Home About us Current issue Back issues Submission Instructions Advertise Contact Login   

Search Article 
  
Advanced search 
 
Saudi Journal of Kidney Diseases and Transplantation
Users online: 3129 Home Bookmark this page Print this page Email this page Small font sizeDefault font size Increase font size 
 

Table of Contents   
ORIGINAL ARTICLE  
Year : 2017  |  Volume : 28  |  Issue : 6  |  Page : 1307-1313
Nutrition screening tools as predictor of malnutrition for hemodialysis patients in Dr. Sardjito Hospital in Yogyakarta, Indonesia


1 Department of Nutrition and Health, Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia
2 Department of Internal, Faculty of Medicine, Dr. Sardjito Hospital, Universitas Gadjah Mada, Yogyakarta, Indonesia

Click here for correspondence address and email

Date of Web Publication18-Dec-2017
 

   Abstract 


The risk of malnutrition in maintenance hemodialysis (MHD) patients must be monitored routinely through nutrition screening so that morbidity and mortality can be decreased. Comparing the validity of the simple nutrition screening tool (SNST) and nutritional risk screening 2002 (NRS 2002) as valid and reliable nutrition screening tools in predicting malnutrition. The data were collected from March to April 2015 in the Hemodialysis Unit of Dr. Sardjito Hospital, Indonesia as an observational study. A cross-sectional design study was used to screen 105 MHD patients using the SNST and NRS 2002, and then, the nutritional status of all individuals was assessed used the following subjective parameters: subjective global assessment (SGA) and dialysis malnutrition score (DMS). The objective parameters were the following: Body mass index (BMI), mid-upper-arm circumference (MUAC), handgrip strength (HGS), and a three-day food record. Chi-squared test, t-test, and receiving operating characteristic curve were used for the statistical analysis. In predicting malnutrition, the validity of the SNST is better than the NRS 2002 in MHD patients against either SGA (Se 94.3% vs. 82.9%; Sp 60% vs. 58.6%; and area under curve (AUC) 0.847 vs. 0.749) or DMS (Se 90.0% vs. 81.6%; Sp 74.0% vs. 62.8%; and AUC 0.833 vs. 0.746), while the NRS 2002 is better than the SNST based on BMI, MUAC, HGS, and energy intake (P <0.001). In predicting malnutrition, SNST is better than NRS 2002 based on the subjective assessments (SGA and DMS), and NRS 2002 is better than SNST based on the objective assessments (BMI, MUAC, and HGS).

How to cite this article:
Susetyowati S, Djarwoto B, Faza F. Nutrition screening tools as predictor of malnutrition for hemodialysis patients in Dr. Sardjito Hospital in Yogyakarta, Indonesia. Saudi J Kidney Dis Transpl 2017;28:1307-13

How to cite this URL:
Susetyowati S, Djarwoto B, Faza F. Nutrition screening tools as predictor of malnutrition for hemodialysis patients in Dr. Sardjito Hospital in Yogyakarta, Indonesia. Saudi J Kidney Dis Transpl [serial online] 2017 [cited 2019 Dec 5];28:1307-13. Available from: http://www.sjkdt.org/text.asp?2017/28/6/1307/220871



   Introduction Top


End-stage renal disease (ESRD) is a major public health problem contributing to significant morbidity and mortality.[1] Protein–energy malnutrition (PEM) is the one of major problems in maintenance hemodialysis (MHD) patients which increases the risk of infection, difficult wound healing, fatigue, malaise, and the risk of morbidity and mortality.[2],[3] The prevalence of PEM in ESRD population according to various reports ranges between 20% and 71%.[2],[3],[4],[5],[6],[7]

Nutritional Risk Screening 2002 (NRS 2002) was recommended by The European Society for Clinical Nutrition and Metabolism (ESPEN) as a valid and reliable nutrition screening tool to predict malnutrition for hospitalized adult patients,[8] but there have few studies in out-patient settings, such as with monitoring MHD patients.[9]

Susetyowati et al have developed a nutrition screening tool named Simple Nutrition Screening Tool (SNST) as a valid screening tool that is reliable, simple, and rapid, which can be performed by any health-care provider, in addition, is noninvasive and does not need anthropometry or biochemical measurements.[10] Hence, the SNST offers operational feasibility in large units. Studies about the implementation of SNST have been done for outpatient diabetic patients[11] but not for MHD patients.

The National kidney foundation Kidney Disease/Dialysis Outcome and Quality Initiative recommended subjective global assessment (SGA) as a nutrition assessment for the MHD population,[12] which was developed into a dialysis malnutrition score (DMS) as nutrition assessment specifically for MHD patients with a scoring system that is better than SGA.[13] Studies on the ability of nutrition screening tools to predict malnutrition have been performed but have rarely specifically examined MHD patients.[14]

This study aimed to compare the validity, i.e., sensitivity (Se), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV), and area under curve (AUC), of both the SGA and DMS, and determine the ability of the nutrition screening tools to predict the risk of malnutrition against objective assessment (body mass index (BMI), mid-upper arm circumference (MUAC), handgrip strength (HGS), and three-day food record).


   Subjects and Methods Top


This was an observational study with a cross-sectional study design. The data were collected from March to April 2015 in Dr. Sardjito Hospital. Individuals were selected by purposive sampling, and 105 individuals were obtained. The inclusion criteria included the following: MHD ×2/week for ≥3 months, full consciousness (compos mentis), age ≥19 years old, able to communicate well, and written informed consent from a individual. The exclusion criteria included pregnant or postpartum patients and nonhospitalized patients. The study was approved by the Ethic Committee of Faculty of Medicine, Universitas Gadjah Mada, Dr. Sardjito Hospital. Data were collected using SNST, NRS 2002, SGA, DMS, three-day food record, and measurements, i.e., HGS, BMI, and MUAC. Interviews and measurements were performed by trained enumerators in the same sitting in the HD unit of Dr. Sardjito Hospital, Yogyakarta, Indonesia. All of the assessments were made by a single observer. Independent variables were the SNST and NRS 2002; the dependent variables were SGA, DMS, and the three-day food record, HGS, BMI, and MUAC.

First, the individual was screened by the SNST and NRS 2002 to determine the risk of malnutrition (at risk or not). The SNST nutrition screening tool includes six simple questions without the need for anthropometry measurements.[10],[15] The questions are as follows: “Does the patients look thin?,” “Have you recently lost weight unintentionally (6 months)?,” “Have you decreased your food intake during a week?,” “Do you feel weak, sluggish and lethargic?,” and “Do you suffer from a disease that results in a change in the amount or type of food you eat?” Each question of the SNST is scored 0 for a “No” answer and 1 for a “Yes” answer. The subject is categorized at risk of malnutrition if the total score >2.[12],[16]

The NRS 2002 questionnaire includes four questions during the initial screening about BMI, weight loss in the past three months, low dietary intake in the past week, and the severity of disease. If there are any positive responses, follow-up screening is required. The follow-up screening is about nutritional status, food intake, and severity of disease. Malnutrition risk is established if the total scores of all points in the follow-up screening ≥3.[8]

Then, the subject was assessed by SGA, DMS,BMI, MUAC, HGS, and three days food record to determine their nutrition status (malnutrition or not). BMI was calculated as the dry weight in kilograms divided by the square of height in meters. We assumed the dry weight as the weight recorded at the end of dialysis. The MUAC and HGS are the measurements that are most often used to detect PEM, where the amount of fatty tissue under the skin is small.[15] The three-day food record was used to evaluate energy and protein intake.

The SGA questions included weight loss during the past six months, symptoms of gastrointestinal tract dysfunction, functional capacity, loss of subcutaneous fat, and edema or ascites, while the DMS questions were the same as the SGA, but there was an additional question about the history of dialysis. Malnutrition was established if the total score of the SGA questionnaire was B or C, while in the DMS questionnaire malnutrition was established if the total score was 8–35.[13]

A univariate analysis was used to analyze the characteristic data, and a bivariate analysis was performed using Chi-squared. The diagnostic tests, i.e., Se, Sp, NPV, PPV, and AUC, were calculated to compare the accuracy of both nutrition screening tools in predicting malnutrition. The AUC needs to be calculated as part of a validity test to determine the discrimination value of the nutrition screening tool. The discrimination values of the AUC determine the accuracy of the nutrition screening tool to detect malnutrition.[17] Values for each nutritional screening tool were interpreted as acceptable (0.70–0.80), excellent (0.80–0.90), or outstanding or the highest level (>0.90).[17] A t-test was used to determine the difference of the averages between the screening tools regarding the BMI, MUAC, HGS, and three-day food record for normal data, and the Mann–Whitney test was used for abnormal data.


   Results Top


Subject characteristics

Of the 105 HD patients, most were males (56.2%) [Table 1]. Moreover, the percentage of adults (41–60 years old) was the greatest (52.4%). Based on SNST, 58.1% of individuals were determined as a malnutrition risk, and 55.2% of individuals based on NRS 2002.
Table 1: Subject characteristics.

Click here to view


The comparison of nutrition assessment tools using the Subjective Global Assessment and Dialysis Malnutrition Score

[Table 2] shows the moderate agreement between the SGA and DMS (κ = 0.55, 95% confidence interval 0.40–0.55). More of the participants were malnourished using the DMS (41.0%) versus using SGA (33.4%).
Table 2: Comparison of nutrition assessment tools using the SGA and DMS.

Click here to view


The validity of nutrition screening tools against Subjective Global Assessment and Dialysis Malnutrition Score

A validity test was used to determine the ability of each tool to measure what should be measured.[18] In this study, the validity test was used to determine the ability of each nutrition screening tool in predicting malnutrition risk against the SGA and the DMS. [Table 3] demonstrates the values of Se, Sp, PPV, NPV, and AUC from the SNST were higher than those from the NRS 2002. This means that the validity of the SNST is better than the NRS 2002.
Table 3: Validity of nutrition screening tools against SGA and DMS.

Click here to view


The association between body mass index, mid-upper arm circumference, handgrip strength and the three-day food record and the nutrition screening tools

[Table 4] shows different averages between the SNST and NRS 2002 among the objective parameters. There were significant differences between individuals who were at risk and those not at risk for malnutrition regarding MUAC, HGS, and energy intake based on the SNST, while BMI, MUAC, HGS, and energy intake were significantly different in individuals who were at risk and not at risk of malnutrition based on the NRS 2002.
Table 4: Association between nutrition screening tools with objective parameter.

Click here to view



   Discussion Top


The present study compared two validated nutrition screening tools (SNST and NRS 2002) against two commonly used nutrition assessment tools (SGA and DMS) within MHD patients. A moderate agreement was found between the SGA and DMS (κ = 0.55, [Table 2]), indicating that these nutrition assessments identify different at-risk groups. The validity value (Se, Sp, NPV, PPV, and AUC) of the SNST was better than the NRS 2002 [Table 3] either against the SGA or DMS. This result is in accordance with the study of Faza et al[12] who stated that the SNST has a better validity than the NRS 2002.

A study by Susetyowati et al[15] showed that the SNST has a good validity against SGA as the gold standard and a good reliability in determining malnutrition risk (κ >0.700). The study on 287 hospitalized patients showed that there was an association between the SNST with SGA as the gold standard (P <0.05).[16] A study on 268 elderly patients hospitalized also showed an association between the SNST with anthropometry (BMI and MUAC) values and a biochemical assessment (albumin, hemoglobin and total lymphocytes) (P <0.001).[19] In accordance, the results of the two studies above were strengthened by the assessment that the SNST related more accurately to subjective and objective nutrition assessment.

A study by Saka at al[20] showed a strong correlation between the NRS 2002 and SGA (P <0.0001; r = 0.70). A similar study was prospectively conducted in 90 MHD patients and showed that the NRS 2002 related better to the nutrition assessment and biochemical parameters, i.e., protein serum and bioelectrical impedance (P <0.001; RP = 4.24).[9] The NRS 2002 also showed the same prevalence rate of malnutrition risk with the present study, which was approximately 54%, with statistically significant differences in serum albumin, hemoglobin B, and lymphocyte counts between MHD patients with or without malnutrition risk.[11] A study about the association between the NRS 2002 with DMS as a nutrition assessment has not been performed before because DMS was also a new nutrition assessment developed by Kalantar-Zadeh.[13]

The sensitivity of both the SNST and NRS 2002 was higher than the specificity. The sensitivity and specificity of the SNST were higher than the NRS 2002 [Table 3]. This is in accordance with the theory that states that a nutrition screening tool should have a high sensitivity so that it can predict more malnutrition risk in patients.[15] This is the intended nutritional care process and can be done properly so that malnutrition incidence can be prevented earlier.[15]

Based on the predictive value, the NPV was higher than the PPV both in the SNST and NRS 2002 [Table 3]. The NPV and PPV of the SNST were higher than the NRS 2002 [Table 3].

In the present study, the NPV of the SNST is higher than the NRS 2002 either against SGA or DMS, which means that the SNST is more sensitive than the NRS 2002 in predicting malnutrition in MHD patients, while the PPV is approximately 55% for both nutrition screening tools. Hence, these tools are useful for only initially screening whether the patient is at risk of malnutrition or not. The MHD patient who is at risk of malnutrition should be confirmed by either the SGA or DMS whether malnutrition is present or not.[8] Nutrition intervention should occur if the result of the SGA or DMS is malnutrition.[8] Hence, the SNST and NRS 2002 cannot substitute for the SGA and DMS as nutrition assessment tools.

The AUC value of the SNST >0.80 [Table 4], which means that the SNST had excellent discrimination.[21] Meanwhile, the AUC value of the NRS 2002 was within the range 0.70–0.80, which means that the NRS 2002 acceptably discriminated.[22] The previous study showed that the validity of the SNST was better than the NRS 2002 with SGA as the gold standard.[18] This is because all of the questions within the SNST represent four basic components, while the questions within the NRS 2002 only represented three basic components in formulating the nutrition screening recommended by ESPEN.[17]

Both of the nutrition screening tools analyzed the average of BMI, MUAC, HGS, and energy and protein intake to determine their association with objective parameters. There was a significant difference between the SNST with MUAC, HGS, and energy intake [Table 4], which means that patients at risk of malnutrition have lower MUAC, HGS, and energy intake values than those who are not at risk of malnutrition. Meanwhile, the BMI and protein intake also show different average values, which are lower in patients at risk of malnutrition but not significantly. This was not in accordance with the studies by Mayasari et al[19] and Susetyowati et al,[15] which state that there are significant differences between subjects at risk of malnutrition and those not at risk of malnutrition based on the SNST against BMI (P <0.001). Analyzed by the NRS 2002, a significant difference in BMI, MUAC, HGS, and energy intake occurred, which means that subjects at risk of malnutrition have BMI, MUAC, and HGS lower than those not at risk of malnutrition, while protein intake did not show a difference.

The results were different due to the difference of questionnaire components of the screening tools. The SNST was designed as a simple, rapid, valid, and reliable questionnaire without any components related to questions of anthropometry measurements, such as BMI and MUAC. Meanwhile, in developing the NRS 2002, there were questionnaire components related to anthropometry measurements such as BMI, weight loss, and food intake both in early and advanced screening.[23] Thus, the NRS 2002 is better in predicting malnutrition based on anthropometry parameters than the SNST.


   Conclusion Top


We can conclude that the SNST is a good predictor for malnutrition in MHD patients based on subjective parameters. Based on objective parameters, i.e., BMI, MUAC, and HGS, the NRS 2002 is better than the SNST in predicting malnutrition as demonstrated by significant differences in subjects at risk and not at risk of malnutrition.

We suggest nutrition screening should be done periodically to detect the risk of malnutrition. Both the SNST and NRS 2002 can be used as nutrition screening tools in MHD patients to predict the risk of malnutrition.

Conflict of interest: None declared.



 
   References Top

1.
Fatema K, Abedin Z, Mansur A, et al. Screening for chronic kidney diseases among an adult population. Saudi J Kidney Dis Transpl 2013;24:534-41.  Back to cited text no. 1
[PUBMED]  [Full text]  
2.
Yuvaraj A, Vijayan M, Alex M, Abraham G, Nair S. Effect of high-protein supplemental therapy on subjective global assessment of CKD-5D patients. Hemodial Int 2016;20:56-62.  Back to cited text no. 2
    
3.
Espahbodi F, Khoddad T, Esmaeili L. Evaluation of malnutrition and its association with biochemical parameters in patients with end stage renal disease undergoing hemodialysis using subjective global assessment. Nephrourol Mon 2014;6:e16385.  Back to cited text no. 3
    
4.
Chan M, Kelly J, Batterham M, Tapsell L. Malnutrition (Subjective Global Assessment) scores and serum albumin levels, but not body mass index values, at initiation of dialysis are independent predictors of mortality: A 10-year clinical cohort study. J Ren Nutr 2012;22:547-57.  Back to cited text no. 4
    
5.
Boado VJ, Redondo DC, Orio JF, et al. Nutritional assessment of patients on maintenance hemodialysis using dialysis malnutrition score (DMS). J Parenter Enteral Nutr 2014;-24:74-88.  Back to cited text no. 5
    
6.
As'habi A, Tabibi H, Nozary-Heshmati B, Mahdavi-Mazdeh M, Hedayati M. Comparison of various scoring methods for the diagnosis of protein-energy wasting in hemodialysis patients. Int Urol Nephrol 2014;46:999-1004.  Back to cited text no. 6
    
7.
Koor BE, Nakhaie MR, Babaie S. Nutritional assessment and its correlation with anthropometric measurements in hemodialysis patients. Saudi J Kidney Dis Transpl 2015;26:697-701.  Back to cited text no. 7
[PUBMED]  [Full text]  
8.
Mueller C, Compher C, Ellen DM, American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S.P.E.N. Clinical guidelines: Nutrition screening, assessment, and intervention in adults. JPEN J Parenter Enteral Nutr 2011;35:16-24.  Back to cited text no. 8
    
9.
Fiedler R, Jehle PM, Osten B, Dorligschaw O, Girndt M. Clinical nutrition scores are superior for the prognosis of haemodialysis patients compared to lab markers and bioelectrical impedance. Nephrol Dial Transplant 2009;24: 3812-7.  Back to cited text no. 9
    
10.
Susetyowati S, Hadi H, Hakimi M, Asdie AH. Development of nutrition screening tool method for hospitalized adult patients. Indones Clin Nutr J 2012;8:188-94.  Back to cited text no. 10
    
11.
Rohimah BB, Sugiarto S, Probandari AA, Wiboworini BB. Comparison of a simple nutrition screening tool (SNST) compared with subjective global assessment (SGA) in body mass index (BMI) assessments of type 2 diabetic patients validation of SNST versus BMI in T2 diabetes. Pak J Nutr 2016;15:412-8.  Back to cited text no. 11
    
12.
Faza F. Comparison of Simple Nutrition Screening Tool and Nutritional Risk Screening 2002 to Subjective Global Assessment and Dialysis Malnutrition Score for Chronic Kidney Disease Patients with Hemodialysis in Dr. Sardjito Hospital Yogyakarta. Thesis. Nutrition and Health, Universities Gadjah Mada 2016.  Back to cited text no. 12
    
13.
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 1999;14: 1732-8.  Back to cited text no. 13
    
14.
Steiber AL, Kalantar-Zadeh K, Secker D, et al. Subjective global assessment in chronic kidney disease: A review. J Ren Nutr 2004;14:191-200.  Back to cited text no. 14
    
15.
Susetyowati S, Hadi H, Hakimi M, Asdie AH. Development, validation and reliability of the simple nutrition screening tool (SNST) for adult hospital patient in Indonesia. Pak J Nutr 2014;13:157-63.  Back to cited text no. 15
    
16.
Andini R. Comparison Nutrition Screening Tool Method in Adult Patients Hospitalized: Simple Nutrition Screening Tool Study, Nutritional Risk Screening 2002, Malnutrition Screening Tool, and Malnutrition Universal Screening Tool in Yogyakarta. Thesis. Nutrition and Health, Universities Gadjah Mada, Indonesia 2014.  Back to cited text no. 16
    
17.
Hosmer DW Jr., Lemeshow S. Applied Logistic Regression 392 (John Wiley & Sons, 2004). Available from: http://www.books.google.com/books?hl=en&lr=&id=Po0RLQ7USIMC&pgis=1.  Back to cited text no. 17
    
18.
Rasmussen HH, Holst M, Kondrup J. Measuring nutritional risk in hospitals. Clin Epidemiol 2010;2:209-16.  Back to cited text no. 18
    
19.
Mayasari M, Susetyowati S, Lestariana W. Simple nutritional screening tool (SNST) has good validity to identify risk of malnutrition on hospitalized elderly patients. Pak J Nutr 2014;13:573-8.  Back to cited text no. 19
    
20.
Saka B, Ozturk BG, Uzun S, et al. Nutritional risk in hospitalized patients: Impact of nutritional status on serum prealbumin. Rev Nutr 2011;24:89-98.  Back to cited text no. 20
    
21.
Jones JM. Validity of nutritional screening and assessment tools. Nutrition 2004;20:312-7.  Back to cited text no. 21
    
22.
Zhu W, Zeng N, Wang N. Sensitivity, specificity, accuracy, associated confidence interval and ROC analysis with practical SAS® implementation. NESUG Health Care Life Sciences. 2010. http://www.cpdm.ufpr.br/documentos/ROC.pdf  Back to cited text no. 22
    
23.
Kondrup J, Rasmussen HH, Hamberg O, Stanga Z, Ad Hoc ESPEN Working Group. Nutritional risk screening (NRS 2002): A new method based on an analysis of controlled clinical trials. Clin Nutr 2003;22:321-36.  Back to cited text no. 23
    

Top
Correspondence Address:
Susetyowati Susetyowati
Department of Nutrition and Health, Faculty of Medicine, Universitas Gadjah Mada, North Sekip, Yogyakarta, 55281
Indonesia
Login to access the Email id


DOI: 10.4103/1319-2442.220871

PMID: 29265041

Rights and Permissions



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
   
 
 
    Similar in PUBMED
    Search Pubmed for
    Search in Google Scholar for
    Email Alert *
    Add to My List *
* Registration required (free)  
 


 
    Abstract
   Introduction
   Subjects and Methods
   Results
   Discussion
   Conclusion
    References
    Article Tables
 

 Article Access Statistics
    Viewed1705    
    Printed17    
    Emailed0    
    PDF Downloaded361    
    Comments [Add]    

Recommend this journal