Abstract

Background: The efficacy of triglyceride/high-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratios have been demonstrated as predictors of adverse cardiovascular events and mortality predictors in healthy patients. However, limited studies have been performed to evaluate their efficacy as mortality predictors in hemodialysis patients.

Methods: An observational, retrospective, case-control study was performed on a total of 586 patients enrolled with treatment of end-stage kidney disease on hemodialysis treated in the Hemodialysis Unit of Centro Medico Siglo XXI, Mexico from January 2019 to December 2022. The medical records, albumin levels, total cholesterol, HDL-C, LDL-C, triglyceride, TG/HDL- C and non-HDL-C/HDL-C serum levels were recorded. The TG/HDL- C ratio and non-HDL-C/HDL-C ratio were categorized into quintiles. The association of both TG/HDL- C ratio and non-HDL-C/HDL-C ratio and mortality were evaluated by univariate and multivariate logistic regression analysis, considering a p =< 0.05 as a statistically significant value.

Results: A total of 586 patients were enrolled. They were distributed as 148 deceased patients (cases) and 436 living patients living (control). The multivariate logistic regression analysis showed that TG/HDL-C ratio (1.70-2.46), increases by 1.16 times the risk of death (2.16 OR, 95% CI 1.155 - 4.004), while quintile 3 of non-HDL-C/HDL-C ratio (2.47 - 3.46) show a tendency of increase the risk of death (1.015 OR, 95% CI 0.526 - 1.957) with no statistically significant difference (p = 0.965).

Conclusions: The TG/HDL-C ratio has potential to predict mortality in hemodialysis patients. The non-HDL-C/HDL-C ratio failed as a prognostic tool, with no statistically significant results in the analysis.

Keywords

TG/HDL-C Ratio; non-HDL-C/HDL-C Ratio; Mortality; Hemodialysis Patients

Introduction

Chronic Kidney Disease (CKD) is estimated to affect 11% of people worldwide [1], with a substantial increase in the incidence and prevalence due to the combination of factors: environment, increase in life expectancy as well as comorbidities such as diabetes, hypertension and obesity [2]. In Mexico, diabetes is the second cause of mortality [3] with a predominance of cardiovascular events as mortality cause greater than CKD itself [4]. The mortality risk increases as the disease progresses to End-Stage Renal Disease (ESRD) and exacerbates when Renal Replacement Therapy (RRT) is initiated with an HR 9.2 in peritoneal dialysis (95% CI 6.6-12.7), 12.6 in hemodialysis (95% CI 10.8- 14.6), and 5.6 in kidney transplant (95% CI 3.5-8.9) compared with healthy patients [5]. Currently, none of the inflammation, oxidative stress, endothelial dysfunction, vascular calcification or insulin resistance biomarkers have demonstrated usefulness as prognostic tools [6], which creates the need to develop risk mortality tools.

The atherogenic risk pattern of CKD is characterized by hypertriglyceridemia, low High-Density Lipoprotein (HDL) levels, normal or mildly decreased total cholesterol (T-Chol) and low LDL levels [7] caused by uremic toxins, oxidative stress, malnutrition and low-grade inflammation [8] suggest their ability as a mortality risk predictor. Several studies have shown the potential of Triglyceride/ HDL-Cholesterol (TG/HDL-C) and non-HDL Cholesterol/HDLCholesterol (non-HDL-C/HDL-C) ratio as predictors of cardiovascular events and mortality in CKD patients shown as advantage been accessible, low-cost and repeatable tool [9-12]. However, there are limited contradictory reports about their utility in ESRD patients with RRT.

The aim of this study was to evaluate the TG/HDL-C and nonHDL C/HDL-C ratios as mortality risk predictors in ESRD patients in treatment with chronic hemodialysis.

Materials and Methods

The study was approved by the local ethics committee. An observational, retrospective, case-control study was performed. The information was obtained from the physical and electronic records of the patients with ESKD in RRT on hemodialysis treated in the Hemodialysis Unit of Centro Medico Nacional Siglo XXI, Mexico from January 2019 to December 2022. Cases were defined as all deceased patients aged 18 years or older in hemodialysis treatment, with a measurement of Triglycerides (TG), T-Chol and HDL-C. Patients without relevant information for study, a single hemodialysis session or recovery of kidney function were excluded. Control was defined as all living patients aged 18 years or older in hemodialysis treatment, with a measurement of TG, T-Chol and HDL-C. The same exclusion criteria were used. The sample size calculation was based on a 3:1 ratio for the control and case group respectively. The difference in proportions formula was used with a prevalence of study variable of 52% to detect a relative risk of at least 2.28, with a power of 90%, confidence level of 95%, and error limit of 0.05%.

The general patient data (age, sex, Body Max Index (BMI), time in hemodialysis treatment, Ultra Filtration (UF), history of Chronic Kidney Diseases (diabetes, hypertension, dyslipidemia), use of reninangiotensin system blockers (SRAAi), lipid-lowering treatments, and laboratory (albumin levels, T-Chol, HDL-C, LDL-C, TG) serum levels were recorded from medical records.

The TG/HDL-C ratio was calculated with serum TG level divided by serum levels of HDL-C. The non HDL- Cholesterol value was obtained by subtracting serum HDL-C from T-Chol. The non-HDL-C/HDL-C ratio was calculated with serum non HDL-C level divided by serum levels of HDL-C.

Statistical Analysis

The collected data was registered in Excel® file and then exported to SPSS® (IBM ®, United States), 26 version statistical program for data analysis. Descriptive statistic was used for general patient information (clinical and sociodemographic data). Kolmogorov-Smirnov’s test was used to evaluate normality. All variables showed non-normal distribution. The quantitative variables were reported with a median and interquartile range 25-75 (IQR). The categorical variables were described with frequencies and percentages. To evaluate the general characteristics of case and control groups Mann Whitney U test was performed for quantitative variables, while the chi-squared test was used for qualitative variables. The TG/HDL-C ratio and non-HDL-C/ HDL-C ratio were treated as categorical variables ratio and divided into quintiles to determine the value associated with the primary outcome. For both ratios, the reference category was the first quintile. To evaluate differences between each quintile ratios, Kruskal-Wallis test was performed for quantitative variables and qualitative variables were evaluated with the Chi-square test for linear trend. A bivariate analysis was conducted to determine the factors associated with death through a logistical regression analysis obtained odds ratio (OR) with 95% Confidence Intervals (CI). The multivariate logistic regression analysis was used to develop two risk models. Model 1 was based on clinical characteristics and model 2 involved the treatments implemented and serum albumin. For all statistical analyses, values of p <0.05 were established as statistically significant.

Results

A total of 586 patients were enrolled. They were distributed as 436 control group (living patients) and 148 cases group (deceased patients). It was observed deceased patients were older (median 57 years, IQR 48-68 years), in relation to living patients (median 50 years, IQR 39-62 years), with a statistically significant difference (p = <0.001). A statistically significant difference (p = <0.001) was found in median serum albumin in living patients 3.80 g/dL (3.30 - 4.20 g/dL) compared with deceased patients median serum albumin 3.57 g/dL (2.90 - 3.90 g/dL), as shown in Table 1.

Characteristics		Alive n= 438	Deceased n= 148	p
Age (years), median (IQR)		50 (39 - 62)	57 (48 - 68)	< 0.001*
Sex
	Men, n (%)	228 (52.2)	83 (56.1)	0.678†
	Women, n (%)	209 (47.8)	65 (43.9)
Time on HD (month), median (IQR)		24.5 (13 - 60)	24 (12-36)	< 0.001*
Average UF (L), median (IQR)		2 (1.5 - 2.5)	2 (1.4 - 2.8)	0.854*
BMI (kg/m2), median (IQR)		24.22 (21.36 - 27.34)	24.42 (21.50 - 27.21)	0.972*
Diabetes, n (%)		173 (39.5)	75 (51.4)	0.012†
Hypertension, n (%)		385 (87.9)	121 (82.9)	0.122†
Treatment
	ACEi, n(%)	20 (4.6)	8 (5.6)	0.630†
	ARA2, n(%)	179 (40.9)	60 (41.4)	0.914†
Lipid lowering treatment
	Statins, n (%)	86 (19.6)	22 (15.3)	0.243†
	Fibrates, n (%)	10 (2.3)	6 (4.2)	0.244†
	Ezetimibe, n(%)	10 (2.3)	3 (2.1)	0.593†
Albumin (g/dL), median (IQR)		3.80 (3.30 - 4.20)	3.57 (2.90 - 3.90)	< 0.001*
T-Chol (mg/dL), median (IQR)		146.00 (123.00 - 176.00)	142.10 (111.00 - 166.00)	0.018*
HDL-C (mg/dL), median (IQR)		41.90 (33.75 - 51.60)	38.15 (29.85 - 53.30)	0.159*
TG (mg/dL), median (IQR)		117.00(87.00- 167.00)	121.50 (88.13 - 161.60)	0.746*
TG/HDL-C, median (IQR)		2.72 (1.88 - 4.42)	3.15 (1.73 - 5.31)	0.178*
Col no HDL/HDL-C, median (IQR)		2.49 (1.75 - 3.41)	2.46 (1.63 - 3.60)	0.911*
ACEi: Angiotensin Converting Enzyme inhibitor, ARA2: Aldosterone Antagonist Receptor, BMI: Body Mass Index, HDL-C: High-Density Lipoprotein Cholesterol, non-HDL-C/HDL-C: non-HDL Cholesterol/HDL-Cholesterol, T- Chol: Total Cholesterol, TG: Triglycerides, TG/HDL-C: Triglyceride/HDL- Cholesterol Ratio, UF: Ultrafiltration * Mann Whitney U test † chi-squared test

Table 1: Baseline characteristics of the study population

The baseline demographics, clinical, and laboratory characteristics of the patients according to serum TG/HDL-C ratio and non-HDL-C/ HDL-C quintiles are summarized in Table 2.

Table 2: Baseline characteristics according to TG/HDL-C ratio and non-HDL-C/HDL-C ratio

The TG/HDL-C ratio mean age are 49 (IQR 39-64), 53 (IQR 41-68), 52 (IQR 39-64), 51 (IQR 40-65), 54 (IQR 43-65) years respectively, with no statistically significant difference (p = 0.780). A male predominance in all groups is observed with no statistically significant difference between groups (p = 0.777). No statistically significant difference is observed in the percentage of patients with diabetes (p = 0.208) and hypertension (p = 0.698) between groups. The median serum albumin is 4 (IQR 3.40-4.30), 3.80 (IQR 3.31-4.19), 3.60 (IQR 2.97-4.10) and 3.33 (IQR 2.70-4.10) g/dL respectively, with statistically significant difference between groups (p = 0.009).

The non-HDL-C/HDL-C ratio quintiles show a mean age are 51 (IQR 39-65), 54 (IQR 41-67), 51 (IQR 60-63), 53 (IQR 40-64), 54 (IQR 38-61) years respectively, with no statistically significant difference (p = 0.772). A male predominance is also observed with no statistically significant difference between groups (p = 0.432). No statistically significant difference is observed in the percentage of patients with diabetes (p = 0.568) and hypertension (p = 0.524) between groups. The median serum albumin are 4 (IQR 3.40-4.30), 3.80 (IQR 3.31-4.19), 3.60 (IQR 2.97-4.10) and 3.33 (IQR 2.70-4.10) g/dL respectively and statistically significant difference is observed (p = 0.009).

The logistic regression analysis shows that quintile 2 of TG/HDL-C ratio (1.70-2.46), increases by 1.16 times the risk of death (2.16 OR, 95% CI 1.155 - 4.004), while quintile 3 of non-HDL-C/HDL-C ratio (2.47 - 3.46) show a tendency of increase the risk of death (1.015 OR, 95% CI 0.526 - 1.957) with no statistically significant difference (p= 0.965). The study also demonstrates serum albumin <3.4 g/dL increases the risk of death (2.014 OR, 95% CI 1.353 - 2.996, p = 0.001). Age over 60 years (0.505 OR, 95% CI 0.345 - 0.739, p = <0.001) and diabetes (0.618 OR, 95% CI 0.424 - 0.901, p = 0.012) showed a reduction in risk of death with a statistically significant difference. (Table 3).

Characteristics	OR	95% CI		p
			Upper
Age > 60 years	0.505	0.345	0.739	<0.001
Men	0.854	0.587	1.243	0.411
BMI > 30 kg/m2	1.322	0.776	2.253	0.304
Diabetes	0.618	0.424	0.901	0.012
Hypertension	1.501	0.894	2.518	0.124
RAAS blockers	0.926	0.635	1.349	0.688
Lipid lowering treatment	1.329	0.81	2.181	0.259
Albumin <3.4 g/dL	2.014	1.353	2.996	0.001
T-Chol > 200 mg/dL	1.552	0.807	2.871	0.194
HDL-C <35 mg/dL	0.631	0.424	0.939	0.023
TG > 150 mg/dL	0.999	0.996	1.001	0.221
Q2 TG/HDL (1.84 - 2.84)	2.16	1.155	4.04	0.016
Q3 Col no HDL/HDL-C (2.47 - 3.46)	1.015	0.526	1.957	0.965
BMI: Body Mass Index,   HDL-C: High-Density Lipoprotein Cholesterol, non-HDL-C/HDL-C: non-HDL Cholesterol/HDL-Cholesterol, Q: Quintile, RAAS: Renin-Angiotensin- Aldosterone System, T-Chol: Total Cholesterol,  TG: Triglycerides, TG/HDL-C: Triglyceride/HDL- Cholesterol Ratio

Table 3: Univariate analysis of prognostic factors of death.

The quintile 2 of TG/HDL-C ratio was assessed into two logistic regression models in order to predict the association with the risk of death. In the first model adjusted by age, sex and comorbidities (model 1), the TG/HDL-C ratio persists as a risk factor of death (2.057 OR, 95% CI 1.25 - 3.383). Hypertension also showed an increase in the risk of death (2.001 OR, 95% CI 1.145 - 3.498, p = 0.015), while age over 60 years reduce in 48% the risk of death (0.52 OR, 95% CI 0.344 - 0.788, p=0.002). In the second model adjusted by antihypertensive of hypolipidemic treatment, was observed that the quintile 2 of TG/ HDL-C ratio increase 0.94 times the risk of death (1.943 OR, 95% CI 1.180 - 3.201, p=0.009), also serum albumin <3.4 g/dL increase 1.027 times the risk of death (2.027 OR, 95% CI 1.350 - 3.004, p = 0.001) (Table 4).

Characteristics	Model 1				Model 2
	OR	95% CI		p	OR	95% CI		p
		Lower	Upper			Lower	Upper
Age > 60 years	0.52	0.344	0.788	0.002
Men	0.879	0.596	1.297	0.516
Diabetes	0.67	0.439	1.024	0.064
Hypertension	2.001	1.145	3.498	0.015
Albumin <3.4 g/dL					2.027	1.35	3.044	0.001
RAAS blockers					1.005	0.683	1.479	0.981
Lipid lowering treatment					1.373	0.831	2.27	0.216
Q2 TG/HDL (1.84 - 2.84)	2.057	1.25	3.383	0.005	1.943	1.18	3.201	0.009
Q: Quintile, RAAS: Renin-Angiotensin- Aldosterone System, TG/HDL-C: Triglyceride/HDL-Cholesterol Ratio

Table 4: Multivariate analysis of prognostic factors of death.

Discussion

A retrospective, case and control study was developed with the aim of evaluating the TG/HDL-C and non-HDL-C/HDL-C ratios as mortality prognostic tools in ESRD patients with chronic hemodialysis. Both ratios have shown their prognostic ability in healthy populations, however in CKD patients’ evidence is limited, with different results depending on the glomerular filtration rate, the initiation of RRT and the type of therapy administrated. In chronic hemodialysis patients a controversial relationship is observed between dyslipidemia and mortality, with a low serum concentration of cholesterol, low HDL, and high levels of small dense low-density lipoprotein, A-lipoprotein and triglycerides due to the mechanism of reverse epidemiology [13,14] which promotes an atherogenic process associated with the predominance of small dense Low-Density Lipoprotein (LDL) cholesterol [15], a significant increase in apoC-III and a moderate increase in apoB, VLDL and IDL due reduction in LPL activity that promotes hypertriglyceridemia [16].

In our center, reduced total cholesterol was observed, however, serum triglycerides were observed in normal values (mean 117 in living (IQR 87 - 167 mg/dL) vs 121.5 mg/dL (IQR 88.13 - 161.6 mg/ dL) in deceased patients. It has been observed that in hemodialysis patients have also noticed some atherogenic lipoprotein changes with a low concentration of HDL-C and elevated IDL-C, in the absence of hyperlipidemia. [15].

The previous studies where TG/HDL-C ratio has shown different results according to RRT implemented. In China, Qi L, and cols [17] evaluated the association between TG/HDL-C ratio and mortality in hemodialysis patients, were found a reduction in the risk of death in the highest quartile ( ≥ 2.64) (0.50 OR, 95% CI 0.33 - 0.76, p = 0.001). Meanwhile, Chang, T.I., and cols [11] in 2017 found higher mortality in lower deciles (1.59 - 2.57) (1.07 and 1.09 OR, p = 0.06 and 0.03 respectively) and lower mortality in the higher deciles (6.41 - 8.63) (0.85 and 0.71, p = <0.001 and p = <0.001). In contrast, Chen, H-Y., and cols. [12] evaluate TG/HDL-C ratio in peritoneal dialysis and hemodialys is patients in Taiwan, where the highest quintile (>6.6) was associated with the highest risk of all-cause mortality (adjusted HR 1.94, 95% CI 1.1-3.39).

In our study, we observed that TG/HDL-C ratio range to 1.84 to 2.84 increases de risk of death, with no effect observed in the mortality risk in other quintiles. Despite the different information reported, we observe that our study showed a similar tendency with the highest risk in the lower value (2.16 OR, 95% CI 1.155 - 4.004, p = 0.016). Nevertheless, the highest quintile shows a tendency to also increase the risk of death with no statistically significant difference (1.181 OR, 95% CI 0.465 - 3.001, p = 0.726). We suggest that the difference between studies is associated with the involvement in modification of atherogenic metabolism according to RRT implemented, due to the type of membrane and also de type of anticoagulation have a direct effect on reverse epidemiology process, low grade inflammation and the lipolysis and atherogenesis mechanisms [15,16], also other characteristics that were not evaluated impact in the serum concentration as obesity, alcohol consumption, dietary carbohydrate intake and diabetes [18]. Albumin is other factor implicated in lipid metabolism due to its function in transport, storage of fatty acids [19] and markers of nutritional status and systemic inflammation, consider low levels as risk factor of cardiovascular disease and all cause death in patients [20]. In our study, hypoalbuminemia associated with TG/ HDL-C ratio increase 1.027 times the risk of death (2.027 OR, 95% CI 1.350 - 3.044, p = 0.01).

This is the first study to evaluate non-HDL-C/HDL-C ratio in chronic hemodialysis patients. The previous study carried out by Kims and cols. [10] in 2021 in dialysis treatment found that a ratio ≥ 2.96 increases the risk of death for all causes (OR 2.58, 95% IC 1.39 - 4,98, p = 0.003). In our study the third quintile (2.47 - 3.46) was used based on the report, showing a tendency to increase the risk of death (1.015 OR, 95% IC 0.526 - 1.957). However, no statistically significant difference (p = 0.965) was found. Despite the ability of HDL-C in reduce the atherosclerosis and anti-inflammatory function, it was observed in hemodialysis patients an alteration in their proteomic and lipidic composition of HDL with a reduction in apoA-I and apoA-II that reduces the binding capacity to ATP-binding cassette transporter ABCA1 inhibiting the reverse cholesterol transport [21] an increase in apoC-III, apoA-IV and proinflammatory proteins as serum amyloid A or lipoprotein-associated phospholipase A2 that reduces their atheroprotective function and increase cardiovascular mortality, that explain the reduction in protective effect expected.

The present study has some limitations. The case and control design promotes some bias in data collection and hides some characteristics that can modify the course of the disease as comorbidities, nutritional status, adherence and adjustment treatment.

This is a preliminary study to determine the ability of TG/HDL-C and non-HDL-C/HDL-C ratio as predictors of death in Mexican population. The results obtained propose the capacity of TG/HDL-C ratio as a predictor of the risk of death in hemodialysis patients. A cohort study is proposed to evaluate TG/HDL-C ratio with the addition of some characteristics that impact in the lipid profile of patients as hypothyroidism, high carbohydrate diet, obesity, insulin resistance, treatments as steroids, immunosuppressive drugs, beta blockers, thiazide diuretics, and also is proposed and additional study to evaluate both ratios in 3 different RRT (peritoneal dialysis, hemodialysis and kidney transplant).

Conclusion

The non-HDL-C/HDL-C index has not shown utility as a predictor of mortality in chronic hemodialysis patients. The TG/HDL-C ratio ranges to 1.84 to 2.84 increasing de risk of death.

References

1. Lucas B, Taal MW (2023) Epidemiology and causes of chronic kidney disease. Med 51: 165-169. [Ref.]
2. Torres-Toledano M, Granados-García V, López Ocaña LR (2017) Carga de la enfermedad renal crónicaen México. Rev Med Inst Mex Seguro Soc 55: S118-S1123. [Ref.]
3. Agudelo-Botero M, Valdez-Ortiz R, Giraldo-Rodríguez L, González- Robledo MC, Mino-León D, et al. (2020) Overview of the burden of chronic kidney disease in México: secondary data analysis based on the Global Burden of Disease Study 2017. BMJ Open 10: 1-9. [Ref.]
4. Jankowski J, Floege J, Fliser D, Böhm M, Marx N (2021) Cardiovascular Disease in Chronic Kidney Disease: Pathophysiological Insights and Therapeutic Options. Circulation 143: 1157-1172. [Ref.]
5. Neovius M, Jacobson SH, Eriksson JK, Elinder CG, Hylander B (2014) Mortality in chronic kidney disease and renal replacement therapy: a population-based cohort study. BMJ Open 4: e004251. [Ref.]
6. RubinC, Nolin TD, Himmelfarb J (2007) Are biomarkers useful for assessing cardiovascular risk in patients with chronic kidney disease? Curr Opin Nephrol Hyperten 16: 506-511. [Ref.]
7. Deighan CJ, Caslake MJ, McConnell M, Boulton-Jones JM, Packard CJ (2000) Atherogenic lipoprotein phenotype in end-stage renal failure: Origin and extent of small dense low-density lipoprotein formation. Am J Kidney Dis 35: 852-862. [Ref.]
8. Gansevoort RT, Correa-Rotter R, Hemmelgarn BR, Jafar TH, Heerspink HJ, et al. (2013) Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and prevention. Lancet 382: 339-352. [Ref.]
9. Sonmez A, Yilmaz MI, Saglam M, Unal HU, Gok M, Cetinkaya H, et al. (2015) The role of plasma triglyceride/high-density lipoprotein cholesterol ratio to predict cardiovascular outcomes in chronic kidney disease. Lipids Health Dis. 14: 2-8.
10. Kim Y, Lee S, Lee Y, Kang MW, Park S, et al. (2021) Predictive value of triglyceride/high-density lipoprotein cholesterol for major clinical outcomes in advanced chronic kidney disease: a nationwide population-based study. Clin Kidney J 14: 1961-1968. [Ref.]
11. Chang TI, Streja E, Soohoo M, Kim TW, Rhee CM, et al. (2017) Association of Serum Triglyceride to HDL Cholesterol Ratio with All-Cause and Cardiovascular Mortality in Incident Hemodialysis Patients. Clin J Am Soc Nephrol 12: 591-602. [Ref.]
12. Chen HY, Tsai WC, Chiu YL, Hsu SP, Pai MF, et al. (2015) Triglyceride to High-Density Lipoprotein Cholesterol Ratio Predicts Cardiovascular Outcomes in Prevalent Dialysis Patients. Medicine (Baltimore) 94: e619. [Ref.]
13. Ulusoy S, Ozk G (2013) Lipid Abnormalities in Hemodialysis Patients. InTech 101-126. [Ref.]
14. Kalantar-Zadeh K, Block G, Humphreys MH, Kopple JD (2003) Reverse epidemiology of cardiovascular risk factors in maintenance dialysis patients. Kidney Int 63: 793-808. [Ref.]
15. Shoji T, Nishizawa Y, Kawagishi T, Tanaka M, Kawasaki K, et al. (1997) Atherogenic lipoprotein changes in the absence of hyperlipidemia in patients with chronic renal failure treated by hemodialysis. Atherosclerosis 131: 229-236. [Ref.]
16. Tsimihodimos V, Mitrogianni Z, Elisaf M (2011) Dyslipidemia Associated with Chronic Kidney Disease. Open Cardiovasc Med J 5: 41-48. [Ref.]
17. Qi L, Zhang A, Zhang Y, Ren Z, Zhao C, et al. (2024) Association between the triglyceride to high-density lipoprotein cholesterol ratio and mortality in Chinese maintenance haemodialysis patients: a retrospective cohort study. BMJ Open14: e078981. [Ref.]
18. Oh B, Sung J, Chun S (2019) Potentially modifiable blood triglyceride levels by the control of conventional risk factors. Lipids Health Dis 18: 222. [Ref.]
19. Van der Vusse GJ (2009) Albumin as fatty acid transporter. Drug Metab Pharmacokinet 24: 300-307. [Ref.]
20. Tang J, Wang L, Luo J, Xi D, Huang W, et al. (2021) Early albumin level and mortality in hemodialysis patients: a retrospective study. Ann Palliat Med 10: 10697-10705. [Ref.]
21. Bulbul MC, Dagel T, Afsar B, Ulusu NN, Kuwabara M, et al. (2018) Disorders of Lipid Metabolism in Chronic Kidney Disease. Blood Purif 46: 144-152.

Download Provisional PDF Here

 

Article Information

Article Type: RESEARCH ARTICLE

Citation: López-Cabrera Y, Hernández-Rivera JCH, Ramos-Gordillo M, Guillén-Graf AE, Hernández-Ayala RG, et al. (2025) Evaluation of Triglyceride/ HDL-Cholesterol and Non-HDL Cholesterol/HDL-Cholesterol Ratios as Mortality Predictors in Chronic Hemodialysis Patients. Int J Nephrol Kidney Fail 11(1): dx.doi.org/10.16966/2380-5498.251

Copyright: ©2025 López-Cabrera Y, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Publication history: 

Received date: 10 Jan, 2025

Accepted date: 20 Jan, 2025

Published date: 24 Jan, 2025