Subjective Global Assessment for the Diagnosis of Protein–Energy Wasting in Nondialysis-Dependent Chronic Kidney Disease Patients

ORIGINAL RESEARCH

Subjective Global Assessment for the Diagnosis of Protein–Energy Wasting in Nondialysis-Dependent Chronic Kidney Disease Patients Lilian Cuppari, PhD,*,† Marion Schneider Meireles, MS,† Christiane Ishikawa Ramos, MS,† and Maria Ayako Kamimura, PhD† Objectives: Subjective global assessment (SGA) has been demonstrated to be a reliable method for protein–energy wasting (PEW) evaluation in chronic kidney disease (CKD) patients on dialysis. Few data are available on PEW evaluation in nondialysis stages of CKD, and the validity of SGA has been scarcely investigated in this population. Herein, we aimed to evaluate in nondialysis-dependent CKD patients (NDD-CKD): (1) the prevalence of PEW by SGA; (2) the most common abnormalities of the SGA components; and (3) the agreement of SGA with the traditional anthropometric parameters. Design and Subjects: This is a retrospective cross-sectional study including 922 NDD-CKD patients referred to the renal dietitians in the period of 2001 to 2012. Nutritional status was assessed by 7-point SGA. Body mass index (BMI), midarm circumference, midarm muscle circumference, and triceps skinfold thickness were available from 494 patients. Results: From the 922 patients, 58.6% were men, mean age was 63.8 6 13.6 years, BMI was 27.7 6 5.3 kg/m2. The majority of the patients were in CKD Stages 3 (48.9%) or 4 (40.3%). PEW (SGA #5) was present in 11% of the patients and 32% had signs of PEW (SGA 6). In the logistic regression analysis, the presence of comorbidities and worse renal function were independently associated with PEW. Among the SGA components, the most frequent abnormality in patients with PEW was muscle and fat wasting (88.6%). BMI, midarm circumference, midarm muscle circumference, and triceps skinfold thickness were lower across the worse SGA scores, and a moderate to good level of agreement was found between the anthropometric parameters and presence of PEW evaluated by SGA. Conclusions: The prevalence of PEW was 11% in our unselected cohort of NDD-CKD patients. The physical examination component (muscle/fat wasting) was the most frequent alteration found in those patients. When compared with anthropometric parameters, 7-point SGA has shown to be a valid tool to assess PEW in NDD-CKD population. Ó 2014 by the National Kidney Foundation, Inc. All rights reserved.

Introduction

I

NDIVIDUALS WITH CHRONIC kidney disease are at increased risk of protein–energy wasting (PEW) because of multiple disturbances related to the disease and its treatment. The consequences of PEW, particularly for CKD patients on maintenance dialysis, are devastating in terms of quality of life, morbidity, and mortality.1-3 Therefore, early detection of PEW is of great importance to implement appropriate interventions that may potentially result in less adverse outcomes. In the setting of CKD, a number of tools have been used for the assessment of nutritional status. Among them the subjective global assessment (SGA) has

* Department of Medicine, Division of Nephrology, Federal University of S~ao Paulo, S~ao Paulo, Brazil. † Graduation Program on Nutrition, Federal University of S~ao Paulo, S~ao Paulo, Brazil. Support: See Acknowledgments on page 389. Address correspondence to Lilian Cuppari, PhD, Federal University of S~ao Paulo, Rua Pedro de Toledo, 282 Cep: 04039-000, S~ao Paulo, SP, Brazil.

E-mail: [email protected] Ó

2014 by the National Kidney Foundation, Inc. All rights reserved. 1051-2276/$36.00 http://dx.doi.org/10.1053/j.jrn.2014.05.004

Journal of Renal Nutrition, Vol 24, No 6 (November), 2014: pp 385-389

been shown to be a reliable and valid method for the diagnosis of PEW in patient on dialysis therapy.2,4,5 Studies including incident and prevalent patients on dialysis from several centers around the world have shown a prevalence of PEW by SGA ranging from 17% to 55%.2,5-8 The prevalence of PEW in CKD patients in the earlier stages of the disease has been poorly investigated and the number of studies that used SGA to diagnose PEW in those patients is even more limited. In small cohorts of selected NDDCKD patients, mostly on Stages 4 or 5, the prevalence of PEW by SGA has been reported to vary from 20% to 39%.9-13 The concurrent and predictive validity of 7-point SGA have been established in multicenter studies with patients on dialysis. The CANUSA study, a landmark study of SGA, found the 7-point SGA to be independently predictive of death and days of hospitalization in a cohort of patients on peritoneal dialysis.6 Steiber et al.5 demonstrated in a diverse hemodialysis population that body mass index (BMI) and serum albumin were reduced across the lower 7-point SGA scores, whereas the frequency of hospitalization was greater. In a large cohort of incident patients on hemodialysis, de Mutsert et al.2 demonstrated, in a prospective analysis, a dose- and time-dependent trend of 7-point SGA scores with mortality. SGA validation studies including CKD 385

386

CUPPARI ET AL

patients not on dialysis therapy are scarce. In a cross-sectional study of 50 CKD patients with Stages 4 and 5, Campbell et al.11 showed that body cell mass was decreased in the patients with PEW diagnosed by the original SGA version. Also investigating the performance of the original SGA in a group of CKD patients, Lawson et al.9 demonstrated in 50 patients, mostly on Stages 4 and 5 of CKD, that BMI and midarm circumference were significantly lower in patients with PEW. Additionally, the stratification of patients according to SGA classification identified patients who had increased risk of morbidity and mortality. Given the paucity of studies on nutritional evaluation by SGA in CKD patients in the earlier stages of the disease, our objectives were (1) to characterize the nutritional status of a large cohort of CKD patients by using the 7-point SGA, (2) to identify the most frequent abnormalities of the SGA categories, and (3) to test the validity of SGA in relation to anthropometric parameters in these patients.

Comorbidities Comorbidities were scored by calculating the Charlson comorbidity index (CCI), which assigns 1 point for history of myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease (transient ischemic attack or cerebrovascular accident with minor or no residua), dementia, chronic pulmonary disease, connective tissue disorder, peptic ulcer disease, mild liver disease, and diabetes without end-organ damage; 2 points are assigned for hemiplegia, moderate to severe renal disease, diabetes with end-organ damage, tumor without metastases, leukemia, lymphoma, and myeloma; 3 points are assigned for moderate or severe liver disease; and 6 points are assigned for metastatic solid tumor or AIDS. For every decade over 40 years of age, 1 point is added to the score. For the purposes of the present study, all patients received 2 for the presence of renal disease.17

Patients and Methods

Statistical Analysis Variable distribution was examined by Shapiro–Wilk test. Those with skewed distribution were log transformed (natural base). Categorical and continuous variables were expressed as percentage or mean and standard deviation, respectively. Comparisons between groups were performed using analysis of variance with post-hoc Bonferroni test or Pearson Chi-square test, as appropriate. Logistic regression analysis was applied to evaluate the factors associated with PEW. The agreement between SGA scores and anthropometric markers was evaluated by Kappa coefficient test. Data were analyzed by SPSS software, version 18 (SPSS Inc, Chicago, IL). Statistical significance was defined as P ,.05.

This is a retrospective cross-sectional study. In the period of 2001 to 2012, a total of 922 NDD-CKD patients were seen by specialized renal dietitians of a single outpatient clinic. The files were carefully reviewed and the demographic, clinical, and nutritional data from the first visit to the center were registered. The study was approved by the University Ethical Advisory Committee.

Nutritional Assessment Subjective Global Assessment The 7-point SGA questionnaire6 was applied by trained dietitians. This tool is based on two major categories: medical history and physical examination. The following five components comprised medical history: weight change, dietary intake change, gastrointestinal symptoms, functional impairment, and comorbidities. The physical examination includes the evaluation of fat and muscle wasting, presence of edema and ascites related to nutritional condition. Each SGA component is scored 1 to 7, with the lowest values indicative of severity. On the basis of subjective consideration of all scores from each component, an overall score is assigned to each patient: 1 to 2, severe PEW; 3 to 5, moderate to mild PEW; and 6 to 7, well nourished. In the present study, SGA scores #5 were considered as presence of PEW. Anthropometric Parameters Body weight and height were measured and BMI was calculated. Triceps skinfold thickness (TSF), midarm circumference (MAC), and midarm muscle circumference (MAMC) were measured according to the standard techniques.14 BMI ,23 kg/m2 and TSF, MAC, and MAMC ,90% of adequacy in relation to the 50th percentile of a reference population14 were adopted to denote PEW.15 Glomerular filtration rate (GFR) was estimated by the CKD-EPI equation.16

Results From the 922 patients, 58.6% were men, the age was 63.8 6 13.6 years, BMI was 27.7 6 5.3 kg/m2. The prevalence of diabetes was 44.6% and the CCI was 4.9 6 1.7. GFR was 32.4 6 13.5 mL/min/1.73 m2. The majority of the patients were in CKD Stages 3 (48.9%) or 4 (40.3%).

Figure 1. Distribution of patients according to SGA scores. SGA, subjective global assessment. SGA 1 and 2, severe PEW; SGA 3 to 5, moderate to mild PEW; SGA 6 and 7, well nourished.

387

PEW BY SGA IN CKD Table 1. Characteristics of the Patients According to SGA Groups Characteristics Male (%) Age (y) DM (%) CCI BMI (kg/m2) eGFR (mL/min/1.73 m2) CKD Stage 2 (%) CKD Stage 3 (%) CKD Stage 4 (%) CKD Stage 5 (%)

SGA #5 (n 5 105)

SGA 6 (n 5 293)

SGA 7 (n 5 524)

62.9 65.9 6 16.1* 34.3† 5.4 6 2.1* 22.1 6 3.8† 31.5 6 15.7 6.8 37.9† 47.6† 7.8

54.3 65.9 6 12.7* 46.4 5.1 6 1.6 26.7 6 4.6 30.5 6 13.3* 2.4 43.1 46.5 8.0

60.1 62.2 6 13.3 45.6 4.6 6 1.7 29.4 6 5.0 33.7 6 13.2 2.9 54.2 38.4 7.5

BMI, Body mass index; CCI, Charlson comorbidity index; CKD, chronic kidney disease; DM, Diabetes mellitus; eGFR, estimated glomerular filtration rate. Values expressed as mean 6 standard deviation or percent. *P , .05 versus SGA 7. †P , .05 versus SGA 6 and 7.

Only 3.2% and 7.6% of the patients were in CKD Stages 2 or 5, respectively. As demonstrated in Figure 1, 57% of the patients scored SGA 7, 32% scored SGA 6, and 11% scored SGA #5. The frequency of PEW was significantly higher in patients with CKD Stages 4 and 5 combined (13%) when compared with patients with CKD Stage 3 (9%; P 5.04). Table 1 shows the characteristics of the patients according to SGA groups. No gender difference was observed among the groups. Patients in SGA #5 were older and had lower BMI. The frequency of diabetes was lower in the group of patients with SGA #5, whereas the CCI was significantly higher. The frequency CKD Stage 4 was more frequent among patients in SGA #5. In the regression analysis (Table 2), presence of comorbidities, assessed by CCI, and worse renal function were the independent risk factors for PEW (SGA # 5). Figure 2 shows the frequency of abnormal scores (score #5) in each SGA category in the groups of SGA #5, SGA 6, and SGA 7. As can be seen, in patients with SGA #5, the most frequent abnormality was the muscle and fat wasting (89%) followed by dietary intake change (53%), and weight change (43%). In the group of SGA 6, the leading abnormalities were the changes in dietary intake (27%) and gastrointestinal symptoms (23%). Anthropometric evaluation was available in 494 patients, and the data are presented in Table 3. The parameters of BMI as well as MAC, MAMC, and TSF adequacies were Table 2. Logistic Regression Analysis of Risk Factors Associated With PEW (SGA #5) Variables Gender Age $65 y CKD Stages 4 and 5 CCI

B

P

95% CI

0.89 1.28 1.73 2.15

.60 .37 .01 .04

0.57-1.38 0.75-2.21 1.12-2.68 1.06-4.38

CCI, Charlson comorbidity index; CI, confidence interval; CKD, chronic kidney disease; PEW, protein–energy wasting; SGA, subjective global assessment.

all significantly reduced across the lower SGA score groups. The kappa test was performed to analyze the agreement between SGA and anthropometric markers of PEW. As can be seen in Table 4, a moderate to good agreement was observed between them.

Discussion In the present study, we aimed to characterize the nutritional status of a large cohort of unselected NDD-CKD patients and to test the validity of 7-point SGA in relation to anthropometric parameters. PEW (SGA #5) was found in 11% of the patients and 32% had signs of PEW (SGA 6). The stratification of the patients according to SGA scores was consistent with anthropometric parameters, supporting the concurrent validity of SGA to assess PEW in this population. The few studies that investigated the nutritional status of NDD-CKD patients using SGA have found a prevalence of PEW higher than that observed in the present study. Differences in the SGA version used, criteria for classification of PEW, and demographic and clinical characteristics of the studied population may have accounted for such disparity. Indeed, an elevated prevalence of PEW (39%) assessed by the 4-point scale SGA version was found by Stenvinkel et al.13 in a cohort of CKD patients close to start dialysis (average GFR 5 7.0 mL/minute). In groups of patients with better renal function (average GFR 5 20 mL/ minute), a prevalence of 28% (3-point SGA)9 and 19% (3-point SGA)11 of PEW have been demonstrated. In the present study, patients had a higher GFR (average of 32 mL/minute) what may explain, at least in part, the lower prevalence of PEW in our patients. In fact, the frequency of patients with PEW among those with CKD Stage 3 was significantly lower in comparison with those with CKD Stages 4 and 5 combined. Additionally, the worse renal function was independently associated with an increased risk of PEW (Table 2). This finding confirms the well-

388

CUPPARI ET AL

Figure 2. Distribution of patients with abnormal SGA components (score #5) according to SGA # 5, SGA 6, and SGA 7 groups. SGA, subjective global assessment. SGA 1 and 2, severe PEW; SGA 3 to 5, moderate to mild PEW; SGA 6 and 7, well nourished.

demonstrated relationship between worsening nutritional condition with the advance of CKD in previous studies.9,12,18-20 It is important to highlight that the presence of comorbidities, which are commonly associated with CKD, was also an important determinant of PEW in the present study. Considering the SGA method involves a judgment of nutritional status based on several components, we were interested in evaluating the influence of each category into the final score. In accordance with previous studies with patients on dialysis,2,4 we found that the alteration of physical examination, which includes the detection of muscle and/or fat wasting, was the most frequent abnormality in the identification of PEW. It is well known that a number of CKD-related disturbances contribute to the reduction of body compartments, especially of lean body mass. This finding is of importance because loss of muscle mass has been demonstrated to be associated with poor outcomes in CKD patients.1,21,22 Specifically, using the physical examination of the SGA method, Carrero et al.23 showed that a moderate to severe muscle wasting was associated Table 3. Anthropometric Parameters According to SGA Groups in 494 Nondialysis-Dependent CKD Patients Parameters BMI (kg/m2) ,23 kg/m2 (%) MAC adequacy #90% (%) MAMC adequacy #90% (%) TSF adequacy #90% (%)

SGA #5

SGA 6

SGA 7

81 (16%)

191 (39%)

222 (45%)

22.0 6 3.9* 27.0 6 5.0† 29.5 6 5.5 60.5* 19.4† 7.7 82.8 6 11.0* 98.8 6 15.6† 104.6 6 14.2 79.0* 31.4† 12.6 86.2 6 10.2* 98.9 6 14.3 101.0 6 12.3 65.5* 28.3† 18.5 77.5 6 38.6* 109.4 6 52.7† 132.9 6 64.8 70.4* 36.7† 22.6

BMI, body mass index; CKD, chronic kidney disease; MAC, midarm circumference; MAMC, midarm muscle circumference; SGA, subjective global assessment; TSF, triceps skinfold thickness. Values expressed as mean 6 standard deviation or percent. *P , .05 versus SGA 6 and 7. †P , .05 versus SGA 7.

with 2.62 and 3.04 increase in mortality risk of incident and prevalent patients on hemodialysis, respectively. Anorexia is another common complication of CKD implicated with the development PEW. Indeed, decreased protein and energy intake because of poor appetite is highly prevalent among CKD patients and it has been associated with worse outcomes.24-26 Despite the subjective nature of food intake evaluation in the SGA questionnaire, decreased appetite seems to be an important contributor to PEW diagnosis because change in dietary intake was the second most frequent component among our patients classified with SGA #5. The concurrent validity of SGA was tested by comparing the derived scores with the well-established anthropometric parameters for nutritional evaluation. In accordance with the previous studies in dialysis population,4,5 we showed that the impairment of nutritional status detected by SGA was accompanied by the decrease of anthropometric markers. In addition, a moderate to good agreement of SGA #5 with anthropometric markers found herein corroborates the validity of SGA in CKD patients in the nondialysis stages. In several studies, patients with a final SGA score of 6 are grouped with those scored with SGA 7. However, in the present study, because of the relatively elevated frequency of nutritional abnormalities such as reduced food intake and gastrointestinal symptoms in the SGA 6 group, it seems Table 4. Agreement Between SGA #5 and Anthropometric Markers of PEW in 494 Nondialysis-Dependent CKD Patients Parameters BMI ,23 kg/m2 MAC #90% MAMC #90% TSF #90%

Kappa Coefficient

95% CI

0.56 0.64 0.45 0.43

0.47-0.65 0.54-0.73 0.34-0.57 0.32-0.55

BMI, body mass index; CI, confidence interval; CKD, chronic kidney disease; MAC, midarm circumference; MAMC, midarm muscle circumference; PEW, protein–energy wasting; SGA, Subjective global assessment; TSF, triceps skinfold thickness.

PEW BY SGA IN CKD

advisable to analyze separately patients classified with SGA 6 to provide appropriate nutritional care as early as possible. Therefore, because SGA comprises a combination of a variety of PEW markers, this tool may contribute to early detect nutritional abnormalities in these patients. Limitations of the present study should be mentioned. Its cross-sectional design precludes the validation of SGA in relation to outcomes. In addition, anthropometric data were not available in the entire cohort for the concurrent validation of the SGA method. In fact, this study faces the usual limitations of the studies based on database, challenging particular aspects as missing data (e.g., some important confounders such as biochemical parameters were not available). However, our cohort was representative, and the data available reflected the majority of important predictors of PEW. Finally, because our results were based on patients referred to a single center, which may reduce the generalizability of our findings, validation of our results in other patient population is recommended. In conclusion, this study conducted in a large and representative cohort of NDD-CKD patients showed a prevalence of 11% of PEW by the SGA method. The physical examination component (muscle/fat wasting) was the most frequent alteration found in those patients. Compared with anthropometric markers, the 7-point SGA demonstrated to be a valid tool to diagnose PEW in nondialysisdependent CKD patients. Further studies investigating the predictive power of SGA including hard outcomes in this population of patients are warranted.

Practical Application This study highlights the utility of SGA as a valuable tool to be used in the clinical practice for diagnosing PEWand to detect early signs of PEW of patients in the nondialysis stages of CKD.

Acknowledgment This study was supported by Oswaldo Ramos Foundation. The authors would like to express our gratitude for the dietitians who have performed the SGA evaluation as part of their clinical practice. The authors thank Mariana Leister Rocha and Ana Catarina Medeiros de Castro for their assistance in collecting the data. The authors have no conflict of interest to declare.

References 1. Noori N, Kopple JD, Kovesdy CP, et al. Mid-arm muscle circumference and quality of life and survival in maintenance hemodialysis patients. Clin J Am Soc Nephrol. 2010;5:2258-2268. 2. de Mutsert R, Grootendorst DC, Boeschoten EW, et al. Subjective global assessment of nutritional status is strongly associated with mortality in chronic dialysis patients. Am J Clin Nutr. 2009;89:787-793. 3. Feroze U, Noori N, Kovesdy CP, et al. Quality-of-life and mortality in hemodialysis patients: roles of race and nutritional status. Clin J Am Soc Nephrol. 2011;6:1100-1111.

389

4. Enia G, Sicuso C, Alati G, et al. Subjective global assessment of nutrition in dialysis patients. Nephrol Dial Transplant. 1993;8:1094-1098. 5. Steiber A, Leon JB, Secker D, et al. Multicenter study of the validity and reliability of subjective global assessment in the hemodialysis population. J Ren Nutr. 2007;17:336-342. 6. Adequacy of dialysis and nutrition in continuous peritoneal dialysis: association with clinical outcomes. Canada-USA (CANUSA) Peritoneal Dialysis Study Group. J Am Soc Nephrol. 1996;7:198-207. 7. Mazairac AH, de Wit GA, Penne EL, et al. Protein-energy nutritional status and kidney disease-specific quality of life in hemodialysis patients. J Ren Nutr. 2011;21:376-386 e371. 8. Oliveira GT, Andrade EI, Acurcio Fde A, et al. Nutritional assessment of patients undergoing hemodialysis at dialysis centers in Belo Horizonte, MG, Brazil. Rev Assoc Med Bras. 2012;58:240-247. 9. Lawson JA, Lazarus R, Kelly JJ. Prevalence and prognostic significance of malnutrition in chronic renal insufficiency. J Ren Nutr. 2001;11:16-22. 10. Holden RM, Morton AR, Garland JS, et al. Vitamins K and D status in stages 3-5 chronic kidney disease. Clin J Am Soc Nephrol. 2010;5:590-597. 11. Campbell KL, Ash S, Bauer JD, et al. Evaluation of nutrition assessment tools compared with body cell mass for the assessment of malnutrition in chronic kidney disease. J Ren Nutr. 2007;17:189-195. 12. Cupisti A, D’Alessandro C, Morelli E, et al. Nutritional status and dietary manipulation in predialysis chronic renal failure patients. J Ren Nutr. 2004;14:127-133. 13. Stenvinkel P, Barany P, Chung SH, et al. A comparative analysis of nutritional parameters as predictors of outcome in male and female ESRD patients. Nephrol Dial Transplant. 2002;17:1266-1274. 14. Frisancho AR. New norms of upper limb fat and muscle areas for assessment of nutritional status. Am J Clin Nutr. 1981;34:2540-2545. 15. Fouque D, Kalantar-Zadeh K, Kopple J, et al. A proposed nomenclature and diagnostic criteria for protein-energy wasting in acute and chronic kidney disease. Kidney Int. 2008;73:391-398. 16. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604-612. 17. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373-383. 18. Duenhas MR, Draibe SA, Avesani CM, et al. Influence of renal function on spontaneous dietary intake and on nutritional status of chronic renal insufficiency patients. Eur J Clin Nutr. 2003;57:1473-1478. 19. Ikizler TA, Greene JH, Wingard RL, et al. Spontaneous dietary protein intake during progression of chronic renal failure. J Am Soc Nephrol. 1995;6:1386-1391. 20. Kopple JD, Greene T, Chumlea WC, et al. Relationship between nutritional status and the glomerular filtration rate: results from the MDRD study. Kidney Int. 2000;57:1688-1703. 21. Araujo IC, Kamimura MA, Draibe SA, et al. Nutritional parameters and mortality in incident hemodialysis patients. J Ren Nutr. 2006;16:27-35. 22. Huang JW, Lien YC, Wu HY, et al. Lean body mass predicts long-term survival in Chinese patients on peritoneal dialysis. PLoS One. 2013;8:e54976. 23. Carrero JJ, Chmielewski M, Axelsson J, et al. Muscle atrophy, inflammation and clinical outcome in incident and prevalent dialysis patients. Clin Nutr. 2008;27:557-564. 24. Burrowes JD, Larive B, Chertow GM, et al. Self-reported appetite, hospitalization and death in haemodialysis patients: findings from the Hemodialysis (HEMO) Study. Nephrol Dial Transplant. 2005;20:2765-2774. 25. Lopes AA, Elder SJ, Ginsberg N, et al. Lack of appetite in haemodialysis patients–associations with patient characteristics, indicators of nutritional status and outcomes in the international DOPPS. Nephrol Dial Transplant. 2007;22:3538-3546. 26. Carrero JJ. Identification of patients with eating disorders: clinical and biochemical signs of appetite loss in dialysis patients. J Ren Nutr. 2009;19:10-15.