Bioelectrical Impedance Analysis-derived Phase Angle as a Determinant of Protein-energy Wasting, Frailty, and Worse Outcome in Maintenance Hemodialysis Patients: retrospective cohort study


 Background

To evaluate the relationship between phase angle (PA) measured by bioimpedance electrical analysis and protein-energy wasting (PEW) or frailty, and its impact on 2-year mortality in patients with hemodialysis (HD).
Methods

This retrospective observational study included 116 adult HD patients (35% female, 64 ± 12 years of age) in a single dialysis center. Patients were classified according to the PA quartiles into four groups (quartile 1, lowest; quartile 4, highest). International Society of Renal Nutrition and Metabolism (ISRNM) criteria and Japanese version of Cardiovascular Health Study (J-CHS) criteria were used to identify PEW and frailty.
Results

The lower PA group was associated with a greater risk of PEW (35% vs. 24% vs. 21% vs. 3%; p = 0.032), frailty (59% vs. 40% vs. 21% vs. 3%; p < 0.001). In multivariate logistic regression analysis, the first quartile group (PA < 3.7°) was at a significantly greater risk of both PEW and frailty compared with the fourth quartile group (PA ≥ 5.0°) after adjusting for other confounding factors. In addition, Kaplan-Meier survival analysis showed a worse survival rate in the first quartile group than in the third quartile group (PA4.2-5.0°) and fourth quartile group (Log-rank test p = 0.05, respectively). The Cox regression analysis found that the first quartile group had a significantly greater risk of all-cause mortality than the patients in the fourth quartile group (HR 5.461 95%CI 1.180–25.280).
Conclusions

Lower PA was associated with a greater risk of PEW and frailty and found to have prognostic significance for 2-year all-cause mortality in HD patients.


Introduction
Protein-energy wasting (PEW), de ned as the loss of somatic and circulation body protein and energy reserves, is a common complication among hemodialysis (HD) patients. 1 Frailty can be de ned as a biological syndrome of decreased reserve and resistance to stressors that results from cumulative decline across multiple physiological systems and is highly prevalent in patients with HD. HD patients accompanied by PEW or frailty are associated with accelerated biological ageing, and an increased risk of death. 1,2 A more recent proposal suggests early screening and diagnosis of PEW and frailty are important in clinical practice among HD patients. [1][2][3] Bioimpedance electrical analysis (BIA) is a noninvasive, validated assessment of body composition and hydration status in patients with chronic kidney disease (CKD) and in HD patients. Phase angle (PA) measured by BIA re ects the resistance and reaction of the body in response to the application of an external current. A lower PA level indicates decreased cell integrity or cell death, whereas higher PA suggests large quantities of intact cell membranes. 4 Moreover, PA has been recently found to be a predictor of survival in many clinical situations. 5 However, the prognostic signi cance of PA for PEW, frailty, and all-cause mortality remains uncertain among HD patients. The main purpose of the present study was to assess the validity of PA in predicting PEW, frailty, and all-cause mortality in patients with HD.

Subjects
The present study included 116 adult HD patients (35% female, 64 ± 12 years of age) from a single unit of the Meisei-kai Toyo Clinic Yachimata, Chiba, Japan between January 2018 and March 2018. Patients were eligible to participate if they were over 18 years of age, had received maintenance HD at least 3 times per week for more than 6 months, and had no contraindications for BIA including patients with pacemakers or were not limbless. The exclusion criteria of present study were comorbidities malignant tumors and recent surgical intervention that might in uence nutritional or functional status. Study collaborators interviewed patients before or during a HD session, obtained recent clinical and laboratory data from medical records, and measured muscle strength and physical performance prior to the start of the HD session. In addition, study collaborators measured the body composition using a BIA after a midweek dialysis session.

Clinical outcomes and other criteria
All-cause mortality during 2-year follow-up periods were collected using medical records or the hospital database. Cardiovascular (CV) risk score was calculated using new risk model developed by Japan Dialysis Outcomes and Practice Patterns Study (J-DOPPS) 6 . This CV risk model had a more accurate dose-dependent association with observed CV events than the Framingham risk score among HD patients. The J-DOPPS CV risk model contained only six variables: age, diabetes mellitus, history of CV events, dialysis time per session, phosphorus level, and albumin level, ranging from 0 to 20 points with higher scores re ecting greater risk of CV events.

Diagnosis Of Protein-energy Wasting
International Society of Renal Nutrition and Metabolism (ISRNM) criteria were used to identify PEW, 7 which has been described elsewhere. 8 PEW was scored as the grading of 1 selected item in each of the four categories of wasting syndrome as follows: serum albumin, body mass index (BMI) or unintentional weight loss, pre-dialysis serum creatinine normalized by the body surface area (sCr/BSA), and normalized protein nitrogen appearance (nPNA). The cutoff values were as follows: serum albumin, 3.8 g/dL; BMI, 23 kg/m 2 or unintentional weight loss (5% over 3 months or 10% over 6 months); sCr/BSA, 380 µmol/L/m 2 ; and nPNA, 0.8 g/kg per day. BSA was estimated by the following formula: A lower value than the cutoff value was scored as 1 point, and the PEW score was calculated as the sum of the four-item score. PEW was de ned as a PEW score ≥ 3 points.

Diagnosis Of Frailty
Frailty was evaluated based on the Japanese version of Cardiovascular Health Study (J-CHS) criteria consisting of 5 components: weight loss, exhaustion, low physical activity, slowness and weakness. 9 (1) Weight loss was evaluated using the question "Have you lost 2 kg or more in the past 6 months?". (2) Exhaustion was measured using the question: "In the past 2 weeks, have you felt tired without a reason ?". (3) Low physical activity was measured using the two questions: "Do you engage in moderate levels of physical exercise or sports aimed at health?", and "Do you engage in low levels of physical exercise aimed at health?". (4) Slowness was measured using usual gait speed: patients were asked to 5 m-walk at their comfortable pace using any walking aids to maintain balance and function. (5) Weakness was evaluated by measuring handgrip strength in the sitting position. The J-CHS comprises the following: (1) Weight loss: 1 point for "yes" to the question; (2) Exhaustion: 1 point for "yes" to the question; (3) Low physical activity: 1 point for "no" to both questions; (4) Slowness: 1point if gait speed < 1.0 m/s; (5) Weakness: 1point if handgrip strength < 26 kg in men and < 18 kg in women. Summing up the J-CHS scores, we calculated a total J-CHS score; a cut off of ≥ 3 was used to identify frailty.

Bioelectrical Impedance Analysis
The seca mBCA515 (seca®, Hamburg, Germany), an integrated platform with a handrail system was used. Electrodes were placed in the ascending handrail, of which two were chosen depending on the subject's height. Another two pairs of electrodes contacted the soles of the feet. The prediction equations for total body water, and extracellular water (ECW) were validated by a prior study. 10 Resistance (R), the opposition of an ionic solution in both intra and extracellular spaces and reactance (Xc), representing the capacitance from cell membranes values obtained at 5 and 50 kHz for different body segments were used in the prediction equations. BIA was performed under standardized conditions according to the manufacturer's protocol. The PA was calculated using the following equation: PA (degree) = arctan (Xc/R) × (180/π)), is related to body cell mass and soft tissue composition.
To examine the PA values adjusting for age, sex, and body mass index, the PA values were converted into s.d. score by the following equation: Where X is the observed value, average X is the mean of the normal value at the respective age, sex, and body mass index, and s.d. is the standard deviation from the mean.

Statistical Analysis
Continuous variables are expressed at mean ± standard deviation and as counts and percentages as appropriate. For the comparison of continuous variables among PA groups, one-way analysis of variance was used, and for categorical variables, the Pearson chi-square test was performed. To adjust for effects due to potential confounders for PA, multivariate logistic regression models of PEW, and frailty were performed, and odds ratios (ORs) and 95% con dence intervals (95% CI) were determined. A Kaplan-Meier survival analysis with the log-rank signi cance test, and univariate Cox regression analysis were performed. The PA ≥ 5.0° (fourth quartile group) was considered the reference for this analysis. In the analysis for the CV event risk, we compared the CV event risk model score among PA groups using Kruskal-Wallis test. Statistical analyses were performed using SPSS software, version 21, and in all statistical calculations, a two-tailed p < 0.05 was considered statistically signi cant.
The clinical characteristics of the study population according PA groups are shown in Table 1. HD patients with lower PA were signi cantly older, had a higher proportion of females, and lower BMI, serum creatinine level, albumin level, modi ed creatinine index, and handgrip strength. Our ndings demonstrated that 35% of patients in the rst quartile group, 24% in the second quartile group, 21% in the third quartile group, and 3% in the fourth quartile group exhibited PEW based on ISRNM criteria (p = 0.032). Moreover, the prevalence of frailty was 59% in the rst quartile group, 40% in the second quartile group, 21% in the third quartile group, and 3% in the fourth quartile group (p < 0.001). The remaining clinical variables were not signi cantly different among PA groups.      BMI body mass index, HD hemodialysis, Hb hemoglobin, sCr serum creatinine, BUN blood urine nitrogen, Alb albumin, P phosphorus, Ca calcium, K potassium, CRP C-reactive protein, KT/V Kdialyzer clearance of urea, t dialysis time, V volume of distribution of urea, nPNA normalized protein nitrogen appearance, SNAQ Simpli ed Nutritional Appetite Questionnaire, PA phase angle, SDS standard deviation score, ECT extracellular water, TBW total body water, SPPB short physical performance battery, PEW protein energy wasting. Figure 2 shows the relationship between phase angle and four quartile subgroups of CV risk model score among HD patients. The rst quartile and second quartile groups were signi cantly higher CV risk score compared with forth quartile groups (p = 0.001 and p = 0.003).

Discussion
PEW and frailty are common complication associated with functional decline, and worse prognosis in HD patients. 7,11,12 The present study demonstrated that a low PA measured by BIA as a simple alternative screening tool is an independent predictor of PEW and frailty as well as worse outcome in HD patients.
The biological meaning of the PA remains uncertain; however, it seems to re ect body cell mass, or cell membrane function. 5 Increased ECW is associated with poor nutritional status, and reduced total body water (TBW), an indicator of lower body cellular mass. Therefore, an increase in the ECW/TBW may be explained by malnutrition or skeletal muscle mass loss, as well as by uid overload status. 13 Our ndings also demonstrated that lower PA tended to have a signi cantly higher ECW/TBW ratio among HD patients. Moreover, a low PA showed a tendency for association with lower BMI, hand grip strength, and higher ECW-TBW and C-reactive protein levels, which are included in the PEW or frailty diagnostic criteria and were consistent with results from prior studies. 14,15 Moreover, a lower PA correlated with PEW, the highest OR in the multivariate models was 10.967 and 11.099 in the rst quartile group compared to the reference group (fourth quartile group). Ruperto et al. subsequently con rmed that PA < 4° was an independent risk predictor for HD patients with PEW, 16 and is in line with our results. Thus, we also recognized that a low PA was an important indicator of malnutrition and hydration in HD patients. In addition, we showed that a low PA was associated with low TBW as an indicator of skeletal muscle mass in HD patients. Moreover, low PA was a greater risk factor for frailty even after adjusting for other clinical indicators. Several prior studies have reported an association between low PA and frailty phenomenon in older subjects, 17,18 or cardiac surgery patients, 19 although very few studies have focused on HD patients. 20 In the present study, we also determined that low PA is a representative comprehensive biomarker of malnutrition, skeletal muscle wasting, frailty, as well as hydration in HD patients. Thus, we propose that regular screening would be essential to monitor the progression of PEW or frailty over time, and to avoid the development of the vicious cycle of PEW or frailty. Regular screening may help in the early identi cation of patients accompanied by PEW or frailty when they are the most treatable as well as provide prognostic information. We therefore suggest that PA could be a useful, simple indicator to predict PEW, frailty, and all-cause mortality among HD patients.

Study Limitations
Several limitations of our present study should be noted. First, our ndings are limited to a relatively small number of patients at a single HD center, though most of the results are comparable to those from prior clinical studies. The small sample size study may not allow su cient statistical power, therefore we could not perform the multivariate cox regression analyses in order to evaluate the signi cant prognostic factors among HD patients; further studies are therefore needed to assess outcomes. Second, it has suggested that PEW is cachexia and should be termed kidney disease cachexia as a continuum with PEW rst followed by cachexia. Our ndings are limited to a small number of patients with severe PEW or kidney disease cachexia, therefore we could not assess the relationship between phase angle and severity of PEW including kidney disease cachexia. Future research needs to evaluate the diagnostic, prognostic, and predictive accuracy of phase angle on severe PEW or kidney disease cachexia status.
In conclusion, PA could be a useful, simple indicator to predict PEW, frailty, and all-cause mortality among HD patients. Lower PA was associated with a greater risk of PEW and frailty and found to have prognostic signi cance for all-cause mortality in hemodialysis patients. ORs, odds ratios; PA, Phase angle; PEW, Protein-energy wasting; SDS, standard deviation score; TBW, total body water.

Declarations
Ethics approval and consent to participate This study was approved by the institutional review board at the Meisei-kai Toyo Clinic, Chiba, Japan, and informed consent was obtained before data collection. The ethics committee granted approval to waive the requirement for written informed consent for the additional follow-up from 2018-2020 because of the retrospective nature of this study.

Consent for publication
Not applicable Availability of data and materials The data that support the ndings of the study are not publicly available due to privacy restrictions (the data contains information that could compromise the privacy of the study participants).  Phase angle and CV risk model score developed by J-DOPPS among HD patients