An integrative approach to detect protein–energy wasting among chronic kidney disease maintenance hemodialysis patients

Sunitha Premalatha; Namratha Shivani; Vaishnavi Yadav; Urmila Anandh

doi:10.4103/jrnm.jrnm_15_21

ORIGINAL ARTICLE

Year : 2021 | Volume : 7 | Issue : 2 | Page : 43-47

An integrative approach to detect protein–energy wasting among chronic kidney disease maintenance hemodialysis patients

Sunitha Premalatha¹, Namratha Shivani¹, Vaishnavi Yadav¹, Urmila Anandh²
¹ Department of Nutrition, Yashoda Hospitals, Somajiguda, Hyderabad, Telangana, India
² Department of Nephrology, Yashoda Hospitals, Secunderabad, Telangana, India

Date of Submission	08-Sep-2021
Date of Acceptance	14-Sep-2021
Date of Web Publication	25-Feb-2022

Correspondence Address:
Dr. Urmila Anandh
Department of Nephrology, Yashoda Hospitals, Secunderabad, Telangana
India

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jrnm.jrnm_15_21

Abstract

Background: Malnutrition is a major predictor of overall outcome in patients on hemodialysis. Regular and frequent evaluation of the nutritional status of these patients is advisable. Aims and Objectives: This study aimed to look at nutritional status of a hemodialysis cohort and to evaluate whether multiple assessment tools improve the detection of malnutrition in this cohort. Materials and Methods: A prospective study in two outpatient hemodialysis centers was conducted over 6 months. Stable patients without any irreversible organ damage and preserved cognitive function were included in the study. Data collected included demographics, comorbid conditions, and baseline laboratory investigations. The nutritional assessment tools included body mass index (BMI), 7-point Subjective Global Assessment, Global Leadership In Malnutrition (GLIM), handgrip strength, and body composition analysis. Results: A total of 121 subjects (77 males, 44 females) participated in the study. Based on BMI, only 14% were underweight. 7-point SGA detected 77 malnourished subjects, whereas according to GLIM criteria, all patients had some degree of malnutrition. Body composition analysis showed depleted total body protein mass in majority of patients. There was a correlation between total body protein mass and handgrip strength. The assessment tools showed some degree of correlation in patients who were malnourished. Conclusions: Use of a single assessment tool often underdiagnoses malnutrition in hemodialysis patients. An integrative approach using multiple evaluation tools may be beneficial in these groups of patients.

Keywords: 7-point Subjective Global Assessment, Global Leadership In Malnutrition, handgrip strength, protein–energy wasting

How to cite this article:
Premalatha S, Shivani N, Yadav V, Anandh U. An integrative approach to detect protein–energy wasting among chronic kidney disease maintenance hemodialysis patients. J Renal Nutr Metab 2021;7:43-7

How to cite this URL:
Premalatha S, Shivani N, Yadav V, Anandh U. An integrative approach to detect protein–energy wasting among chronic kidney disease maintenance hemodialysis patients. J Renal Nutr Metab [serial online] 2021 [cited 2023 May 28];7:43-7. Available from: http://www.jrnm.in/text.asp?2021/7/2/43/338548

Introduction

Malnutrition is a powerful predictor of morbidity and mortality.^[1] This is particularly important in patients with chronic kidney disease (CKD) as malnutrition plays an important underlying role in the two most important causes of mortality in this subgroup of patients – cardiovascular disease and infections.^[2] The prevalence of malnutrition worsens as the glomerular filtration rate declines.^[3] This makes it necessary to assess the nutritional status of renal failure patients periodically and take measures to prevent malnutrition. Malnutrition is usually caused by the combination of inadequate nutrient intake, inflammatory catabolic illnesses, inflammatory processes that are associated with specific diseases other than CKD, oxidant stress, carbonyl stress, increased nutrient losses in urine (e.g., proteinuria) or dialysate (e.g., protein, peptide, and free amino acid losses), decreased circulating concentrations of anabolic hormones, increased levels of catabolic hormones, metabolic acidosis, aging, and physical deconditioning.^[4],[5] The prevalence of malnutrition in maintenance hemodialysis (MHD) has been reported to be quite high, almost half of dialysis patients in a study from Palestine had malnutrition.^[6] It is higher in peritoneal dialysis compared to MHD patients in the <65 years age group.^[7] Early detection of malnutrition requires vigilant clinical evaluation and regular nutritional assessment in this subset of patients.^[8] We report the use of multiple nutritional assessment tools (7-point Subjective Global Assessment [SGA], handgrip, body composition analysis, and Global Leadership In Malnutrition [GLIM] scale) in MHD patients and suggest an integrative approach in the evaluation of malnutrition.

Materials and Methods

A prospective study was conducted in two hemodialysis centers over a period of 6 months. All adults who were on maintenance hemodialysis and in clinically stable condition were included in the study. Children (age <18 years of age), pregnant or lactating women, and terminally ill patients with irreversible organ damage (chronic decompensated liver disease and congestive heart failure) were excluded from the study. Patients with cognitive impairment and underlying psychiatric illness which precludes them to understand the nature of the study and prevents them from giving informed consent were also excluded from the study.

Snowball sampling (random/nonprobability sampling) methodology was used to select the patients based on the inclusion/exclusion criteria.

Study description

MHD patients undergoing twice/thrice-weekly dialysis on an outpatient basis in two units of a quaternary referral center hospital participated in the study. Study measurements were performed at baseline (at enrollment). Data on demographics (age, gender, and education qualifications), comorbid conditions, personal habits (smoking, alcohol intake), height, weight, and functional ability were collected and used for final analysis. Body mass index (BMI) in kg/m² was calculated from height and weight. Body composition measures included body weight, muscle mass, protein mass, fat mass, and subcutaneous fat which were derived from bioelectrical impedance analysis (Body composition analyzer Omron Healthcare Co. Ltd., Japan). Handgrip strength (HGS) was measured with a baseline hydraulic hand dynamometer (Fabrication Enterprises Inc., Elmsford, NY, USA) after 1 h post dialysis. Data on HGS were collected on all the three dialysis visits on the week of study and the mean of all the three values was considered in the final analysis. While assessing handgrip strength, it was ascertained that the patients had used nonfistula hand for the measurement of HGS. Information from other assessment tools such as 7-point SGA and GLIM was collected only during the first visit. Values were recorded and analyzed using SPSS software (SPSS Version Version 21. Armonk, NY, USA)

A semi-structured valid questionnaire was used to collect the data related to sociodemographic details of the subject, biochemical parameters, personal habits, and 7-point SGA, GLIM, and BCA details.

Assessment tools

7-point Subjective Global Assessment

7-point SGA is a semi-quantitative method for determining nutritional status. SGA is often used in hemodialysis patients, both for research and clinical practice. 7-point SGA derives from SGA which is used routinely in dialysis patients and is recommended by KDOQI 2020 guidelines.^[9] The 7-point SGA measurement is essentially the same as the original SGA. The original SGA has a bias in food intake, functional capacity, fluid accumulation status when used in late-stage CKD patients.^[10] The assessment is further classified into 7 assessment sections where a score of 6–7 is said to be good nutrition, 3–5 is said to be mild-to-moderate malnutrition, and 1–2 is said to be severe malnutrition.

Global Leadership In Malnutrition

The Global Leadership Initiative on Malnutrition (GLIM) created a consensus-based framework consisting of phenotypic and etiologic criteria to record the occurrence of malnutrition in adults. This is a minimum set of practicable indicators for use in characterizing a patient as malnourished, considering the global variations in screening and nutrition assessment, and to be used across different health care settings. The top five ranked criteria included three phenotypic criteria (nonvolitional weight loss, low BMI, and reduced muscle mass) and two etiologic criteria (reduced food intake or assimilation, and inflammation or disease burden). To diagnose malnutrition, at least one phenotypic criterion and one etiologic criterion should be present. Phenotypic metrics for grading severity as Stage 1 (moderate) and Stage 2 (severe) malnutrition are proposed. It is recommended that the etiologic criteria be used to guide intervention and anticipated outcomes. The recommended approach supports the classification of malnutrition into four etiology-related diagnosis categories.^[11]

Handgrip

Hydraulic hand dynamometer is an instrument which is used to test a person's general strength level. Handgrip measurement, a measure of muscle function, is also used as a surrogate marker for muscle mass and is an indicator of nutrition status. The participant is asked to sit comfortably with the shoulder adducted and neutrally rotated, with the elbow toward the body and flexed at 90° with the forearm and wrist in a neutral position. Hand dynamometer is placed in the participant's hand in a way it fits comfortably in the hand. The indicator needle is reset by rotating it to zero. The participant is requested to squeeze with maximum strength. The needle will automatically record the highest force exerted.^[12],[13]

Body composition analysis

Body composition analysis is a method that describes the various components of the body that include body fat, bone weight, muscle mass, and body water. It is a more accurate method of describing weight than BMI. The given body composition analyzer works on bioelectrical impedance analysis (BIA). BIA is a method of measuring impedance by applying alternating electrical currents to a user, measuring their volume of water through impedance values. This noninvasive technique involves the placement of electrodes on the person's feet, hands, or both. A low-level electrical current is sent through the body and the flow of the current is affected by the amount of water in the body. BIA device measures how this signal is impeded through different types of tissue (muscle has high conductivity, but fat slows the signal down).^[14] We looked at the muscle mass, total protein mass, fat mass, and subcutaneous fat mass and visceral fat mass index in our study. The components were classified as low, ideal, and high according to ranges available with the machine. Visceral fat index was categorized as ideal, alert, and danger subgroups.

Results

A total of 121 MHD patients were included in the study. There were 44 (36%) females in the observational cohort. Of the 121, 77 (64%) patients had diabetes mellitus and 110 (91%) had hypertension. The mean (± standard deviation [SD]) age of the cohort was 56.59 (±13.58) years. Most of the patients were on long-term maintenance hemodialysis for more than 6 months. One patient was on dialysis for more than 193 months. The mean (±SD) dialysis vintage was 28.42 (±28.67) months. The biochemical parameters of the cohort are given in [Table 1]. The mean levels of serum creatinine, blood urea nitrogen, serum potassium, and serum phosphorus were high for the cohort as is expected of an MHD cohort. The lowest serum albumin level was 2 g/dl, but the mean serum albumin levels of the cohort were satisfactory. The mean hemoglobin level was also in the acceptable range, as most patients on dialysis were on iron supplementation and erythropoiesis-stimulating agents.

Table 1: Laboratory parameters of the maintenance hemodialysis patients

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The basic nutritional and body composition analyses data are given in [Table 2]. In the current study, according to BMI assessment, underweight patients were 17 (14%), normal weight were 34 (28.1%), and 55% were classified as overweight or obese (I and II). According to 7-point SGA criteria, the frequency of well-nourished patients was 44 (36.4%), 75 (62%) were mild to moderately malnourished, and 2 (1.7%) were severely malnourished. According to GLIM criteria, 84 (69.4%) patients were moderately malnourished, whereas 37 (30.6%) patients were severely malnourished. There was not a single patient with normal nutrition according to GLIM in our cohort.

Table 2: Basic anthropometric data and body composition analyses of the cohort

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The nutritional status of the patients based on the nutritional assessment tools (7-point SGA and GLIM) is given in [Table 3]. It is apparent that nutritional tools detect degrees of malnutrition differently. In our study using 7-point SGA, we had 44 well-nourished individuals on dialysis, whereas there were none with the GLIM criteria. However, these nutritional tools show a significant correlation in malnourished patients. A correlation done between BMI and GLIM (P = 0.001) and 7-point SGA (P = 0.011) showed a significant negative correlation between these tools [Table 4]. Hence, it can be interpreted that as the BMI decreases, the severity of malnutrition increases according to 7-point SGA and GLIM scores. A positive correlation was noted between HGS and muscle mass in BCA.

Table 3: Nutritional status of the cohort based on two different assessment tools

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Table 4: Correlation between body mass index, Global Leadership In Malnutrition, and 7-point Subjective Global Assessment

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The results obtained in body composition analysis are given in [Table 5]. It is to be noted that 57% of patients have low total body protein mass in our study. The total body fat mass seems to be preserved in majority of our patients. The visceral fat index showed that 60% of the subjects had ideal visceral fat. About 40% of our subjects had high levels of visceral fat which has been shown in many studies in Indian subjects.

Table 5: Body composition analysis data of the cohort (n=118)

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Discussion

Malnutrition in HD is multifactorial and plays a major role in the quality of life and mortality in these patients.^[15] Assessment of nutritional status with a single tool can often give the treating physician misleading information. Emphasis on weight only as a follow-up parameter is inadequate as there are many fallacies in estimating weight in a volume overloaded HD patient.^[16] In addition, weight can decrease during an intercurrent illness. Higher BMI in the general population is associated with an increased cardiovascular and all-cause mortality, whereas in the HD population, higher BMI has a paradoxical impact.^[17] One of the reasons for this paradox is that an elevated BMI may actually have an increased lean body mass. Hence, a simple BMI as a nutritional tool may not give the right picture and a body composition analysis is perhaps a better assessment tool to understand malnutrition in HD patients.

Furthermore, over the years, the knowledge, inflammation plays an important role in malnutrition in the dialysis population, is increasingly becoming clearer. Many authors emphasize the role of protein–energy wasting (PEW) in these patients as an important parameter predicting mortality. This concept of PEW was introduced in 2007 emphasizing the role of uremic toxins, and inflammation in the progressive loss of body protein and energy stores, finally leading to loss of muscle and fat mass and cachexia.^[18] This concept should be differentiated from malnutrition arising from simple inadequate nutrient intake.^[19]

The nutritional tools detecting malnutrition in HD patients should also look at the component of inflammation in these patients. Assessment tools such as Malnutrition Inflammation Score (MIS), Dialysis Malnutrition Score (DMS), and recently developed GLIM are used to assess inflammation in HD patients. We used GLIM in our study and the results showed that with the use of 7-point SGA alone, we miss many malnourished patients who need clinical intervention. We used GLIM as an assessment tool as it is useful in picking up early malnutrition and also looks at the inflammatory component of PEW, similar to that of MIS.^[20] Handgrip gives an easy point of care evaluation of the muscle mass of the patients and a body composition analysis gives a complete picture of all components including fat mass. BCA is an advanced tool which reflects the total body protein and fat mass accurately. Both total body protein fat mass and protein mass are predictors of mortality.^[21],[22] BCA can be used in patients where we need to detect and treat PEW early and effectively. It can also be used to monitor the efficacy of the interventions offered to these patients.

Our study emphasizes the utility of multiple evaluation tools in the detection of malnutrition in HD patients. A single tool can often miss early nutritional distress. Ours is one of the earliest studies where we have used GLIM as an assessment tool.

The major limitation of our study is the lack of prospective follow-up to understand which tool gives us a better understanding of clinical outcomes. We wish to address this in an ongoing prospective study.

Conclusions

Malnutrition is common in hemodialysis patients and often impacts the overall outcome of these patients. Regular evaluation of nutritional status is advised in these vulnerable patients. Use of an integrated approach using multiple assessment tools looking at various facets of nutritional status often improves early detection and intervention in these patients.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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