Assessment of Nutritional Status in Patients with Head and Neck Cancer Before Radiotherapy: A Single-center, Cross-sectional Study.

Objective: It is important to assess nutritional status to determine the presence of malnutrition because poor nutritional status will reduce the efficacy and increase the side effects of radiotherapy. The aim of this research was to assess nutritional status by comparing several parameters, namely anthropometry, biochemistry, physical condition, and inflammatory parameters, with Patient Generated-Subjective Global Assessment (PG-SGA) as the gold standard. Methods: A cross-sectional study with 78 subjects was conducted at the General Hospital Dr. Sardjito Yogyakarta, Indonesia, in 2022. The Malnutrition Screening Tool, Simple Nutrition Screening Tool, PG-SGA, and objective parameter data were used in the nutritional assessment. The objective parameters were determined by analyzing anthropometric data [body weight, mid-upper arm circumference (MUAC), and body fat], biochemical data (albumin and a complete blood profile), physical data (hand grip strength), and food intake data using the 1×24-hour recall method. The data were analyzed using One-Way ANOVA and the Kruskal-Wallis test. Results: Malnutrition was found in 33.3% of pre-radiotherapy head and neck cancer (HNC) patients. Patients with good nutritional status did not experience weight loss, decreased appetite, gastrointestinal symptoms, decreased functional capacity, or fat and/or muscle deficit (p<0.05). The findings showed a significant relationship between PG-SGA and nutritional status based on body weight, weight loss, MUACs, handgrip strength, visceral fat, resting metabolic rate (RMR), and hemoglobin (p<0.05). A better nutritional status was associated with higher parameter values. Conclusions: The method for nutritional status assessment in HNC patients undergoing radiotherapy can be performed by measuring body weight, weight loss, upper arm circumference, visceral fat, hemoglobin, and RMR in addition to PG-SGA as the gold standard.

Identifying Challenges and Potential Solutions for Sustainable Kidney Nutrition Care Delivery in Selected Asian Countries.

BACKGROUND: Recent surveys highlight gross workforce shortage of dietitians in global kidney health and significant gaps in renal nutrition care, with disparities greater in low/low-middle income countries. OBJECTIVE: This paper narrates ground experiences gained through the Palm Tocotrienols in Chronic Hemodialysis (PaTCH) project on kidney nutrition care scenarios and some Asian low-to-middle-income countries namely Bangladesh, India, and Malaysia. METHOD: Core PaTCH investigators from 3 universities (USA and Malaysia) were supported by their postgraduate students (n = 17) with capacity skills in kidney nutrition care methodology and processes. This core team, in turn, built capacity for partnering hospitals as countries differed in their ability to deliver dietitian-related activities for dialysis patients. RESULTS: We performed a structural component analyses of PaTCH affiliated and nonaffiliated (Myanmar and Indonesia) countries to identify challenges to kidney nutrition care. Deficits in patient-centered care, empowerment processes and moderating factors to nutrition care optimization characterized country comparisons. Underscoring these factors were some countries lacked trained dietitians whilst for others generalist dietitians or nonclinical nutritionists were providing patient care. Resolution of some challenges in low-to-middle-income countries through coalition networking to facilitate interprofessional collaboration and task sharing is described. CONCLUSIONS: We perceive interprofessional collaboration is the way forward to fill gaps in essential dietitian services and regional-based institutional coalitions will facilitate culture-sensitive capacity in building skills. For the long-term an advanced renal nutrition course such as the Global Renal Internet Course for Dietitians is vital to facilitate sustainable kidney nutrition care.

Comparison of Tools for Nutritional Assessment and Screening of Hospitalized Patients: A study on Surgical Patients.

Objective: To compare the Simple Nutrition Screening Tool (SNST) with other nutritional screening tools [Nutrition Risk Screening 2002 (NRS-2002), Nutrition Risk index (NRI)], nutritional assessment parameters, and the Subjective Global Assessment (SGA) in surgical patients. Methods: A comparative observational study with a total of 122 surgical patients. Patients were assessed during the first 24 h of admission in the ward from January to July 2022 using the NRI, NRS-2002, SNST, body mass index (BMI), mid-upper arm circumferences (MUAC), albumin serum, hemoglobin level, total lymphocyte count (TLC), and SGA. Sensitivity, specificity and predictive values were calculated to evaluate NRI, NRS-2002, SNST, BMI, MUAC, albumin, hemoglobin, TLC compared to SGA. Results: The screening tools identified a high nutritional risk in surgical patients from 58.2%-72.1%. Meanwhile, about 29.5% to 71.3% was affected by malnutrition based on nutritional assessment tools. There were significant associations between the type of disease, the screening tools, the anthropometric parameters, albumin, TLC as well and SGA (p<0.05). The SNST has a good category among the nutritional screening tools with sensitivity and specificity >80%, as well as area under the curve >0.8. Conclusions: There were significant associations for screening (NRS-2002, SNST) and nutritional assessment tools (BMI, MUAC, albumin) compared with SGA. Both these tools can be used to determine the risk of malnutrition in surgical patients.

Designing and collecting data for a longitudinal study: the Sleman Health and Demographic Surveillance System (HDSS).

BACKGROUND: This paper describes the methodological considerations of developing an urban Health and Demographic Surveillance System (HDSS), in the Sleman District of Yogyakarta, Indonesia. METHODS: 1) The Sleman District was selected because it is mostly an urban area. 2) The minimum sample size was calculated to measure infant mortality as the key variable and resulted in a sample of 4942 households. A two-stage cluster sampling procedure with probability proportionate to size was applied; first, 216 Censuses Blocks (CBs) were selected, and second, 25 households in each CB were selected. 3) A baseline survey was started in 2015, and collected data on demographic and economic characteristics and verbal autopsy (VA); the 2nd cycle collected updated demographic data, VA, type of morbidity (communicable and non-communicable diseases, disability and injury) and health access. 4) The data were collected at a home visit through a Computer-Assisted Personal Interview (CAPI) on a tablet device, and the data were transferred to the server through the Internet. 5) The quality control consisted of spot-checks of 5% of interviews to control for adherence to the protocol, re-checks to ensure the validity of the interview, and computer-based data cleaning. 6) A utilization system was designed for policy-makers (government) and researchers. RESULTS: In total, 5147 households participated in the baseline assessment in 2015, and 4996 households participated in the second cycle in 2016 (97.0% response rate). CONCLUSIONS: Development of an urban HDSS is possible and is beneficial in providing data complementary to the existing demographic and health information system at local, national and global levels.

Evaluation of Pictorial Dietary Assessment Tool for Hospitalized Patients with Diabetes: Cost, Accuracy, and User Satisfaction Analysis.

Although nutritional screening and dietary monitoring in clinical settings are important, studies on related user satisfaction and cost benefit are still lacking. This study aimed to: (1) elucidate the cost of implementing a newly developed dietary monitoring tool, the Pictorial Dietary Assessment Tool (PDAT); and (2) investigate the accuracy of estimation and satisfaction of healthcare staff after the use of the PDAT. A cross-over intervention study was conducted among 132 hospitalized patients with diabetes. Cost and time for the implementation of PDAT in comparison to modified Comstock was estimated using the activity-based costing approach. Accuracy was expressed as the percentages of energy and protein obtained by both methods, which were within 15% and 30%, respectively, of those obtained by the food weighing. Satisfaction of healthcare staff was measured using a standardized questionnaire. Time to complete the food intake recording of patients using PDAT (2.31 ± 0.70 min) was shorter than when modified Comstock (3.53 ± 1.27 min) was used (p < 0.001). Overall cost per patient was slightly higher for PDAT (United States Dollar 0.27 ± 0.02) than for modified Comstock (USD 0.26 ± 0.04 (p < 0.05)). The accuracy of energy intake estimated by modified Comstock was 10% lower than that of PDAT. There was poorer accuracy of protein intake estimated by modified Comstock (<40%) compared to that estimated by the PDAT (>71%) (p < 0.05). Mean user satisfaction of healthcare staff was significantly higher for PDAT than that for modified Comstock (p < 0.05). PDAT requires a shorter time to be completed and was rated better than modified Comstock.

Nutrition screening tools as predictor of malnutrition for hemodialysis patients in Dr. Sardjito Hospital in Yogyakarta, Indonesia.

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).

A simple dietary assessment tool to monitor food intake of hospitalized adult patients.

BACKGROUND/OBJECTIVES: Monitoring food intake of patients during hospitalization using simple methods and minimal training is an ongoing problem in hospitals. Therefore, there is a need to develop and validate a simple, easy to use, and quick tool that enables staff to estimate dietary intake. Thus, this study aimed to develop and validate the Pictorial Dietary Assessment Tool (PDAT). SUBJECTS AND METHODS: A total of 37 health care staff members consisting of dietitians, nurses, and serving assistants estimated 130 breakfast and lunch meals consumed by 67 patients using PDAT. PDAT was developed based on the hospital menu that consists of staple food (rice or porridge), animal source protein (chicken, meat, eggs, and fish), and non-animal source protein (tau fu and tempeh), with a total of six pictorials of food at each meal time. Weighed food intake was used as a gold standard to validate PDAT. Agreement between methods was analyzed using correlations, paired t-test, Bland-Altman plots, kappa statistics, and McNemar's test. Sensitivity, specificity, and area under the curve of receiver operating characteristic were calculated to identify whether patients who had an inadequate food intake were categorized as at risk by the PDAT, based on the food weighing method. Agreement between different backgrounds of health care staff was calculated by intraclass correlation coefficient and analysis of variance test. RESULTS: There was a significant correlation between the weighing food method and PDAT for energy (r=0.919, P<0.05), protein (r=0.843, P<0.05), carbohydrate (r=0.912, P<0.05), and fat (r=0.952; P<0.05). Nutrient intakes as assessed using PDAT and food weighing were rather similar (295±163 vs 292±158 kcal for energy; 13.9±7.8 vs 14.1±8.0 g for protein; 46.1±21.4 vs 46.7±22.3 g for carbohydrate; 7.4±3.1 vs 7.4±3.1 g for fat; P>0.05). The PDAT and food weighing method showed a satisfactory agreement beyond chance (k) (0.81 for staple food and animal source protein; 0.735 for non-animal source protein). Intraclass correlation coefficient ranged between 0.91 and 0.96 among respondents. There were no differences in energy, protein, carbohydrate, and fat intake estimated among health care staff (P=0.967; P=0.951; P=0.888; P=0.847, respectively). CONCLUSION: In conclusion, PDAT provides a valid estimation of macronutrient consumption among hospitalized adult patients.