Secondary Logo

Journal Logo

Original Article

The impact of malnutritional status on survival in elderly hemodialysis patients

Tsai, Ming-Tsuna,b; Liu, Hsiang-Chunga; Huang, Tung-Poa,*

Author Information
Journal of the Chinese Medical Association: June 2016 - Volume 79 - Issue 6 - p 309-313
doi: 10.1016/j.jcma.2016.01.015

    Abstract

    1. Introduction

    Similar to many other developed countries, the population in Taiwan is rapidly aging. This demographic change will have a major impact on the rise in prevalence of chronic illnesses. Aging is associated with several other risk factors, including hypertension, diabetes mellitus, obesity, and cardiovascular disease, and may contribute to the development and progression of chronic kidney disease.1,2 Yang and Hwang3 revealed that the elderly constituted the major proportion of patients with end-stage renal disease (ESRD) in Taiwan. Moreover, protein-energy wasting (PEW), a state of loss of body protein mass and energy fuels, is prevalent and associated with increased mortality in elderly ESRD patients.4,5 Routine nutritional evaluation is strongly recommended for timely identification, prevention, and treatment of malnutrition in all elderly dialysis patients. Because PEW consists of many causes and clinical manifestations, a gold standard method is currently not available for diagnosis of this entity.6

    The geriatric nutritional risk index (GNRI), which is calculated from height, body weight, and serum albumin, was initially proposed to predict nutrition-related complications in hospitalized elderly patients.7 Due to its simplicity, GNRI is widely applied in various clinical settings.8,9 Recently, the GNRI was reportedly used to successfully assess the nutritional status and predict long-term outcome in ESRD patients.10,11 However, the validity of GNRI is examined mainly in adult dialysis patients. Whether the GNRI could predict mortality in geriatric ESRD patients remains unclear. Therefore, we performed a single-center, prospective cohort study to investigate the predictive value of the GNRI for overall mortality among elderly hemodialysis (HD) patients.

    2. Methods

    2.1. Ethics statement

    The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board of the Changhua Christian Hospital, Changhua County, Taiwan (CCHIRB-140904). Informed consent was obtained in written form from all participants before enrollment.

    2.2. Study design

    The study recruited a cohort of patients receiving HD therapy at a single dialysis unit from July 1, 2008 to December 31, 2008. Initially, 119 patients older than 65 years and ongoing dialysis for ≥6 months were screened. The following patients were excluded from the study: (1) those with inadequate dialysis defined as Kt/V urea <1.2 (n = 2); (2) those on dialysis for <12 h/wk (n = 3); and (3) patients with clinical conditions of infectious disease (n = 1), malignancy (n = 5), or hepatobiliary disease (n = 4). Finally, 104 clinically stable patients (54 men and 50 women; mean age 72 years) were enrolled and followed up until December 31, 2013.

    All patients received HD therapy three times weekly with a standard bicarbonate-buffered dialysate bath utilizing disposable biocompatible dialyzers with a membrane surface area of 1.6–1.7 m2. The mean dialysis duration before study entry was 64 months. No major adjustments were made in terms of dialysis treatments or protocols during this follow-up period. A thorough medical history of all patients was taken at the beginning of study. The presence of cardiovascular disease (CVD) was defined as a medical history, clinical symptoms, or findings of congestive heart failure, arrhythmia, coronary artery, cerebrovascular, and/or peripheral arterial disease. The primary endpoint was all-cause mortality from the time of inclusion.

    2.3. GNRI

    The GNRI is calculated incorporating serum albumin levels, body weight, and height by modifying the nutritional risk index for elderly patients, as reported by Bouillanne et al.7 The GNRI equation is as follows:

    The ideal body weight was calculated from the height and a body mass index (BMI) of 22 kg/m2 because of its validity and its reported association with the lowest mortality in the Asian population.12,13 Body weight/ideal body weight was set to 1 when the patient's body weight exceeded the ideal body weight. The cut-off value of GNRI for predicting mortality was derived from creating a receiver operating characteristic (ROC) curve. The area under the ROC curve defined the probability for discriminating risk of mortality. The best cutoff with the highest sensitivity and lowest 1 – specificity for GNRI was 92 (Table 1).

    Table 1
    Table 1:
    Areas under receiver operating characteristic (ROC) curve and cutoff values of geriatric nutritional risk index (GNRI), serum albumin, body mass index (BMI), and body weight with sensitivity and specificity for prediction of mortality.

    Dietary protein intake was estimated by calculating normalized protein catabolic rate from the urea generation rate by using single-pool urea kinetics.14 Body weight was determined as dry weight, and measured subsequent to each dialysis session. Blood pressure was measured at the beginning of each HD session with a standard sphygmomanometer in the nonaccess arm by dialysis staff while the patient was resting for at least 5 minutes with both feet on the floor. Patient response to erythropoietin treatment was examined using erythropoietin resistance index (ERI), defined as the weekly weight-adjusted erythropoietin dose (U/kg/wk) divided by hemoglobin level (g/dL).

    2.4. Laboratory measurements

    All blood samples were taken from patients who had fasted overnight before the mid-week dialysis session. Serum levels of high-sensitivity C-reactive protein (hs-CRP) were determined by utilizing an immunoturbidimetric assay and rate nephelometry (Beckman Coulter, Galway, Ireland). Serum creatinine, urea, albumin, calcium, phosphate, iron, and total iron-binding capacity levels were measured by using a model 7600 Autoanalyzer (Hitachi Ltd, Tokyo, Japan). Transferrin saturation was determined by calculating the ratio of serum iron and total iron-binding capacity, multiplied by 100. Serum levels of ferritin were measured with a radioimmunoassay kit (Incstar, Stillwater, MN, USA). The dialysis dose was measured by calculating mid-week Kt/V urea, which was computed by use of the Daugirdas equation.15

    2.5. Statistical analyses

    Data are expressed as the mean values ± standard deviation for continuous variables with a normal distribution, and percentages for categorical variables, respectively. Potential differences between the groups were evaluated by Student t test for continuous variables and by Pearson χ2 test for categorical variables. We further applied areas under ROC curve and cutoff values of GNRI, serum albumin, BMI, and body weight, respectively, with optimal sensitivity and specificity for prediction of overall mortality. To determine the independent factors that correlated with GNRI, a multivariate linear regression analysis was performed. Baseline variables with a p value <0.1 by univariate analysis were entered into a multivariate model to determine independent predictors for the endpoint. A Cox proportional hazard analysis was used to calculate hazard ratio (HR) and 95% confidence intervals (CI) for determining the association of baseline variables with all-cause mortality. Survival curves were examined by the Kaplan–Meier method. Differences were considered statistically significant at p < 0.05. Statistical analyses were performed using SPSS version 16.0 (SPSS Inc., Chicago, IL, USA).

    3. Results

    3.1. Clinical characteristics of patients

    To compare the discriminative ability among GNRI, serum albumin, BMI, and body weight, areas under the ROC curve were calculated (Table 1). The GNRI had a relatively good predictive value. Its cutoff value of 92 was validated by comparing the areas under the ROC curve, and was determined to exhibit better accuracy in assessing the risks of mortality in the geriatric hemodialysis patients.

    The clinical characteristics of all patients are shown in Table 2. Patients with baseline GNRI <92 had significantly lower body weight, body mass index, serum albumin, and hemoglobin, and higher erythropoietin doses as compared to those with GNRI ≥92. We further performed a multivariate regression analysis for the contributing factors of GNRI at baseline. No correlation was found between GNRI and traditional risk factors, including age, sex, hypertension, diabetes mellitus, and previous CVD. However, baseline GNRI was negatively correlated with ERI (β = −1.97, p < 0.001) and serum hs-CRP (β = −0.71, p = 0.021; Table 3).

    Table 2
    Table 2:
    Baseline characteristics and laboratory data of the elderly hemodialysis patients.
    Table 3
    Table 3:
    Factors are associated with geriatric nutritional risk index at baseline in multivariate regression analysis.a

    3.2. Association of GNRI with outcome

    During the follow-up period (median, 38.5 months), 14 patients were censored at the time they were transferred to other dialysis units (n = 12) or shifted to peritoneal dialysis (n = 2). Overall, 45 patients (43.3%) had died by the end of the study period. The Kaplan–Meier survival curves showed that patients with baseline GNRI of ≥92 were associated with a lower probability of overall mortality (Fig. 1, solid line).

    Fig. 1
    Fig. 1:
    Kaplan–Meier analysis curves for all-cause mortality among elderly hemodialysis patients in close relationship with the geriatric nutrition risk index (GNRI). Patients were stratified into groups based on the cutoff values 92 of GNRI.

    The association between GNRI and all-cause mortality was assessed through Cox proportional hazard analysis (Table 4). Patients with GNRI value of ≥92 were associated with lower risk for overall mortality (HR = 0.41; 95% CI = 0.22–0.90; p = 0.005) and the risk of death for each increment in one unit of GNRI was also significantly reduced (HR = 0.91; 95% CI = 0.85–0.91; p < 0.001) after adjustment for other potential confounders.

    Table 4
    Table 4:
    Multivariate Cox proportional hazard analysis for relative risk of overall mortality calculated by geriatric nutritional risk index (GNRI) levels in a median follow-up of 38.5 months.

    4. Discussion

    In this study, we demonstrated the validity of GNRI in predicting overall mortality among elderly HD patients. The risk of all-cause death significantly increased in patients with GNRI <92 at baseline during long-term follow-up. In addition, high ERI and hs-CRP were correlated with low GNRI. Those patients with low GNRI also had low body weight, low body mass index, low serum albumin, low hemoglobin, and high ERI. These components are compatible with syndromes of PEW.

    As life expectancy has risen due to improvements in Taiwan's public health and medical care, there has been an increasing number of geriatric patients undergoing renal replacement therapy due to ESRD.3 These patients are at the risk of frailty and PEW due to various reasons such as reduced food intake due to poor appetite, chronic inflammation, loss of nutrients during dialysis, metabolic acidosis, increased energy expenditure, and hormonal and primary neuromuscular disorders.16–19 PEW is always underestimated and may lead to serious consequences in geriatric ESRD patients, including impaired physical functioning, poorer quality of life, frequent superimposed illness, and increased mortality.20,21 Among the available nutritional screening tools, GNRI was the easiest to perform for identifying PEW status in ESRD patients undergoing maintenance dialysis.10,11,22 In this study, we further confirmed that declining GNRI is closely associated with hypoalbuminemia and reduced BMI. Thus, the GNRI is considered to be a useful diagnostic material for the presence of PEW in elderly patients undergoing HD therapy.

    Notably, the presence of PEW is found in 18–75% of ESRD patients in previous studies using different criteria.4,23 However, there are fewer data concerning the frequency of PEW in elderly ESRD patients. In our study, the prevalence of malnutrition based on a GNRI cutoff value of 92 was ˜22%, and no difference was observed between men and women. This prevalence rate was much lower than that (53.4%) in Japanese incident HD patients using the same diagnostic criteria.24 The causes of the discrepancy in frequency of PEW between these two reports were not clear. Whether the nutritional risk of our patients improves after undergoing maintenance HD therapy needs to be further examined.

    As mentioned above, GNRI has been validated as a simpler and more accurate nutritional indicator than other screening tools and was reported to be correlated with mortality, various nutritional parameters, oxidative stress,25 and inflammation24,26 in maintenance HD patients. To the best of our knowledge, this is the first recent study demonstrating that patients with low GNRI were associated with anemia and poor response to erythropoietin treatment owing to high ERI (Table 3). Kalantar-Zadeh et al27 studied 339 maintenance HD patients and found the existence of elements of malnutrition–inflammation complex syndrome as indicated by increased inflammatory markers as well as decreased nutritional status in close relationship with erythropoietin hyporesponsiveness and refractory anemia. Therefore, GNRI may be a reliable method to predict the required doses of erythropoietin in this population based on the degree of malnutrition.

    There are some limitations that need to be mentioned. First, we cannot exclude the possibility of residual confounding factors, although most factors have been adjusted in our study. Second, in a prospective cohort study, we cannot prove the causality. Therefore, further studies are needed to confirm this association.

    In conclusion, lower GNRI was associated with a higher risk of overall mortality in the elderly ESRD patients undergoing maintenance HD. The clinical practitioners, nephrologists, may use GNRI to assess nutritional status in elderly HD patients since such expensive laboratory tests are not widely available.

    Acknowledgments

    This study is partly supported by the intramural grant of the Wei Gong Memorial Hospital (103–1-003), Miaoli, Taiwan, R.O.C.

    References

    1. Fox CS, Larson MG, Leip EP, Culleton B, Wilson PW, Levy D. Predictors of new-onset kidney disease in a community-based population. JAMA. 2004;291:844-850.
    2. Eriksen BO, Ingebretsen OC. The progression of chronic kidney disease: a 10-year population-based study of the effects of gender and age. Kidney Int. 2006;69:375-382.
    3. Yang WC, Hwang SJ. Incidence, prevalence and mortality trends of dialysis end-stage renal disease in Taiwan from 1990 to 2001: the impact of national health insurance. Nephrol Dial Transplant. 2008;23:3977-3982.
    4. Dukkipati R, Kopple JD. Causes and prevention of protein-energy wasting in chronic kidney failure. Semin Nephrol. 2009;29:39-49.
    5. Kim JC, Kalantar-Zadeh K, Kopple JD. Frailty and protein-energy wasting in elderly patients with end stage kidney disease. J Am Soc Nephrol. 2013;24:337-351.
    6. Fouque D, Kalantar-Zadeh K, Kopple J, Cano N, Chauveau P, Cuppari L, et al. A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney Int. 2008;73:391-398.
    7. Bouillanne O, Morineau G, Dupont C, Coulombel I, Vincent JP, Nicolis I, et al. Geriatric Nutritional Risk Index: a new index for evaluating at-risk elderly medical patients. Am J Clin Nutr. 2005;82:777-783.
    8. Cereda E, Pedrolli C, Zagami A, Vanotti A, Piffer S, Opizzi A, et al. Nutritional screening and mortality in newly institutionalised elderly: a comparison between the geriatric nutritional risk index and the mini nutritional assessment. Clin Nutr. 2011;30:793-798.
    9. Narumi T, Arimoto T, Funayama A, Kadowaki S, Otaki Y, Nishiyama S, et al. The prognostic importance of objective nutritional indexes in patients with chronic heart failure. J Cardiol. 2013;62:307-313.
    10. Yamada K, Furuya R, Takita T, Maruyama Y, Yamaguchi Y, Ohkawa S, et al. Simplified nutritional screening tools for patients on maintenance hemodialysis. Am J Clin Nutr. 2008;87:106-113.
    11. Kobayashi I, Ishimura E, Kato Y, Okuno S, Yamamoto T, Yamakawa T, et al. Geriatric Nutritional Risk Index, a simplified nutritional screening index, is a significant predictor of mortality in chronic dialysis patients. Nephrol Dial Transplant. 2010;25:3361-3365.
    12. Shah B, Sucher K, Hollenbeck CB. Comparison of ideal body weight equations and published height-weight tables with body mass index tables for healthy adults in the United States. Nutr Clin Pract. 2006;21:312-319.
    13. Matsuzawa Y, Tokunaga K, Kotani K, Keno Y, Kobayashi T, Tarui S. Simple estimation of ideal body weight from body mass index with the lowest morbidity. Diabetes Res Clin Pract. 1990;10(Suppl. 1):S159-S164.
    14. Depner TA, Daugirdas JT. Equations for normalized protein catabolic rate based on two-point modeling of hemodialysis urea kinetics. J Am Soc Nephrol. 1996;7:780-785.
    15. Daugirdas JT. Second generation logarithmic estimates of single-pool variable volume Kt/V: an analysis of error. J Am Soc Nephrol. 1993;4:1205-1213.
    16. Carrero JJ, Stenvinkel P, Cuppari L, Ikizler TA, Kalantar-Zadeh K, Kaysen G, et al. Etiology of the protein-energy wasting syndrome in chronic kidney disease: a consensus statement from the International Society of Renal Nutrition and Metabolism (ISRNM). J Ren Nutr. 2013;23:77-90.
    17. Mak RH, Cheung W, Cone RD, Marks DL. Leptin and inflammation-associated cachexia in chronic kidney disease. Kidney Int. 2006;69:794-797.
    18. Utaka S, Avesani CM, Draibe SA, Kamimura MA, Andreoni S, Cuppari L. Inflammation is associated with increased energy expenditure in patients with chronic kidney disease. Am J Clin Nutr. 2005;82:801-805.
    19. Chang EP, Lin YS, Huang SC, Tarng DC, Huang TP. High serum DcR3 levels are associated with the occurrence of peritonitis in patients receiving chronic peritoneal dialysis. J Chin Med Assoc. 2012;75:644-648.
    20. Lacquaniti A, Bolignano D, Campo S, Perrone C, Donato V, Fazio MR, et al. Malnutrition in the elderly patient on dialysis. Ren Fail. 2009;31:239-245.
    21. Kalantar-Zadeh K, Streja E, Kovesdy CP, Oreopoulos A, Noori N, Jing J, et al. The obesity paradox and mortality associated with surrogates of body size and muscle mass in patients receiving hemodialysis. Mayo Clin Proc. 2010;85:991-1001.
    22. Kang SH, Cho KH, Park JW, Yoon KW, Do JY. Geriatric Nutritional Risk Index as a prognostic factor in peritoneal dialysis patients. Perit Dial Int. 2013;33:405-410.
    23. Mehrotra R, Kopple JD. Nutritional management of maintenance dialysis patients: why aren’t we doing better? Annu Rev Nutr. 2001;21:343-379.
    24. Takahashi H, Ito Y, Ishii H, Aoyama T, Kamoi D, Kasuga H, et al. Geriatric nutritional risk index accurately predicts cardiovascular mortality in incident hemodialysis patients. J Cardiol. 2014;64:32-36.
    25. Honda H, Ueda M, Kojima S, Mashiba S, Hirai Y, Hosaka N, et al. Assessment of myeloperoxidase and oxidative alpha1-antitrypsin in patients on hemodialysis. Clin J Am Soc Nephrol. 2009;4:142-151.
    26. Beberashvili I, Azar A, Sinuani I, Kadoshi H, Shapiro G, Feldman L, et al. Comparison analysis of nutritional scores for serial monitoring of nutritional status in hemodialysis patients. Clin J Am Soc Nephrol. 2013;8:443-451.
    27. Kalantar-Zadeh K, McAllister CJ, Lehn RS, Lee GH, Nissenson AR, Kopple JD. Effect of malnutrition-inflammation complex syndrome on EPO hyporesponsiveness in maintenance hemodialysis patients. Am J Kidney Dis. 2003;42:761-773.
    Keywords:

    elderly; geriatric nutritional risk index; hemodialysis; mortality

    © 2016 by Lippincott Williams & Wilkins, Inc.