Comparison of body composition in different dialysis states of end-stage renal disease and analysis of influencing factors

doi:10.21203/rs.3.rs-2576342/v1

Objective:To compare the differences in body composition in end-stage renal disease patients.

Methods:General data, biochemical data, and body composition indexes were collected to compare the differences in body composition indexes in ND, PD, and HD states. Spearman’s correlation and multiple linear stepwise regression analyses were performed to investigate the factors influencing the dependent variables.

Results: (1) Skeletal muscle index and phase angle were higher in the PD group than in the HD group (p < 0.05); total body water was lower in the PD and HD groups than in the CKD5-ND group (p < 0.05). (2) In the CKD5-ND and PD groups, the influencing factors of PHA were age, albumin, and prealbumin.

Conclusion: The patients with this central abdominal dialysis were better than those with HD in terms of nutrition and inflammation. PHA may be used to evaluate the nutritional status of patients with CKD5-ND and PD.

end-stage renal disease

body composition

peritoneal dialysis

hemodialysis

PHA

Chronic kidney disease (CKD) is a chronic progressive disease with a prevalence of 9.1%. Among 697.5 million cases of CKD worldwide, 0.07% develop end-stage renal disease (ESRD) ^[1]. Dialysis remains the primary treatment option for most ESRD patients^[2]. Patients with different dialysis states present varied pathophysiological characteristics, dialysis outcomes, quality of life, and long-term prognosis.

Bioelectrical impedance analysis (BIA) is rapid monitoring and assessment of patients’ nutritional status and fluid distribution based on the difference in the electrical conductivity of different tissue components, such as inorganic salts, proteins, water, and fat in the human body that are used to measure the fluid and nutrition-related indicators ^[3]. It is an accurate and reproducible method and is now widely used in the assessment of fluid and nutrition in ESRD patients^[4]. As one of the body composition indicators, phase angle (PHA) has become a valid measurement for the diagnosis, condition management, and prognosis assessment of many diseases, which reflect the nutritional and inflammatory status of the body. However, the biological significance of PHA is yet unclear, and there is no uniform reference value of PHA, limiting its application in clinical practice^[5]. In this study, we aimed to compare the differences in volume, nutrition, and inflammation of ESRD patients with CKD but under non-dialysis (ND) and different dialysis states using the BIA tool to assess the survival status of patients. We also investigated the factors influencing the PHA to provide a scientific basis for its clinical application, which is crucial for the clinical guidance to select the dialysis modalities for ESRD patients.

Subjects

A total of 634 patients with ESRD (including CKD5-ND, hemodialysis (HD), and peritoneal dialysis (PD)) treated at Hospital between October 2019 and March 2021 were included in this study.

Inclusion and exclusion criteria

Inclusion criteria

(1) 18 years ≤ age ≤ 80 years; (2) ESRD calculated estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m² according to MDRD formula, including CKD5-ND, HD, and PD patients.

Exclusion criteria

(1) PD time < 3 months; (2) HD time < 6 months; (3) combined treatment of both HD and PD; (4) combined with malignant diseases such as tuberculosis, tumor, or human immunodeficiency virus (HIV) infection; (5) serious infections such as peritonitis and tunnelitis and catheterization within the last 1 month; (6) combined multiorgan failure; (7) inability to test body composition due to foreign body implantation (metal medical device or pacemaker placed in the body) or amputation; (8) parathyroidectomy; (9) incomplete clinical data.

Research methodology

Clinical data collection

The demographic data, including age, sex, height, weight, and dialysis age, laboratory inflammatory index C-reactive protein (CRP), nutritional index albumin (ALB), prealbumin, and hemoglobin (Hb), and toxin index creatinine (Cr), blood urea nitrogen (BUN), and uric acid were collected from all patients. All the above indexes were obtained from the clinical laboratory of the Hospital.

Body composition measurement

The measurements were performed using an InBody 770 (Biospace, Seoul, Korea) multifrequency body composition analyzer by a trained technician. Patients were asked to rest quietly, empty their bladders at least 15 min before the test, and remain barefoot and in a standing position during the test, either on a ND day or at least 15 h after completion of an HD session for hemodialysis patients or in a dry abdomen for PD patients. All patients underwent body composition testing on the day of blood collection. The body composition parameters included body mass index (BMI), extracellular water (ECW), intracellular water (ICW), total body water (TBW), extracellular water/total body water (ECW/TBW), soft lean mass (SLM), skeletal muscle index (SMI), percent of body fat (PBF), visceral fat area (VFA), and PHA.

Statistical analysis

SPSS 26.0 (Chicago, IL, USA) was used for statistical analysis. The one-sample Kolmogorov–Smirnov method was used to test whether the data satisfied the normal distribution. (1) Descriptive analysis: Normally distributed data were expressed as mean ± standard deviation, while skewed data were expressed as median ± interquartile spacing. (2) Comparison of differences between groups: One-way analysis of variance (ANOVA) was performed to compare the differences between groups for multiple consecutive measures that satisfied normal distribution; for non-normally distributed measures, Mann–Whitney U test was used to compare the differences between two groups. (3) Correlation and regression analysis: Pearson’s correlation analysis was used for normally distributed measures, and Spearman’s correlation analysis was used for non-normally distributed measures. Subsequently, multiple linear stepwise regression analysis was used to explore the influence of the dependent variables. All the above tests were performed at a two-sided α=0.05 level.

Comparison of general information of ESRD patients with different dialysis status

In this study, 53.63% of patients were males; the mean age was 53.11 ± 12.63 years; the mean age of dialysis was 28.31 ± 37.48 months for HD patients and 33.01 ± 31.65 months for PD patients (Table 1), with no significant difference between the groups.

Comparison between groups of nutrition-related indicators in patients with different dialysis status

Compared to the CKD5-ND group, Hb, ALB, and prealbumin were higher in the PD group (p < 0.05). Compared to the CKD5-ND group, Hb was lower in the HD group (p < 0.05). Compared to the HD group, prealbumin levels were higher in the PD group (p < 0.05). BMI, SMI, and PHA were lower in the HD group compared to the CKD5-ND group (p < 0.05), and SMI and PHA were higher in the PD group compared to the HD group (p < 0.05) (Tables 2 and Table 3).

Intergroup comparison of inflammation-related indexes in patients with different dialysis status

Compared to the CKD5-ND group, the CRP was lower in the PD group (p < 0.05) and higher in the HD group (p < 0.01). Compared to the HD group, the CRP was lower in the PD group (p < 0.01). Compared to the CKD5-ND group, the PHA was higher in the PD group, but the comparison between the two groups was not statistically significant (p > 0.05). Compared to the CKD5-ND group, the PHA was significantly lower in the HD group (p < 0.05), and compared to the HD group, the PHA was higher in the PD group (p < 0.05) (Tables 2 and Table 3).

Comparison between groups of volume-related indexes in patients with different dialysis status

The comparison between the PD and the CKD5-ND groups did not find any significant difference in the brain natriuretic peptide (BNP) (p＞0.05). The BNP was higher in the HD group compared to the CKD5-ND group (p＜0.05). Compared to the HD group, the BNP was lower in the PD group (p＜0.05). In addition, TBW was higher in the PD group than in the HD group (p < 0.05), while ICW, ECW, and ECW/TBW were lower than those in the CKD5-ND group (p < 0.05); also, ECW/TBW was not statistically significant (p > 0.05) (Tables 2 and Table 3).

Factors influencing the PHA of different dialysis states of ESRD

In the overall ESRD population, Spearman’s correlation analysis revealed that height, weight, age, BMI, Hb, ALB, prealbumin, blood Cr, and triglycerides (TG) were positively correlated with PHA. The age on dialysis, low-density lipoprotein (LDL), high-density lipoprotein (HDL), CRP, and BNP were negatively correlated with PHA. Multiple linear stepwise regression analysis suggested that age, weight, ALB, and Hb were independent factors of PHA (Figure 1).

In the CKD5-ND group, body weight, Hb, ALB, and uric acid were positively correlated with PHA, and age and HDL were negatively correlated with PHA (p < 0.05). In the PD group, ALB and prealbumin were positively correlated with PHA, and age on dialysis and HDL were negatively correlated with PHA (p < 0.05). In the HD group, body weight, BMI, Hb, ALB, prealbumin, total protein, and blood Cr were significantly and positively correlated with PHA, while age was significantly and negatively correlated with PHA (p < 0.05). Multiple linear stepwise regression analysis showed that weight, Hb, ALB, uric acid, age, and HDL were independent factors of PHA in the CKD5-ND group, and age on dialysis, ALB, prealbumin, and HDL were independent factors on PHA in the PD group. Moreover, in the HD group, no significant regression equation was obtained after regression analysis, suggesting that none of the above factors are independent factors on PHA in this population. The above results suggested that age, ALB, and prealbumin were the main factors of PHA in the CKD5-ND and PD groups (Tables 4, Table 5, Table 6).

The results of this study showed that Hb, ALB, and prealbumin levels were significantly higher in the PD group than in the other two groups, and no significant differences were detected in ALB and prealbumin in the HD group compared to the CKD5-ND group. The comparison of the nutritional parameters of body composition, BMI, and SMI were the lowest in the HD group among the three groups, suggesting that the nutritional status of the PD group was better than that of the HD group. This phenomenon could be related to the HD membrane pore size, solute removal mechanism, and loss of nutrients, especially amino acids and proteins, during HD ^[6,7]. Also, the contact between blood and the dialysis membrane activates the complement and causes protein breakdown, resulting in malnutrition ^[8]. On the other hand, PD fluid contains glucose, and the glucose absorbed by peritoneal tissues from PD fluid can be used as an energy supply substance to improve protein-energy consumption. Moreover, our center has set up a special outpatient clinic, which regularly monitors the nutritional status of PD patients and provides timely dietary guidance to patients. Also, the active intervention of physicians plays a critical role in improving the nutritional status of patients.

CRP is a common serum marker of inflammatory status ^[9], and the PHA may also reflect the inflammatory status of the body ^[10]. The results of this study showed that in the ESRD population, HD patients had the highest CRP and the lowest PHA, suggesting a severe inflammatory state in HD patients. Many factors contribute to the inflammation in HD patients, such as biocompatibility of dialyzer membranes, dialysis access-related infections, and the application of impure dialysate containing cytokine-inducing substances labeled as endotoxins^[11,12]. Conversely, the extracorporeal dialysis tubing used for HD activates mononuclear macrophages and releases inflammatory factors. In addition, some dialysis membranes are unable to remove the inflammatory factors, such as CRP^[13], which in turn aggravates the inflammatory state of the patients. In contrast, PD patients use their peritoneum as the dialysis membrane, and the inflammatory factors in the blood enter the PD fluid through diffusion and ultrafiltration, which can remove urotoxins and macromolecular inflammatory substances from the body, and the inflammatory state is mild ^[14].

Volume overload is a common cause of hypertension, heart failure, and death in ESRD patients^[15], and timely and effective volume management is crucial to improving ESRD disease prognosis. The body composition index TBW reflects the total body fluid status, and the biochemical index BNP can assess the volume status ^[16]. The results of this study showed that in ESRD patients, TBW was significantly lower in the HD and PD groups than in the CKD5-ND group, indicating that dialysis has a better effect on water removal; this phenomenon was consistent with the existing clinical reports^[17]. The elevated plasma BNP levels in ESRD patients may be attributed to the hemodynamic stimulation or to other factors, such as anemia, obesity, cachexia, or impaired renal natriuretic peptide clearance ^[18]. The HD group exhibited higher BNP levels than the PD group, probably because HD patients are affected by long-term hemodynamic fluctuations and inflammatory status, and their cardiac structural and functional damage is more pronounced than that of the PD patients ^[19,20]. In addition, the lower Hb and poorer nutritional status of HD patients compared to PD patients might contribute to the higher BNP levels in HD patients, as suggested in the results of the previous study^[21].

PHA is obtained by bioimpedance analysis of the correlation between direct measurements of resistance (R) and electrical resistance (Xc) ^[22]; the values of these parameters depend on the total cell membrane mass and are relevant indicators of cellular health, body cell mass, and cell membrane integrity ^[23]. High PHA implies cell membrane integrity and cell mass, and it is hypothesized that PHA may reflect the nutritional status of cells to some extent. PHA is also associated with oxidative stress and inflammation ^[24], and inflammation can lead to cellular damage and disruption of cellular integrity, such that PHA can be used to assess the inflammatory state of the body. The results of the present study showed the lowest PHA in the HD group, while a previous study showed that patients in the PD group were better than those in the HD group in terms of nutrition and inflammatory status; this might explain why the PHA of patients in the HD group was lower than that of patients in the PD group. The results of the present study showed that the factors influencing PHA in patients in the CKD5-ND and PD groups were mainly age and nutrition-related indexes (ALB and prealbumin) as the cell quality changes with age; the better the nutritional status, the higher the cell quality, which is consistent with the previous findings ^[17,25].

In conclusion, body composition analysis can be a useful tool to assess the volume and nutritional status of ESRD patients; the present central abdominal dialysis patients were better than HD patients in terms of nutrition and inflammation. Notably, this is a cross-sectional, single-center study, which only reflects the management of ESRD patients in our center. Hence, a multicenter clinical study is needed to compare the advantages and disadvantages of different dialysis modalities. In the case of chronic ESRD, especially in dialysis patients, timely, scientific, and comprehensive healthcare management is crucial. In the future, non-invasive monitoring of body composition is expected to assess the nutritional and volume status of dialysis patients and provide guidance for clinical intervention.

Ethics approval and consent to participate：

We confirm that all methods were carried out in accordance with relevant guidelines and regulations. We confirm that all experimental protocols were approved by the Ethics Committee of the Third Xiangya Hospital of Central South University.We confirm that informed consent was obtained from all subjects or their legal guardians.

Consent for publication:

Consent for publication- Not applicable.

Availability of data and materials:

The datasets used during the current study are available from the corresponding author on reasonable request.

Competing interests:

Authors have no conflict of interest to declare.

Funding :

The authors acknowledge the support of Hunan Natural Science Foundation from the Department of Science and Technology in Hunan Province (No. 2020JJ8108).

Authors' contributions:

Yuxin Li and Juan Sun collected the data and drafted the manuscript; Jun Liu, and Shiqi Tang collected the data; Qin Ouyang and Xinyue Peng polished the manuscript; Jianwen Wang and Hong Wu designed the subject, guided the whole work, and polished the language.

Acknowledgements:

There is no acknowledgement.

GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2020 Feb 29;395(10225):709-733.
Bello AK, Levin A, Lunney M. Status of care for end stage kidney disease in countries and regions worldwide: international cross sectional survey. BMJ 2019; 367: l5873.
Rymarz A, Zajbt M, Jeznach-Steinhagen A, Woźniak-Kosek A, Niemczyk S. BodyCompositionand Biochemical Markers of Nutrition in Non-dialysis-Dependent Chronic Kidney Disease Patients. Adv Exp Med Biol. 2020;1251:81-89.
Gonzalez M, Barbosa-ailva G, Bielemamn M. Phase angle and its determinants in healthy subjects: influence of body composition. [J] .Am J Clin Nutr, 2016, 103: 712-6.
Barrea L, Muscogiuri G, Pugliese G, Laudisio D, de Alteriis G, Graziadio C, Colao A, Savastano S. Phase Angle as an Easy Diagnostic Tool of Meta-Inflammation for the Nutritionist. Nutrients. 2021 Apr 24;13(5):1446.
Van Gelder, M.; Abrahams, A.C.; Joles, J.A.; Kaysen, G.A.; Gerritsen, K. Albumin handling in differenthemodialysismodalities.Nephrol. Dial. T ransplant.2018,33, 906–913.
Salame, C.; Eaton, S.; Grimble, G.; Davenport, A. Protein Losses and Urea Nitrogen Underestimate TotalNitrogen Losses in Peritoneal Dialysis and Hemodialysis Patients.J. Ren. Nutr.2018,28, 317–323.
Poppelaars F, Faria B, Gaya da Costa M, Franssen CFM, van Son WJ, Berger SP, Daha MR, Seelen MA. The Complement System in Dialysis: A Forgotten Story? Front Immunol. 2018 Jan 25;9:71.
Herwald H, Egesten A. C-Reactive Protein: More than a Biomarker. J Innate Immun. 2021;13(5):257-258.
Mundstock E, Amaral MA, Baptista RR. Association between phase angle from bioelectrical impedance analysis and level of physical activity: Systematic review and meta-analysis. Clin Nutr. 2019 Aug;38(4):1504-1510.
Poppelaars, F.; Faria, B.; da Costa, M.G.; Franssen, C.F.M.; van Son, W.J.; Berger, S.P .; Daha, M.R.; Seelen, M.A.The Complement System in Dialysis: A Forgotten Story?Front. Immunol.2018,9, 71.
Abe, M.; Hamano, T.; Wada, A.; Nakai, S.; Masakane, I. Effect of dialyzer membrane materials on survival inchronic hemodialysis patients: Results from the annual survey of the Japanese Nationwide Dialysis Registry .PLoS ONE2017,12, e0184424.
Cobo G, Lindholm B, Stenvinkel P. Chronic inflammation in end-stage renal disease and dialysis. Nephrol Dial Transplant. 2018 Oct 1;33(suppl_3):iii35-iii40.
Deger SM, Hung AM, Gamboa JL, Siew ED, Ellis CD, Booker C, Sha F, Li H, Bian A, Stewart TG, Zent R, Mitch WE, Abumrad NN, Ikizler TA. Systemic inflammation is associated with exaggerated skeletal muscle protein catabolism in maintenance hemodialysis patients. JCI Insight. 2017 Nov 16;2(22):e95185.
Zoccali C, Moissl U, Chazot C, Mallamaci F, Tripepi G, Arkossy O, Wabel P, Stuard S. Chronic Fluid Overload and Mortality in ESRD. J Am Soc Nephrol. 2017 Aug;28(8):2491-2497.
Alexandrou ME, Balafa O, Sarafidis P. Assessment of Hydration Status in Peritoneal Dialysis Patients: Validity, Prognostic Value, Strengths, and Limitations of Available Techniques. Am J Nephrol. 2020;51(8):589-612.
Han BG, Lee JY, Kim JS, Yang JW. Clinical Significance of Phase Angle in Non-Dialysis CKD Stage 5 and Peritoneal Dialysis Patients. Nutrients. 2018 Sep 19;10(9):1331.
Niizuma S, Iwanaga Y, Yahata T, Miyazaki S. Renocardiovascular Biomarkers: from the Perspective of Managing Chronic Kidney Disease and Cardiovascular Disease. Front Cardiovasc Med. 2017 Mar 6;4:10.
Sun CY, Li CY, Sung JM, Cheng YY, Wu JL, Kuo YT, Chang YT. A comparison of the risk of acute myocardial infarction in patients receiving hemodialysis and peritoneal dialysis: A population-based, propensity score-matched cohort study. Atherosclerosis. 2020 Aug;307:130-138.
Aksu U, Aksu D, Gulcu O, Kalkan K, Topcu S, Aksakal E, Aksakal E, Sevimli S, Tanboga IH. The effect of dialysis type on left atrial functions in patients with end-stage renal failure: A propensity score-matched analysis. Echocardiography. 2018 Mar;35(3):308-313.
Kałużna-Oleksy M, Krysztofiak H, Migaj J, Wleklik M, Dudek M, Uchmanowicz I, Lesiak M, Straburzyńska-Migaj E. Relationship between Nutritional Status and Clinical and Biochemical Parameters in Hospitalized Patients with Heart Failure with Reduced Ejection Fraction, with 1-year Follow-Up. Nutrients. 2020 Aug 4;12(8):2330.
Mattiello R, Amaral MA, Mundstock E. Reference values for the phase angle of the electrical bioimpedance: Systematic review and meta-analysis involving more than 250,000 subjects. Clin Nutr. 2020 May;39(5):1411-1417.
Lukaski, H. C., Kyle, U. G., & Kondrup, J. (2017, Sep). Assessment of adult malnutrition and prognosis with bioelectrical impedance analysis: phase angle and impedance ratio. Curr Opin Clin Nutr Metab Care, 20(5), 330-339.
Tomeleri CM, Cavaglieri CR, de Souza MF. Phase angle is related with inflammatory and oxidative stress biomarkers in older women. Exp Gerontol. 2018 Feb;102:12-18.
Huang R, Wu M, Wu H. Lower phase angle measured by bioelectrical impedance analysis is a marker for increased mortality in incident continuous ambulatory peritoneal dialysis patients. [J] .J Ren Nutr, 2020, 30: 119-125.

Table 1. Comparison of general information of patients with different dialysis statuses in ESRD

Variables	Total	CKD5-ND	HD	PD
	N=634	N=275	N=81	N=278
Age (years)	53.11±12.63	54.17±13.27	56.32±13.48	51.12±11.39
Gender (male/female)	340/294	168/107	47/34	125/153
Height (cm)	161.73±7.78	162.46±7.79	162.98±8.39	160.65±7.46
Weight (kg)	60.93±11.02	62.16±11.34	59.97±11.90	60.00±10.33
Dialysis age (months)	-	-	28.31±37.48	33.01±31.65

Table 2. Comparison of biochemical indexes between groups of patients with different dialysis statuses in ESRD

Variables		Total	CKD5-ND	HD	PD	p-value
		N=634	N=275	N=81	N=278
Inflammatory indicators
	CRP(mg/L)	13.25±24.73	14.11±23.80	23.80±38.93^#	9.63±19.28^#&	<0.01^**
Nutritional indicators
	Hb (g/L)	90.38±20.72	84.69±19.60	92.42±22.00^#	95.41±20.06^#	<0.01^**
	ALB(g/L)	33.92±5.36	32.92±5.40	34.16±5.50	34.84±5.13^#	<0.01^**
	Prealbumin(mg/L)	352.03±169.69	283.54±90.15	262.34±87.56	447.11±199.73^#&	<0.01^**
Toxin Indicators
	BUN (mmol/L)	23.01±9.01	26.34±10.30	22.89±9.14^#	19.76±5.89^#&	<0.01^**
	Cr (μmol/L)	918.29±374.25	773.48±358.49	900.64±367.91^#	1066.69±332.93^#&	<0.01^**
Other biochemical indicators
	LDL-C (mmol/L)	2.41±0.87	2.34±0.89	2.08±0.84^#	2.58±0.82^#&	<0.01^**
	HDL-C (mmol/L)	1.18±0.32	1.11±0.29	1.07±0.30^#	1.27±0.33^#&	<0.01^**
	TC (mmol/L)	4.49±1.27	4.25±1.19	3.97±1.25	4.88±1.23^#&	<0.01^**
	TG (mmol/L)	1.77±1.21	1.67±1.21	1.76±1.17	1.87±1.22^#	<0.05^*
	BNP(pg/mL)	10807.61±11109.46	8534.44±10136.71	14935.31±10652.03^#	13304.40±12271.61^#	<0.01^**

Note: # indicates statistical difference compared to the CKD5-ND group; & indicates statistical difference compared to the HD group; CRP: C-reactive protein; Hb: hemoglobin; ALB: serum albumin; BUN: urea nitrogen; Cr: blood creatinine; LDL-C: low-density lipoprotein; HDL-C: high-density lipoprotein; TC: total cholesterol; TG: triglycerides. *p<0.05, **p<0.01 indicates statistical differences between the three groups for comparison.

Table 3. Comparison of differences between groups in the body composition of patients with different dialysis statuses in ESRD

Variables	Total	CKD5-ND	HD	PD	p-value
	N=634	N=275	N=81	N=278
ICW(L)	21.73±4.33	22.18±4.38	21.15±4.49	21.44±4.21	0.072
ECW(L)	14.22±2.96	14.51±3.00	14.03±3.16	13.99±2.84	0.087
TBW(L)	35.95±7.16	36.68±7.26	35.18±7.55	35.44±6.90	＜0.05^*
ECW/TBW	0.46±0.32	0.40±0.17	0.40±0.16	0.40±0.18	0.206
BMI(kg/m²)	23.22±3.46	23.48±3.56	22.46±3.57^#	23.18±3.31	＜0.05^*
SLM(kg)	45.92±9.13	46.87±9.25	44.90±9.60	45.28±8.81	0.066
SMI (kg/m²)	7.91±1.66	7.97±1.57	7.44±1.91^#	7.80±1.66^&	＜0.05^*
VFA (cm²)	56.85±31.64	57.85±32.46	65.27±41.28	53.41±26.82	0.183
PBF (%)	19.67±9.73	19.61±9.97	19.90±11.46	19.67±8.95	0.976
PHA (°)	5.05±1.36	5.11±1.24	4.60±1.81^#	5.12±1.31^&	＜0.01^**

Note: # indicates a statistical difference from CKD5-ND group; & indicates a statistical difference from the HD group; ICW: intracellular water; ECW: extracellular water; TBW: total body water; ECW/TBW: extracellular water/total water; BMI: body mass index; SLM: soft lean mass; SMI: skeletal muscle index; VFA: visceral fat area; PBF: body fat percentage (percent of body fat); PHA: phase angle. *p<0.05, **p<0.01 indicates statistical differences between the three groups.

Table 4. Regression analysis of factors influencing PHA in patients in the CKD5-ND group

		Standardization factor			Covariance statistics
Models		Beta	t	Significance	VIF
	(Constant)		2.286	<0.05
	Age	-0.241	-4.467	<0.01	1.112
	Weight	0.176	3.240	<0.01	1.130
	Hb	0.139	2.556	<0.05	1.120
	ALB	0.461	8.521	<0.01	1.118
	HDL-C	-0.146	-2.726	<0.01	1.089
	UA	0.112	2.085	<0.05	1.094

Dependent variable: PHA, adjusted R²=0.491

Table 5. Regression analysis of factors influencing PHA in PD group patients

		Standardization factor			Covariance statistics
Models		Beta	t	Significance	VIF
	(Constant)		6.835	<0.01
	Dialysis age	-0.162	-2.755	<0.01	1.084
	ALB	0.207	3.058	<0.01	1.432
	Prealbumin	0.131	1.992	<0.05	1.354
	HDL-C	-0.282	-4.838	<0.01	1.060

Dependent variable: PHA, adjusted R²=0.221

Table 6. Regression analysis of factors influencing PHA in HD group patients

	Correlation coefficient	Significance
Indicators	r	(p-value)
Age	-0.310^**	<0.01
Weight	0.235^*	<0.05
BMI	0.271^*	<0.05
Hb	0.231^*	<0.05
ALB	0.511^**	<0.01
Prealbumin	0.391^**	<0.01
TP	0.504^**	<0.01
Cr	0.321^**	<0.01

Note: Hb: hemoglobin; ALB: serum albumin; HDL-C: high-density lipoprotein; UA: uric acid; BMI. body mass index; *p<0.05; **p<0.01

No competing interests reported.

Comparison of body composition in different dialysis states of end-stage renal disease and analysis of influencing factors

Status:

Version 1

Abstract

Figures

Introduction

Subjects And Methods

Results

Discussion

Declarations

References

Tables

Additional Declarations

Status:

Version 1