDF, hemodiafiltration; O2•−, superoxide radical; LOOH, lipid peroxides; PrMDA, protein bound-malondialdehyde; PrTBARS, protein bound-thiobarbituric acid reactive substances; PrCO, protein carbonyls.
Table 3. Comparison of three dialysis modalities based on dialysis-induced difference (Δ-value = pre-post dialysis) of each OS marker.
Table 3. Comparison of three dialysis modalities based on dialysis-induced difference (Δ-value = pre-post dialysis) of each OS marker.
Oxidative stress markers Modality of
dialysis		 Δ-value
(pre – post
dialysis)		 P value
O2•− Low-flux HD -4.59 (±2.2) 0.185
High-flux HD -2.98(±3.3)
Pre-dilution HDF -4.06 (±2.7)
LOOH Low-flux HD -0.045 (±0.031) 0.016
High-flux HD -0.008 (±0.035)
Pre-dilution HDF -0.018 (±0.029)
PrMDA Low-flux HD 0.53 (±0.66) 0.910
High-flux HD 0.68 (±0.73)
Pre-dilution HDF 0.59 (±0.99)
PrTBARS Low-flux HD 0.95 (±1.54) 0.570
High-flux HD 1.71 (±1.92)
Pre-dilution HDF 1.06 (±1.9)
PrCO Low-flux HD 0.027 (±0.29) 0.701
High-flux HD 0.054 (±0.17)
Pre-dilution HDF 0.024 (±0.27)
Notes: values are presented as mean ± standard deviation (SD). Abbreviations: HD, hemodialysis; HDF, hemodiafiltration; O2•−, superoxide radical; LOOH, lipid peroxides; PrMDA, protein bound-malondialdehyde; PrTBARS, protein bound-thiobarbituric acid reactive substances; PrCO, protein carbonyls.
Table 4. Correlation of OS markers and patients age using Spearman’s rho coefficient (r).
Table 4. Correlation of OS markers and patients age using Spearman’s rho coefficient (r).
OS markers vs Age Spearman’s rho coefficient (r) P value
O2•− -0.006 0.973
LOOH -0.121 0.483
PrMDA 0.303 0.16
PrTBARS 0.187 0.127
PrCO 0.204 0.09
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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