Assessment of AOPP, TBARS, and Inflammatory Status in Diabetic Nephropathy and Hemodialyzed Patients

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript “Assessment of AOPP, TBARS, and Inflammatory Status in Diabetic Nephropathy and Hemodialyzed Patients” presents a very interesting and actual subject in diabetic patients – the inflammation and oxidative stress. Caragea et al evaluated oxidative and inflammatory associations in DN and HD. Although the aim of the study is challenging, I have some major question regarding the methods of the study:

1. The study included 90 subjects with diabetic nephropathy and 90 hemodialyzed subjects. What was the underling disease in the dialyzed subjects? Were they diabetic or not?
2. The diabetic subject had any other complaication of diabetes?
3. I consider necessarily a larger presentation of the groups: do the subjects have microvascular/macrovascular complications of diabetes?
4. Did the diabetic subjects had CKD? It is known that in subjects with advanced CKD the oxidative stress and inflammatory stress is more intense than in subjects with stage 1 and 2 CKD?
5. The inclusion and exclusion criteria are not clearly stated.

Taking into account all these aspects, I recommend major revision.

Author Response

Thank you for reviewing our work. We appreciate your time and careful attention. Your comments were clear and practical. We addressed each point and updated the document. We clarified the goals, tightened the wording, and fixed the issues you flagged. Your feedback improved the quality. Thank you again for your help.

 

Comment 1: The study included 90 subjects with diabetic nephropathy and 90 hemodialyzed subjects. What was the underling disease in the dialyzed subjects? Were they diabetic or not?

Response 1: The 90 patients with diabetic nephropathy were not hemodialyzed. The 90 patients on hemodialysis were not diabetic.

 

Comment 2:The diabetic subject had any other complaication of diabetes?

Response 2: As we mentioned in the inclusion criteria, patients with other micro/macrovascular complications were excluded. We have introduced a flowchart, please check Figure 3 from Materials and Methods.

 

Comment 3: I consider necessarily a larger presentation of the groups: do the subjects have microvascular/macrovascular complications of diabetes?

Response 3:  Patients with other micro/macrovascular complications were excluded.

 

Comment 4: Did the diabetic subjects had CKD? It is known that in subjects with advanced CKD the oxidative stress and inflammatory stress is more intense than in subjects with stage 1 and 2 CKD?

Response 4: Yes diabetic subjects had DN, hence CKD;DN being a cause of chronic kidney disease. The patients with DN had different stages of KDIGO classification G2 to G4.

 

Comment 5: The inclusion and exclusion criteria are not clearly stated.

Response 5: We have added the flowchart for a better understanding.

Reviewer 2 Report

Comments and Suggestions for Authors

This study employed a cross-sectional design to systematically evaluate the association between oxidative stress markers (AOPP, TBARS) and systemic inflammation indices (such as AISI, SII, SIRI) in patients with diabetic nephropathy (DN) and those undergoing hemodialysis (HD). The research enrolled 180 participants (90 DN and 90 HD patients), utilizing ELISA technology to quantify serum markers and calculating inflammation indices from routine blood test data. In the HD group, all correlations were attenuated due to interference from dialysis-related factors. The authors propose that AOPP may serve as a stable marker coupling oxidative stress and inflammation in DN, whereas TBARS better reflects short-term lipid peroxidation.​

The simultaneous assessment of protein oxidation (AOPP) and lipid peroxidation (TBARS), along with their correlation with multiple inflammatory indices (e.g., SII, NLR, MLR), provides a multidimensional perspective on the oxidative-inflammatory axis.

some Limitations Requiring Improvement：​​

1.Although the study identified significant associations between AOPP and inflammatory indices, the inherent nature of the cross-sectional design prevents determination of causal relationships between oxidative stress and inflammation. We recommend supplementing with longitudinal cohort data or interventional studies (e.g., antioxidant interventions) to verify temporal sequences.

2.All participants were recruited from a single medical center (Craiova, Romania), potentially introducing selection bias. The absence of comparisons across different geographical regions, ethnicities, or healthcare systems restricts the external validity and generalizability of the conclusions.

3.The partial correlation analyses adjusted only for age, sex, and serum albumin, while potentially important confounders were not considered. These include diabetes duration, glycemic control levels (HbA1c), dialysis membrane type, dialysis vintage, antihypertensive medications (e.g., ACEIs/ARBs), or antioxidant use. This omission may compromise the validity of the observed associations.

Author Response

Thank you for reviewing our manuscript. We value the time and care you put into your comments. Your suggestions strengthened our analysis and clarified the methods. We revised the text and tables to address each point. We appreciate your help and clear guidance.

 

Comment 1: Although the study identified significant associations between AOPP and inflammatory indices, the inherent nature of the cross-sectional design prevents determination of causal relationships between oxidative stress and inflammation. We recommend supplementing with longitudinal cohort data or interventional studies (e.g., antioxidant interventions) to verify temporal sequences.

Response 1:  We have now extended the analysis. Please check the Results section: 

2.4. Principal component analysis of inflammatory indices in hemodialysis and diabetic nephropathy cohorts

2.5. Multiple linear regressions

2.5.1. Multiple linear regressions of HD cohort

2.5.1.1. Multiple linear regressions of HD cohort for AOPP

2.5.1.2. Multiple linear regressions of HD cohort for TBARS

2.5.2. Multiple linear regressions of T2DM-DN cohort

2.5.2.1. Multiple linear regressions of T2DM-DN cohort for AOPP

2.5.2.2. Multiple linear regressions of T2DM-DN cohort for TBARS

 

Comment 2: All participants were recruited from a single medical center (Craiova, Romania), potentially introducing selection bias. The absence of comparisons across different geographical regions, ethnicities, or healthcare systems restricts the external validity and generalizability of the conclusions.

Response 2: Thank you for this comment. We agree that local recruitment can introduce selection bias and limit generalizability. Recruitment occurred in two Craiova services, the University Hospital of Craiova and the Filantropia Municipal Clinical Hospital, both within the same metropolitan area. This work is part of a doctoral study at the University of Medicine and Pharmacy of Craiova. The single city setting ensured protocol feasibility, close oversight, and uniform laboratory workflows within available resources. We state the single-center limitation in the Limitations section.

 

Comment 3: The partial correlation analyses adjusted only for age, sex, and serum albumin, while potentially important confounders were not considered. These include diabetes duration, glycemic control levels (HbA1c), dialysis membrane type, dialysis vintage, antihypertensive medications (e.g., ACEIs/ARBs), or antioxidant use. This omission may compromise the validity of the observed associations.

Response 3: 

We appreciate this valuable observation. In the revised version, we have added relevant information regarding these variables. Most of the hemodialysis patients in our cohort (approximately 85%) were treated with synthetic high-flux polysulfone membranes, known for their superior biocompatibility and reduced inflammatory activation compared with cellulosic membranes. The mean dialysis vintage was 48 ± 22 months, with no significant differences between subgroups. We have also included in the Discussion section a note acknowledging that both dialysis membrane type and dialysis vintage may act as potential confounders influencing oxidative stress and inflammatory markers. Future studies incorporating these variables into multivariate models may provide a more accurate interpretation of these associations.

Another factor to be considered is the influence of dialysis membrane type and dialysis vintage on oxidative and inflammatory markers. In our cohort, most hemodialysis patients (approximately 85%) were treated with synthetic high-flux polysulfone membranes, which are known for superior biocompatibility and lower inflammatory activation compared with cellulosic membranes.
The mean dialysis vintage was 48 ± 22 months, showing no significant subgroup differences. However, these parameters may act as potential confounders that could modulate oxidative and inflammatory responses. Including these factors in future regression models could help refine the interpretation of the observed associations.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I recommend acceptance for publication.

Reviewer 2 Report

Comments and Suggestions for Authors

The author has revised the article according to the reviewers' suggestions and it can be accepted.