Simplified Adequate Energy Requirements for Patients on Maintaince Hemodialysis in Taiwan: A Cross- Sectional Observation Study

  

    
 
    
Correct percentage    (%)
  
  

    
Male
    
Female
  
  

    
Alb = 3.5 g/dL
    
60.9
    
54.8
  
  

    
Cr = 10 mg/dL
    
60.9
    
54.8
  
  

    
TC: 150-199 mg/dL
    
60.9
    
61.9
  
  

    
nPNA = 1.2 g/kg
    
60.9
    
59.5
  
  

    
GNRI = 91.2 score
    
60.9
    
59.5
  
  

    
Alb: Albumin; Cr: Creatinine;    TC: Total Cholesterol; nPNA: Normalization of Protein Equivalent of total Nitrogen    Appearance; GNRI: Geriatric Nutritional Risk Index 
      
 
  

Table 6:  The correct percentage on five nutritional parameters.

Discussion

The patients in this study had similar mean ages and serum Alb levels compared with the population of HD patients in Taiwan. According to the 2013 Medical Service Quality of Dialysis [39], Taiwanese HD patients were 62.89 ± 13.31 years old, and the mean serum Alb level was 3.9 g/dL. 10.2 percent of Taiwanese HD patients have serum Alb levels lower than 3.5 g/dL. Taipei has the highest number of HD patients in Taiwan. Therefore, the characteristics of patients in this study could represent the population of Taiwanese HD patients.

In our study, nutritional status showed no significant difference between participants whether or not their DEI was lower than the recommended K/DOQI values. Several studies showed that energy expenditure of patients undergoing maintenance HD is similar to other healthy individuals [4-6]. Some studies have demonstrated a 20% increase in energy expenditure during HD [7]. Slomowitz et al. established the requirements for DEI in a study that examined 6 HD patients [8]. These 6 HD patients ingested 25, 35, and 45 kcal/kg/day and had a DPI of 1.13 g/kg/day for 21 days each. The experts used a regression equation to indicate that the mean DEI necessary to maintain both neutral nitrogen balance and unchanging body composition was approximate to 35 kcal/kg/day [8]. Based on this study, the NKF KDOQI guideline suggests that the energy requirements (ERs) of HD patients are approximately similar to normal adults of the same age who are engaged in mild daily physical activity, as indicated in the Recommended Dietary Allowances. This energy recommendation is 35 kcal/kg/day for HD patients < 60 years old and 30 to 35 kcal/kg/day for HD patients = 60 years old [5,9,10]. However, no Asian patients were recruited in previous studies, and the body compositions and ERs differ among various ethnicities. Because of various differences in ethnicity, dietary habits, and physical activity between Taiwanese and Americans, the energy recommendations of the 2012 edition of the Dietary Reference Intakes (DRIs) in Taiwan [32,33] are lower than those in the United States [34,35]. The energy recommendation of the K/DOQI is might potentially higher than necessary for Taiwanese HD patients.

The average DEI was about 23 kcal/kg/day in current study. The majority of studies in Asia and elsewhere have demonstrated the similar result with our study, the DEI was lower than the recommended K/DOQI values [12-16,40-43]. The mean DEI of HD patients in the Europe and America area were 22.8–29.0 kcal/kg/day [44]. In Japan, in Ichikawa et al., the nutritional status and the body composition were compared among 4 groups of patients in each gender that were divided by the combination of DEI and DPI; high energy (HE)/high protein (HP), HE/low protein (LP), low energy (LE)/HP and LE/ LP groups. HE means DEI?30 kcal/kg IBW/day and HP means nPNA?1.0 g/kg IBW/day. In the two low energy groups (LE/HP and LE/LP) were approximately 24.2–25.0 kcal/kg BW/d, the mean serum albumin value is 3.7–3.8 g/dL. When they compared the serum albumin and other biochemical indices among the 4 groups, except for minor exceptions they were not significantly different [16]. In Taiwan, in Hung and Tarng, the mean DEI and albumin are 29 kcal/ kg BW/d and 3.8 g/kg BW/day at baseline, when increasing energy intakes above K/DOQI guidelines recommendations, it appears to increase body fat mass and subsequently increase homeostasis model assessment of insulin resistance (HOMA-IR) and might worsen insulin resistance and other associated metabolic disorders [14]. There are several studies proposed that strategies to attenuate adverse metabolic responses without negating the beneficial effects of increases in energy intake need to be evaluated in future studies [45- 46]. In Thus, we suggest that increasing energy intakes above the K/ DOQI guidelines are might not suitable for Taiwanese HD patients.

The DEI (kcal/kg/day) differed significantly with weight and sex (Table 1), and the DEI had a significant linear regression with DPI (P< .0001; Figure 2). This is consistent with previous studies [11,12,16,36]. The majority of previous studies have determined a significant negative correlation between age and DEI [11,12,41,47]. Morley founded that reducing food intake with aging is considered to the decrease in physical activity and early satiation that occurs in response to large meals and a decrease in snacking between meals [48], and it was similar with the study by Wakimoto and Block [49]. Some studies of the general population have shown that multiple factors, such as decreased gastric fundal compliance, lead to rapid antral filling [50], decreased ghrelin levels [51], or high basal levels of cholecystokinin [52], which are involved in the pathogenesis of anorexia of aging [12].

Our results were similar to those of the Nutritional and Inflammatory Evaluation in Dialysis (NIED) Study (n = 893), showing that DPI positively correlated with dietary potassium intake and dietary potassium intake positively correlated with serum potassium levels [53]. Kovesdy et al. used nPNA to represent DPI, determining that the nPNA was positively correlated with serum potassium level [54]. However, some previous studies have suggested that malnourished HD patients have muscle protein degradation, which leads to potassium release from the muscle protein and explains why HD patients show increased serum K concentrations [55].

To maintain an ideal body weight and a healthy nutritional status, the optimal AER is approximate to 24.6 kcal/kg/day for males and 21.0 kcal/kg/day for females. Those particpants had DEI reached AER, but they showed not significant improvement in nutritional status in the follow-up compared with the baseline. However, in male patients = 60 years old, the serum Alb values and GNRI scores in the follow-up increased from the baseline, although non-significantly. We suggest that the proposed AER is appropriate for maintaining a healthy nutritional status.

Measuring energy expenditure is the most accurate method for assessing ERs. The common methods for measuring energy expenditure are indirect calorimetry or prediction equations. Compared with indirect calorimetry, predictive equations are easily accessible, inexpensive, and require no specialized equipment [56,57]. Although numerous nutritional authorities have encouraged using the Harris and Benedict equation or the Schofield equation [58,59], these methods could reduce the level of accuracy among patients with different diseases. In Kamimura et al., both the Harris and Benedict and Schofield equations overestimated the resting energy expenditures of HD patients, but the errors were minimized by the presence of comorbidities [57]. To date, few studies have addressed the reliability of energy prediction equations for HD patients. When more recent studies were reviewed, there is a significant gap of knowledge regarding the accurate estimation of energy needs for patients undergoing HD.

Our study is advantageous because we develop population and disease-specific equations to adequately estimate the AER of HD patients Taiwan. The study populations are Taiwanese HD patients, compared with other common energy prediction equation, it will reduce the body compositions and AER differ among various ethnicities and enhance the level of accuracy among HD patients. We used the simple linear regression analysis to examine correlation between DEI (dependent variable) and demographic, anthropometric and biomedical variables (independent variable). And using multiple linear regression analysis with stepwise selection to evaluate the factors affecting DEI, then consider and adjust the factor which will reduce the level of accuracy for the result of prediction equation, selection of an appropriate regression model to derive the adequate energy prediction equation. This is the first paper to derive the energy prediction equation for HD patients in Taiwan.

    

    

    Figure 3:  Correlation between dietary protein and energy intake.