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The association between MNA and PG-SGA malnutrition assessment and the quality of life among hemodialysis patients

Open AccessPublished:May 30, 2022DOI:https://doi.org/10.1016/j.cegh.2022.101075

      Abstract

      Background

      The simple nutritional assessment tools by Mini Nutritional Assessment (MNA) and Patient Generated Subjective Global Assessment (PG – SGA) was proposed to affect the Quality of Life (QOL) in hemodialysis patients. However, currently, no evidence assessed the potency of MNA and PG - SGA for predicting the QOL in hemodialysis patients.

      Objective

      To assess the potential implication of MNA and PG-SGA nutritional tools and the QOL among hemodialysis patients.

      Methods

      A cross - sectional study was performed in Universitas Muhammadiyah Malang Hospital, Malang, Indonesia. A validated Kidney Disease Quality of Life – 36™ (KDQOL – 36™) instrument was used to assess the QOL. The nutritional status was assessed using MNA and PG - SGA checklist. The association between nutritional status and QOL was determined by using multiple logistic regression.

      Results

      A total of 96 hemodialysis patients was enrolled in our study. Of them, good QOL was observed in 75 patients (78.12%). We found that hemodialysis patients with higher MNA score and lower PG - SGA score was associated with good QOL. We also found that normal MNA nutritional status was associated with good QOL. Moreover, we also found that the score of MNA ≥23.75 and PG - SGA score ≤3,5 were associated with good QOL.

      Conclusion

      MNA and PG-SGA nutritional assessment tools are the important indicator in predicting the QOL in hemodialysis patients.

      Keywords

      1. Introduction

      Hemodialysis was first introduced in 1943 by Willem Kolff for the management of end stage renal disease (ESRD). Since providing the efficient outcome, hemodialysis was widely used as a rescue therapy in the case of ESRD.
      • Wankowicz Z.
      The role of technological progress vs. accidental discoveries and clinical experience.
      The prevalence of ESRD was 10.6%–13.4%,
      • Hill N.R.
      • Fatoba S.T.
      • Oke J.L.
      • et al.
      Global prevalence of chronic kidney disease - a systematic review and meta-analysis.
      and of them, 13%–43% was treated with hemodialysis.
      • Robinson B.M.
      • Zhang J.
      • Morgenstern H.
      • et al.
      Worldwide, mortality risk is high soon after initiation of hemodialysis.
      The mortality rate of hemodialysis patients was 16.9%–26.7%.
      • Robinson B.M.
      • Zhang J.
      • Morgenstern H.
      • et al.
      Worldwide, mortality risk is high soon after initiation of hemodialysis.
      In the guideline for the management of ESRD, the potential outcomes should be evaluated, such as: mortality, comorbidity, renal bio - markers, anemia, mineral disorders, nutritional status, and Quality of Life (QOL).
      • Eknoyan G.
      • Lameire N.
      • Eckardt K.
      • et al.
      KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease.
      However, the majority studies only focused on the refinement of the bio – markers.
      • Hojs R.
      • Bevc S.
      • Ekart R.
      Biomarkers in hemodialysis patients.
      The limited studies assessing the QOL in hemodialysis patients suggested that the focus of ESRD management has changed from the commitment of patient care, from patient – centered care to disease – centered care.
      • Donahue K.T.
      • vanOstenberg P.
      Joint Commission International accreditation: relationship to four models of evaluation.
      This ironic circumstance should be returned to the primary objective of patient care. Therefore, the assessment of QOL in hemodialysis patients should be a priority.
      QOL assessment was first proposed in 1966 by Elkinton.
      • Elkinton J.R.
      Medicine and the quality of life.
      The QOL instruments included Assessment of Quality of Life – 4D (AQoL-4D); Control, Autonomy, Self-realization and Pleasure – 16 (CASP-16); EuroQol - 5D (EQ-5D); EuroQol - Visual Analogue Scale (EQ-VAS); Patient-Reported Outcomes Measurement Information System (PROMIS), Quality of life scale (QoL scale), 8-Item Short-Form Health Survey (SF-8), 12-Item Short-Form Health Survey (SF-12), and Medical Outcomes Study Short-Form 36 (SF-36);
      • Pequeno N.P.F.
      • Cabral N.L.A.
      • Marchioni D.M.
      • Lima S.
      • Lyra C.O.
      Quality of life assessment instruments for adults: a systematic review of population-based studies.
      and in the context of renal disease, the guideline has recommended the Kidney Disease Quality of Life – 36™ (KDQOL – 36™)
      • Eknoyan G.
      • Lameire N.
      • Eckardt K.
      • et al.
      KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease.
      which has been validated in several regions including Indonesia.
      • Supriyadi R.
      • Rakhima F.
      • Gondodiputro R.S.
      • Darmawan G.
      Validity and reliability of the Indonesian version of kidney disease quality of life (KDQOL-36) questionnaire in hemodialysis patients at hasan Sadikin hospital, Bandung, Indonesia.
      The components of KDQOL instrument consisted of SF – 12, burden kidney disease, symptoms or problems, and effect of kidney disease.
      • Cohen D.E.
      • Lee A.
      • Sibbel S.
      • Benner D.
      • Brunelli S.M.
      • Tentori F.
      Correction to: use of the KDQOL-36 for assessment of health-related quality of life among dialysis patients in the United States.
      Therefore, this instrument was reported reflecting the achievement of ESRD management. The QOL is governed by several factors including comorbidity, physiological aspect, physical health, relationships with other people and the environment in which the person lives, level of independence, and nutritional status.
      • Sosnowski R.
      • Kulpa M.
      • Zietalewicz U.
      • et al.
      Basic issues concerning health-related quality of life.
      Of them, some studies revealed that nutritional status was the simplest tool and having the high impact to affect the QOL.
      • Carson T.L.
      • Hidalgo B.
      • Ard J.D.
      • Affuso O.
      Dietary interventions and quality of life: a systematic review of the literature.
      ,
      • Amarantos E.
      • Martinez A.
      • Dwyer J.
      Nutrition and quality of life in older adults.
      The nutritional assessment tools might include Instant Nutritional Assessment (INA), Nutrition Risk Score (NRI), Mini Nutritional Assessment (MNA), and Patient Generated Subjective Global Assessment (PG – SGA).
      • Xu Y.C.
      • Vincent J.I.
      Clinical measurement properties of malnutrition assessment tools for use with patients in hospitals: a systematic review.
      Most of those tools have complexity in measurement and may involve laboratory examination and professional skills. To provide the frequent and comprehensive monitoring; the simple, reliable, easy to use, and non - invasive tool is required. Since MNA and PG-SGA have multifunctional property and simple to test, we speculated that MNA and PG-SGA might be able to evaluate the functional status and quality of life among hemodialysis patients.
      • Xu Y.C.
      • Vincent J.I.
      Clinical measurement properties of malnutrition assessment tools for use with patients in hospitals: a systematic review.
      However, to date, no study assessed the role of MNA and PG – SGA in predicting the QOL of hemodialysis patients. Therefore, we aimed to evaluate the association between the nutritional status, assessed by MNA and PG – SGA, and the QOL of hemodialysis patients. Our present study might provide the preliminary data concerning the application of MNA and PG – SGA instruments in the case of ESRD.

      2. Methods

      2.1 Design and participants

      A cross - sectional study was conducted in Universitas Muhammadiyah Malang Hospital, Malang, Indonesia. A minimal of 92 sample size was required based on the estimated prevalence of ESRD treated with hemodialysis was 10.6%–13.4%
      • Hill N.R.
      • Fatoba S.T.
      • Oke J.L.
      • et al.
      Global prevalence of chronic kidney disease - a systematic review and meta-analysis.
      with 5% margin error and 95% confidence interval, following the formula of sample size calculation for cross – sectional study n = Zα2P(1-P)/d2.
      • Charan J.
      • Biswas T.
      How to calculate sample size for different study designs in medical research?.
      We used a G power software to calculate the estimated sample size (G power ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany). The inclusion criteria were hemodialysis patients with age was more than 18 years old. The exclusion criteria were patients with hemodialysis duration less than three months, patients with end stage malignant disease, patients with uncorrected dry weight, and hemodynamically unstable. The protocols of our current study conformed with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist
      • von Elm E.
      • Altman D.G.
      • Egger M.
      • et al.
      Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.
      and the principles outlined in the declaration of Helsinki.
      • World Medical A.
      World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects.
      The STROBE checklist in our present study is outlined in the supplementary files.
      • Fajar J.
      Supplementarry files: the association between MNA and PG-SGA malnutrition assessment and quality of life among hemodialysis patients.
      Our present study had been registered and approved by the local ethical committee of Universitas Muhammadiyah Malang Hospital (No: E5a/214/KEPK-UMM/X/2021). Before involving in the study, the participants were explained on the aims, benefits, and risks of the study. Participants were also explained that they could quite from our study at any time. Participants were voluntary, and no incentive was given.

      2.2 Study covariates

      The predictor covariates in our present study were MNA and PG-SGA nutritional assessment. The MNA assessment was conformed with the checklist of full length MNA,
      • Guigoz Y.
      The Mini Nutritional Assessment (MNA) review of the literature--What does it tell us?.
      and PG-SGA was adapted from PG-SGA checklist.
      • Nitichai N.
      • Angkatavanich J.
      • Somlaw N.
      • Voravud N.
      • Lertbutsayanukul C.
      Validation of the scored patient-generated subjective global assessment (PG-SGA) in Thai setting and association with nutritional parameters in cancer patients.
      MNA assessment consisted of the following items: food intake, weight loss, mobility, psychological stress, neuropsychological problem, body mass index, daily activity, drug consumption, skin ulcer, daily intake, protein intake, fruit or vegetable intake, fluid consumption, mode of feeding, self - view of nutritional status, comparison to other people of the same age, mid – arm circumference, and calf circumference. The score <17 indicated malnutrition, score 17–23.5 indicated the risk of malnutrition, and score 24–30 indicated normal nutritional status.
      • Guigoz Y.
      The Mini Nutritional Assessment (MNA) review of the literature--What does it tell us?.
      For PG-SGA, the instrument consisted of weight, nutrient intake, nutrition impact symptoms, daily activity, and physical examination. The score 0–1 indicated well-nourished and no intervention is required (stage A), score 2–3 indicated moderate malnourished or suspected of being malnourished and educating patient and family is recommended (stage B), score 4–8 indicated severe malnourished and required intervention as indicated by symptoms (stage C), and score ≥9 indicated severely malnourished and implied critical need for intervention (stage D).
      • Nitichai N.
      • Angkatavanich J.
      • Somlaw N.
      • Voravud N.
      • Lertbutsayanukul C.
      Validation of the scored patient-generated subjective global assessment (PG-SGA) in Thai setting and association with nutritional parameters in cancer patients.
      We also assessed MNA and PG – SGA as continuous covariate (in score number) and determined the desire cut – off in our population. The outcome measure was health – related quality of life, measured by KDQOL – 36™, divided into poor QOL (score <50) and good QOL (score ≥50).
      • Cohen D.E.
      • Lee A.
      • Sibbel S.
      • Benner D.
      • Brunelli S.M.
      • Tentori F.
      Correction to: use of the KDQOL-36 for assessment of health-related quality of life among dialysis patients in the United States.
      A validated KDQOL – 36™ questionnaire (Indonesian version) adapted from previous studies in Indonesia was used to assess the QOL.
      • Supriyadi R.
      • Rakhima F.
      • Gondodiputro R.S.
      • Darmawan G.
      Validity and reliability of the Indonesian version of kidney disease quality of life (KDQOL-36) questionnaire in hemodialysis patients at hasan Sadikin hospital, Bandung, Indonesia.
      ,
      • Suhardjono
      • Umami V.
      • Tedjasukmana D.
      • Setiati S.
      The effect of intradialytic exercise twice a week on the physical capacity, inflammation, and nutritional status of dialysis patients: a randomized controlled trial.
      This instrument consisted of symptoms of kidney disease, effect of kidney disease, burden of kidney disease, and SF-12. Prior to use in the real study, the questionnaire was tested for reliability and validity in 30 participants. The reliability and validity of KDQOL -36™ questionnaire in our present study is presented in supplementary files. We also collected the baseline characteristics among groups, retrieved from medical records, including age, gender, body weight, body height, Body Mass Index (BMI), job type, educational levels, smoking status, comorbidity, and laboratory findings.

      2.3 Statistical analysis

      We presented our data in mean ± SD or n (%). The numerical covariates in our study were tested for normality using Kolmogorov - Smirnov test. Data were considered normal if the p value was more than 0.05. All baseline characteristics between groups were analyzed for homogeneity using chi – squared for categorical covariates and unpaired t – test for numerical covariates. Data were considered having homogeneity if the p value was more than 0.05. The association between MNA and PG - SGA and the KDQOL among hemodialysis patients was assessed using multiple logistic regression. The p value of less than 0.05 was considered statistically significant. The effect estimate was determined by calculating mean difference (MD) for numerical data and odd ratio and 95% confidence interval (OR95%CI) for categorical data. The equation in our study was calculated by the following formula Y = B0 + B1X + e, and the logistic probability was p = exp(B0+B1X)/1 + exp(B0+B1X), where B referred to logistic coefficient and e referred to error variance. The optimal cut-off on the levels of MNA and PG-SGA score were determined by Receiving Operator Characteristic (ROC) analysis. The highest level of J Index was considered the optimal cut-off. The software of Statistical Package for The Social Sciences (SPSS) version 17 (IBM SPSS, Chicago, IL) was used to analyze the data.

      3. Results

      3.1 Patient selection

      Initially, we enrolled a total of 121 hemodialysis patients. Of them, we excluded 25 patients due to the hemodialysis duration was less than three months (n: 15), end stage cervical cancer (n: 7), and uncorrected dry weight (n: 3). Finally, a total of 96 hemodialysis patients were included in our study. Fig. 1 describes the flowchart of patient selection on our study, and Table 1 presents the baseline characteristics of patients among groups. Our data indicated that our study participants between groups were age and sex matched. The raw data of patients in our study is outlined in the Supplementary files.
      • Fajar J.
      Supplementarry files: the association between MNA and PG-SGA malnutrition assessment and quality of life among hemodialysis patients.
      Fig. 1
      Fig. 1A flowchart of patient selection in our study.
      Table 1Baseline characteristics of patients included in our study.
      CharacteristicsGood QOL (n = 75)Poor QOL (n = 21)p
      Age (years)54.1 ± 11.753.7 ± 13.60.8940
      Male (n[%])42 [56]8 [38.1]0.1510
      BW (kg)60.5 ± 12.158.3 ± 12.40.4640
      BH (cm)161.0 ± 7.1161.0 ± 7.41.0000
      BMI (kg/m2)23.3 ± 3.522.4 ± 3.40.2950
      Job
       Housewife (n[%])32 [42.7]13 [61.9]0.1230
       Civil servant (n[%])6 [8.0]2 [9.5]0.8240
       Enterpreneur (n[%])37 [49.3]6 [28.6]0.0970
      Educational levels
       Primary (n[%])5 [6.7]0 [0.0]0.4190
       Junior high school (n[%])23 [30.7]12 [57.1]0.0300
       Senior high school (n[%])34 [45.3]6 [28.6]0.1740
       Diploma (n[%])3 [4.0]0 [0.0]0.6330
       University (n[%])10 [13.3]3 [14.3]0.9100
      Smoking (n[%])13 [17.3]2 [9.5]0.3910
      Comorbidity
       Diabetes mellitus (n[%])27 [36.0]9 [42.9]0.5670
       Hypertension (n[%])42 [56.0]13 [61.9]0.6290
       Renal stone (n[%])2 [2.7]0 [0.0]0.8080
       CGN (n[%])2 [2.7]0 [0.0]0.8080
       Uric acid (n[%])3 [4.0]1 [4.8]0.8770
      Laboratory findings
       Hemoglobin (gr/dl)9.4 ± 1.99.3 ± 2.00.8330
       Urea (mg/dl)118.2 ± 28.5119.8 ± 39.30.8350
       Creatinine (mg/dl)11.5 ± 8.410.1 ± 5.50.4710
       Systolic BP (mmHg)131.3 ± 13.4131 ± 10.40.9240
       Diastolic BP (mmHg)80.4 ± 6.280.5 ± 2.20.9420
       HD duration (months)27.4 ± 15.921.7 ± 9.80.1190
       UF (ml/h/kg)2 ± 0.92.3 ± 1.10.1190
       Qb (ml/min)240 ± 28233 ± 20.50.2860
       KT/V target1.4 ± 0.11.4 ± 0.11.0000
      Note, data were presented in mean ± SD or n (%); QOL, quality of life; BW, body weight; BH, body height; BMI, body mass index; CGN, chronic glomerulonephritis; BP, blood pressure; HD, hemodialysis; UF, ultrafiltration; Qb, blood flow; Kt/V, clearance of urea multiple by time per the volume of cleared urea.

      3.2 MNA nutritional status and the quality of life among hemodialysis patients

      Our study indicated that hemodialysis patients with good QOL had higher MNA score compared to those with poor QOL (MD: 2.80; 95%CI: 1.13–4.47). Moreover, in the classification of nutritional status following the MNA score, our results found that normal nutritional status was significantly observed in patients with good QOL than patients with poor QOL (OR: 5.84; 95%CI: 2.59, 21.52). Furthermore, our analysis in ROC identified that 23.75 was the optimal cut - off point of MNA score (Supplementary file),
      • Fajar J.
      Supplementarry files: the association between MNA and PG-SGA malnutrition assessment and quality of life among hemodialysis patients.
      and we found that hemodialysis patients with MNA score >23.75 was associated with 5.84 - fold to have good QOL than those with MNA score <23.75 (OR: 5.84; 95%CI: 2.59, 21.52) (Table 2, Fig. 2A).
      Table 2The summary of the association between MNA and PG-SGA malnutrition assessment and quality of life among hemodialysis patients.
      ParametersGood QOL (n = 75)Poor QOL (n = 21)MD/OR (adjusted)95%CIp
      MNA score22.7 ± 3.419.9 ± 3.62.80*1.13–4.470.0010
      Malnutrition4 [5.3]4 [19.0]0.24**0.05–1.060.0590
      Risk of malnutrition34 [45.3]14 [66.7]0.42**0.15–1.140.0890
      Normal37 [49.3]3 [14.3]5.84**1.59–21.510.0080
      MNA (≥23.75 vs. < 23.75)37 [49.3]3 [14.3]5.84**1.59–21.510.0080
      PG – SGA score3.3 ± 2.34.8 ± 1.9−1.50*(-2.58) – (−0.43)0.0060
      Stage A17 [22.7]0 [0.0]12.86**0.74–223.330.0790
      Stage B33 [44.0]5 [23.8]2.51**0.84–7.580.1010
      Stage C23 [30.7]15 [71.4]0.18**0.06–0.510.0010
      Stage D2 [2.7]1 [4.8]0.55**0.05–6.360.6300
      PG – SGA (<3.5 vs. ≥ 3.5)25 [33.3]16 [76.2]0.16**0.05–0.480.0010
      Note, data were presented in mean ± SD or n (%); MD, mean difference; OR, odd ratio; CI, confidence interval; * indicated MD; ** indicated OR; MNA, Mini Nutritional Assessment; PG – SGA, Patient-Generated Subjective Global Assessment.
      Fig. 2
      Fig. 2ROC of the association between MNA (A) and PG – SGA (B) malnutrition status and the quality of life among patients with hemodialysis. The AUC for MNA and PG -SGA were 71.1 and 72.9, suggesting that MNA and PG – SGA were acceptable for predicting the QOL of hemodialysis patients. The J index revealed that 23.75 was the optimal cut – off for MNA and 3.5 was the optimal cut – off for PG – SGA for predicting the QOL of hemodialysis patients.

      3.3 PG - SGA nutritional status and quality of life among hemodialysis patients

      We identified that hemodialysis patients with good QOL had lower PG - SGA score than patients with poor QOL (MD: −1.50; 95%CI: −2.68, −0.43). Following the interpretation of PG - SGA score, we clarified that stage C PG – SGA patients were associated with poor QOL (OR: 0.18; 95%CI: 0.06–0.51). Our ROC analysis found that the PG - SGA score 3.5 was the optimal cut - off point (Supplementary file).
      • Fajar J.
      Supplementarry files: the association between MNA and PG-SGA malnutrition assessment and quality of life among hemodialysis patients.
      We found that hemodialysis patients with the PG - SGA score >3.5 was associated with poor QOL (OR: 0.16; 95%CI: 0.05, 0.48) (Table 2, Fig. 2B).

      4. Discussion

      Our study found that good nutritional status, assessed by MNA & PG - SGA, was associated with good QOL among hemodialysis patients. Moreover, we found that MNA score ≥23.75 and PG - SGA score <3.5 were the optimal cut - off points for the predictor of good QOL in hemodialysis patients. Our current study was the first study reporting the role of MNA and PG - SGA as the predictor of QOL on hemodialysis patients. Therefore, the particular comparison between regions was unable to perform. However, similar studies assessing the correlation between QOL and nutritional status had been widely reported in the case of hemodialysis patients. Previous study found that some nutritional tools such as food recall, SGA,
      • Feasel-Aklilu S.
      • Marcus A.
      • Parrott J.S.
      • Peters E.
      • Byham-Gray L.
      Is nutrition specific quality of life associated with nutritional status?.
      and malnutrition inflammation score,
      • Harvinder G.S.
      • Swee W.C.
      • Karupaiah T.
      • et al.
      Dialysis Malnutrition and Malnutrition Inflammation Scores: screening tools for prediction of dialysis-related protein-energy wasting in Malaysia.
      and the improvement of dietary intake in patients with hemodialysis was associated with the better QOL.
      • Md Yusop N.B.
      • Yoke Mun C.
      • Shariff Z.M.
      • Beng Huat C.
      Factors associated with quality of life among hemodialysis patients in Malaysia.
      Another study also confirmed that nutritional status assessed by the components of appetite, energy intake, serum albumin, and serum creatinine was associated with the QOL among patients with hemodialysis.
      • Dwyer J.T.
      • Larive B.
      • Leung J.
      • et al.
      Nutritional status affects quality of life in Hemodialysis (HEMO) Study patients at baseline.
      On the other hand, the implementation of nutritional assessment in hemodialysis patients by using MNA and PG - SGA had been shown to affect the final prognosis.
      • Desbrow B.
      • Bauer J.
      • Blum C.
      • Kandasamy A.
      • McDonald A.
      • Montgomery K.
      Assessment of nutritional status in hemodialysis patients using patient-generated subjective global assessment.
      Therefore, in our present study, while we used different nutritional assessment tools, it was conceived that MNA and PG - SGA nutritional assessment tools had the association with the QOL of hemodialysis patients.
      QOL is an important indicator for predicting the outcome of the disease. In the case of ESRD, QOL has been proposed as one of the successfully treatment indicators. In the context of the association between nutritional status and QOL among patients with hemodialysis, the studies reported a wide variety of findings.
      • Feasel-Aklilu S.
      • Marcus A.
      • Parrott J.S.
      • Peters E.
      • Byham-Gray L.
      Is nutrition specific quality of life associated with nutritional status?.
      • Harvinder G.S.
      • Swee W.C.
      • Karupaiah T.
      • et al.
      Dialysis Malnutrition and Malnutrition Inflammation Scores: screening tools for prediction of dialysis-related protein-energy wasting in Malaysia.
      • Md Yusop N.B.
      • Yoke Mun C.
      • Shariff Z.M.
      • Beng Huat C.
      Factors associated with quality of life among hemodialysis patients in Malaysia.
      • Dwyer J.T.
      • Larive B.
      • Leung J.
      • et al.
      Nutritional status affects quality of life in Hemodialysis (HEMO) Study patients at baseline.
      ,
      • dos Santos A.C.
      • Machado Mdo C.
      • Pereira L.R.
      • Abreu J.L.
      • Lyra M.B.
      Association between the level of quality of life and nutritional status in patients undergoing chronic renal hemodialysis.
      Those variation might be due to the fact that the components of nutritional assessment were differed among the tools. In our present study, we used MNA and PG - SGA as the tools of nutritional assessment. In MNA, the components included anthropometric, mobility, neuro-psychologic factors, and nutritional and water intake. In PG - SGA, several components including comorbidity, metabolic, and physical activity were assessed. Those components measurements might reflect the real nutritional status than conventional nutritional assessment following BMI alone. Physiological function was reported to affect the QOL in some disease settings including aging, pulmonary arterial hypertension, photo-dermatoses, and amyotrophic lateral sclerosis.
      • van Groenestijn A.C.
      • Kruitwagen-van Reenen E.T.
      • Visser-Meily J.M.
      • van den Berg L.H.
      • Schroder C.D.
      Associations between psychological factors and health-related quality of life and global quality of life in patients with ALS: a systematic review.
      Moreover, nutritional and water intake, one of components in MNA and PG - SGA assessment, was shown to contribute the QOL in geriatric patients and cancer.
      • Trabal J.
      • Leyes P.
      • Forga M.T.
      • Hervas S.
      Quality of life, dietary intake and nutritional status assessment in hospital admitted cancer patients.
      On the other hand, studies also revealed that comorbidity and metabolic disorders contributed to the altered of QOL.
      • Saboya P.P.
      • Bodanese L.C.
      • Zimmermann P.R.
      • Gustavo A.D.
      • Assumpcao C.M.
      • Londero F.
      Metabolic syndrome and quality of life: a systematic review.
      Therefore, it was realist that in our present study we found that the nutritional assessment following the methods of MNA and PG - SGA provided the association with the QOL among hemodialysis patients.
      To the best of our knowledge, our findings were the first report notifying that MNA and PG - SGA were the prominent and simple nutritional assessment tools for predicting the QOL of hemodialysis patients. While previous studies had shown other nutritional assessment tools including food recall, SGA,
      • Feasel-Aklilu S.
      • Marcus A.
      • Parrott J.S.
      • Peters E.
      • Byham-Gray L.
      Is nutrition specific quality of life associated with nutritional status?.
      and malnutrition inflammation score
      • Harvinder G.S.
      • Swee W.C.
      • Karupaiah T.
      • et al.
      Dialysis Malnutrition and Malnutrition Inflammation Scores: screening tools for prediction of dialysis-related protein-energy wasting in Malaysia.
      had the prognostic point on predicting the QOL of hemodialysis patients, we also showed that MNA and PG - SGA which had simple assessment had the important role to govern the QOL of hemodialysis patients. On the other hand, to date, the guideline for the management of ESRD had been established and updated periodically.
      • Eknoyan G.
      • Lameire N.
      • Eckardt K.
      • et al.
      KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease.
      However, the implementation might only focus on the biomarker refinement even the nutritional guideline had been recommended in the case of ESRD.
      • Ikizler T.A.
      • Burrowes J.D.
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      • et al.
      KDOQI clinical practice guideline for nutrition in CKD: 2020 update.
      Therefore, we proposed that the QOL of patients with hemodialysis should also be a concern since the Joint Commission International (JCI) revealed that patients centered care is the primary concern of patients care.
      • Donahue K.T.
      • vanOstenberg P.
      Joint Commission International accreditation: relationship to four models of evaluation.
      In this context, we expected that nutritional assessment tools of hemodialysis patients, either using MNA or PG - SGA, should be included in the guideline. However, further studies are warranted to assess the role of MNA and PG - SGA nutritional assessment tools for predicting the QOL of hemodialysis patients in other regions, and therefore we could compare the specific settings and the optimal cut - off points. Besides, we also expected that further studies are conducted to assess the nutritional intake in patients with hemodialysis.
      Our study had several important limitations. First, we did not analyze the potential confounding factors that might also affect the QOL among hemodialysis patients including dietary and water intake, environmental, and socio – economic factors. Second, the non – proportional sample size between groups in our current study might also govern the final findings. Third, since our study was not RCT, the potential of bias findings might be occurred. Therefore, a special concern should be used to interpret our findings.

      5. Conclusion

      Our study has identified that hemodialysis patients with better nutritional status, assessed by both MNA and PG – SGA, is associated with the good QOL. We also identified that the score of MNA ≥23.75 and the score of PG – SGA <3.5 are the strong predictors of good QOL among hemodialysis patients.

      Ethics approval and consent to participate

      Participants had provided written informed consent prior to involve in the study. Our study had been approved by local ethical committee (No: E5a/214/KEPK-UMM/X/2021).

      Availability of data and materials

      The supplementary data were presented in Figshare (https://doi.org/10.6084/m9.figshare.16680574.v2).

      Consent for publication

      Not applicable.

      Funding source

      This study received no external funding.

      Authors contributions

      Idea/concept: AR, DS. Design: AR, DS. Control/supervision: JKF, AG. Data collection/processing: AR, DS. Extraction/Analysis/interpretation: JKF. Literature review: AR, DS, JKF, AG. Writing the article: JKF. Critical review: AG. All authors have critically reviewed and approved the final draft and are responsible for the content and similarity index of the manuscript.

      Declaration of competing interest

      None.

      Acknowledgement

      We thank to RSU Universitas Muhammadiyah Malang for supporting this project.

      Appendix A. Supplementary data

      The following are the Supplementary data to this article:

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