In maintenance hemodialysis patients, there were “U-shaped” relationships between serum albumin level and mortality or hospitalization, negative linear relationship between serum albumin level and hospitalization for infection.

doi:10.21203/rs.2.15824/v1

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In maintenance hemodialysis patients, there were “U-shaped” relationships between serum albumin level and mortality or hospitalization, negative linear relationship between serum albumin level and hospitalization for infection.

https://doi.org/10.21203/rs.2.15824/v1

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Background: Few studies are available on the non-linear association between serum albumin (S-Alb) level and prognosis in maintenance hemodialysis (MHD) patients. Methods: All stable MHD patients treated in our center from 2007 to 2011 were enrolled into this study. Demographics, laboratory data, hospitalization and mortality were collected; Cox regressive models were fitted to investigate predicting outcomes, restricted cubic splines (RCS) were allowing for non-linear association between S-Alb and prognosis. Results: S-Alb was independent protective factor for mortality, all-cause hospitalization, hospitalization for cardiovascular or cerebrovascular disease and hospitalization for infection. The relationships between S-Alb and mortality, all-cause hospitalization, hospitalization for cardiovascular or cerebrovascular disease were U-shaped; relationships between S-Alb and hospitalization for infection were negative linear relationships both in univariable Cox regression models and in multivariable Cox regression. Conclusions: In MHD population, there were “U-shaped” relationships between serum albumin level and mortality or hospitalization; the potential risks associated with excessive S-Alb should been taken into consideration. There was negative linear relationship between S-Alb and hospitalization for infection, S-Alb may be even more important in preventing infection in MHD population.

Urology & Nephrology

hemodialysis

serum albumin

mortality

hospitalization

infection

cardiovascular or cerebrovascular disease

S-Alb has mainly been considered a biomarker of visceral protein and nutrition status. In patients with end-stage renal disease (ESRD), hypoalbuminemia is a frequently and independently predictor for mortality and systemic inflammation[1, 2]; in dialysis patients, it is the strongest biomarker affect the patient’s prognosis among Ca-P-iPTH, acidosis, Kt/V and so on[3-5]. For the above reasons, S-Alb has been included in monthly blood testing in most dialysis centers. In 2000, the National Kidney Foundation Kidney Disease Outcomes Quality Initiative clinical practice guidelines for nutrition in chronic renal failure recommend that “patients on dialysis achieve a serum albumin level equal to or greater than the lower limit of the normal range (4.0 g/dl for the bromcresol green laboratory method) to ensure optimal nutrition and decrease risks of protein-energy wasting”[6]; since then, the S-Alb target of more than 4.0 g/dl is still being used today for MHD patients, few studies have discussed whether the upper limit should be set for S-Alb in MHD patients, few data are available on the non-linear association between serum albumin (S-Alb) level and prognosis in MHD patients.

Study Population and Data Source

All stable adult MHD patients in our center during the period January 1, 2007 through December 31, 2011, were included in this retrospective study. Inclusion criteria were age > 18 years and underwent MHD for at least 3 months, exclusion criteria were hospitalization within 3 months before the study, combined with uncured malignant tumor or active liver disease. The study was approved by the Ethics Committee of Qianfoshan Hospital, and all subjects gave their informed consent.

Demographic and biochemical data

Base-line and follow-up datas were collected from medical records. The following data were collected at base-line: demographic factors (age, sex, and vintage); whether comorbid diabetes; physical constitution (systolic blood pressure(SBP) and diastolic blood pressure(DBP) before single dialysis); hemoglobin(Hb) and serum biochemical data (albumin(Alb), creatinine(Cr), blood urea nitrogen(BUN), calcium(Ca), phosphorus(P), magnesium(Mg), intact parathyroid hormone(iPTH), triglyceride(TG), cholesterol(CH), low density lipoprotein(LDL).

Blood samples were drawn from dialysis pipeline immediately after initiation of single hemodialysis treatment and shipped to our central laboratory, where measurements were made using automated and standardized methods. The S-Alb level was determined with the BCG method; the normal reference range in this study was 4.0-5.5g/dl. The corrected total serum calcium (S-Ca) and serum magnesium (S-Mg) was calculated according to the following formula: corrected S-Ca (mmol/L) = measured S-Ca (mmol/L) + (40 – S-Alb [g/L]) × 0.02, S-Mg (mmol/L) = measured S-Mg (mmol/L) + (40 – S-Alb[g/L]) × 0.005.

Follow-up and study endpoints

All patients were followed up to the study endpoint, administrative censoring (including renal transplantation, switch to peritoneal dialysis, transfer to another HD center, loss to follow-up or withdrawal from treatment) or the end of the study follow-up period (31 July 2018). The primary study endpoint was mortality, the secondary endpoint was hospitalization. Causes of death and hospitalization were collected, for subgroup analysis. If a death or hospitalization had two or more potential causes, we generally ascribed to the initial presenting condition.

Statistical Analyses

Categorical data are presented as frequencies and percentages. Continuous variables are expressed as mean ± standard deviation (SD) for normally distributed variables and as median and interquartile range (IQR, 25th–75th percentile) for variables with skewed distribution.

All these above demographic and biochemical data were assessed as potential predictors of hospitalization and mortality outcomes by univariable and multivariable Cox regression. If there were 2 or more hospitalizations, the first hospitalization was taken into Cox regression analyses. The adjustments were as follows: Model 1 (case mix): sex, age and all parameters that were significant in univariable analysis comorbidities; Model 2 (bone mineral metabolism factors): sex, age, comorbid diabetes, S-Alb, corrected S-Ca, S-P, corrected S-Mg, iPTH; Model 3(classic cardiovascular and cerebrovascular risk factors) : sex, age, comorbid diabetes, SBP, DBP, S-Alb, TG, CH, LDL.

The non-liner relationships of base-line S-Alb levels and outcomes were evaluated by restricted cubic spline(RCS) fitting univariable or multivariable Cox model; 6 knots were set and percentiles were P5, P23, P41, P59, P77, P95, respectively. For RCS fitting multivariable Cox model, only model 1 was used respectively.

All statistical analyses were two-tailed and P value <0.05 was considered significant. RCS were conducted in Stata/IC 14 (StataCorp, College Station, TX), other analyses were performed using the SPSS version 13.0 (SPSS, Chicago, IL).

Demographic and biochemical data

Demographic and clinical characteristics of the total 230 MHD patients are depicted in Table 1. The median age was 56 years (range, 19-89 years). Male to female ratio was 1.1:1. Median time on hemodialysis was 3 months (range, 3-159 months). Sixty-nine (30%) patients combined diabetes mellitus. SBP pressure was 134.0(126, 142.25) mmHg, DBP was 74(68, 87) mmHg. Hb was 97.7±21.33 g/L, S-Alb was 38.25(33.78, 42) g/L, serum Cr was 755.3(510.55, 947.33)μmol/L, serum BUN was 27.15(20.18, 32.85)mmol/L, S-Ca was 2.23(2.11, 2.34)mmol/L, serum P was 1.84±0.59mmol/L, S-Mg was 1.15(1.02, 1.27)mmol/L, serum iPTH was 211(115.1, 369.2)pg/mL, serum TG was 1.14(0.88, 1.56) mmol/L, serum CH was 4.28(3.34,4.98) mmol/L, serum LDL was 2.47(1.96,3.09) mmol/L.

Predictors of mortality

Median follow-up times were 51.9months (range, 3-112.9months).

During follow-up, 74 deaths occurred median survival time was 43.3 months (range, 3.6-68.1 months); causes of death were: 33 (44.6%) cardiovascular or cerebrovascular disease, 15(20.3%) infections, 8(10.8%) carcinomas, 1 (1.4%) gastrointestinal bleedings, and 17(23%) unknown causes. Table 2 shows age (years; HR, 1.04; 95% CI, 1.02-1.06; P<0.000) was independent risk factor for mortality, S-Alb (g/L; HR, 0.94; 95% CI, 0.9-0.99; P=0.011) was independent protective factors for mortality

Predictors of hospitalization

There were all together 865 hospitalizations occurred, the median number of hospitalizations per patient-year was 0.72 (interquartile range: 0.23–1.60). The first four causes of hospitalization were: 278(32.1%) infections, 221(25.5%) cardiovascular or cerebrovascular disease, 28(3.2%) gastrointestinal bleedings, and 18 (2.1%) fractures. We created Cox regression models separately according to the first all-cause hospitalization, the first hospitalization for infection, and the first hospitalization for cardiovascular or cerebrovascular disease.

Table 3 shows S-Alb was independent protective factor for all-cause hospitalization. Table 4 shows S-Alb was independent protective factor of hospitalization for infection. Table 5 shows S-Alb were both independent protective factors of hospitalization for cardiovascular or cerebrovascular disease, except adjustment for bone mineral metabolism factors in model2.

Association between S-Alb and prognosis

Figure 1 shows the association between S-Alb and prognosis.

Relationships between S-Alb and mortality(Figure 1 a, b), all-cause hospitalization(Figure 1 c, d), hospitalization for cardiovascular or cerebrovascular disease(Figure 1 g, h) were U-shaped, lowest points of HR corresponds to S-Alb values of about 42g/L.

Either in univariable Cox regression models, or in multivariable Cox regression, relationships between S-Alb and hospitalization for infection were both negative linear relationships (Figure 1 e, f).

To our knowledge, the current retrospective study is the first single-center report discusses the potential upper limit of S-Alb in MHD patients. There were U-shaped relationships between S-Alb and mortality, all-cause hospitalization, hospitalization for cardiovascular or cerebrovascular disease.

Former studies and this study have confirmed that low S-Alb is associates with poor clinical outcome in MHD [7, 8]; this phenomenon may due to better nutrition and decreased inflammatory status [1, 9, 10]. However, there was no research on the reason why MHD patients with relatively higher S-Alb level had worse prognosis. In our view, there may be several reasons. First, to achieve higher S-Alb levels, higher protein diets are often required; which result in excessive metabolites (such as P, BUN and so on) that cannot be completely eliminated. The second, because of the Gibbs-Donnan effect, protein-bound uremic toxins are difficult to remove during hemodialysis [11-14].

Different from those above prognosis outcomes, a negative linear relationship between S-Alb and hospitalization for infection has been found in this study; which hints S-Alb may be even more important in preventing infection in MHD population. In 2009, de Mutsert R et al [10] described “association between serum albumin and mortality in dialysis patients is partly explained by inflammation, not by malnutrition, as measured with SGA and nPNA”. Mukai H et al [15] had also reported that “the mortality risk was increased in ESRD patients with low S-Alb and high CRP at baseline, but the risk was not increased in patients with low S-Alb and normal CRP, suggesting that the higher mortality associated with low S-Alb in ESRD to a large extent is dependent on concomitant presence of systemic inflammation”. Inflammation can cause low S-Alb though insufficient food intake and protein's consumption increases [16-18]; low S-Alb can cause inflammation though oxidative stress and decreased immune function. That is, low S-Alb and infection interact as both cause and effect in MHD population [19, 20].

In addition, more attentions have been paid to relationships between serum Mg levels and prognosis in MHD patients. Most studies have reported that lower Mg levels were associated with increased all-cause and cardiovascular mortality [21-24]. A rencent study[25] showed “hypomagnesaemia is not an independent risk factor for mortality in Japanese maintenance hemodialysis patients”. In our present cohort, S-Mg level was neither independent risk factor for mortality nor for hospitalization.

The limitation of this study is that neither indicator of inflammation(C-reactive protein) nor subjective global assessment was recorded for further analysis.

In our MHD retrospective cohort, S-Alb is the most important prognostic factor for patient's mortality or hospitalization. There were “U-shaped” relationships between S-Alb level and mortality or hospitalization; the potential risks associated with excessive S-Alb level should been taken into consideration. There was negative linear relationship between S-Alb and hospitalization for infection, S-Alb may be even more important in preventing infection in MHD population.

Alb	Albumin
BUN	Blood urea nitrogen
Ca	Calcium
CH	Cholesterol
Cr	Creatinine
DBP	Diastolic blood pressure
ESRD	End-stage renal disease
Hb	Hemoglobin
iPTH	intact parathyroid hormone
LDL	Low density lipoprotein
MHD	Maintenance hemodialysis
Mg	Magnesium
P	Phosphorus
RCS	Restricted cubic splines
S-Alb	Serum albumin
SDP	Systolic blood pressure
TG	Triglyceride

Acknowledgments

We would like to thank Dr Fang Tang, at center for data science in health and medicine, Shandong University, Jinan, China, for their valuable inputs in data analysis.

Authors’ contributions

XYJ and DMX participated in the study design. XYJ, XW, ZSW, NZ, YZ and PC acquired the data. XYJ, JC, XLK and YPL analysed the data. XYJ, YW and LW participated in the manuscript preparation. All authors read and approved the final manuscript.

Fundings

This work was supported by the National Natural Science Foundation of China (81970615 to Dongmei Xu)；the Natural Science Foundation of Shandong Province (ZR2019MH038 to Dongmei Xu)； the National Natural Science Foundation of China (81500555 to Yipeng Liu)；the National Natural Science Foundation of China (81600552 to Na Zhao)；the Third Project of Jinan City Science and Technology Development Plan (201503002 to Yipeng Liu)；the Medical Big Data Alliance of Blood Purification of Shandong Province (N/A)；the Young Taishan Scholars Program to Yipeng Liu.

Availability of data and materials

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

Ethics approval and consent to participate

The local independent ethics committee approved the study protocol. Need for consent was waived, as data was de-identified.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Table1. Demographic and Clinical Characteristics of MHD Patients

Characteristic	Total(N=230)
Male/female	121/109
Age (years)	56(42,70)
Vintage (months)	3(3, 5)
Comorbid diabetes, n(%)	69(30%)
Systolic blood pressure(mmHg)	134.0(126, 142.25)
Diastolic blood pressure(mmHg)	74(68, 87)
Hemoglobin(g/L)	97.7±21.33
Serum albumin(g/L)	38.25(33.78, 42)
Serum creatinine(μmol/L)	755.3(510.55, 947.33)
Serum urea nitrogen(mmol/L)	27.15(20.18, 32.85)
Serum calcium(mmol/L)	2.23(2.11, 2.34)
Serum phosphorus(mmol/L)	1.84±0.59
Serum magnesium(mmol/L)	1.15(1.02, 1.27)
Serum iPTH(pg/mL)	211(115.1, 369.2)
Serum triglyceride(mmol/L)	1.14(0.88, 1.56)
Serum cholesterol(mmol/L)	4.28(3.34,4.98)
Serum low density lipoprotein(mmol/L)	2.47(1.96,3.09)
Follow-up time (months)	51.9 (range, 3-112.9)
Death	74
survival time(months)	43.3 (range, 3.6-68.1)
Hospitalizations	865
number of hospitalizations per patient-year	0.72 (0.23,1.60)

Table 2. Prognostic significance on patient survival

Variable	Univariable Analysis		Multivariable Analysis (Model 1)		Multivariable Analysis (Model 2)		Multivariable Analysis (Model 3)
Variable	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Sex (male)	0.56(0.35-0.88)	.013	0.84(0.51-1.38)	.488	0.81(0.48-1.35)	.415	0.73(0.42-1.28)	.276
Age (years)	1.05(1.03-1.07)	<.001	1.04(1.02-1.06)	<.000	1.05(1.03-1.06)	<.001	1.04(1.01-1.06)	.002
Vintage (months)	1(0.99-1.01)	.534
Comorbid diabetes, n(%)	1.92(1.21-3.06)	.006	0.98(0.59-1.63)	.935	1.18(0.71-1.96)	.533	1.03(0.59-1.79)	.931
Systolic blood pressure(mmHg)	1.01(0.99-1.02)	.320					1.03(1.01-1.05)	.012
Diastolic blood pressure(mmHg)	0.97(0.96-0.99)	.005	1(0.98-1.02)	.799			0.97(0.93-1)	.066
Hemoglobin(g/L)	0.99(0.98-1)	.208
Serum albumin(g/L)	0.93(0.89-0.96)	<.001	0.94(0.9-0.99)	.011	0.95(0.9-0.99)	.013	0.94(0.89-0.99)	.013
Serum creatinine(μmol/L)	1(1-1)	<.001	1(1-1)	.181
Serum urea nitrogen(mmol/L)	0.97(0.94-0.99)	.009	0.99(0.95-1.02)	.422
Serum calcium(mmol/L)	2.43(0.76-7.72)	.132			1.35(0.39-4.69)	.641
Serum phosphorus(mmol/L)	0.6(0.4-0.91)	.016	1.37(0.79-2.38)	.259	1.04(0.64-1.7)	.880
Serum magnesium(mmol/L)	0.35(0.1-1.29)	.115			0.73(0.16-3.29)	.683
Serum iPTH(pg/mL)	1(1-1)	.457			1(1-1)	.319
Serum triglyceride(mmol/L)	1.01(1-1.02)	.129					1(0.99-1.02)	.521
Serum cholesterol(mmol/L)	0.96(0.8-1.16)	.675					0.94(0.66-1.34)	.729
Serum low density lipoprotein(mmol/L)	0.81(0.6-1.08)	.155					0.82(0.46-1.45)	.492

Model 1 (case mix): sex, age and all parameters that were significant in univariable analysis comorbidities; Model 2 (bone mineral metabolism factors): sex, age, comorbid diabetes, S-Alb, corrected S-Ca, S-P, corrected S-Mg,iPTH; Model 3(classic cardiovascular and cerebrovascular risk factors) : sex, age, comorbid diabetes, SBP, DBP, S-Alb, TG, CH, LDL.

Table 3. Prognostic significance on all-cause hospitalization

Variable	Univariable Analysis		Multivariable Analysis (Model 1)		Multivariable Analysis (Model 2)		Multivariable Analysis (Model 3)
Variable	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Sex (male)	0.95(0.71-1.27)	.722	1.07(0.78-1.47)	.688	1.01(0.74-1.39)	.945	0.96(0.68-1.35)	.810
Age (years)	1.02(1.01-1.03)	<.001	1.01(1-1.02)	.224	1.01(1-1.02)	.023	1.01(1-1.03)	.045
Vintage (months)	1(0.99-1)	.325
Comorbid diabetes, n(%)	1.71(1.26-2.33)	.001	1.23(0.87-1.74)	.249	1.26(0.89-1.79)	.196	1.23(0.86-1.75)	.259
Systolic blood pressure(mmHg)	1(0.99-1.01)	.858					1.01(0.99-1.02)	.309
Diastolic blood pressure(mmHg)	0.99(0.98-1)	.029	0.99(0.98-1.01)	.377			0.99(0.97-1.01)	.400
Hemoglobin(g/L)	1(0.99-1)	.522
Serum albumin(g/L)	0.95(0.93-0.97)	<.001	0.96(0.93-0.98)	.001	0.95(0.93-0.98)	<.001	0.95(0.92-0.98)	<.001
Serum creatinine(μmol/L)	1(1-1)	.001	1(1-1)	.610
Serum urea nitrogen(mmol/L)	1(0.99-1.02)	.641
Serum calcium(mmol/L)	1.2(0.61-2.36)	.594			0.92(0.46-1.84)	.807
Serum phosphorus(mmol/L)	0.84(0.65-1.08)	.168			1.17(0.87-1.56)	.302
Serum magnesium(mmol/L)	0.75(0.35-1.61)	.455			0.99(0.43-2.3)	.988
Serum iPTH(pg/mL)	1(1-1)	.013	1(1-1)	.281	1(1-1)	.190
Serum triglyceride(mmol/L)	1(0.99-1.01)	.740					1(0.99-1.01)	.775
Serum cholesterol(mmol/L)	1.02(0.91-1.15)	.676					0.94(0.73-1.23)	.668
Serum low density lipoprotein(mmol/L)	1.04(0.87-1.24)	.677					1.13(0.77-1.65)	.537

Table 4. Prognostic significance on hospitalization for infection

Variable	Univariable Analysis		Multivariable Analysis (Model 1)		Multivariable Analysis (Model 2)		Multivariable Analysis (Model 3)
Variable	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Sex (male)	0.92(0.61-1.37)	.668	1.2(0.77-1.86)	.428	1.01(0.74-1.39)	.945	0.91(0.56-1.49)	.705
Age (years)	1.02(1.01-1.03)	.005	1(0.98-1.02)	.862	1.01(1-1.02)	.023	1.01(0.98-1.03)	.560
Vintage (months)	1(0.99-1.01)	.832
Comorbid diabetes, n(%)	1.03(0.67-1.57)	.900			1.26(0.89-1.79)	.196	0.9(0.53-1.51)	.684
Systolic blood pressure(mmHg)	0.99(0.98-1)	.066					0.99(0.96-1.01)	.256
Diastolic blood pressure(mmHg)	0.98(0.96-1)	.014	0.98(0.97-1)	.085			0.99(0.96-1.02)	.495
Hemoglobin(g/L)	0.99(0.98-1)	.116
Serum albumin(g/L)	0.92(0.89-0.96)	<.001	0.93(0.9-0.97)	<.001	0.95(0.93-0.98)	<.001	0.92(0.89-0.96)	<.001
Serum creatinine(μmol/L)	1(1-1)	.004	1(1-1)	.105
Serum urea nitrogen(mmol/L)	0.99(0.96-1.01)	.224
Serum calcium(mmol/L)	0.86(0.29-2.54)	.781			0.92(0.46-1.84)	.807
Serum phosphorus(mmol/L)	0.76(0.53-1.09)	.138			1.17(0.87-1.56)	.302
Serum magnesium(mmol/L)	0.39(0.13-1.16)	.090			0.99(0.43-2.3)	.988
Serum iPTH(pg/mL)	1(1-1)	.003	1(1-1)	.075	1(1-1)	.190
Serum triglyceride(mmol/L)	1.12(0.9-1.39)	.305					1.02(0.76-1.38)	.894
Serum cholesterol(mmol/L)	1.03(0.85-1.26)	.755					0.87(0.54-1.4)	.557
Serum low density lipoprotein(mmol/L)	1.08(0.83-1.41)	.563					1.35(0.72-2.53)	.355

Table 5. Prognostic significance on hospitalization for cardiovascular or cerebrovascular disease

Variable	Univariable Analysis		Multivariable Analysis (Model 1)		Multivariable Analysis (Model 2)		Multivariable Analysis (Model 3)
Variable	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value	HR (95% CI)	P Value
Sex (male)	1.05(0.71-1.55)	.817	1.28(0.84-1.96)	.257	1.36(0.87-2.12)	.179	1.18(0.74-1.89)	.482
Age (years)	1.01(1-1.03)	.093	1(0.98-1.02)	.959	1.01(0.99-1.03)	.342	0.99(0.97-1.01)	.448
Vintage (months)	1(0.99-1.01)	.381
Comorbid diabetes, n(%)	1.52(1.01-2.28)	.044	1.72(1.1-2.68)	.017	1.59(0.99-2.57)	.056	1.81(1.13-2.9)	.013
Systolic blood pressure(mmHg)	0.99(0.98-1)	.095					1(0.98-1.02)	.701
Diastolic blood pressure(mmHg)	0.98(0.96-1)	.011	0.97(0.96-0.99)	.004			0.97(0.94-1.01)	.124
Hemoglobin(g/L)	1(0.99-1.01)	.626
Serum albumin(g/L)	0.96(0.93-1)	.028	0.96(0.92-1)	.043	0.97(0.94-1.01)	.150	0.95(0.91-1)	.029
Serum creatinine(μmol/L)	1(1-1)	.086
Serum urea nitrogen(mmol/L)	0.99(0.97-1.01)	.300
Serum calcium(mmol/L)	1.4(0.57-3.43)	.467			0.91(0.33-2.56)	.861
Serum phosphorus(mmol/L)	0.82(0.59-1.15)	.258			0.92(0.6-1.4)	.692
Serum magnesium(mmol/L)	0.99(0.34-2.85)	.985			1.31(0.37-4.66)	.673
Serum iPTH(pg/mL)	1(1-1)	.466			1(1-1)	.964
Serum triglyceride(mmol/L)	1(0.8-1.26)	.967					1(0.74-1.35)	.994
Serum cholesterol(mmol/L)	0.99(0.83-1.19)	.954					1.12(0.77-1.64)	.556
Serum low density lipoprotein(mmol/L)	0.93(0.73-1.19)	.569					0.8(0.48-1.34)	.396

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In maintenance hemodialysis patients, there were “U-shaped” relationships between serum albumin level and mortality or hospitalization, negative linear relationship between serum albumin level and hospitalization for infection.

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