|Year : 2020 | Volume
| Issue : 4 | Page : 89-96
Nutritional status of Iraqi adults on maintenance hemodialysis: A multicenter study
Luay Jebur Mousa1, Aseel A Naj2, Wedyan A Mohammed1, Ala Sh Ali3
1 Department of Public Health, Al-Karkh Health Directorate, The Medical City, Baghdad, Iraq
2 Department of Public Health, Ministry of Health and Environment, The Medical City, Baghdad, Iraq
3 Nephrology and Renal Transplantation Centre, The Medical City, Baghdad, Iraq
|Date of Submission||17-Jun-2021|
|Date of Acceptance||26-Jun-2021|
|Date of Web Publication||20-Jul-2021|
Dr. Ala Sh Ali
Nephrology and Renal Transplantation Centre, The Medical City, Baghdad
Source of Support: None, Conflict of Interest: None
Objective: The objective is to assess the prevalence of malnutrition and its associated factors in adult patients on hemodialysis (HD). Patients and Methods: A total of 271 participants (149 males and 122 females) from four major dialysis units were included in this descriptive cross-sectional study conducted from October 2020 to March 2021. Nutritional status was measured using a subjective global assessment tool. The anthropometric indices, body mass index (BMI), and biochemical parameters, including albumin and electrolytes, were also measured in all patients. Results: The overall prevalence of estimated nutritional status was as follows: 50.2% were well-nourished, 42.4% were mildly/moderately malnourished, and 7.4% were severely malnourished. The primary etiology of kidney disease was mostly due to hypertension (38.7%) and diabetes (32.8%). No significant association was detected with regard to age, sex, residence, marital status, occupation, and cause of kidney disease (P > 0.05). Higher educational level, lower BMI, and serum albumin were significantly associated with malnutrition (P < 0.02, <0.005, and <0.02, respectively). Conclusion: Approximately 50% of the adults on HD had variable degrees of malnutrition. BMI and serum albumin levels were significantly associated with the state of malnutrition. Comprehensive clinical nutrition services and counseling should be incorporated into the structure of HD units under the care of a dedicated nutritionist.
Keywords: Hemodialysis, Iraq, malnutrition, subjective global assessment
|How to cite this article:|
Mousa LJ, Naj AA, Mohammed WA, Ali AS. Nutritional status of Iraqi adults on maintenance hemodialysis: A multicenter study. J Renal Nutr Metab 2020;6:89-96
|How to cite this URL:|
Mousa LJ, Naj AA, Mohammed WA, Ali AS. Nutritional status of Iraqi adults on maintenance hemodialysis: A multicenter study. J Renal Nutr Metab [serial online] 2020 [cited 2022 Dec 5];6:89-96. Available from: http://www.jrnm.in/text.asp?2020/6/4/89/321990
| Introduction|| |
Malnutrition is an imbalance of the need and supply of energy, protein, and micronutrients, which leads to growth and developmental defects. Malnutrition is widely prevalent among patients with end-stage renal disease (ESRD) undergoing maintenance hemodialysis (HD), which is the main form of renal replacement therapy worldwide. The prevalence of malnutrition varies between 28% and 54% depending on the region, racial differences, and clinical parameters used to define malnutrition.
A body of evidence has highlighted the relationship between malnutrition and outcome in ESRD-HD patients, with increased hospitalization rates, susceptibility to infection, and higher morbidity and mortality.
Simple malnutrition refers to nutritional abnormalities that are induced by inadequate nutritional intake, whereas protein-energy wasting (PEW), caused by chronic kidney disease (CKD), refers to nutritional abnormalities that may be associated with inflammation, and cannot be corrected solely by increasing nutritional intake; this is the most prevalent type among this patient group. In 2008, PEW was coined by the International Society of Renal Nutrition and Metabolism as a single pathological condition in which undernourishment and hypercatabolism converge.
The nutritional requirements of patients with ESRD are altered due to multiple factors, including metabolic acidosis; hormonal changes; co-morbidities and hospitalizations; loss of nutrients, including glucose, amino acids, proteins, and vitamins, which occur during dialysis treatment; dialysis-induced catabolism and infection; and inadequate protein/caloric intake and increased energy expenditure. Several of these factors can lead to ineffective energy production despite adequate intake of carbohydrates and proteins.
Malnourishment appears to develop prior to the initiation of dialysis, most likely during CKD stage 3 or earlier. Poor predialysis nutritional status increases patient morbidity and mortality after the initiation of HD therapy.
At all stages of CKD and ESRD, careful nutritional evaluation and management are needed to overcome the serious consequences of malnutrition. In HD, the delivered dialysis dose should be adapted to target the uremic milieu and to remove uremic toxins, correct chronic acidosis, and relieve anorexia and other uremic symptoms to improving the quality of life.
No single measurement can precisely estimate nutritional status. However, nutritional screening using one of the validated tools and related nutritional biochemical markers can provide a basis for dietetic referrals for the prescription of appropriate nutritional support.
The subjective global assessment (SGA) is a practical and reliable tool that can be used to assess the nutritional status of patients on HD. The SGA uses several components of medical history, such as weight change, dietary intake, gastrointestinal symptoms, functional capacity, and relation to disease. It can provide an overview of nutritional intake and body composition, including a rough assessment of both muscle and fat mass, and it correlates with mortality rates. The validity and reproducibility of the SGA have been documented previously. Moreover, the SGA is useful in clinical and research settings; it is inexpensive, rapid, and can be used effectively by providers from different disciplines, such as nurses, dietitians, and physicians. The national kidney foundation kidney dialysis outcome quality initiative recommends incorporating the SGA tool for evaluation and monitoring of nutritional status in all stages of CKD.
According to the Iraqi society of nephrology and renal transplantation, there are 7000 patients on HD, 175 per million people, distributed over 43 HD units across the country. Dialysis services are provided by different providers according to official leasing contracts with the Ministry of Health and Environment (oral personal communication, February 2021). Renal nutritionists have no specific job description, and renal dietary advice is provided in a nonstructured form by primary care physicians, dialysis nurses, and nephrologists. A previous report in 2011 stated that malnutrition was found in 63% of 86 patients on HD from five dialysis units.
This study aimed to assess the prevalence of malnutrition and its related factors in patients on HD from four governmental dialysis units using the SGA tool, anthropometric measurements, and biochemical tests.
| Patients and Methods|| |
This is a descriptive cross-sectional study with analytic elements.
The study was conducted in four governmental HD units from October 2020 to March 2021.
We included patients with ESRD who were scheduled to undergo regular HD (at least two sessions per week for >3 months).
The exclusion criteria were as follows:
- Any chronic disease or acute infection in the last month, including coronavirus disease (COVID-19)
- Patients with an anticipated life expectancy of 6 months (e.g., due to metastatic malignancy or terminal disease)
- Clinically evident cachexia (fat and muscle wasting due to disease and inflammation)
- Sarcopenia (reduced muscle mass and strength)
- Ongoing enteral or parenteral nutrition
- Use of steroids or immunosuppressive agents
- Advanced senility or dementia that interferes with the application of the nutritional questionnaire.
The sample size was calculated using the sample size equation:
N = (z)2× (p × q)/d2= (1.96)2× (0.11 × 0.89)/(0.05)2 = 148
N = sample size
Z = standard deviation at level of confidence 95% (1.96)
P = population proportion (estimated frequency of occurrence of CKD, 11%)
q = 1– p = the frequency of nonoccurrence
d = degree of precision (5%).
Based on this equation, the estimated sample size was 148. The duration of the study permitted the expansion of the sample size, which could provide more reliable and representative results.
Sampling method and technique
A multistage sampling method was used. In the first stage, simple random sampling was applied to make the sample representative, and four centers were chosen out of the 11 the major renal dialysis units and tertiary referral institutes from different districts of the city. In the second stage, each center had a fixed dialysis schedule for their patients, and the researchers visited the centers to cover all of the sessions throughout the day. All eligible outpatients on HD who were registered in the chosen units were asked to participate, and a total of 271 patients who fulfilled the selection criteria and agreed to participate were included. The research objectives and methods were explained to the patients and informed written consent forms were obtained from all included patients.
Data were collected by direct interviews using a preconstructed questionnaire consisting of two parts. The first part included the history of socio-demographic characteristics (age, sex, marital status, residence, occupation, and educational level). In addition to the medical history regarding the main cause of kidney disease, information on the type of dialysis access, and the date since starting maintenance HD was also collected. The second part included the conventional SGA tool, which was based on the history and physical examination of the participants.
Based on the participants' dialysis records, pre- and post-dialysis urea were recorded, as were the patients' serum creatinine, serum albumin, potassium, phosphorus, calcium, and hemoglobin levels. Machine-estimated measures of HD adequacy were not applied to all dialysis units for logistic reasons. Moreover, the laboratory data were incomplete for some of the study groups because of unit-specific logistic issues and/or nonprovision by the dialysis service provider.
Conventional subjective global assessment tool
- The patient's history consisted of seven components: food intake, weight loss (during the previous 2 weeks and 6 months), gastrointestinal symptoms and their duration (pain on eating, anorexia, feeling full quickly, nausea, dysphagia, diarrhea, dental problems, vomiting, and constipation), functional capacity, and comorbidities (recorded directly from the patient's medical file)
- The patient's physical examination was performed by the researcher and consisted of three components: loss of subcutaneous fat, muscle wasting, and the presence of edema and/or ascites (only when documented by imaging)
- Loss of subcutaneous fat was assessed under the eyes, over the triceps, ribs, lower back, and sides of the trunk, and muscle wasting was assessed by examining the temples, clavicle, shoulder scapula/ribs, quadriceps, and interosseous muscle between the thumb and forefinger (back of the hand).
The overall score of the SGA was categorized as A (well-nourished), B (mildly/moderately malnourished), or C (severely malnourished).
- Height measurement, based on recently documented measures from the patient's record
- Weight measurement, based on the documented last postdialysis weight measurements
- Body mass index (BMI) was calculated by dividing the dry weight over the squared height in meters, and was classified according to the World Health Organization categorization for patients on HD as follows: underweight (<18.5 kg/m2), underweight to normal (≥18.5– <22.5 kg/m2), normal (>22.5– <25 kg/m2), overweight (≥25– <30 kg/m2), and obese (≥30 kg/m2).
- The following reference ranges were used for patients on HD during the data analysis: normal serum calcium range, 8.5–10.2 mg/dl; phosphorous, 3–6 mg/dl, and calcium x phosphorus product, <55. Serum potassium level > 5.5 mmol/L was defined as hyperkalemia. Albumin values were categorized as either optimal (≥4 g/dL) or suboptimal (<4 g/dL).
Cachexia and sarcopenia
- Cachexia is a complex metabolic syndrome associated with an underlying illness that is characterized by a loss of muscle with or without loss of fat mass
- Sarcopenia is characterized by reduced muscle mass and strength, with evidence of an underlying disorder (e.g. aging) and no or limited improvement with optimal nutrient intake.
- Dialysis adequacy was estimated by calculating the urea reduction ratio (URR)
- The URR refers to the treatment-related reduction in serum urea concentration and is computed as follows
- URR (%) = (1 − Ct/C0) ×100%
Where Ct is the postdialysis serum urea concentration and C0 is the predialysis serum urea concentration
- Kt/V was calculated based on the URR using the following formula
- Kt/V = (0.026 × URR)–0.46. The minimum Kt/V was 1.2, and Kt/V≥1.2, which is acceptable.
The primary outcome of this study was to assess the prevalence of malnutrition and related factors in patients on HD, as determined using the SGA tool, anthropometric measurements, and biochemical tests.
Administrative and ethical approval
The objectives of the study and the confidentiality of the data (a code was used to connect the participants to the answers) were explained to the participants. The study participants provided written informed consent according to the National Research Ethics Code, 2018.
Data management and statistical analysis
Data were entered and analyzed using the IBM SPSS Statistics for Windows (version 21.0, IBM Corp., Armonk, NY). Descriptive statistics are presented as percentages or frequencies, means, and standard deviations according to the type of the variable. The Chi-square test was used to assess the significance of the relationship between nutritional status and other categorical variables. The Pearson correlation coefficient was used to measure statistical relationships or associations between two continuous variables. In the case of continuous data, ANOVA was used to determine the significance of the differences. Statistical significance was set at P < 0.05.
| Results|| |
Two hundred and seventy-one patients on HD were recruited, 149 (55%) of whom were male. The mean age of the patients was 51.2 ± 14.5 years, most were urban dwellers (83.4%), approximately 20% of them were illiterate, and only 14.4% had completed higher educational levels. Hypertension and diabetes were the most common etiologies of ESRD (38.7% and 32.8%, respectively).
The mean BMI of the study group was 24.2 ± 5.6. Approximately half (49.8%) of the participants had a normal BMI, while 23.2% were overweight and 14% were obese. The remainder of the participants were underweight (12.9%). The mean serum albumin level of the patients was 3.83 ± 0.49 mg/dl.
[Table 1] shows the baseline characteristics of the study group.
[Figure 1] shows the distribution of the study group according to BMI.
[Table 2] shows the baseline dialysis data of the study group. Most of the patients (66.1%) had been receiving HD for 1–5 years. A dual lumen catheter was the dialysis access in 75 patients (27%) of the study group. Less than half of the participants (44%) were undergoing three HD sessions a week and 56% were undergoing only two HD sessions a week. The mean dialysis time was 7.57 ± 1.66 h/week, and the mean dialysis session time was 3.1 ± 0.27 h. All patients had dialysis therapy using a low flux dialyzer and a bicarbonate-based dialysate. The URR was 57% and the Kt/v of the study group was 1.
Based on conventional SGA, 50.2% of the patients were well-nourished, 42.4% were mildly/moderately malnourished, and 7.4% were severely malnourished [Figure 2]. There were no statistically significant differences in the nutritional status between the four dialysis units.
|Figure 2: Distribution and categorization of the study group by the nutritional status|
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We found no significant association between nutritional status and age, sex, marital status, residence, and occupation (P > 0.05), while a higher educational level was significantly associated with malnutrition (P = 0.02). Moreover, there was no significant association between nutritional status and primary etiology of ESRD (P = 0.62). There was a significant correlation between nutritional status and BMI (P = 0.005), and a lower mean BMI was significantly associated with severe malnourishment (P = 0.001, ANOVA test) [Table 3]. There was no significant correlation between nutritional status and dialysis vintage (P = 0.08), dialysis frequency, session time (P = 0.34), and type of vascular access (P = 0.18). There was a significant correlation between dialysis adequacy, URR, and Kt/v, and the nutritional status of the study group (P = 0.021).
|Table 3: The relationship of nutritional status with body mass index, of the study group|
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Those with severe malnutrition had significantly lower serum albumin levels than the well-nourished group (P = 0.003, ANOVA). There were no significant differences in the means of the other measured biochemical values with nutritional status (P > 0.05, ANOVA). Of the total study sample, 129 patients (47%) had their total cholesterol recorded with a mean of 145.73 + 38.38 mg/dl. When categorized according to their serum albumin (<4 vs. >4 mg/dl), at lower serum albumin, there was a correlation between serum cholesterol of <150 mg/dl and malnourishment (P = 0.019), but there was no correlation with higher levels of albumin [Table 4].
|Table 4: Subgroup analysis of the relationship between nutritional status, cholesterol according to serum albumin|
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| Discussion|| |
In the current study, we demonstrate that approximately 49.8% of the study group had varying degrees of malnutrition (42.4% mild/moderate malnutrition and 7.4% severe malnutrition). A previous report by Al-Saedy A, et al. in 2011 showed that malnutrition was prevalent in 63.5% of patients on HD.
Different studies have used the SGA to assess nutritional status in patients on HD. The prevalence of malnutrition among patients on HD was 55%, 67%, 65%, 36.4%, and 36% in Saudi Arabia, Egypt, Palestine, Turkey, and Iran, respectively.,,,, From these figures, it is apparent that the prevalence of malnutrition in patients on HD varied according to geography, ethnicity, sociodemographic characteristics, dietary habits, disease etiology, therapeutic plans, and many other factors. This is applicable to different units within the same country, as in this study (39% vs. 57%), and those from two Saudi cities (55% vs. 32%)., In the current study, we found no statistically significant difference in the prevalence of malnutrition among the four HD units studied. Moreover, we found no significant effect of sex, age, occupation, or residence on nutritional status. In contrast, many other studies have reported that older patients are more prone to malnutrition than younger patients., Furthermore, data from Jordan and Turkey revealed that malnutrition was significantly higher in women than in men., This emphasizes the need for a study using objective methods to assess nutritional status and target a specific population, such as the elderly.
The most common causes of ESRD in this study were hypertension and diabetes (38.7% and 32.8%, respectively). This is consistent with the majority of patients with CKD/ESRD; the main risk factors for CKD are hypertension and diabetes mellitus. In the current study, the primary ESRD etiology was not significantly correlated with nutritional status.
Surprisingly, in this study, malnutrition was significantly related to a higher educational level. Given that there was no education regarding nutritional behavior or dietary plans for outpatients on HD in the studied units, we assume that in the absence of proper nutritional advice, those with higher education could have overly reduced their protein-energy intake, with inappropriate dietary restrictions. Further studies should be carried out on the basis of energy and protein intake and should evaluate the nutritional knowledge of both patients and health caregivers.
Approximately half of the study group had a normal body weight, and 12.9% of the participants were underweight. The mean BMI of the patients was 24.2 ± 5.61, which was significantly related to nutritional status (P = 0.001). The lowest mean BMI was in the unit with the longest dialysis time per week. Ultrafiltration for excess volume may have contributed to this result as this, in turn, will change the BMI measurement; however, more edema fluid may indicate more protein wasting either through reduced oral intake or excess protein loss through HD.
The measurement of BMI is limited by its inability to differentiate between the bone, muscle, and fat compartments. However, unlike the general population, a high BMI seems to have a protective effect in chronic HD patients. Many studies have shown that the mortality risk is higher in patients with lower BMI, and there is no indication of increased risk associated with obesity. In contrast to older dialysis patients, younger patients with low or very high BMI had a substantially increased risk of death.
It is well documented that low albumin levels are inversely related to nutritional status. In the current study, the mean serum albumin level of the study group was 3.8 ± 0.49 g/dl. The serum albumin concentration has been identified as the most powerful indicator of mortality in patients undergoing HD. However, despite its importance and utility, the serum albumin level cannot be used as a stand-alone indicator of nutrition and adequate dialysis. Many other factors influence the generation and catabolism of albumin, such as the inhibition of albumin synthesis in the uremic milieu, increased albumin degradation, dilution by edema fluid, and protein loss through the dialyzer. Therefore, the inverse significant association with malnutrition in the current study and previous studies is not only due to poor intake, but may also be related to HD therapy itself.
The mean corrected calcium and phosphorus levels in the study group were 8.31 ± 1.3 mg/dl and 6.13 ± 2.01 mg/dl, respectively, neither of which were within the recommended targets of the KDIGO guidelines. Furthermore, 31.4% of the study group had a Ca x PO4 bi-product >55, which is below the recommended target. Moreover, the mean parathyroid hormone (PTH) level in the 73 patients was 606.24 ± 53.72 pg/ml. Such high mean phosphate, PTH, and bi-product are mostly attributed to excess dietary phosphate and poor dietary counseling about phosphate, in addition to inadequate dialysis. Dietary phosphate restriction is a fundamental component of the recommendations issued by the KDIGO guidelines.,
Numerous studies have demonstrated that the relationship between ESRD mortality and cholesterol level is in the form of a U-shaped curve. A large database analysis revealed that patients with total cholesterol levels between 200 and 250 mg/dL had the lowest risk of death, whereas those with levels >350 mg/dL had a 1.3-fold relative risk and those with levels of 100 mg/dL had a 4.2-fold unadjusted relative risk. It has been suggested that the inverse relationship between cholesterol and ESRD mortality may be related to the effects of systemic inflammation and malnutrition, both of which are prevalent in dialysis patients. The U-shaped curve depicting the association between cholesterol and mortality appeared to be more linear after adjustment for serum albumin. The impact of inflammation and malnutrition in patients on dialysis has been previously confirmed by a large, 10-year prospective study of Japanese patients on HD. In the current study, the mean total cholesterol value was recorded for 129 participants, and was 145.73 ± 38.38 mg/dl. Cholesterol is significantly related to the nutritional status of patients with serum albumin <4 mg/dl. This suggests that the relationship becomes more linear as much as we have lower serum albumin. A larger sample size is needed to confirm this correlation.
We did not assess the relationship between PTH and cholesterol with the nutritional status of the entire study group due to incomplete records of these variables.
The mean Hb of the study group was 8.9 ± 1.62 g/l, which is below the recommended target according to the KDIGO guidelines of 10–12 g/l. Anemia in patients with ESRD-HD can be caused by many factors, with poor nutritional intake being the most common and serves as an indirect marker of the nutritional status of the study group.,,, Serum Hb showed no statistically significant association with the nutritional status of the study group, which may reflect the multifaceted mechanisms of anemia in HD patients.
The dialysis data in this study were slightly improved from those reported previously by Al-Saedy et al. in 2011. The mean duration of dialysis therapy was 34.3 ± 12.57 months versus 26.4 months and the mean dialysis time per week was 7.5 ± 1.66 h versus 6.4 h/week. Moreover, 44% of the study participants were undergoing three HD sessions per week (vs. 30%). This may explain the lower prevalence of malnutrition in the current study than in the previous report (49.8% vs. 63.5%). Moreover, while there was no significant correlation between any of the variables and nutritional status in our study, Al-Saran et al. reported a dialysis vintage of 2 years was significantly correlated with nutritional status. Furthermore, Zahra et al. reported a lower prevalence of malnutrition (36%), which was partially due to more frequent dialysis, (93% of patients had 3 HD sessions/week).
The provision of adequate dialysis time and frequency leads to the provision of an adequate dialysis dose. According to the above data, the major units included in the current study are providing inadequate dialysis. The URR and Kt/v of the study group were 57% and 1, respectively, in comparison to the previous data of 57% and 1.02, respectively. In Turkey, Yigit et al. found no significant relationship between malnutrition and dialysis adequacy, while the results from Freitas et al. showed that low dialysis adequacy (Kt/V) was associated with malnutrition in patients on HD.,
Although the dialysis data have improved in comparison to the 2011 report, the figures are still lagging neighboring countries, as evidenced by the dialysis outcomes and practice patterns study practice monitor report of the Gulf region in 2018. This is particularly true for dialysis frequency, session length, dialysis adequacy, and nutritional status of patients on maintenance HD.
The dual lumen catheter was used for dialysis access in 75 patients (27%) in the study group, which is still higher than recent data from the Gulf region. The type of vascular access did not correlate with the nutritional status of the study group.
This study was limited by the logistics of busy overloaded HD units and the inadequate records of some variables. Moreover, we did not test for markers of inflammation. The subjective nature of nutritional assessment may not be reflective of the nutrition and volume status in the absence of specific measurement appliances and apparatuses. Therefore, prospective studies should be conducted to assess malnutrition and its associated factors, as well as the impact of preventive and therapeutic interventions on malnutrition status.
In the current study, approximately half of adults on HD showed variable degrees of malnutrition. BMI and serum albumin levels were significantly associated with the state of malnutrition. Comprehensive clinical nutrition services and counseling should be incorporated into the structure of HD units under the care of a dedicated nutritionist.
This study emphasizes the need for dedicated renal nutritionists in HD units to deliver proper patient education and nutritional management. This should be supplemented by the provision of adequate dialysis therapy.
We would like to thank all of the physicians and nursing staff of the four dialysis units for their help and support in conducting this study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Becker P, Carney LN, Corkins MR, Monczka J, Smith E, Smith SE, et al
. Consensus statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition: Indicators recommended for the identification and documentation of pediatric malnutrition (undernutrition). J Acad Nutr Diet 2014;114:1988-2000.
Carrero JJ, Thomas F, Nagy K, Arogundade F, Avesani CM, Chan M, et al.
Global prevalence of protein-energy wasting in kidney disease: A meta-analysis of Contemporary Observational Studies From the International Society of Renal Nutrition and Metabolism. J Ren Nutr 2018;28:380-92.
Gracia-Iguacel C, González-Parra E, Mahillo I, Ortiz A. Criteria for classification of protein-energy wasting in dialysis patients: Impact on prevalence. Br J Nutr 2019;121:1271-8.
Carrero JJ, Stenvinkel P, Cuppari L, Ikizler TA, Kalantar-Zadeh K, Kaysen G, et al.
Etiology of the protein-energy wasting syndrome in chronic kidney disease: A consensus statement from the International Society of Renal Nutrition and Metabolism (ISRNM). J Ren Nutr 2013;23:77-90.
Khan IH, Catto GR, Edward N, MacLeod AM. Death during the first 90 days of dialysis: A case control study. Am J Kidney Dis 1995;25:276-80.
Ikizler TA, Burrowes JD, Byham-Gray LD, Campbell KL, Carrero JJ, Chan W, et al.
KDOQI clinical practice guideline for nutrition in CKD: 2020 update. Am J Kidney Dis 2020;76:S1-107.
Hand RK, Burrowes JD. Renal dietitians' perceptions of roles and responsibilities in outpatient dialysis facilities. J Ren Nutr 2015;25:404-11.
Chung S, Koh ES, Shin SJ, Park CW. Malnutrition in patients with chronic kidney disease. Open J Int Med 2012;2:89-99.
Steiber AL, Kalantar-Zadeh K, Secker D, McCarthy M, Sehgal A, McCann L. Subjective Global Assessment in chronic kidney disease: A review. J Ren Nutr 2004;14:191-200.
Al-Saedy AJ, Al-Kahichy HR. The current status of hemodialysis in Baghdad. Saudi J Kidney Dis Transpl 2011;22:362-7.
] [Full text]
Evans WJ, Morley JE, Argilés J, Bales C, Baracos V, Guttridge D, et al.
Cachexia: A new definition. Clin Nutr 2008;27:793-9.
Papadopoulou SK. Sarcopenia: A contemporary health problem among older adult populations. Nutrients 2020;12:1293.
Daniel WW. Biostatistics: A Foundation for Analysis in the Health Sciences. 7th
ed. New York: John Wiley and Sons; 1999.
De Nicola L, Zoccali C. Chronic kidney disease prevalence in the general population: Heterogeneity and concerns. Nephrol Dial Transplant 2016;31:331-5.
Detsky AS, McLaughlin JR, Baker JP, Johnston N, Whittaker S, Mendelson RA, et al.
What is subjective global assessment of nutritional status? JPEN J Parenter Enteral Nutr 1987;11:8-13.
Flegal KM, Kit BK, Orpana H, Graubard BI. Association of all-cause mortality with overweight and obesity using standard body mass index categories: A systematic review and meta-analysis. JAMA 2013;309:71-82.
Ghorbani A, Hayati F, Karandish M, Sabzali S. The prevalence of malnutrition in hemodialysis patients. J Renal Inj Prev 2020;9:E15.
Alharbi K, Enrione EB. Malnutrition is prevalent among hemodialysis patients in Jeddah, Saudi Arabia. Saudi J Kidney Dis Transpl 2012;23:598-608. [Full text]
Zaki DS, Mohamed RR, Mohammed NA, Abdel-Zaher RB. Assessment of malnutrition status in hemodialysis patients. Clinical Medicine and Diagnostics 2019;9:8-13. [doi: 10.5923/j.cmd.20190901.02].
Omari AM, Omari LS, Dagash HH, Sweileh WM, Natour N, Zyoud SH. Assessment of nutritional status in the maintenance of haemodialysis patients: A cross-sectional study from Palestine. BMC Nephrol 2019;20:92.
Yigit IP, Ulu R, Celiker H, Dogukan A. Evaluation of nutritional status using anthropometric measurements and MQSGA in geriatric hemodialysis patients. North Clin Istanb 2016;3:124-30.
Zahra A, Farzaneh S, Mohsen N, Safarian M, Malekahmadi M, Barkhidarian B, et al
. Assessment of nutritional status in maintenance hemodialysis patients: A multicenter cross-sectional study in Iran. Semin Dial 2021;34:77-82.
Al-Saran KA, Elsayed SA, Molhem AJ, AlDrees AS, AlZara HM. Nutritional assessment of patients in a large Saudi dialysis center. Saudi Med J 2009;30:1054-9.
Yamada K, Furuya R, Takita T, Maruyama Y, Yamaguchi Y, Ohkawa S, et al.
Simplified nutritional screening tools for patients on maintenance hemodialysis. Am J Clin Nutr 2008;87:106-13.
Kanda E, Ai M, Kuriyama R, Yoshida M, Shiigai T. Dietary acid intake and kidney disease progression in the elderly. Am J Nephrol 2014;39:145-52.
Kalantar-Zadeh K, Streja E, Kovesdy CP, Oreopoulos A, Noori N, Jing J, et al.
The obesity paradox and mortality associated with surrogates of body size and muscle mass in patients receiving hemodialysis. Mayo Clin Proc 2010;85:991-1001.
Hoogeveen EK, Halbesma N, Rothman KJ, Stijnen T, van Dijk S, Dekker FW, et al.
Obesity and mortality risk among younger dialysis patients. Clin J Am Soc Nephrol 2012;7:280-8.
Kalantar-Zadeh K, Kilpatrick RD, Kuwae N, McAllister CJ, Alcorn Jr H, Kopple JD, et al.
Revisiting mortality predictability of serum albumin in the dialysis population: Time dependency, longitudinal changes and population-attributable fraction. Nephrol Dial Transplant 2005;20;1880-8.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group. KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Kidney Int Suppl. 2009:S1-130.
Barreto FC, Barreto DV, Massy ZA, Drüeke TB. Strategies for phosphate control in patients with CKD. Kidney Int Rep 2019;4:1043-56.
Lowrie EG, Lew NL. Death risk in hemodialysis patients: The predictive value of commonly measured variables and an evaluation of death rate differences between facilities. Am J Kidney Dis 1990;15:458-82.
Iseki K, Yamazato M, Tozawa M, Takishita S. Hypocholesterolemia is a significant predictor of death in a cohort of chronic hemodialysis patients. Kidney Int 2002;61:1887-93.
Gluba-Brzozka A, Franczyk B, Rysz J. Cholesterol Disturbances and the Role of Proper Nutrition in CKD Patients. Nutrients. 2019;11:2820.
National Kidney Foundation. KDOQI clinical practice guideline for hemodialysis adequacy: 2015 update. Am J Kidney Dis 2015;66:884-930.
Freitas AT, Vaz IM, Filizola IM, Gluba-Brzozka A, Franczyk B, Rysz J.
Prevalence of malnutrition and associated factors in hemodialysis patients. Rev Nutr 2014;27:357-66.
Al-Saedy AJ, Al-Kahichy HRA. The current status of hemodialysis in Baghdad SJKD 2011;22:362-7.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]