24 boado et al nutass hemodialysis 0018 copy ·...

PhilSPEN Online Journal of Parenteral and Enteral Nutrition http://dpsys120991.com/Philspen_Online_Abstracts4.php PHILIPPINE SOCIETY OF PARENTERAL AND ENTERAL NUTRITION (PhilSPEN) (Article 24| http://www.dpsys120991.com/POJ_0018.html) Issue Feb 2012 – Dec 2014: 74-‐88

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Submitted: October 10, 2013 Posted: October 6, 2014 TITLE: Nutritional assessment of patients on maintenance hemodialysis using Dialysis Malnutrition Score (DMS) AUTHORS: Jo-‐Ann Rene V. Boado MD (2), Divina Cristy Redondo MD (1), Jovi Flauta-‐Orio MD (2), Ma. Lourdes M. Gomez MD (2), Aurora Valencia RND (1), Michelle Joy Ingalla RND (1), Romelle M. Ferrer RN (1)

INSTITUTION WHERE STUDY WAS CONDUCTED:

1. Medical Nutrition and Weight Management Center, Premiere Medical Center, Nueva Ecija, Philippines

2. Department of Internal Medicine, Premiere Medical Center, Nueva Ecija Philippines

ABSTRACT BACKGROUND: Malnutrition is prevalent among dialysis patients and a strong association exists between poor nutritional status and morbidity and mortality in patients with end-‐stage renal disease who are treated with hemodialysis. OBJECTIVE: This study aimed to determine the prevalence of malnutrition of MHD patients at a dialysis center in a provincial hospital in the Philippines using the Dialysis Malnutrition Score (DMS), another modified Subjective Global Assessment (SGA). It also aimed to analyze possible correlation between dialysis malnutrition score and different techniques of nutritional assessment including food intake and anthropometric measurement. METHODOLOGY: This is a prospective observational study in which the MHD patients were nutritionally assessed by modified SGA dialysis malnutrition score, food intake recall and anthropometry. RESULTS: 45% have moderate malnutrition and 36% have severe malnutrition. The severity of malnutrition was not associated with age, and duration of dialysis while food intake and anthropometric variables have weak negative correlation. CONCLUSION: Thirty sex percent of MHD patients are severely malnourished and this is not associated with the duration of dialysis. RECOMMENDATION: More comparative, longitudinal studies with larger population are needed to further validate the reliability of DMS. KEYWORDS: anthropometric; maintenance hemodialysis; malnutrition score; subjective global assessment


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INTRODUCTION Malnutrition is common among patients on maintenance hemodialysis. A 40% prevalence of malnutrition was found in patients with advanced renal failure at the beginning of dialysis treatment (1). As shown by several cross-‐sectional studies in the United States, Japan, and Europe, end-‐stage renal disease (ESRD) patients treated by maintenance hemodialysis (MHD) are at risk of malnutrition. In fact, virtually every study examining the nutritional status of hemodialysis patients indicates that such patients frequently manifest protein-‐energy malnutrition (2). Protein-‐energy malnutrition (PEM) is one of prevalent complications appearing in patients undergoing hemodialysis (3, 4). With reported annual mortality rates range from 23.6% in the United States in 1993 (5), to 10.7% in Europe (6), and to 9.5% in Japan in 1994 (7), a common factor of increased death risk in these populations is malnutrition (8). Fundamental for preventing, diagnosing and treating protein-‐energy malnutrition on dialysis patients is the periodical monitoring of the nutritional status. Early identification and treatment of nutritional deficit can reduce the risk of infections, other complications, and mortality for those patients (9). However, assessment of nutritional status is frequently ignored in many dialysis centers (10) because of the difficulty of an accurate determination of the nutritional status in HD patients, which depends on indirect methods. The accuracy of some nutritional markers used in nutrition assessment is also questionable (11,12). The reliable assessment of nutritional status requires multidisciplinary procedures including anthropometric measurements, body composition measurements, biochemical measurements, functional assessments, dietary assessments, and subjective assessments. However, most of these procedures are time-‐consuming and cumbersome (13) and in a rural setting, it can be costly. The subjective global assessment (SGA) was designed to circumvent many of these problems (14,15), but its semi-‐quantitative scale consisting of only three discrete severity levels restricts its reliability and precision (16). Using the conventional SGA, Kalantar-‐Zadeh et al (16) developed a fully quantitative scoring system for dialysis patients which they concluded can be performed in minutes and can reliably assess the nutritional status of patients on hemodialysis. SGA is a structured assessment of the nutritional status based on a concentrated history and physical examination [17,18]. Five features of the history are elicited, the amount and pattern of weight loss in the previous six months, changes in dietary intake, gastrointestinal symptoms, functional capacity or energy level and metabolic demands of the patient's condition. The features in the physical examination are loss of subcutaneous fat, muscle wasting, edema and ascites. However, the presence of edema or ascites of the original SGA physical examination are usually not used for dialysis patients. Hence, using the components of the conventional SGA, a quantitative scoring system called Dialysis Malnutrition S core (DMS) was developed. (19) DMS consists of seven components of the conventional SGA: weight change, dietary intake, GI symptoms, functional capacity, co-‐morbidity, loss of subcutaneous fat, and signs of muscle wasting, and number of years of dialysis therapy was added to the co-‐morbidity component. This study aimed to determine the prevalence of malnutrition of MHD patients with chronic kidney failure at a dialysis center in a provincial hospital in the Philippines using the Dialysis Malnutrition Score (DMS), another modified Subjective Global Assessment. This study also


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aimed to analyze possible correlations between modified SGA and different techniques of nutritional assessment including food intake and anthropometric measurements. METHODOLOGY Patients This study was conducted on 33 patients between May 2010 to October 2010 at a dialysis center in Premiere Medical Center (PMC), Nueva Ecija, Philippines. Criteria for inclusion in the study are: 18–85 years old males and females who are on hemodialysis (HD) for at least 1 month, receiving oral diet, without incidental infection, and access via arterio-‐venous fistula. The exclusion criteria are as follows: presence of sepsis, shock, multiple organ failure, coma, clinical or surgical hospitalization in the last 30 days, with ongoing enteral and parenteral nutrition, use of steroidal or non-‐steroidal anti-‐inflammatory or immune-‐supressive agents, cardiac pacemaker. Patients received daily treatment prescribed by their physicians which include anti-‐hypertensive medications, phosphate binding, erythropoietin, iron medications and vitamin supplements. Before joining the study, written informed consent was obtained from the participants.

Food Intake Dietary recall forms, which include two-‐day food intake in midweek and one-‐day intake on weekends, were gathered by trained clinical dietitians. The calorie and protein consumed by the patients were compared with the recommended daily calorie and protein requirements based from the American Society for Parenteral and Enteral Nutrition (ASPEN) guidelines. Anthropometric measurement Body dry weight and skin–fold measurements were performed after termination of the dialysis session. Triceps skin–fold (TSF) was measured with skin–fold caliper. Mid-‐arm circumference (MAC) was measured using a tape measure. All the above measurements were performed three times on the non-‐access arm of each dialysis patient and the average result of the three measurements was registered as the final result. Mid-‐arm muscle circumference (MAMC) was derived according to the following formula: MAMC = MAC – (0.31415 x TSF). Body mass index (BMI) was calculated as the ratio between end dialysis body weight in kilogram and the square of height in meter. Dialysis Malnutrition Score (DMS) Dialysis malnutrition score consists of seven features: weight change, dietary intake, GI symptoms, functional capacity, co-‐morbidity, subcutaneous fat and signs of muscle wasting was recently developed (see Table 1). Each component has a score from one (normal) to five (very severe). The malnutrition score (sum of all seven components) is a number between seven to 10 (normal) and 11-‐15 (moderate malnutrition) and 16-‐35 (severe malnutrition). A lower score denotes tendency towards a normal nutritional status while a higher score is considered to be


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an indicator of the severity of malnutrition, that is, the higher the nutritional score, the stronger the tendency towards protein energy malnutrition. Table 1 shows the Dialysis Malnutrition Score consisting of two parts: 1.) patient’s related medical history (weight change, dietary intake, gastro-‐intestinal symptoms, functional capacity, co-‐morbidities) and 2.) physical examination (decreased fat stores or loss of subcutaneous fat and signs of muscle wasting). For weight change, the overall change in the post-‐dialysis dry weight was obtained. The lowest score of one was given if there was no weight change or if patient had gained weight. Score of two was given for minor weight loss (<5%), score of three for weight loss of 5-‐10%, score of four for weight loss of 10-‐15% and score of five for any weight loss over 15% the last 6 months. Dietary intake was scored one if it was considered as a regular solid intake with no recent change in the amount or quality of the meals, two for sub-‐optimal solid diet, three for full liquid diet or any moderate overall decrease, four for hypocaloric liquid and five for starvation. Gastrointestinal (GI) symptoms were scored one if there was no symptom, two for nausea, three for vomiting or any moderate GI symptoms, four for diarrhea and five for severe anorexia. Functional capacity was scored one for normal functional capacity and/or any considerable improvement in the level of previous functional impairment, two for any mild to moderate difficulty with ambulation, three for difficulty with normal activity, four for restriction solely light activity and five for a persistent bed/chair-‐ridden state. The co-‐morbidity component of the SGA criteria was modified by incorporating the duration of hemodialysis and advanced age, which both have a bearing on nutrition. The co-‐morbidity was scored as one if there was no other medical problems and if the patient had been hemodialysed for less than one year; two if there was mild co-‐morbidity or if the patient has been dialyzed for one to two years; three if there was moderate co-‐morbidity or if the patient had been dialyzed for two to four years, or if the patient was >75 years of age; four if there was severe co-‐morbidity or if the patient had been dialyzed for over four years; and five if there were very severe, multiple co-‐morbidities. Physical examination in DMS and is composed of two sections: subcutaneous fat and muscle wasting (Table 2). Body fat stores (subcutaneous fat) were scored by assessing subcutaneous fat deposition in four body areas: below the eyes, triceps, biceps and in the chest area. Signs of muscle wasting were obtained by briefly examining seven sites: temple, clavicle, scapula, ribs, quadriceps, knee and interosseous muscles. For each of these two components a score of one to five, representing normal to very severe changes, was assigned according to subjective assessment of the examiner. After completion of physical examinations, patients were classified in one of three groups: normal, moderate malnutrition and severe malnutrition. Total nutritional scoring for each patient was assessed within five to 15 minutes. Nutritional assessment using modified SGA was also performed in all 33 patients on maintenance hemodialysis. To gain maximum benefit of the reliability of the modified SGA, three selected and properly trained staff performed the assessment. Statistical Analysis Answers to categorical variables were tabulated and overall and gender specific mean and standard deviation of continuous variables were obtained. For gender comparisons, Wilcoxon’s rank sum test was utilized. Fischer’s exact test was used to determine if severity of malnutrition


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is associated with gender. Lastly, Pearson’s correlation was used for the malnutrition scores and the select study variables.


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RESULTS A total of 33 patients out of 43 patients were included in the study. Ten patients were excluded because of the following reasons: one patient is below 18 years of age, five had recent infection and were subsequently admitted, two patients received enteral nutrition and two patients had hemodialysis for less than two weeks only. Majority of the subjects were males (61%). For co-‐morbidities, the most common among patients with chronic renal failure was hypertension (79%) followed by coronary artery disease (58%) and diabetes mellitus (52%). Most of the


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patients took iron supplements (55%) and calcium supplements (79%). For frequency of dialysis, a large proportion underwent dialysis twice a week (88%). There were only a few who experienced loss of appetite before, after or during dialysis but 52% of them reported nausea/vomiting.

In Table 4, overall and gender specific summary statistics of continuous variables are presented. Using the Wilcoxon rank sum test, we see that the difference between gender for weight (pre and post dialysis) and height are statistically significant. For the rest of the variables, they are comparable in distribution for males and females.


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Using the modified SGA, 45% of the study participants have moderate malnutrition and 36% have severe malnutrition. Only 18% of them have modified SGA score within the normal range. There are more males than females with moderate to severe scores. However, using Fisher’s exact test, severity was shown to be not associated with gender (p-‐value:0.266).

The dialysis malnutrition scores were correlated with age, duration of dialysis, food intake and anthropometric variables. The scatter plots are shown in figures 1 below. The pair-‐wise correlation between age of the patient and malnutrition score is approximately equal to zero indicating that these two variables are not correlated. For duration of dialysis, the correlation index is also very small at 0.05. Food intake and anthropometric variables are all negatively correlated with the modified SGA malnutrition score. Among these variables, TSF (mm) has the largest index at -‐0.34. The value however only signifies a relatively weak negative correlation between triceps skin-‐fold thickness and malnutrition score (p-‐value:0.06). Body mass index also has a relatively large correlation index at -‐0.31 (p-‐value: 0.08) also indicating a weak negative correlation.


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In figures below, there is no clear linear trend that can be seen. For BMI and TSF in figures 1.F and 1.G, respectively, a weak inverse relationship is implied. As malnutrition score increases, BMI and TSF values decrease. In figures 1.a and 1.b, there is clearly no trend or association between the variables. In figures 1.C and 1.D, the values appear to form a horizontal strip in the graph indicating a linear but weak linear association. There appears to be no trend in figure 1.E and a slightly inverse trend in figures 1.H and 1.I.


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DISCUSSION Malnutrition is common in dialysis patients (14,15,16) and predicts morbidity and mortality (30,31). Nutritional assessments in dialysis patients are imperative, although the task is not necessarily easy. The purpose of such assessment is obviously the identification of patients at risk for complications and a poor outcome before such complications have developed especially with onset of protein energy malnutrition. This allows the implementation and preventive interventions, such as additional nutritional counseling, dietary supplements or psychosocial interventions. Furthermore, routine monitoring of the nutritional status of dialysis patients is more important because protein –energy wasting and malnutrition is more difficult to treat when it is severe. Early detection of the first signs of protein energy malnutrition allows early treatment to anticipate nutritional depletion, and, most importantly to prevent any further deterioration (32). Nevertheless, the nutritional status of dialysis patients is frequently ignored and has rarely been a subject of research until today (33). Several indices of malnutrition are available ranging from the well-‐known anthropometric measurements (34) to more elaborate techniques such as DEXA and bioelectrical impedance (35,36). However, the reliability of these methods in detecting protein-‐calorie malnutrition and their practicability has not been shown (27,37). Moreover, these methods are costly and may not be applicable in our hospital set-‐up. Studies by Baker et al. (18), Detsky and colleagues (38) and Jeejeebhoy and colleagues (39,40), suggest that the SGA not only determines the nutritional status, but also predicts the likelihood of complications in terms of sickness. A fully quantitative malnutrition scoring system (dialysis malnutrition score), derived from conventional SGA was used to answer the practicability our HD patients need. DMS is easy, practical, yet reproducible, guidelines for each single scoring component. It allows a rapid, equipment-‐free scoring on nutrition status in patients with renal failure. The test uses a simple history and physical examination which can be performed by a physician, dietician or trained nurse (17,27). The method is closely correlated with more objective measures (17).


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In this study, 45% have moderate malnutrition and 36% have severe malnutrition using the modified SGA. The severity of malnutrition was not associated with age and duration of dialysis. But using the modified SGA dialysis malnutrition score, we determined a negative correlation between malnutrition, food intake, BMI and TSF. Although indicating a weak negative correlation, body mass index has a relatively large correlation index. Among indicators of body mass, BMI is the most commonly used measure of weight-‐for-‐height (41-‐43) and may be used to assess malnutrition. However, BMI can be heavily influenced by fat mass or hydration status. Nonetheless, a low BMI is a consistent predictor of poor outcome and high death risk in maintenance dialysis patient (44-‐45). However, a low BMI may not indicate pathology in some population such on those from Southeast Asia (46-‐47) like the Philippines. Food intake specifically dietary energy and protein intake has negative correlation with the Modified SGA Dialysis Malnutrition Score as well. An unintentional reduction in dietary protein intake less than about 0.80 gm per kg body weight per day in maintenance dialysis patients and dietary intake less than about 25 kcal per kg body weight per day in maintenance dialysis patients and dietary energy intake less than about 25 kcal per kg body weight can be associated with protein energy wasting. (48) Improved patient outcome may highly be observed if there will be an increased attention to the nutritional status of the patient on maintenance hemodialysis. However, before we can test for any nutritional intervention among MHD patients, it is important that we can assess their nutritional status with a standardized, validated and generally accepted method. CONCLUSION The dialysis malnutrition score can be a potential and reliable nutritional assessment tool for MHD patients and may provide a standardized method in which large number of maintenance hemodialysis patients can be assessed by any trained member of the dialysis care and nutrition support team. RECOMMENDATION More comparative, longitudinal studies with larger population are needed with the recommendation to include not only anthropometric variables, dietary intake but to check for the biochemical parameters as well. This is to further validate the reliability of Dialysis Malnutrition Score. REFERENCES 1. Fouque D and Kopple J. Malnutrition and dialysis In 1272-‐89. 2. Wolfson,M, strong,CJ,Minturn,D,Gray,DK,Kopple,JD: Nutritional status and lymphocyte

function in maintenance hemodialysis patients. Am J Clin Nutr 1984: 39:547-‐555,/Pubmed/ISI/Chemport/

3. Ikizler TA, Hakim RM. Nutrition in end-‐stage renal disease. Kidney Int1996; 50: 343–57.


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4. Stenvinkel P, Heimburger O, Paultre F, et al. Strong association between malnutrition, inflammation, and atherosclerosis in chronic renal failure. Kidney Int 1999; 55: 1899 –911.

5. Held,PJ,Brunner,FB,Odaka,M,Garcia,JR,Port,FK,Gaylin,DS: Five-‐year survival for end-‐stage renal disease patients in the United States, Europe, and Japan, 1982 to 1987. Am J Kidney dis 1990 15: 451-‐457,/pubmed/ISI/Chemport/

6. Valderrabano F, Berthoux F, Jones E, Mehls O. report on management of renal failure in Europe, XXV, 1994. End stage renal disease and dialysis report. Nephrol Dial Transplant 1996; 11 Suppl 1:2-‐21

7. Shinzato T, Nakai S, Akiba T et al. Current status of renal replacement therapy in Japan: results of the annual survey of the Japanese society for dialysis therapy. Nephrol Dial Transplant 1997; 12: 889-‐898

8. Bergstrom, J. Why are dialysis patients malnourished? Am J Kidney Dis 1995; 26: 229-‐41. 9. Lowrie EG, Lew NL. Death risk in hemodialysis patients: the predictive value of commonly

measured variables and an evaluation of death rate differences between facilities. Am J Kidney Dis 1990; 15:458-‐82.

10. Asgaani,F,Mahdavi-‐Mazdeh,et.al, correlation between Modified Subjective Global assessment with anthropometric measurements and laboratory parameters. Acta Medica Irnica, 42 (5): 331-‐337;2004.

11. Passadakis P, Sud K, Dutta A, Singhal M, Pettit J, Chatalalsingh C, et al. Bioelectrical impedance analysis in the evaluation of the nutritional status of Continuous Ambulatory Peritoneal Dialysis Patients. Adv Perit Dial 1999;15:147-‐52.

12. Chumlea WC. Anthropometric and body composition assessment in dialysis patients. Seminars in Dialysis 2004;17(6):466-‐70.

13. Kohsuke Yamada, Ryuichi Furuya, Takako Takita, Yukitaka Maruyama, Yuri Yamaguchi, Sakae Ohkawa, and Hiromichi Kumagai. Simplified nutritional screening tools for patients on maintenance hemodialysis. Am J Clin Nutr 2008;87:106 –13.

14. Hakim R., Levin N. Malnutrition in hemodialysis patients. Am J Kidney Dis 1993; 21: 125-‐137 15. Canada-‐USA (CANUSA) Peritoneal Dialysis Study Group. Adequacy of dialysis and nutrition in

continuous peritoneal dialysis: association with clinical outcomes. J Am Soc Nephrol 1996; 7:198-‐207

16. US Renal Data System. USRDS 1996 Annual Data Report. The National Institute of Health; National Institute of Diabetes and Digestive and Kidney Diseases; Bethesda, MD, 1996

17. Detsky AS, McLaughlin JR, Baker JP, Johnston N, Whittaker S, Mendelson RA, Jeejeebhoy KN. What is subjective global assessment of nutritional status? J Parenter Enteral Ntr 1987; 11: 8-‐13.

18. Baker JP, Detsky AS, Wesson DE, Wolman SL, Stewart S, Whitewell J, Langer B, Jeejeebhoy KN. Nutritional assessment: a comparison of clinical judgement and objective measurements. N. Engl J Med 1982; 306: 969-‐972


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19. Kalantar-‐Zadeh K, Kleiner M, Dunne E, Lee GH, Luft FC: A modified quantitative Subjective Global Assessment of Nutrition for dialysis patients. Nephrol Dial Transplant 14:1732-‐1738, 1999.

20. Kaysen GA, Don BR.Factors that affect albumin concentration in dialysis patients and their relationship to vascular disease. Kidney Int (suppl)2003;84:94-‐7.

21. Jones CH, Wolfenden RC, Wells L. Is subjective global assessment a reliable measure of nutritional status in hemodialysis, J Renal Nutr 2004;14(1):26-‐30.

22. Faintuch J, Morais AAC, Silva MAT, Vidigal EJ, Costa RA, Lyrio DC, et al. Nutritional profile & inflammatory status of haemodialysis patients. Renal Failure 2006;28:295-‐301.

23. Morais AAC, Silva MAT, Faintuch J, Vidigal EJ, Costa RA, Lyrio DC. Correlation of nutritional status and food intake in hemodialysis patients. Clinics 2005;60(3):185-‐92.

24. Suliman ME, Qureshi AR, Stenvinkel P, Pecoits-‐Filho R, Barany P, Heimburger O. Inflammation contributes to low plasma amino acid concentrations in patients with chronic kidney disease. Am J Clin Nutr 2005;82(2):342-‐9.

25. Rasic-‐Milutinovic R, Perunicic G, Pljesa S, Gluvic Z, Ilic M, Stoki E. Metabolic syndrome in HD patients: association with body composition, nutritional status, inflammation and serum iron. Intern Med 2007;46(13):945-‐51.

26. Kaysen GA. Inflammation, nutritional state and outcomein end stage renal disease. Miner Electrolyte Metabol 1999;25:242-‐50.

27. Kalantar-‐Zadeh K, Kleiner M, Dunne E, Nelson M, Ahem K, Koslowe R, Luft FC. Total iron binding capacity-‐estimated transferring concentrations in dialysis paqtients correlate with the subjective global assessment of nutrition. Am J Kidney Dis 1998; 31: 263-‐272

28. Enia G, Sicuso C, Alati G, Zoccali C: Subjective Global Assessment on nutrition in dialysis patients. Nephrol Dial Transplant 8: 1094-‐2008, 1993

29. Kalantar-‐Zadeh K, Ikizler TA, Block G, Avram MM, Kopple JD. Malnutrition-‐inflammation complex syndrome in dialysis patients: causes and consequences. Am J Kidney Dis. 2003 Nov; 42 (5): 864-‐81

30. Owen WF Jr, Lew NL, Liu Y, Lowrie EG, Lazarus JM. The urea reduction ratio and serum albumin concentration as predictors of mortality in patients undergoing hemodialysis. N Engl J Med 1993; 329: 1001-‐1006

31. Cianciaruso B, Brunori G, Kopple JD, et al. Cross-‐sectional comparison of malnutrition in continuous ambulatory peritoneal dialysis and hemodialysis patients. Am J Kidney Dis 1995; 26: 475-‐486

32. Fouque D, Guebre-‐Egziabher F. An update on nutrition in chronic kidney disease. Int Urol Nephrol 2007; 39: 239-‐46

33. Schoenfeld PY, Henry RR, Laird NM, Rote DM. Assessment of nutritional status of national cooperative dialysis study population. Kidney Int 1983; 23 (Suppl 13): 80-‐88

34. Nelson EE, Hong CD, Pesce AL, Peterson DW, Singh S, Pollak VE. Anthropometric norms for dialysis population. Am J Kidney Dis 1990; 16: 32-‐37


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35. Chertow GM, Lowrie EG, Wilmore DW, et al. Nutritional Assessment with bioelectrical impedance analysis in maintenance hemodialysis patients. J Am Soc Nephrol 1995; 6:75-‐81

36. Chertow GM, Jacobs DO, Lazarus JM, Lew NL, Lorie EG. Phase angle predicts survival in hemodialysis patients. J Renal Nutr 1997; 7: 204-‐207

37. Chertow GM, Bullard A, Lazarus JM. Nutrition and the dialysis prescription. Am J Nephrol 1996; 16:79-‐89

38. Detsky AS, Baker JP, Mendelson RA, Wolman SL, Wesson DE, Jeejeebhoy KN. Evaluating the accuracy of nutritional assessment techniques applied to hospitalized patients: methodology and comparisons. J Parenter Enteral Nutr 1987; 8: 153-‐159

39. Jeejeebhoy K, Detsky A, Baker J. Assessment of nutritional status. J Parenter Enetral Nutr 1990; 14 (Suppl 5): 191-‐196

40. Jeejeebhoy K, How should we monitor nutritional support: structure or function? New Horizons 1994; 2: 131-‐138

41. Kalantar-‐Zadeh K, Kopple JD, Kilpatrick RD et al. Association of morbid obesity and weight change over time with cardiovascular survival in hemodialysis population. Am J Kidney Dis 2005; 46: 489-‐500.

42. Kopple JD, Zhu X, Lew NL et al. Body weight-‐for-‐height relationships predict mortality in maintenance hemodialysis patients. Kidney Int 1999; 56: 1136-‐1148.

43. Culp K, Flanigan M, Dudley J et al. Using the Quetlet body mass index as a mortality indicator for patients starting renal replacement therapy. Anna J 1998; 25: 321-‐330;discussion 331-‐332.

44. Salahudeen AK. Obesity and survival on dialysis. Am J Kidney Dis 2003; 41: 925-‐932. 45. Kalantar-‐Zadeh K, Abbott KC, Salahudeen AK et al. Survival advantages of obesity in dialysis

patients. Am J Clin Nutr 2005; 81: 543-‐554. 46. Stevens J, Nowicki EM. Body mass index and mortality in Asian populations: implications for

obesity cut-‐points. Nutr Rev 2003; 61: 104-‐107. 47. Wong JS, Port FK, Hulbert-‐Shearon TE et al. Survival advantage in Asian American end-‐stage

renal disease patients. Kidney Int 1999; 55: 2515-‐2523. 48. National Kidney Foundation I. Kidney Disease-‐Dialysis Outcome Quality Initiative: K/DOQI

Clinical Practice Guidelines for nutrition in chronic renal failure. Am J Kidney Dis 2000;35: S1-‐S140.

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