Abstract
Background
The relationship between high-density lipoprotein cholesterol (HDL-C) concentrations and the risk of peritoneal dialysis-related peritonitis (PDRP) remains unclear. We aimed to examine the association between HDL-C concentrations and the risk of new-onset PDRP in patients undergoing maintenance peritoneal dialysis (PD), while investigating potential modifying factors that may influence this relationship.
Methods
This retrospective cohort study included 512 eligible patients with maintenance PD recruited from January 1, 2010 to December 31, 2020 at the Peritoneal Dialysis Center of Nanfang Hospital. The study outcome was the new-onset PDRP. Cox proportional hazards models were used to examine the association between baseline HDL-C and new-onset PDRP.
Results
During a median follow-up of 45 months, 156 incident peritonitis cases (30.5%) were recorded. There was a significantly inverse association between HDL-C concentrations and the risk of new-onset PDRP (per SD increment, adjusted HR = 0.67, 95%CI: 0.51, 0.88). Compared with patients with low HDL-C ( < 40 mg/dL), those with normal (40-60 mg/dL) and high (≥60 mg/dL) HDL-C concentrations had a 35% (adjusted HR = 0.65, 95%CI: 0.43, 0.98) and 60% (adjusted HR = 0.40, 95%CI: 0.18, 0.87) lower risk of new-onset PDRP, respectively. The inverse association between elevated HDL-C concentrations and reduced PDRP risk persisted consistently across all examined subgroups, including those stratified by age, sex, BMI, diabetes status, cardiovascular disease, dialysis vintage, total weekly Kt/V, and C-reactive protein concentrations (all P-interaction > 0.05)
Conclusion
Higher HDL-C concentrations were independently associated with reduced PDRP risk in maintenance PD patients, suggesting HDL-C may serve as a potential protective marker against peritonitis in this population.
Clinical trial number
Not applicable.
Supplementary information
The online version contains supplementary material available at 10.1186/s12882-025-04598-y.
Keywords: Maintenance peritoneal dialysis, Peritonitis, High-density lipoprotein cholesterol lipid, Cohort study
Introduction
The global adoption of peritoneal dialysis (PD) has increased significantly in recent decades, with particularly rapid expansion in China, Thailand, and the United States [1]. This growth has heightened the importance of optimizing PD quality to ensure sustainable patient outcomes. Peritonitis persists as the leading cause of PD technique failure worldwide [2], underscoring the critical need to identify modifiable risk factors for peritonitis prevention.
Patients with advanced chronic kidney disease (CKD) and end-stage kidney disease (ESRD) commonly exhibit dyslipidemia [3, 4]. Recent advances in lipid biology have revealed novel roles for lipoproteins in immune regulation and infection defense [5–7]. Of particular interest, high-density lipoprotein cholesterol (HDL-C) has demonstrated potentially protective functions in inflammatory and infectious processes through multiple mechanisms [8, 9].
Despite these biological insights, the relationship between HDL-C concentrations and the risk of peritoneal dialysis-related peritonitis (PDRP) remains insufficiently investigated. To date, only a limited number of studies have explored this association in PD patients. Szeto et al. [10] observed that the combination of low HDL-C ( < 1 mmol/L) and diabetes mellitus increased PDRP risk; however, their multivariate regression model did not directly evaluate the association between HDL-C concentrations and peritonitis risk. Similarly, Wang et al. [11] reported no significant association between HDL-C concentrations and peritonitis risk, but their analysis was limited to assessing HDL-C as a continuous variable for linear association, without examining potential differences in PDRP risk across clinically relevant HDL-C strata. Notably, these studies [10, 11] did not account for several important confounding variables, including C-reactive protein (CRP) concentrations, total weekly Kt/V, and total weekly creatinine clearance (CrCl), which may substantially influence the results. Consequently, the relationship between HDL-C concentrations and PDRP risk in PD patients remains unclear.
To address these knowledge gaps and elucidate the potential clinical significance of HDL-C, we conducted a comprehensive investigation examining the association between HDL-C concentrations and new-onset PDRP risk in maintenance PD patients.
Methods
Study design and population
This retrospective single-center cohort study included 672 patients who initiated PD at the Peritoneal Dialysis Center of Nanfang Hospital, China, between January 1, 2010 and December 31, 2020. The study protocol was approved by the Research Ethics Committee of Nanfang Hospital (NFEC-2010–78). Informed consent was waived for this retrospective study by the institutional review board.
We excluded patients with: (1) PD duration < 3 months; (2) missing baseline data on dialysis regimens or lipid profiles; (3) history of kidney transplantation; (4) > 1 year of hemodialysis history; or (5) peritonitis within 30 days post-PD catheter insertion. After these exclusions, 512 patients were included in the final analysis (Fig. S1). Included and excluded subjects had comparable baseline characteristics (Table S1).
Data collection and clinical definitions
Baseline demographic and clinical data were collected by trained nursing staff within the first three months after PD initiation, encompassing age, sex, anthropometric measurements (height and weight), medication history (including lipid-lowering drugs, glucocorticoids and immunosuppressants use), self-reported medical conditions (including diabetes and cardiovascular disease [CVD]), and comprehensive laboratory results. All laboratory analyses—including routine blood tests, biochemical profiles, renal/liver function tests, and lipid panels—were performed at Nanfang Hospital’s central laboratory following standardized operating procedures. The first three months of peritoneal dialysis represent a critical adaptation period characterized by physiological adjustments and potential metabolic instability. To account for natural fluctuations in lipid levels during this phase and to obtain a more stable baseline measurement, all laboratory values—including HDL-C—were calculated as the mean of all available determinations obtained during the initial three months following PD commencement.
PD-specific assessments were conducted per established protocols [12, 13], including total weekly CrCl, weekly Kt/V, and peritoneal equilibration test (PET) results. Total weekly Kt/V was calculated by integrating urea concentrations in the 24-hour dialysate and urine, their respective volumes, and serum urea levels. Total weekly CrCl was determined by combining dialysate and urine creatinine concentrations, urine output, and residual renal function [12]. PET was performed to classify peritoneal transport function into four types (low, low-average, high-average, and high) based on the 4-hour dialysate-to-plasma creatinine ratio (D/Pcr) [13]. CVD was defined as physician-diagnosed heart failure, myocardial infarction, or cerebrovascular accident. Diabetes was diagnosed by clinicians based on the patient’s medical history, medication use, fasting blood glucose, and/or postprandial blood glucose levels. Body mass index (BMI) was calculated by dividing weight (kg) by square of standing height (m).
The study’s principal exposure variable was baseline serum HDL-C concentration, stratified into three clinically relevant categories based on established cut points [14]: low ( < 40 mg/dL), normal (40–60 mg/dL), and high (≥60 mg/dL). This classification enabled examination of potential non-linear associations with clinical outcomes while maintaining clinical interpretability.
Study outcomes and follow-up
The primary outcome was new-onset PDRP, diagnosed according to 2017 ISPD guidelines [15] when meeting ≥2 criteria: (1) abdominal pain with/without cloudy effluent or fever; (2) effluent leukocyte count ≥100 × 106 cells/L ( > 50% polymorphonuclear cells); or (3) positive effluent Gram stain/culture. Pathogen distribution in participants with PDRP stratified by HDL-C concentrations was presented in Fig. S2. To avoid confounding by procedural factors, we excluded catheter insertion-related peritonitis (occurring ≤30 days post-insertion).
Patients were routinely evaluated every 2 months (first year) and 5 months (subsequently) until December 31, 2023. Follow-up terminated at PDRP onset, death, or PD discontinuation. Patients transitioning to hemodialysis, receiving transplants, transferring centers, or lost to follow-up were censored at their last documented clinical encounter.
Statistical analysis
Baseline characteristics were presented as mean (standard deviation, SD) or median (interquartile range [IQR]) for continuous variables and as frequencies (percentages) for categorical variables. Differences across HDL-C categories were assessed using ANOVA for continuous variables and chi-square (χ2) tests for categorical variables.
We initially examined the dose-response relationship between HDL-C concentrations and PDRP risk using restricted cubic splines (RCS). Kaplan-Meier curves were generated to compare cumulative PDRP incidence among HDL-C categories. Multivariable Cox regression models were constructed to estimate hazard ratios (HRs) with 95% confidence intervals (CIs): Model 1 adjusted for age, sex, and BMI; Model 2 additionally adjusted diabetes history, CVD, medication use of lipid-lowering drugs, glucocorticoids and immunosuppressants, serum albumin, CRP, intact parathyroid hormone (iPTH), potassium, lipid profiles (triglycerides, total cholesterol, LDL-C), and dialysis adequacy parameters (total weekly Kt/V and CrCl). Missing data for normally distributed variables (e.g., potassium, albumin, BMI) were imputed using mean values, whereas missing data for non-normally distributed variables (e.g., CRP, iPTH, weekly CrCl, and Kt/V) were imputed using median values. Baseline characteristics of participants with complete-case were presented in Table S2.
Subgroup analyses evaluated effect modification by age ( < 60 vs. ≥60 years), sex, BMI ( < 24 vs. ≥24 kg/m2), diabetes status, CVD history, dialysis vintage ( < 36 vs. ≥36 months), Kt/V ( < 2.2 vs. ≥2.2), and CRP concentrations ( < 3.0 vs. ≥3.0 mg/L), with interaction terms testing for heterogeneity.
We performed four sensitivity analyses to verify the robustness of our findings: (1) excluding patients with pre-existing CVD; (2) repeating analyses using complete-case data without imputation; (3) implementing competing risk regression (Fine-Gray subdistribution models) with death, kidney transplantation, or transition to hemodialysis as competing events; and (4) applying multiple imputation techniques for missing data.
A two-tailed p < 0.05 was considered to be statistically significant. R software (version 4.1.3, http://www.R-project.org) was used for all statistical analyses.
Results
Baseline characteristics of study participants
The final cohort comprised 512 patients with a mean age of 43.1 years (SD 14.1), including 216 (42.2%) female participants, as detailed in Fig. S1.
Baseline demographic and clinical characteristics are presented in Table 1. Compared to patients with low HDL-C concentrations, those with high HDL-C concentrations were more likely to female, had lower BMI, higher use of lipid-lowering drugs, elevated concentrations of total cholesterol and LDL-C, greater total weekly Kt/V and total weekly CrCl, as well as had longer dialysis vintage. Included subjects and subjects with complete-case had comparable baseline characteristics (Table 1 and Table S2).
Table 1.
Baseline characteristics of study patients*
| Characteristics | Overall | HDL-C concentrations | P value | ||
|---|---|---|---|---|---|
| <40mg/dL | 40-60mg/dL | ≥60mg/dL | |||
| N | 512 | 210 | 244 | 58 | |
| Female, n (%) | 216 (42.2) | 59 (28.1) | 115 (47.1) | 42 (72.4) | < 0.001 |
| Age, y | 43.1 (14.1) | 42.5 (14.5) | 43.3 (14.0) | 44.3 (13.1) | 0.657 |
| Body mass index, kg/m2 | 22.3 (3.2) | 23.3 (3.3) | 21.6 (3.1) | 21.2 (2.7) | < 0.001 |
| Dialysis vintage, month | 45.0 (22.0,67.2) | 41.0 (18.2,60.8) | 45.0 (23.8,67.0) | 60.5 (41.5,82.2) | < 0.001 |
| Total weekly Kt/V | 2.2 (1.9,2.7) | 2.1 (1.8,2.5) | 2.3 (1.9,2.7) | 2.5 (2.1,3.0) | < 0.001 |
| Total weekly creatinine clearance, L/1.73 m2 | 70.2 (56.4,93.4) | 68.0 (54.0,94.2) | 70.8 (57.3,91.0) | 77.0 (58.2,112.6) | 0.141 |
| Peritoneal equilibration test, n (%) | 0.581 | ||||
| High | 73 (16.5) | 25 (14.1) | 40 (18.8) | 8 (15.4) | |
| High average | 222 (50.2) | 89 (50.3) | 103 (48.4) | 30 (57.7) | |
| Low average | 132 (29.9) | 55 (31.1) | 63 (29.6) | 14 (26.9) | |
| low | 15 (3.4) | 8 (4.5) | 7 (3.3) | 0 (0.0) | |
| Laboratory results | |||||
| Triglyceride, mg/dL | 124.3(94.0,162.0) | 135.4(111.6,177.3) | 117.0(86.7,152.5) | 107.1(87.0,137.5) | < 0.001 |
| Cholesterol, mg/dL | 182.8 (42.1) | 163.8 (33.0) | 191.6 (40.6) | 214.3 (46.3) | < 0.001 |
| Low-density lipoprotein cholesterol, mg/dL | 113.3 (30.8) | 104.0 (25.9) | 119.2 (32.8) | 122.1 (30.1) | < 0.001 |
| C-reactive protein, mg/L | 3.0 (1.0,8.6) | 4.4 (1.9,10.9) | 2.0 (0.7,7.2) | 1.7 (0.5,5.8) | < 0.001 |
| Albumin, g/L | 35.4 (4.4) | 35.7 (4.5) | 35.2 (4.2) | 34.8 (4.6) | 0.281 |
| Potassium, mmol/L | 4.2 (0.5) | 4.2 (0.5) | 4.2 (0.6) | 4.1 (0.5) | 0.364 |
| Intact parathyroid hormone, pg/mL | 310.4(205.8,443.0) | 325.3(214.9,458.0) | 309.7(207.0,434.4) | 264.5(178.2,416.3) | 0.302 |
| History of disease, n (%) | |||||
| Diabetes | 96 (18.8) | 44 (21.0) | 43 (17.6) | 9 (15.5) | 0.530 |
| Cardiovascular disease | 73 (14.3) | 31 (14.8) | 37 (15.2) | 5 (8.6) | 0.424 |
| Medication use, n (%) | |||||
| Lipid-lowering drugs | 187 (36.5) | 77 (36.7) | 84 (34.4) | 26 (44.8) | 0.335 |
| Glucocorticoids | 18 (3.5) | 5 (2.4) | 8 (3.3) | 5 (8.6) | 0.071 |
| Immunosuppressants | 7 (1.4) | 2 (1.0) | 5 (2.0) | 0 (0.0) | 0.384 |
*Variables were presented as mean (SD) for normally distributed continuous variables and medians (IQR) for non-normally distributed continuous variables, and as proportions for categorical variables, accordingly
Associations between HDL-C concentrations and the risk of new-onset PDRP
During the median follow-up of 45.0 months (IQR 22.0–67.2), we observed the following outcomes among the 512 PD patients: 156 (30.5%) developed new-onset PDRP, 107 (20.9%) died, 104 (20.3%) transitioned to hemodialysis, 150 (29.3%) underwent renal transplantation, and 21 (4.1%) were lost to follow-up (Fig. S1). In the group with HDL-C > 60 mg/dL, Gram-negative bacteria accounted for a significantly higher proportion of infections (33%) compared to both the < 40 mg/dL and 40–60 mg/dL groups (20% each). (Fig. S2).
The analysis revealed a significant inverse relationship between HDL-C concentrations and PDRP risk (per SD increment, adjusted HR = 0.67, 95% CI: 0.51–0.88) (Fig. 1). Kaplan-Meier analysis demonstrated progressively lower cumulative PDRP incidence across increasing HDL-C categories ( < 40, 40–60, and ≥60 mg/dL; log-rank p = 0.048) (Fig. 2). Compared to the low HDL-C group ( < 40 mg/dL), patients with normal (40–60 mg/dL) and high (≥60 mg/dL) concentrations showed 35% (adjusted HR = 0.65, 95% CI: 0.43–0.98) and 60% (adjusted HR = 0.40, 95% CI: 0.18–0.87) reduced PDRP risk, respectively (Table 2).
Fig. 1.
The restricted cubic splines (RCS) curve of the association between HDL-C and the risk of new-onset peritoneal dialysis related peritonitis (PDRP). Adjusted for age, sex, body mass index, history of diabetes and cardiovascular disease, medication use of lipid-lowering drugs, glucocorticoids and immunosuppressants, serum albumin, C-reactive protein, intact parathyroid hormone, potassium, triglyceride, total cholesterol, low-density lipoprotein cholesterol, total weekly Kt/V and total weekly creatinine clearance at baseline
Fig. 2.
Kaplan-Meier curve of cumulative incidence of new-onset peritoneal dialysis related peritonitis (PDRP)
Table 2.
Association between serum HDL-C concentrations and the risk of new-onset peritoneal dialysis related peritonitis (PDRP)
| HDL-C, mg/dL | N | Case (%) | Model 1 | Model 2 | ||
|---|---|---|---|---|---|---|
| HR (95% CI) | P value | HR (95% CI) | P value | |||
| Per SD increment | 512 | 156(30.5) | 0.82 (0.69, 0.97) | 0.020 | 0.67 (0.51, 0.88) | 0.004 |
| Categories | ||||||
| < 40 | 210 | 71(33.8) | Ref | Ref | ||
| 40–60 | 244 | 70(28.7) | 0.74 (0.52, 1.04) | 0.080 | 0.65 (0.43, 0.98) | 0.039 |
| ≥60 | 58 | 15(25.9) | 0.52 (0.29, 0.93) | 0.026 | 0.40 (0.18, 0.87) | 0.021 |
| P for trend | 0.014 | 0.012 | ||||
Model 1: adjusted for age, sex, body mass index
Model 2: adjusted for age, sex, body mass index, history of diabetes and cardiovascular disease, medication use of lipid-lowering drugs, glucocorticoids and immunosuppressants, serum albumin, C-reactive protein, intact parathyroid hormone, potassium, triglyceride, total cholesterol, low-density lipoprotein cholesterol, total weekly Kt/V and total weekly creatinine clearance at baseline
Results were consistent across sensitivity analyses: (1) excluding participants with CVD history (Table S3), (2) performing data analysis without imputation (Table S4), (3) competing risk analysis accounting for competing risks (death, renal transplantation, transition to hemodialysis, and loss to follow-up) using Fine-Gray subdistribution models (Table S5), (4) applying multiple imputation for missing values (Table S6).
Stratified analyses
None of the variables, including age ( < 60 vs. ≥60 years), sex (female vs. male), BMI ( < 24 vs. ≥24 kg/m2), diabetes (yes vs. no), CVD (yes vs. no), dialysis vintage ( < 36 vs. ≥36 months), total weekly Kt/V ( < 2.2 vs. ≥2.2), CRP ( < 3.0 vs. ≥3.0 mg/L) significantly modify the association between HDL-C concentrations and the risk of new-onset PDRP (All P-interactions > 0.05) (Fig. 3).
Fig. 3.
Subgroup analysis on the association between HDL-C and the risk of new-onset peritoneal dialysis related peritonitis (PDRP). Adjusted for age, sex, body mass index, history of diabetes and cardiovascular disease, medication use of lipid-lowering drugs, glucocorticoids and immunosuppressants, serum albumin, C-reactive protein, intact parathyroid hormone, potassium, triglyceride, total cholesterol, low-density lipoprotein cholesterol, total weekly Kt/V and total weekly creatinine clearance at baseline
Discussion
Our study reveals a significant inverse association between HDL-C concentrations and the risk of new-onset PDRP. Patients with high HDL-C concentrations (≥60 mg/dL) showed a remarkable 60% reduction in PDRP incidence compared to those with low HDL-C concentrations ( < 40 mg/dL).
The current evidence regarding HDL-C and PDRP risk remains inconclusive. While one recent study reported an increased PDRP risk in diabetic patients with low HDL-C concentrations [10], its multivariate analysis failed to evaluate the independent effect of HDL-C. Another study found no significant association but only examined HDL-C as a continuous variable, overlooking potential risk differences across clinically meaningful HDL-C strata [11]. Importantly, neither study [10, 11] accounted for key confounding factors such as CRP concentrations, total weekly Kt/V, or CrCl, which could substantially affect the outcomes.
Our study provides robust evidence addressing current knowledge gaps in this field. We identified a significant inverse association between HDL-C concentrations and new-onset PDRP risk, demonstrating that patients with normal or elevated HDL-C concentrations had substantially lower risk compared to those with low HDL-C concentrations. This association is strongly supported by multiple established biological mechanisms involving HDLs immunomodulatory functions. Although the cumulative incidence of PDRP among the three HDL-C subgroups is modest (log-rank p = 0.048), the finding carries substantial clinical importance, as it demonstrates a clear dose-response relationship where higher HDL-C levels (particularly ≥60 mg/dL) correspond to dramatically reduced PDRP risk—with 60 and 35% risk reductions in the high and normal groups, respectively. This suggests that HDL-C may serve as a modifiable marker for risk stratification in peritoneal dialysis patients, highlighting its potential clinical relevance in identifying individuals at elevated risk. However, further research is required to validate its utility in guiding clinical risk assessment, and well-designed intervention studies would be necessary to explore any potential therapeutic applications in this population.
The protective effects of HDL-C are mediated through several distinct pathways. HDL binds pathogen-associated molecular patterns (PAMPs) including LPS (Gram-negative bacteria) and LTA (Gram-positive bacteria), blocking their interaction with Toll-like receptors 4 (TLR4) that initiate inflammatory cascades [16–18]. Additionally, HDL facilitates endotoxin clearance via hepatic SR-BI receptors [19, 20], while its core component apolipoprotein A-I (ApoA-I) mitigates endotoxemia-induced organ damage and monocyte activation [21]. Emerging research further reveals HDLs dual role in infection defense: while promoting cholesterol efflux induces pro-inflammatory macrophage responses, HDL simultaneously enhances bacterial phagocytosis. Animal models with elevated HDL demonstrate superior bacterial clearance capacity [22], indicating HDL protects against infections through both PAMP neutralization and macrophage function enhancement. Within the local peritoneal environment, ApoA-I, the major structural component of HDL-C, plays a critical protective role. It contributes to the maintenance of peritoneal membrane integrity and ultrafiltration capacity in PD patients by suppressing local inflammation, oxidative stress, and epithelial-mesenchymal transition (EMT) [23]. Conversely, reduced ApoA-I levels may compromise peritoneal host defense mechanisms, thereby elevating the risk of peritonitis. Additionally, dyslipidemia can promote peritoneal injury through multiple complementary pathways, such as intracellular lipid accumulation and lipotoxicity, interaction with the renin-angiotensin-aldosterone system (RAAS), endothelial dysfunction, and interplay with high-glucose conditions in PD solution and its metabolites—including advanced glycation end-products (AGEs) and glucose degradation products (GDPs). Together, these processes foster a pro-inflammatory and pro-fibrotic peritoneal microenvironment [24]. This elaborated mechanistic framework is further corroborated by recent evidence demonstrating the anti-infective capacity of HDL constituents in peritonitis [25].
Notably, although our study did not identify a significant modifying effect of CRP, we observed a stronger inverse association between HDL-C and PDRP risk in participants with elevated CRP (≥3.0 mg/L; HR 0.75, 95% CI 0.55–1.03) compared to those with lower CRP ( < 3.0 mg/L; HR 0.55, 95% CI 0.38–0.80). These findings further suggest a potential role of systemic inflammation on HDL-C’s protective effects, warranting further investigation into the underlying mechanisms.
Several study limitations merit consideration. First, the observational nature of our study precludes definitive causal inferences regarding the HDL-C-PDRP association. Second, while we accounted for numerous potential confounders, residual confounding from unmeasured variables (e.g., nutritional status, immunosuppressive medications, or genetic factors) remains possible. Third, the generalizability of our findings may be limited by the relatively young age of our cohort (mean age 43 years). Further investigation in older and more ethnically diverse populations is warranted to confirm and extend our results. Fourth, as the study population was drawn from a single center in southern China, the findings may not be generalizable to populations with different demographics, dietary habits, peritoneal dialysis practices, or genetic backgrounds. Fifth, an important limitation of our study is the reliance on a single baseline measurement of lipid levels, including HDL-C, can fluctuate during long-term dialysis and in response to intercurrent illnesses or changes in nutritional status. These temporal variations could potentially attenuate the observed associations, meaning our results might underestimate the true strength of the relationship between persistently low HDL-C levels and PDRP risk. Future studies incorporating serial HDL-C measurements would be valuable to better characterize this dynamic relationship.
Conclusions
In this retrospective single-center study, we observed a significant inverse association between serum HDL-C levels and the risk of new-onset PDRP. However, our findings must be interpreted as hypothesis-generating due to the inherent limitations of the observational design, and they do not establish causality. Future large-scale, multicenter prospective studies are warranted to confirm this association and to explore its underlying mechanisms. If validated, maintaining optimal HDL-C levels may represent a potential preventive strategy against PDRP in patients undergoing peritoneal dialysis.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We thank all the doctors and nurses at the peritoneal dialysis centers. We thank all patients with PD who participated and provided data for the study.
Abbreviations
- HDL-C
High-density lipoprotein cholesterol
- PD
Peritoneal dialysis
- PDRP
Peritoneal dialysis-related peritonitis
- CKD
Chronic kidney disease
- ESRD
End-stage kidney disease
- CVD
Cardiovascular disease
- Kt/V
Urea clearance index
- CrCl
Creatinine clearance
- PET
Peritoneal equilibration test
- D/Pcr
Dialysate-to-plasma creatinine ratio
- BMI
Body mass index
- CRP
C-reactive protein
- Ipth
Intact parathyroid hormone
- PAMPs
Pathogen-associated molecular patterns
- LPS
Lipopolysaccharide
- LTA
Lipoteichoic acid
- TLR4
Toll-like receptors 4
- SRBI
Scavenger Receptor Class B Type I
- ApoA-I
Apolipoprotein A-I
- EMT
Epithelial-mesenchymal transition
- RAAS
Renin-angiotensin-aldosterone system
- AGEs
Advanced glycation end-products
- GDPs
Glucose degradation products
Author contributions
Concept and design: Jinsheng Mai, Yuanyuan Zhang, Xianhui Qin and Jianping Jiang; Acquisition, analysis, or interpretation of data: All authors; Statistical analysis: Jinsheng Mai and Yiting Wu; Obtained funding: Yuanyuan Zhang, Jianping Jiang and Xianhui Qin; Supervision: Xianhui Qin, Yuanyuan Zhang and Jianping Jiang; Writing-original draft: Jinsheng Mai and Yuanyuan Zhang; Writing-review & editing: All authors.
Funding
This study was supported by the National Natural Science Foundation of China (82070790, 82570914), President Foundation of Nanfang Hospital, Southern Medical University (2024B029), National Key Research and Development Program of China (2022YFC2009600, 2022YFC2009605) and the Development and Reform Commission of Shenzhen Municipality (XMHT20220104055).
Data availability
The data are available from the corresponding author on reasonable request.
Declarations
Ethical approval
The study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee of Nanfang Hospital, Guangzhou, China (ethics number NFEC-2010-78). Informed consent was waived for this retrospective study by the institutional review board.
Consent for publication
All the authors approved the publication.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Yuanyuan Zhang, Email: doctoryyzhang@126.com.
Jianping Jiang, Email: jiangjp_nfyy@126.com.
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Data Availability Statement
The data are available from the corresponding author on reasonable request.