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Article

Higher Serum Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio Is Associated with Increased Mortality among Incident Peritoneal Dialysis Patients

by
Hee-Won Noh
1,
Yena Jeon
2,
Ji-Hye Kim
1,
Ga-Young Lee
1,
Soo-Jee Jeon
1,
Kyu-Yeun Kim
1,
Jeong-Hoon Lim
1,
Hee-Yeon Jung
1,
Ji-Young Choi
1,
Sun-Hee Park
1,
Chan-Duck Kim
1,
Yong-Lim Kim
1,3,* and
Jang-Hee Cho
1,*
1
Division of Nephrology, Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu 41944, Korea
2
Department of Statistics, Kyungpook National University, Daegu 41566, Korea
3
Cell and Matrix Research Institute, Kyungpook National University, Daegu 41944, Korea
*
Authors to whom correspondence should be addressed.
Nutrients 2022, 14(1), 144; https://doi.org/10.3390/nu14010144
Submission received: 7 November 2021 / Revised: 20 December 2021 / Accepted: 24 December 2021 / Published: 29 December 2021
(This article belongs to the Special Issue Eating Habits, Nutrition and Chronic Kidney Disease)
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Abstract

:
This study evaluated the association of the serum total cholesterol to high-density lipoprotein cholesterol ratio (TC/HDL-C) with mortality in incident peritoneal dialysis (PD) patients. We performed a multi-center, prospective cohort study of 630 incident PD patients from 2008 to 2015 in Korea. Participants were stratified into quintiles according to baseline TC, HDL-C, LDL-C and TC/HDL-C. The association between mortality and each lipid profile was evaluated using multivariate Cox regression analysis. During a median follow-up period of 70.3 ± 25.2 months, 185 deaths were recorded. The highest TC/HDL-C group had the highest body mass index, percentage of diabetes and serum albumin level. Multivariate analysis demonstrated that the highest quintile of TC/HDL-C was associated with increased risk of all-cause mortality (hazard ratio 1.69, 95% confidence interval 1.04–2.76; p = 0.036), whereas TC, HDL-C and LDL-C were not associated with mortality. Linear regression analysis showed a positive correlation between TC/HDL-C and body mass index. Increased serum TC/HDL-C was an independent risk factor for mortality in the subgroup of old age, female, cardiovascular disease and low HDL-C. The single lipid marker of TC or HDL-C was not able to predict mortality in PD patients. However, increased serum TC/HDL-C was independently associated with all-cause mortality in PD patients.

1. Introduction

The number of patients with end-stage renal disease (ESRD) requiring maintenance dialysis is increasing worldwide [1]. Although gradual improvements in dialysis treatment have been achieved, patients with ESRD have higher mortality rates when compared to patients with malignancy [1]. The high prevalence of cardiovascular disease (CVD) is considered a major contributor to early mortality in ESRD patients [1,2].
Hypercholesterolemia is a conventional risk factor of CVD in the general population. Both elevated serum total cholesterol (TC) and reduced high-density lipoprotein cholesterol (HDL-C) are associated with CVD. Recent studies show non-traditional lipid profiles, such as the TC to HDL-C ratio (TC/HDL-C), as independent lipoprotein predictors of the development of CVD. High TC/HDL-C is associated with increased risk of left ventricular hypertrophy, coronary heart disease, and ischemic stroke independently of plasma low-density lipoprotein cholesterol (LDL-C) levels [3,4,5,6].
A number of studies reported that a high TC/HDL-C ratio is associated with all-cause and cardiovascular mortality in incident hemodialysis (HD) patients. In contrast to the general population, a cohort study found that a low TC/HDL-C ratio was associated with higher mortality in HD patients [7]. A further study found that decreases in non-HDL-C and non-HDL-C/HDL-C contributed to increased all-cause and cardiovascular mortality in patients undergoing incident hemodialysis [8].
However, there is a lack of studies evaluating the association between non-traditional lipid profiles and CVD risk in peritoneal dialysis (PD) patients. PD patients typically have elevated levels of serum TC and LDL-C, whereas HD patients have normal or low levels of serum TC and LDL-C [9]. As PD patients have different lipid profiles compared to HD patients, non-traditional lipid profiles may have a different association with mortality in PD patients. In addition, a strategy to reduce LDL-C demonstrated no beneficial effect on CVD in dialysis patients [10]. Therefore, it may not be appropriate to evaluate the risk of CVD or mortality using only traditional lipid profiles in PD patients.
In the present study, we investigated the relationship between TC/HDL-C and mortality among incident PD patients. We evaluated the predictive value of TC/HDL-C in detecting the risk of CVD compared with individual traditional lipid profiles alone.

2. Materials and Methods

2.1. Study Population and Data Sources

A total of 630 incident PD patients were enrolled from 2008 to 2015 in a multi-center prospective cohort study conducted in Korea. All enrolled patients were aged 19 years or older who had received at least three consecutive months of PD therapy. Baseline serum TC and HDL-C levels were recorded. Patients who died within three months of dialysis initiation or without recorded baseline TC and HDL-C levels were excluded from the analysis.
This study was conducted in compliance with the ethical principles of the Helsinki declaration and approved by the institutional review board of the Kyungpook National University hospital. Written informed consent was obtained from all participants.
Patients were followed up until death, conversion to HD, or kidney transplantation. Baseline data were collected at the beginning of PD, including age at initiation of dialysis, sex, body mass index, primary renal disease, comorbidity at the initiation of dialysis (congestive heart failure, coronary artery disease, peripheral vascular disease, arrhythmia, cerebrovascular disease, chronic lung disease, peptic ulcer disease, chronic liver disease, connective tissue disease, and malignancy) and lab data at the initiation of dialysis (hemoglobin, blood urea nitrogen [BUN], creatinine, albumin, calcium, phosphorus, urine volume). Modified Charlson comorbidity index values were calculated [11].

2.2. Primary and Secondary Outcomes

Primary and secondary outcomes were all-cause and CVD mortality. CVD included coronary artery disease (angioplasty, coronary artery bypass grafting, and unstable angina), congestive heart failure (typical symptoms combined with systolic or diastolic dysfunction by echocardiography), cerebrovascular disease (ischemia or hemorrhagic infarct confirmed both by typical clinical symptoms and imaging study), and peripheral artery disease (revascularization or amputation).

2.3. Statistical Analyses

A preliminary analysis revealed that TC/HDL-C had a U-shape relationship with mortality rather than a linear relationship. Thus, participants were stratified into quintiles of TC/HDL-C (Q1 ≤ 3.11; 3.11 < Q2 ≤ 3.85; 3.85 < Q3 ≤ 4.6; 4.6 < Q4 ≤ 5.6; 5.6 < Q5). For a comparison of continuous and categorical variables among multiple groups, ANOVA and the Chi-square test, respectively, were used. The cumulative survival rates in each group were estimated by the Kaplan–Meier method and compared by using the log-rank test. Linear regression analyses were performed to identify the relationship between TC/HDL-C and body mass index (BMI), diabetes mellitus (DM), peptic ulcer disease, chronic liver disease, BUN, and albumin.
Multivariate Cox regression analyses were performed to evaluate the association between all-cause mortality and each lipid profile. The following 4 models were examined on the basis of multivariate adjustment: model 1, univariate hazard ratio of TC/HDL-C; model 2, model 1 plus age, sex, and BMI; model 3, model 2 plus hemoglobin, BUN, creatinine, albumin, calcium, and phosphorus; and model 4, model 3 plus 24 h urine volume. Statistical significance was defined as p < 0.05. Statistical analyses were performed using SPSS.

3. Results

3.1. Patient Baseline Characteristics

Baseline demographics, clinical, and laboratory characteristics according to baseline serum TC/HDL-C quintiles are summarized in Table 1. The mean age of patients at the initiation of dialysis was 51.5 ± 12.7 years; 59.4% were male, and the mean BMI was 23.1 ± 3.3 kg/m2. The mean ± standard deviation of TC and HDL-C were 168.4 ± 49.1 mg/dL and 41.0 ± 15.6 mg/dL, respectively. There were significant differences in BMI, prevalence of diabetes, prevalence of peptic ulcer disease, prevalence of liver disease, BUN and serum albumin levels among the TC/HDL-C quintiles. A linear regression analysis demonstrated that patients with elevated TC/HDL-C tended to have a higher BMI and serum BUN levels.

3.2. All-Cause and Cardiovascular Mortality

The mean follow-up duration of PD patients was 70.3 ± 25.2 months. During the follow-up period, 185 patients died. Among them, 73 (39.5%) were from cardiovascular disease and 36 (19.5%) from infectious disease.
Kaplan–Meier survival estimates of all-cause mortality with different levels of TC/HDL-C are shown in Figure 1. All-cause mortality in the combined first-to-fourth TC/HDL-C quintiles at 25, 50, 75, and 100 months was 4.95%, 17.4%, 25.8%, and 33.0%, respectively. On the other hand, all-cause mortality at 25, 50, 75, and 100 months was 8%, 20.9%, 34.7%, and 45.9%, respectively, in the fifth quintile group. There was a trend toward lower survival in the highest TC/HDL-C quintile compared to other groups (p = 0.052).
The multivariate Cox regression analysis found a decrease in patient survival in the highest TC/HDL-C group in PD patients (Table 2). The highest quintile group for baseline TC/HDL-C was associated with the highest all-cause mortality at all four levels of adjustment.
The reference group was quintile 3 (3.85 < TC/HDL-C ≤ 4.6). The hazard ratio (HR) of all-cause mortality in the fifth quintile was 1.74 (95% CI (Confidence interval), 1.09–2.76; p = 0.020) for model 1; 1.65 (95% CI, 1.04–2.64; p = 0.035) for model 2; 1.70 (95% CI, 1.04–2.76; p = 0.034) for model 3; and 1.69 (95% CI, 1.04–2.76; p = 0.036) for model 4. When the quintile 1 was considered as a reference group, there was no statistically significant difference from other groups (Supplementary Table S1). This result suggests that TC/HDL-C has clinical significance only when TC/HDL-C is very high.
A linear regression analysis showed a positive correlation between TC/HDL-C and BMI (Table 3). This result indicates that TC/HDL-C may be a risk factor for death in PD patients when there is a relationship between higher BMI and mortality.
We found no significant association between TC/HDL-C and CV mortality. Additionally, we analyzed a relationship between all-cause mortality and other lipid profiles. We found no significant differences in mortality between TC, HDL-C, and LDL-C quintiles at all four levels of adjustment (Table 4, Table 5 and Supplementary Table S2).

3.3. Subgroup Analyses

Subgroup analyses were performed in patients categorized according to age of 50 years, sex, presence of DM, 24 h urine volume of 100 mL/day, presence of CVD and BMI of 23 kg/m2. The negative association between high TC/HDL-C and survival was significant for patients with older age (≥50 years) and females. Higher TC/HDL-C was associated with the all-cause mortality rate in patients with CVD (Figure 2).
We also divided patients dichotomously according to median values of each serum lipid level as follows: TC < 162.5 mg/dL and ≥162.5 mg/dL, LDL-C < 93.8 mg/dL and ≥93.8 mg/dL, HDL-C < 38 mg/dL and ≥38 mg/dL, and TG < 120 mg/dL and ≥120 mg/dL. The association between TC/HDL-C and all-cause mortality was significant in patients with HDL-C levels < 38 mg/dL (HR, 2.29; 95% CI, 1.13–4.66; p = 0.022).

4. Discussion

The present study showed an association between TC/HDL-C and all-cause mortality among incident PD patients. Patients with higher TC/HDL-C had worse survival during the follow-up period than other groups, whereas no difference in survival was seen for TC, HDL-C and LDL-C. Subgroup analyses demonstrated higher TC/HDL-C as an independent risk factor for all-cause mortality in patients with older age (≥50 years), females, patients with lower HDL-C levels (<38 mg/dL) and the presence of CVD. A linear regression analysis revealed that patients with elevated TC/HDL-C had higher BMI. Our study suggests that non-traditional lipid profiles such as increased serum TC/HDL-C are independently associated with an increased risk of all-cause mortality in PD patients.
The relationship between TC/HDL-C and cardiovascular events has been investigated in several studies [5,12,13,14,15,16,17,18,19,20,21,22]. The exact pathogenic implication of TC/HDL-C is unknown; however, recent data indicate that TC/HDL-C is correlated with LDL-particle (LDL-P). Particle-based measures such as LDL-P or apolipoprotein B (ApoB) are discordantly greater than LDL-C more frequently in patients with insulin resistance, lower HDL-C, lower LDL-C, higher TG, and those on statins [23,24,25,26]. LDL-P accumulates in the arterial wall and leads to the subsequent subendothelial retention of LDL and other ApoB containing lipoproteins, resulting in atherosclerotic disease. LDL-C levels may insufficiently reflect the process of atheroma formation and underestimate CVD risk. Mathews et al. showed that TC/HDL-C was most correlated with LDL-P in standard lipid profiles [18]. This finding indicates that TC/HDL-C may provide more information about lipoprotein particle concentration and size than the standard lipid profile. Moreover, TC/HDL-C was strongly associated with cardiovascular events in the patients whose ratios of apolipoprotein B100 to apolipoprotein A-I, LDL-C, and non-HDL-C levels were discordant [17,19,20,21]. Therefore, our results are consistent with previous studies in that TC/HDL-C was associated with mortality unlike traditional lipid profiles such as TC and HDL-C.
Chronic kidney disease (CKD) causes major alterations in lipid profiles. The distinguishing findings of dyslipidemia in CKD are increased TG, decreased HDL-C, and variable levels of LDL-C. This altered composition of lipoproteins contributes to atherogenicity in patients with CKD [27]. HDL-C levels in both HD and PD patients demonstrate significant impairment of cholesterol efflux, which may be associated with augmented atherosclerosis [28]. However, changes in HDL-C levels may have different impacts on the outcomes of patients on the maintenance of CKD, HD, and PD patients. In a study of CKD patients, TC/HDL-C was independently associated with rapid CKD progression but could not predict mortality [29]. A study of HD patients found that low TC/HDL-C was associated with higher mortality. Increments of HDL-C over 50mg/dL are reportedly paradoxically associated with increased mortality [7]. HDL-C in patients with ESRD on the maintenance of HD is associated with reduced antichemotactic activity and increased macrophage inflammatory cytokine responses, which can increase atheromatosis and CV mortality [30]. Elevated oxidized-HDL-C concentrations are associated with increased CV mortality in HD patients [31].
Contrary to the previous study in HD patients, our results in the present study demonstrated higher TC/HDL-C as a risk factor for all-cause mortality in PD patients, which is consistent with the general population. A previous study also reported that elevated TC/HDL-C could predict survival in 125 patients with continuous ambulatory peritoneal dialysis [32]. These conflicting results may be explained by heterogeneous lipid profiles among HD and PD patients. Reduced lecithin-cholesterol acyltransferase (LCAT) activity may also contribute to delayed HDL-C maturation in patients on HD, leading to decreased cholesterol efflux. However, HDL-C in PD patients is associated with low paraoxonase activity, which is associated with impaired endothelial nitric oxide production and loss of the endothelial anti-inflammatory and endothelial repair-stimulating effects of HDL [31]. The significant reduction in paraoxonase activity can be explained by increased glycation of HDL-C in PD patients [33,34]. Therefore, the composition, function, and enzymatic activities of HDL-C could be altered by dialysis modalities. Although the clinical implication of differences in HDL-C has yet to be fully elucidated, such differences may explain the different impact of HDL-C on the survival of HD and PD patients.
Some registry studies reported that PD has a higher mortality rate than HD among patients with cardiovascular disease [35,36]. Although the SHARP study did not sufficiently confirm the effect of the lipid-lowering agent and was underpowered for PD patients, PD patients showed a much larger effect size than other subgroups [37]. Further studies are needed to confirm the effect of lipid-lowering agents on PD patients for which the mortality could be affected by the combined cardiovascular condition and high TC/HDL-C.
A linear regression analysis showed a positive correlation between TC/HDL-C and BMI. Although the effect of BMI on the survival of PD patients is controversial, several studies reported that obesity is associated with a higher risk of all-cause mortality and CVD mortality [38,39]. An additional subgroup analysis was performed based on BMI 23 kg/m2, but no significant results were found (Figure 2). It is conceivable that high TC/HDL-C has no synergistic or additive effect on mortality in patients with high BMI. Statistical significance may not appear because the number of the patients and events in the subgroup according to BMI is not sufficient. However, our study suggests that higher TC/HDL-C could be a risk factor such as BMI for mortality in patients on the maintenance of PD.
However, unlike all-cause mortality, we found no significant association between TC/HDL-C and CV mortality in our study. This may be explained by the relatively low numbers of deaths from CVD in our study, whereas, in the subgroup analysis, CVD patients were predisposed to have higher all-cause mortality rate in the group with a higher TC/HDL-C ratio compared to patients without CVD. Further studies with a larger number of patients are warranted to elucidate the correlation between TC/HDL-C and CV mortality in PD patients.
Further, we found that increased serum TC/HDL-C was an independent risk factor for mortality in the subgroup of old age, female and HDL-C levels less than 38 mg/dL. Old age and female sex are associated with a higher risk of death in patients with PD than with HD [40,41,42]. Although there are few studies about the role of HDL-C in PD patients [9], low HDL-C is a risk factor for mortality in the general population [43,44]. These suggest that the particular subgroups with increased mortality might be more susceptible to altered cholesterol metabolism such as high TC/HDL-C. Further studies are needed to evaluate the impact of TC/HDL-C on mortality in high-risk subgroups.
The strengths of this study are its prospective nature with a relatively long follow-up of up to 6 years and the availability of detailed data regarding baseline characteristics, comorbidities, and laboratory variables. However, there are some limitations to this study. First, given the observational nature of this study design, the results should be interpreted accordingly. Second, we did not examine other atherogenic lipoproteins such as Apo B100, which may be more specific to LDL-P. Third, our study comprised only Korean patients, so the conclusions cannot be generalized to other ethnicities. Fourth, this study lacked several important peritoneal dialysis data values that could affect lipid profiles such as peritoneal solute transfer rates, glucose prescription, use of icodextrin, and glycemic control at baseline. Fifth, the use of statins was not investigated in our baseline data. However, several studies show that statin therapy did not significantly reduce the risk of major atherosclerotic events in dialysis patients [37,45,46]. Thus, the prescription for statins would not have much effect on our study results.

5. Conclusions

Higher TC/HDL-C was significantly associated with an increased risk of all-cause mortality in incident PD patients. Further, single lipid markers alone such as TC or HDL-C were unable to predict mortality in PD patients. Although the underlying mechanisms are unclear, the use of inexpensive and readily available non-traditional lipid profiles such as TC/HDL-C may inform risk of mortality in patients with PD.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu14010144/s1, Table S1: Relationship between serum TC/HDL-C ratio and mortality (Reference group; Quintile 1); Table S2: Relationship between serum LDL-C and mortality.

Author Contributions

Conceptualization, J.-H.C. and Y.-L.K.; methodology, J.-H.L., H.-Y.J. and J.-Y.C.; formal analysis, Y.J.; data curation, J.-H.K., G.-Y.L., S.-J.J. and K.-Y.K.; writing—original draft preparation, H.-W.N. and J.-H.C.; writing—review and editing, H.-W.N. and J.-H.C.; supervision, S.-H.P. and C.-D.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI15C0001) and by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1I1A1A01055554, 2020R1I1A3068253, 2021R1I1A3059702, 2021R1I1A3047973, 2021R1I1A1A01040336).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of 31 centers affiliated with the Clinical Research Center for End Stage Renal Disease (CRC for ESRD).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data of this study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Chang, T.I.; Streja, E.; Soohoo, M.; Kim, T.W.; Rhee, C.M.; Kovesdy, C.P.; Kashyap, M.L.; Vaziri, N.D.; Kalantar-Zadeh, K.; Moradi, H. Association of serum triglyceride to HDL cholesterol ratio with all-cause and cardiovascular mortality in incident hemodialysis patients. Clin. J. Am. Soc. Nephrol. 2017, 12, 591–602. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Habib, A.N.; Baird, B.C.; Leypoldt, J.K.; Cheung, A.K.; Goldfarb-Rumyantzev, A.S. The association of lipid levels with mortality in patients on chronic peritoneal dialysis. Nephrol. Dial. Transplant. 2006, 21, 2881–2892. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Zheng, J.; Sun, Z.; Zhang, X.; Li, Z.; Guo, X.; Xie, Y.; Sun, Y.; Zheng, L. Non-traditional lipid profiles associated with ischemic stroke not hemorrhagic stroke in hypertensive patients: Results from an 8.4 years follow-up study. Lipids Health Dis. 2019, 18, 9. [Google Scholar] [CrossRef] [Green Version]
  4. Guo, X.; Li, Z.; Sun, G.; Guo, L.; Zheng, L.; Yu, S.; Yang, H.; Pan, G.; Zhang, Y.; Sun, Y. Comparison of four nontraditional lipid profiles in relation to ischemic stroke among hypertensive Chinese population. Int. J. Cardiol. 2015, 201, 123–125. [Google Scholar] [CrossRef]
  5. Arsenault, B.J.; Rana, J.S.; Stroes, E.S.; Després, J.-P.; Shah, P.K.; Kastelein, J.J.; Wareham, N.J.; Boekholdt, S.M.; Khaw, K.-T. Beyond low-density lipoprotein cholesterol: Respective contributions of non–high-density lipoprotein cholesterol levels, triglycerides, and the total cholesterol/high-density lipoprotein cholesterol ratio to coronary heart disease risk in apparently healthy men and women. J. Am. Coll. Cardiol. 2009, 55, 35–41. [Google Scholar]
  6. Wang, H.; Li, Z.; Guo, X.; Chen, Y.; Chang, Y.; Chen, S.; Sun, Y. The impact of nontraditional lipid profiles on left ventricular geometric abnormalities in general Chinese population. BMC Cardiovasc. Disord. 2018, 18, 88. [Google Scholar] [CrossRef]
  7. Moradi, H.; Streja, E.; Kashyap, M.L.; Vaziri, N.D.; Fonarow, G.C.; Kalantar-Zadeh, K. Elevated high-density lipoprotein cholesterol and cardiovascular mortality in maintenance hemodialysis patients. Nephrol. Dial. Transplant. 2014, 29, 1554–1562. [Google Scholar] [CrossRef]
  8. Chang, T.I.; Streja, E.; Ko, G.J.; Naderi, N.; Rhee, C.M.; Kovesdy, C.P.; Kashyap, M.L.; Vaziri, N.D.; Kalantar-Zadeh, K.; Moradi, H. Inverse Association Between Serum Non–High-Density Lipoprotein Cholesterol Levels and Mortality in Patients Undergoing Incident Hemodialysis. J. Am. Heart Assoc. 2018, 7, e009096. [Google Scholar] [CrossRef] [Green Version]
  9. Park, C.H.; Kang, E.W.; Park, J.T.; Han, S.H.; Yoo, T.-H.; Kang, S.-W.; Chang, T.I. Association of serum lipid levels over time with survival in incident peritoneal dialysis patients. J. Clin. Lipidol. 2017, 11, 945–954.e3. [Google Scholar] [CrossRef]
  10. Chen, H.-Y.; Tsai, W.-C.; Chiu, Y.-L.; Hsu, S.-P.; Pai, M.-F.; Yang, J.-Y.; Peng, Y.-S. Triglyceride to high-density lipoprotein cholesterol ratio predicts cardiovascular outcomes in prevalent dialysis patients. Medicine 2015, 94, e619. [Google Scholar] [CrossRef] [PubMed]
  11. Charlson, M.E.; Pompei, P.; Ales, K.L.; MacKenzie, C.R. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J. Chronic Dis. 1987, 40, 373–383. [Google Scholar] [CrossRef]
  12. Criqui, M.H.; Golomb, B.A. Epidemiologic aspects of lipid abnormalities. Am. J. Med. 1998, 105, 48S–57S. [Google Scholar] [CrossRef]
  13. Wang, T.-D.; Chen, W.-J.; Chien, K.-L.; Su, S.S.-Y.; Hsu, H.-C.; Chen, M.-F.; Liau, C.-S.; Lee, Y.-T. Efficacy of cholesterol levels and ratios in predicting future coronary heart disease in a Chinese population. Am. J. Cardiol. 2001, 88, 737–743. [Google Scholar] [CrossRef]
  14. Kinosian, B.; Glick, H.; Garland, G. Cholesterol and coronary heart disease: Predicting risks by levels and ratios. Ann. Intern. Med. 1994, 121, 641–647. [Google Scholar] [CrossRef] [PubMed]
  15. Emanuele, D.A.; Pei, G.; Lisa, P.; Stephen, K.; Muriel, C.; Alexander, T.; Adam, S.B.; Nadeem, S.; David, W.; Danish, S. Lipid-related markers and cardiovascular disease prediction. JAMA 2012, 307, 506. [Google Scholar]
  16. Ebong, I.A.; Goff, D.C., Jr.; Rodriguez, C.J.; Chen, H.; Sibley, C.T.; Bertoni, A.G. Association of lipids with incident heart failure among adults with and without diabetes mellitus: Multiethnic Study of Atherosclerosis. Circ. Heart Fail. 2013, 6, 371–378. [Google Scholar] [CrossRef] [Green Version]
  17. Kastelein, J.J.; Van Der Steeg, W.A.; Holme, I.; Gaffney, M.; Cater, N.B.; Barter, P.; Deedwania, P.; Olsson, A.G.; Boekholdt, S.M.; Demicco, D.A. Lipids, apolipoproteins, and their ratios in relation to cardiovascular events with statin treatment. Circulation 2008, 117, 3002–3009. [Google Scholar] [CrossRef] [Green Version]
  18. Mathews, S.C.; Mallidi, J.; Kulkarni, K.; Toth, P.P.; Jones, S.R. Achieving secondary prevention low-density lipoprotein particle concentration goals using lipoprotein cholesterol-based data. PLoS ONE 2012, 7, e33692. [Google Scholar] [CrossRef] [Green Version]
  19. Ingelsson, E.; Schaefer, E.J.; Contois, J.H.; McNamara, J.R.; Sullivan, L.; Keyes, M.J.; Pencina, M.J.; Schoonmaker, C.; Wilson, P.W.; D’Agostino, R.B. Clinical utility of different lipid measures for prediction of coronary heart disease in men and women. JAMA 2007, 298, 776–785. [Google Scholar] [CrossRef] [Green Version]
  20. Ridker, P.M.; Rifai, N.; Cook, N.R.; Bradwin, G.; Buring, J.E. Non–HDL cholesterol, apolipoproteins AI and B100, standard lipid measures, lipid ratios, and CRP as risk factors for cardiovascular disease in women. JAMA 2005, 294, 326–333. [Google Scholar] [CrossRef] [Green Version]
  21. Elshazly, M.B.; Nicholls, S.J.; Nissen, S.E.; John, J.S.; Martin, S.S.; Jones, S.R.; Quispe, R.; Stegman, B.; Kapadia, S.R.; Tuzcu, E.M. Implications of total to high-density lipoprotein cholesterol ratio discordance with alternative lipid parameters for coronary atheroma progression and cardiovascular events. Am. J. Cardiol. 2016, 118, 647–655. [Google Scholar] [CrossRef]
  22. Elshazly, M.B.; Quispe, R.; Michos, E.D.; Sniderman, A.D.; Toth, P.P.; Banach, M.; Kulkarni, K.R.; Coresh, J.; Blumenthal, R.S.; Jones, S.R. Patient-Level Discordance in Population Percentiles of the Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Comparison with Low-Density Lipoprotein Cholesterol and Non–High-Density Lipoprotein Cholesterol: The Very Large Database of Lipids Study (VLDL-2B). Circulation 2015, 132, 667–676. [Google Scholar] [PubMed] [Green Version]
  23. Sniderman, A.D.; Lamarche, B.; Contois, J.H.; de Graaf, J. Discordance analysis and the Gordian Knot of LDL and non-HDL cholesterol versus apoB. Curr. Opin. Lipidol. 2014, 25, 461–467. [Google Scholar] [CrossRef] [PubMed]
  24. Otvos, J.D.; Mora, S.; Shalaurova, I.; Greenland, P.; Mackey, R.H.; Goff, D.C., Jr. Clinical implications of discordance between low-density lipoprotein cholesterol and particle number. J. Clin. Lipidol. 2011, 5, 105–113. [Google Scholar] [CrossRef] [Green Version]
  25. Barter, P.J.; Ballantyne, C.M.; Carmena, R.; Cabezas, M.C.; Chapman, M.J.; Couture, P.; De Graaf, J.; Durrington, P.; Faergeman, O.; Frohlich, J. Apo B versus cholesterol in estimating cardiovascular risk and in guiding therapy: Report of the thirty-person/ten-country panel. J. Intern. Med. 2006, 259, 247–258. [Google Scholar] [CrossRef]
  26. Cromwell, W.C.; Otvos, J.D.; Keyes, M.J.; Pencina, M.J.; Sullivan, L.; Vasan, R.S.; Wilson, P.W.; D’Agostino, R.B. LDL particle number and risk of future cardiovascular disease in the Framingham Offspring Study—Implications for LDL management. J. Clin. Lipidol. 2007, 1, 583–592. [Google Scholar] [CrossRef] [Green Version]
  27. Dincer, N.; Dagel, T.; Afsar, B.; Covic, A.; Ortiz, A.; Kanbay, M. The effect of chronic kidney disease on lipid metabolism. Int. Urol. Nephrol. 2019, 51, 265–277. [Google Scholar] [CrossRef] [PubMed]
  28. Holzer, M.; Schilcher, G.; Curcic, S.; Trieb, M.; Ljubojevic, S.; Stojakovic, T.; Scharnagl, H.; Kopecky, C.M.; Rosenkranz, A.R.; Heinemann, A. Dialysis modalities and HDL composition and function. J. Am. Soc. Nephrol. 2015, 26, 2267–2276. [Google Scholar] [CrossRef] [Green Version]
  29. Ali, I.; Chinnadurai, R.; Ibrahim, S.T.; Green, D.; Kalra, P.A. Predictive factors of rapid linear renal progression and mortality in patients with chronic kidney disease. BMC Nephrol. 2020, 21, 345. [Google Scholar] [CrossRef] [PubMed]
  30. Yamamoto, S.; Yancey, P.G.; Ikizler, T.A.; Jerome, W.G.; Kaseda, R.; Cox, B.; Bian, A.; Shintani, A.; Fogo, A.B.; Linton, M.F.; et al. Dysfunctional high-density lipoprotein in patients on chronic hemodialysis. J. Am. Coll. Cardiol. 2012, 60, 2372–2379. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  31. Honda, H.; Ueda, M.; Kojima, S.; Mashiba, S.; Michihata, T.; Takahashi, K.; Shishido, K.; Akizawa, T. Oxidized high-density lipoprotein as a risk factor for cardiovascular events in prevalent hemodialysis patients. Atherosclerosis 2012, 220, 493–501. [Google Scholar] [CrossRef] [PubMed]
  32. Little, J.; Phillips, L.; Russell, L.; Griffiths, A.; Russell, G.I.; Davies, S.J. Longitudinal lipid profiles on CAPD: Their relationship to weight gain, comorbidity, and dialysis factors. J. Am. Soc. Nephrol. 1998, 9, 1931–1939. [Google Scholar] [CrossRef]
  33. Ferretti, G.; Bacchetti, T.; Marchionni, C.; Caldarelli, L.; Curatola, G. Effect of glycation of high density lipoproteins on their physicochemical properties and on paraoxonase activity. Acta Diabetol. 2001, 38, 163–169. [Google Scholar] [CrossRef]
  34. Boemi, M.; Leviev, I.; Sirolla, C.; Pieri, C.; Marra, M.; James, R.W. Serum paraoxonase is reduced in type 1 diabetic patients compared to non-diabetic, first degree relatives; influence on the ability of HDL to protect LDL from oxidation. Atherosclerosis 2001, 155, 229–235. [Google Scholar] [CrossRef]
  35. Sens, F.; Schott-Pethelaz, A.M.; Labeeuw, M.; Colin, C.; Villar, E. Survival advantage of hemodialysis relative to peritoneal dialysis in patients with end-stage renal disease and congestive heart failure. Kidney Int. 2011, 80, 970–977. [Google Scholar] [CrossRef] [Green Version]
  36. McDonald, S.P.; Marshall, M.R.; Johnson, D.W.; Polkinghorne, K.R. Relationship between dialysis modality and mortality. J. Am. Soc. Nephrol. 2009, 20, 155–163. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Baigent, C.; Landray, M.J.; Reith, C.; Emberson, J.; Wheeler, D.C.; Tomson, C.; Wanner, C.; Krane, V.; Cass, A.; Craig, J.; et al. The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): A randomised placebo-controlled trial. Lancet 2011, 377, 2181–2192. [Google Scholar] [CrossRef] [Green Version]
  38. Liu, J.; Zeng, X.; Hong, H.G.; Li, Y.; Fu, P. The association between body mass index and mortality among Asian peritoneal dialysis patients: A meta-analysis. PLoS ONE 2017, 12, e0172369. [Google Scholar]
  39. Kiran, V.R.; Zhu, T.Y.; Yip, T.; Lui, S.L.; Lo, W.K. Body mass index and mortality risk in Asian peritoneal dialysis patients in Hong Kong-impact of diabetes and cardiovascular disease status. Perit. Dial. Int. 2014, 34, 390–398. [Google Scholar] [CrossRef] [Green Version]
  40. Mehrotra, R.; Chiu, Y.W.; Kalantar-Zadeh, K.; Bargman, J.; Vonesh, E. Similar outcomes with hemodialysis and peritoneal dialysis in patients with end-stage renal disease. Arch. Intern. Med. 2011, 171, 110–118. [Google Scholar] [CrossRef] [Green Version]
  41. Yeates, K.; Zhu, N.; Vonesh, E.; Trpeski, L.; Blake, P.; Fenton, S. Hemodialysis and peritoneal dialysis are associated with similar outcomes for end-stage renal disease treatment in Canada. Nephrol. Dial. Transplant. 2012, 27, 3568–3575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Han, S.S.; Park, J.Y.; Kang, S.; Kim, K.H.; Ryu, D.R.; Kim, H.; Joo, K.W.; Lim, C.S.; Kim, Y.S.; Kim, D.K. Dialysis Modality and Mortality in the Elderly: A Meta-Analysis. Clin. J. Am. Soc. Nephrol. 2015, 10, 983–993. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Zhong, G.C.; Huang, S.Q.; Peng, Y.; Wan, L.; Wu, Y.Q.; Hu, T.Y.; Hu, J.J.; Hao, F.B. HDL-C is associated with mortality from all causes, cardiovascular disease and cancer in a J-shaped dose-response fashion: A pooled analysis of 37 prospective cohort studies. Eur. J. Prev. Cardiol. 2020, 27, 1187–1203. [Google Scholar] [CrossRef] [Green Version]
  44. Rodriguez, A. High HDL-Cholesterol Paradox: SCARB1-LAG3-HDL Axis. Curr. Atheroscler. Rep. 2021, 23, 5. [Google Scholar] [CrossRef]
  45. Wanner, C.; Krane, V.; März, W.; Olschewski, M.; Mann, J.F.; Ruf, G.; Ritz, E. Atorvastatin in patients with type 2 diabetes mellitus undergoing hemodialysis. N. Engl. J. Med. 2005, 353, 238–248. [Google Scholar] [CrossRef] [PubMed]
  46. Fellström, B.C.; Jardine, A.G.; Schmieder, R.E.; Holdaas, H.; Bannister, K.; Beutler, J.; Chae, D.W.; Chevaile, A.; Cobbe, S.M.; Grönhagen-Riska, C.; et al. Rosuvastatin and cardiovascular events in patients undergoing hemodialysis. N. Engl. J. Med. 2009, 360, 1395–1407. [Google Scholar] [CrossRef] [Green Version]
Nutrients 14 00144 g001 550
Figure 1. Kaplan–Meier curve of all-cause mortality according to TC/HDL-C.
Figure 1. Kaplan–Meier curve of all-cause mortality according to TC/HDL-C.
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Nutrients 14 00144 g002 550
Figure 2. Subgroup analysis according to age, sex, presence of DM, 24 h urine volume, presence of CVD, BMI, and serum lipid levels.
Figure 2. Subgroup analysis according to age, sex, presence of DM, 24 h urine volume, presence of CVD, BMI, and serum lipid levels.
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Table
Table 1. Baseline characteristics of individuals by baseline serum TC/HDL-C ratio quintile.
Table 1. Baseline characteristics of individuals by baseline serum TC/HDL-C ratio quintile.
VariablesTC/HDL-C
1st2nd3rd4th5thp-Value
Age at initiation of dialysis (years)51.61 ± 14.4552.46 ± 12.1949.95 ± 11.9051.05 ± 12.8552.58 ± 11.990.451
Sex (Male, %)69 (54.8)74 (59.2)74 (58.23)75 (59.1)82 (65.6)0.526
Body mass index (kg/m2)21.94 ± 3.2422.39 ± 2.9223.13 ± 3.2223.66 ± 3.4024.36 ± 3.34<0.001
Primary renal disease, n (%)
Diabetes50 (39.7)50 (40.0)45 (35.4)52 (40.9)70 (56.0)0.034
Hypertension27 (21.4)27 (21.6)21 (16.5)25 (19.7)16 (12.8)
Glomerulonephritis26 (20.6)30 (24.0)24 (18.9)24 (18.9)19 (15.2)
Others23 (18.3)18 (14.4)37 (29.1)26 (20.5)20 (16.0)
Comorbidity at initiation of dialysis, n (%)
Congestive heart failure9 (7.1)12 (9.7)13 (10.2)14 (11.0)11 (8.8)0.858
Coronary artery disease15 (11.9)14 (11.2)7 (5.6)12 (9.5)12 (9.6)0.473
Peripheral vascular disease7 (5.6)7 (5.6)7 (5.7)5 (3.9)4 (3.2)0.838
Arrhythmia4 (3.2)0 (0.0)2 (1.6)3 (2.4)1 (0.8)0.285
Cerebrovascular disease5 (15.6)5 (15.6)8 (6.3)7 (5.6)7 (5.6)0.887
Chronic lung disease6 (4.8)2 (1.6)3 (2.4)6 (4.7)3 (2.4)0.476
Peptic ulcer disease1 (0.79)7 (5.6)10 (7.87)3 (2.36)3 (2.4)0.023
Moderate to severe chronic liver disease9 (7.1)6 (4.8)2 (1.6)1 (0.8)3 (2.4)0.032
Connective tissue disease9 (7.1)10 (8.0)16 (12.6)14 (11.0)14 (11.2)0.558
Malignancy5 (4.0)5 (4.0)3 (2.4)5 (4.0)2 (1.6)0.723
Modified Charlson comorbidity index4.55 ± 2.265.55 ± 2.264.28 ± 2.054.41 ± 2.134.69 ± 1.980.607
Laboratory data at initiation of dialysis
Hemoglobin (g/dL)9.34 ± 1.879.67 ± 1.499.76 ± 1.969.61 ± 1.459.72 ± 1.510.282
Blood urea nitrogen (mg/dL)77.27 ± 34.9982.58 ± 40.1374.76 ± 34.2969.99 ± 31.1969.64 ± 30.240.015
Creatinine (mg/dL)8.42 ± 3.559.06 ± 3.968.44 ± 3.298.67 ± 3.539.30 ± 4.190.236
Albumin (g/dL)3.38 ± 0.583.58 ± 0.553.52 ± 0.593.55 ± 0.493.70 ± 0.630.016
Calcium (mg/dL)7.99 ± 0.988.02 ± 0.997.96 ± 1.008.10 ± 1.088.17 ± 0.940.458
Phosphorus (mg/dL)5.49 ± 1.935.37 ± 1.565.14 ± 1.895.35 ± 1.705.48 ± 1.750.517
Urine volume (mL/day)920.91 ± 575.85989.49 ± 692.301000.31 ± 653.44937.47 ± 623.06885.30 ± 647.410.586
Table
Table 2. Relationship between serum TC/HDL-C ratio and mortality.
Table 2. Relationship between serum TC/HDL-C ratio and mortality.
Quintile 1Quintile 2Quintile 4Quintile 5
HR (95% CI)p-ValueHR (95% CI)p-ValueHR (95% CI)p-ValueHR (95% CI)p-Value
Model 11.12 (0.77–2.08)0.3471.40 (0.87–2.27)0.1801.36 (0.84–2.21)0.2081.74 (1.09–2.76)0.020
Model 21.17 (0.71–1.95)0.5351.22 (0.75–2.00)0.4201.30 (0.80–2.11)0.2861.65 (1.04–2.64)0.035
Model 31.27 (0.76–2.13)0.3661.29 (0.79–2.12)0.3151.46 (0.88–2.40)0.1411.70 (1.04–2.76)0.034
Model 41.27 (0.75–2.13)0.3741.29 (0.78–2.12)0.3191.45 (0.88–2.34)0.1481.69 (1.04–2.76)0.036
HR, hazard ratio. Reference group was Quintile 3. Model 1: Unadjusted. Model 2: Model 1 plus age, sex, and body mass index. Model 3: Model 2 plus laboratory data and MCCI. Model 4: Model 3 plus 24 h urine volume.
Table
Table 3. Univariate and multivariate linear regression of TC/HDL-C.
Table 3. Univariate and multivariate linear regression of TC/HDL-C.
UnivariateMultivariate
βStdtp-ValueR2βStdtp-ValueR2
(intercept) 1.84009371.960.05000.036
BMI0.1290.0304.38<.00010.0300.1250.0314.09<0.0001
DM0.2870.2001.440.15100.0030.1200.2150.560.5762
PUD−0.2420.522−0.460.64320.000−0.1430.518−0.280.7832
CLD0.0210.5710.040.97020.0000.0600.5670.110.9158
BUN−0.0060.003−2.060.03970.007−0.0050.003−1.750.0807
Albumin0.0120.1750.070.94770.0000.0410.1870.220.8265
Table
Table 4. Relationship between total serum cholesterol and mortality.
Table 4. Relationship between total serum cholesterol and mortality.
Quintile 1
(N = 126)		Quintile 2
(N = 125)		Quintile 4
(N = 127)		Quintile 5
(N = 125)
HR (95% CI)p-ValueHR (95% CI)p-ValueHR (95% CI)p-ValueHR (95% CI)p-Value
Model 11.12 (0.71–1.77)0.6160.99 (0.62–1.57)0.9530.97 (0.61–1.53)0.8881.74 (1.09–2.76)0.786
Model 20.94 (0.59–1.49)0.7930.92 (0.58–1.46)0.7220.91 (0.57–1.44)0.6830.87 (0.55–1.40)0.570
Model 30.76 (0.47–1.24)0.2710.90 (0.56–1.45)0.6640.79 (0.49–1.26)0.3150.73 (0.45–1.17)0.188
Model 40.77 (0.47–1.24)0.2780.90 (0.56–1.45)0.6780.79 (0.50–1.27)0.3310.73 (0.45–1.18)0.198
HR, hazard ratio. Reference group was Quintile 3. Model 1: Unadjusted. Model 2: Model 1 plus age, sex, and body mass index. Model 3: Model 2 plus laboratory data and MCCI. Model 4: Model 3 plus 24 h urine volume.
Table
Table 5. Relationship serum HDL-C and mortality.
Table 5. Relationship serum HDL-C and mortality.
Quintile 1
(N = 126)		Quintile 2
(N = 125)		Quintile 4
(N = 127)		Quintile 5
(N= 125)
HR (95% CI)p-ValueHR (95% CI)p-ValueHR (95% CI)p-ValueHR (95% CI)p-Value
Model 11.39 (0.90–2.15)0.1360.79 (0.49–1.27)0.3281.24 (0.80–1.93)0.3450.70 (0.42–1.17)0.170
Model 21.32 (0.85–2.06)0.2140.87 (0.53–1.42)0.5861.28 (0.82–2.01)0.2730.80 (0.47–1.34)0.392
Model 31.23 (0.78–1.94)0.3710.81 (0.49–1.33)0.4051.17 (0.74–1.85)0.4970.70 (0.41–1.18)0.175
Model 41.21 (0.77–1.93)0.3980.80 (0.49–1.33)0.3931.17 (0.74–1.84)0.5060.69 (0.41–1.17)0.171
HR, hazard ratio. Reference group was Quintile 3. Model 1: Unadjusted. Model 2: Model 1 plus age, sex, and body mass index. Model 3: Model 2 plus laboratory data and MCCI. Model 4: Model 3 plus 24 h urine volume.
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Noh, H.-W.; Jeon, Y.; Kim, J.-H.; Lee, G.-Y.; Jeon, S.-J.; Kim, K.-Y.; Lim, J.-H.; Jung, H.-Y.; Choi, J.-Y.; Park, S.-H.; et al. Higher Serum Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio Is Associated with Increased Mortality among Incident Peritoneal Dialysis Patients. Nutrients 2022, 14, 144. https://doi.org/10.3390/nu14010144

AMA Style

Noh H-W, Jeon Y, Kim J-H, Lee G-Y, Jeon S-J, Kim K-Y, Lim J-H, Jung H-Y, Choi J-Y, Park S-H, et al. Higher Serum Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio Is Associated with Increased Mortality among Incident Peritoneal Dialysis Patients. Nutrients. 2022; 14(1):144. https://doi.org/10.3390/nu14010144

Chicago/Turabian Style

Noh, Hee-Won, Yena Jeon, Ji-Hye Kim, Ga-Young Lee, Soo-Jee Jeon, Kyu-Yeun Kim, Jeong-Hoon Lim, Hee-Yeon Jung, Ji-Young Choi, Sun-Hee Park, and et al. 2022. "Higher Serum Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio Is Associated with Increased Mortality among Incident Peritoneal Dialysis Patients" Nutrients 14, no. 1: 144. https://doi.org/10.3390/nu14010144

APA Style

Noh, H. -W., Jeon, Y., Kim, J. -H., Lee, G. -Y., Jeon, S. -J., Kim, K. -Y., Lim, J. -H., Jung, H. -Y., Choi, J. -Y., Park, S. -H., Kim, C. -D., Kim, Y. -L., & Cho, J. -H. (2022). Higher Serum Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio Is Associated with Increased Mortality among Incident Peritoneal Dialysis Patients. Nutrients, 14(1), 144. https://doi.org/10.3390/nu14010144

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