Development of an electronic food ordering system and a la carte menu: Enhancing patient involvement in nutritional care.

BACKGROUND: Malnutrition is a significant issue in hospitals, leading to weight loss and reduced quality of life for patients. Hospital food plays a crucial role in preventing malnutrition, especially for patients with high nutritional risk or malnourishment. However, barriers to providing adequate nutritional care include a lack of tools to record patients' nutritional intake and a limited understanding of energy and protein content in hospital menus. OBJECTIVE: The study aimed to develop an electronic patient-centered food ordering system and an à la carte menu to improve patients' nutritional care and involvement in their dietary choices. METHODS: The study was conducted in two parts. Part 1 involved a questionnaire survey among hospitalized patients to determine their food preferences, self-assessed ability to use an electronic food ordering system, and preferences for different types of cuisine. The survey also investigated patients' meal choices for a full day, including portion sizes. Part 2 comprised usability tests of the electronic food ordering system prototype, conducted on hospitalized patients to identify interface issues and assess overall satisfaction. RESULTS: A total of 99 patients participated in the questionnaire survey. The majority (78.7 %) found the selection of dishes appropriate. Patients' preferences were used to adjust the à la carte menu to reflect their meal choices. In the usability tests, the electronic food ordering system prototype showed positive results, and the System Usability Score was above the threshold for minor adjustments. CONCLUSION: The study successfully developed an electronic patient-centered food ordering system and an à la carte menu that aligned with patients' preferences and needs. The system demonstrated usability and potential to improve patients' nutritional care and involvement in their dietary decisions. By addressing the barriers to nutritional care, this system offers a feasible solution to prevent and treat malnutrition in hospitalized patients.

Concordance between changes in calf circumference and muscle mass exists: A narrative literature review.

Technological methods such as BIA or DXA are not always accessible in clinical practice, thus GLIM supports the use of calf circumference measurements to examine muscle mass. However, it has not been described if measurements of calf circumference can detect a change in muscle mass to the same degree as the technological methods. The aim of this study was to assess, whether changes in calf circumference can be used as a valid proxy for changes in muscle mass. 10 studies including measurements of muscle mass by calf circumference and technological methods at baseline and follow-up were identified through a narrative literature review. Results were used to determine concordance between measurements. Predominantly concordance between changes in calf circumference and muscle mass assessed by BIA or DXA was reviled. However, the results were not uniform for hospitalized patients or older adults as groups. Thus, uncertainty whether changes in calf circumference can be used as a valid proxy for changes in muscle mass in these groups still exist.

Low-intake dehydration and nutrition impact symptoms in older medical patients - A retrospective study.

BACKGROUND AND AIMS: Malnutrition and low-intake dehydration both increase complications and mortality in hospitalized older medical patients. Nutrition Impact Symptoms (NIS) are barriers for obtaining an adequate nutritional intake and possibly adequate fluid. Therefore, we aimed to assess the prevalence of low-intake dehydration and specific NIS, and the relation between low-intake dehydration and specific NIS. METHODS: A retrospective cohort study among older patients (≥65 years) from the Medical Department at Herlev-Gentofte Hospital and referred to a clinical dietitian. Data about sex, age, BMI, prevalence of nutritional risk (NRS-2002), low-intake dehydration (calculated osmolarity >295 mmol/L), and NIS (the EATEN-questionnaire, comprising 16 NIS-questions and whether these were respectively present and limiting nutritional intake) were collected from the hospital records. RESULTS: We included 99 patients (61% women), mean age 81 years (±7.9), median BMI 21.8 kg/m2 (IQR:19.5-25.4). Nutritional risk was found in 74%, and low-intake dehydration in 40% of the included patients. The three most frequent NIS-present were: Early satiety (84%), no appetite (82%), and tiredness (72%). The three most frequent NIS-limiting intake were: No appetite (73%), early satiety (69%), and dry mouth (42%). We found low-intake dehydration to be related to a lower prevalence of the following NIS-present; dry mouth (58% vs.80%, p = 0.0210), and breathlessness (24% vs.49%, p = 0.0179). Among the NIS-limiting intake a lower prevalence of other pains was related to low-intake dehydration (7% vs.29%, p = 0.0233). CONCLUSION: NIS and low-intake dehydration are highly prevalent in older patients. There is limited association between low-intake dehydration and specific NIS.

The association between nutrition impact symptoms, nutritional risk, and risk of reduced overall survival in patients with head and neck cancer. A retrospective study.

BACKGROUND & AIMS: To examine which nutritional impact symptoms (NIS) were most prevalent at the initial state of treatment in outpatients with head and neck cancer (HNC). Secondly, to examine whether there is a potential relation between risk of reduced overall survival to NIS or nutritional risk. METHODS: Retrospective data collection from outpatients with HNC undergoing radiotherapy and/or systemic therapy. A clinical dietitian consulted all patients with the inclusion of a nutritional risk screening according to the Nutritional Risk Screening tool (NRS 2002) and Eastern Cooperative Oncology Group performance status (ECOG), and an assessment of NIS collected with a structured questionnaire, with the prevalence of 16 symptoms and to what degree they were nutritionally limiting. Weight loss at two months follow-up was calculated and patients were categorized as either at low or high risk of reduced overall survival in accordance with a BMI-adjusted weight loss grading system (high, score 0-2; low, score 3-4). RESULTS: A total of 110 patients were included (male, 77%; age, 66 (59-71)). The mean weight loss was 4.5 kg at two months follow-up, increasing with higher BMI. Eighty-six percentage of the patients experienced 3 or more of the present NIS (P-NIS), and 44% of the patients experienced 3 or more of the nutritionally limiting NIS (L-NIS). Patients who have a high risk of reduced overall survival accounted for 45% and consisted of patients with low BMI and high percentual weight loss. No significant difference was found between the two groups in terms of NIS. CONCLUSION: We found NIS to be highly prevalent among patients with head and neck cancer. Women experienced more NIS than men. Half of the patients were categorized as being at high risk of reduced overall survival, but no relation between the risk of reduced overall survival to NIS or nutritional risk was found in this study.

The association between malnutrition and dehydration in older adults admitted to a geriatric unit: An observational study.

BACKGROUND AND AIM: There is an overlap between the risk factors causing low intake of water and low intake of nutrients, respectively. This study aims to explore the agreement between the assessment of malnutrition and the outcome of low-intake dehydration in a population of older hospitalized patients. METHODS: Patients ≥65 years old and hospitalized at the geriatric hospital ward were screened for eligibility within 96 h of admission. Dehydration was assessed with the calculated serum osmolarity ≥295 mmol/L (1.86 × (Na+ + K+) + 1.15 × glucose + urea + 14), and (risk of) malnutrition was assessed with NRS-2002 ≥ 3 points, MNA-SF ≤ 7 points, MNA-LF < 17, MUST ≥ 2 points, and GLIM after screening with NRS-2002 and MNA-LF. Follow-up data regarding exercise rehabilitation, readmissions, and mortality was collected 30 days after discharge. Statistics used were the Chi-squared test, Fishers-exact test, and Wilcoxon signed rank test. RESULTS: A total of 114 patients (57% females) were included. Median age 85.5 (IQR 80; 89.25) years. A total of 49 (43%) were dehydrated. Fewer females were dehydrated (F: 42.9% vs. M: 67.7%, p = 0.013). The patients with osmolarity ≥295 mmol/L had a higher median weight (68.3 (IQR 58.5; 78.4) vs. 62 (IQR 51.8; 72.1), p = 0.021) and mid-up-arm circumference (27 (IQR 26; 30) vs. 25.5 (IQR 22.9; 28.3), p = 0.004). No significant difference was found in the prevalence of malnutrition between those with or without dehydration (NRS-2002; 70% vs. 81%, p = 0.174; MNA-SF: 23.1 vs. 23.2%, p = 1.0; MNA-LF: 37.1 vs. 30.2%, p = 0.644; MUST: 24.5 vs. 33.8%, p = 0.308; GLIM after screening with NRS-2002: 84.4 vs. 74.5%, p = 0.405, GLIM after screening with MNA-LF: 74.1 vs. 75.6%, p = 0.438). Kappa values varied around 0 and reflected low agreement. There were no differences in the follow-up data, between those who were normohydrated and those who were dehydrated. CONCLUSION: We found low agreement between the assessment of malnutrition and low-intake dehydration in a population of older hospitalized patients. All geriatric patients should therefore be assessed for both conditions.

Evaluation of Multi-Frequency Bioelectrical Impedance Analysis against Dual-Energy X-ray Absorptiometry for Estimation of Low Muscle Mass in Older Hospitalized Patients.

The accuracy of multi-frequency (MF) bioelectrical impedance analysis (BIA) to estimate low muscle mass in older hospitalized patients remains unclear. This study aimed to describe the ability of MF-BIA to identify low muscle mass as proposed by The Global Leadership Initiative on Malnutrition (GLIM) and The European Working Group on Sarcopenia in Older People (EWGSOP-2) and examine the association between muscle mass, dehydration, malnutrition, and poor appetite in older hospitalized patients. In this prospective exploratory cohort study, low muscle mass was estimated with MF-BIA against dual-energy X-ray absorptiometry (DXA) in 42 older hospitalized adults (≥65 years). The primary variable for muscle mass was appendicular skeletal muscle mass (ASM), and secondary variables were appendicular skeletal muscle mass index (ASMI) and fat-free mass index (FFMI). Cut-off values for low muscle mass were based on recommendations by GLIM and EWGSOP-2. MF-BIA was evaluated against DXA on the ability to estimate absolute values of muscle mass by mean bias, limits of agreement (LOA), and accuracy (5% and 10% levels). Agreement between MF-BIA and DXA to identify low muscle mass was evaluated with sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). The association between muscle mass, dehydration, malnutrition, and poor appetite was visually examined with boxplots. MF-BIA overestimated absolute values of ASM with a mean bias of 0.63 kg (CI: -0.20:1.46, LOA: -4.61:5.87). Agreement between MF-BIA and DXA measures of ASM showed a sensitivity of 86%, specificity of 94%, PPV of 75% and NPV of 97%. Boxplots indicate that ASM is lower in patients with malnutrition. This was not observed in patients with poor appetite. We observed a tendency toward higher ASM in patients with dehydration. Estimation of absolute ASM values with MF-BIA should be interpreted with caution, but MF-BIA might identify low muscle mass in older hospitalized patients.

A multimodal nutritional intervention after discharge improves quality of life and physical function in older patients - a randomized controlled trial.

BACKGROUND: Many older hospitalized patients are at nutritional risk or malnourished and the nutritional condition is often further impaired during hospitalization. When discharged to own home, a "Nutrition Gap" often occurs, causing inadequate dietary intake, and potentially impeded recovery. Previously, cross-sectorial studies of single component nutritional intervention have shown a limited effect on clinically relevant outcomes. We hypothesized that a multimodal nutritional intervention is necessary to elicit a beneficial effect on clinically relevant outcomes. METHODS: A randomized controlled trial was performed for a period of 16 weeks. At discharge, the intervention group (IG) received dietetic counselling including a recommendation of daily training, an individual nutrition plan and a package containing foods and drinks covering dietary requirements for the next 24 h. Further, a goodie-bag containing samples of protein-rich milk-based drinks were provided. Information regarding recommendations of nutritional therapy after discharge was systematically and electronically communicated to the municipality. The dietician performed telephone follow-ups on day 4 and 30 and a home visit at 16 weeks. The control group (CG) received standard treatment. The primary outcome was readmissions within 6 month, secondary outcomes were Length of Stay (LOS), Health Related Quality of Life (EQ-5D-3L), nutritional status, physical function (30s-CST) and mortality. This trial was registered under ClinicalTrials.gov Identifier no. NCT03488329. RESULTS: We included 191 patients (IG: n = 93). No significant difference was seen in readmissions within 6 month (IG: 45% vs. CG: 45%, Risk Ratio (RR): 0.96 0.71-1.31, p = 0.885). At the 16-weeks follow-up more patients in the IG reached at least 75% of energy and protein requirements (82% vs. CG: 61%, p = 0,007). The energy (kcal) and protein intake (g) per kg was significantly higher in the IG (26.4 kcal/kg (±7.4) vs. 22.6 (±7.4), p = 0.0248) (1.1 g/kg (±0.3) vs. 0.9 g/kg (±0.3). Furthermore, significant lower weight loss was seen in IG (0.7 (±4.3) vs. -1.4 (±3.6), p = 0.002). A significant and clinically relevant difference was found in the EQ-5D-3L VAS-score (IG: mean 61.6 ± 16.2 vs. CG: 53.3 ± 19.3, p = 0.011) (Δ14.3 (±15.5) vs. Δ5.6 (±17.2), p = 0.002). A significant difference in mean 30s-CST in IG was also found (7.2 (±4.3) vs. 5.3 (±4.1), p = 0.010). The improvements in physical function were of clinical relevance in both groups, but significantly higher in the IG (Δ4.2 (±4.4) vs. Δ2.2 (±2.5), p = 0.008). In fact, 86% in IG experienced improvements in the 30s-CST compared with 68% in the CG (p = 0.022). LOS was found to be lower at all time points, however not significant (30 days: -3 (-8.5 to 2.5), p = 0.276, 16 weeks: -4 (-10.2 to 2.2, p = 0.204), 6 months: -3 (-9.3 to 3.3, p = 0346)). All-cause mortality was not different between groups, however RR showed a non-significantly 47% reduction at day 30 (0.53 (0.14-2.05, p = 0.499)) and a 17% reduction at 16 weeks (0.83 (0.40-1.73, p = 1.000)) in IG. Per protocol (PP) analysis revealed a non-significant decrease of 32% in readmission at 6 months (RR: 0.68 (0.42-1.08), p = 0.105). CONCLUSION: The present study, using a multimodal nutritional approach, revealed no significant effect on readmissions however a significant positive effect on nutritional status, quality of life and physical function was found. The improvements in quality of life and physical function were of clinical relevance. No significant effect was found on LOS and mortality.

Narrative Review of Low-Intake Dehydration in Older Adults.

Low-intake dehydration is a common and often chronic condition in older adults. Adverse health outcomes associated with low-intake dehydration in older adults include poorer cognitive performance, reduced quality of life, worsened course of illness and recovery, and a high number of unplanned hospital admissions and increased mortality. The subjective methods to assess (risk of) dehydration are not reliable, and the evidence about preventive measures are also limited. So is the knowledge about the optimal intake of beverages per day. This narrative review presents the state of the science on the role of low intake hydration in older adults. Despite its simple cause-the inadequate intake of beverages-low-intake dehydration appears to be a very complex problem to address and much more research is needed in the area. Based on the existing evidence, it seems necessary to take setting specific differences and individual problems and needs into account to tackle dehydration in older adults. Further, it is necessary to increase awareness of the prevalence and severity of low-intake dehydration among older adults and in nursing staff in care homes and hospitals as well as among caregivers of older adults living at home.

Accuracy of the calculated serum osmolarity to screen for hyperosmolar dehydration in older hospitalised medical patients.

BACKGROUND AND AIMS: Simple hyperosmolar dehydration, also termed water-loss dehydration (HD), is common in older hospitalised patients, thus increasing the risk of morbidity and mortality. Directly measured serum osmolality is the reference standard to determine HD; however, it is not a routine test due to its complexity and cost. Thus, a simple valid objective diagnostic tool to detect HD is needed. Consequently, we aimed to validate the agreement between measured s-osmolality (mOsm/kg) and calculated s-osmolarity (mOsm/L). METHODS: Patients aged >65 were included from the emergency medical department at Herlev Hospital, Copenhagen, Denmark. Exclusion criteria were: eGFR< 30 mmol/L, severe heart failure, decompensated cirrhosis, alcohol intake or initiated rehydration treatment. We obtained data for measured s-osmolality as well as calculated osmolarity, using the by ESPEN recommended equation [1.86x (Na+ + K+)+1.15 ∗glucose + urea+14]. To determine accuracy, we used cut-off values of >295 mOsm/L versus >300 mOsm/kg. RESULTS: A total of 90 patients (female 53%), age median 78 yrs (72-86 yrs) were included. According to the measured mOsm/kg, impending HD was evident in 32% (n = 10), of these 11% (n = 10) had current HD. There was a significant association between calculated mOsm/L and measured Osm/kg (r2 = 0.7513, p < 0.0001). A sensitivity of 90% (95% CL: 56%-100%), a specificity of 68% (95% CL: 56%-78%), Positive predictive value (PPV) of 26% (95% CL: 12%-43%), and Negative predictive value (NPV) of 98% (95% CL: 90%-100%) were observed. Notably, only 20% (n = 2) of the patients who were dehydrated according to the measured Osm/kg were correctly clinically diagnosed with dehydration. CONCLUSIONS: The equation recommended by ESPEN to calculate osmolarity was found to be an accurate objective diagnostic tool to assess HD in older hospitalised medical patients. The method is markedly superior to the current clinical practice.

Poor performance in nutrition risk screening may have serious consequences for hospitalized patients.

BACKGROUND AND AIM: Finding patients at nutrition risk and securing sufficient nutritional intake, is vital to decrease risk of adverse outcomes and all-cause mortality. The aims of this study were therefore to investigate the prevalence of patients being screened for nutrition risk, to determine nutritional coverage in at-risk patients and assess the prevalence of readmissions and mortality within 30 days. METHODS: A one-day cross-sectional study was performed at Herlev Hospital, Denmark in June 2019. Patients >18 y and hospitalized for ≥4 days were enrolled. Exclusion criteria were admission to the intensive, palliative, acute medical or maternal ward. If a patient was not screened by the ward a clinical dietitian screened the patient. Patients found to be at nutrition-risk underwent a 24-h dietary recall to assess energy and protein intake. Data on length of stay, readmissions, and mortality within 30 days were collected from the hospital patient register. RESULTS: In total 197 (F:52%) patients were included. Median (IQR) age 74y (65-81). At the audit day n = 76 (39%) had a primary screening, and n = 42 (21%) were screened within 24 h. A NRS-2002-score ≥ 3 was found in 111 patients (63%). At-risk patients were more likely to be readmitted within 30 days (45% vs. 27%, p = 0.024) and had a higher mortality within 30 days after discharge (23% vs. 10%., p = 0.0285). In patients at nutrition risk 23% covered ≥75% of their energy- and protein requirement the last 24 h. More patients covered their energy- and protein-need if they were supplemented with enteral and/or parenteral nutrition fully or partly (63% vs. 15%, p < 0.001 or had been in contact with a clinical dietitian during the admission (33% vs. 15%, p = 0.0337. There were no differences in prevalence of readmissions and mortality between those patients at nutrition risk, who covered their energy and protein need and those who did not. CONCLUSIONS: The results demonstrate that the current nutritional care process is inadequate and may have serious consequences for hospitalized patients. Further effort is needed on the awareness of screening patients and how to fulfil their requirements during hospitalization. An abstract with part of the results has been accepted as a poster to ESPEN 2020.

Effect of nutritional interventions on discharged older patients: study protocol for a randomized controlled trial.

BACKGROUND: During hospitalization, many older patients are at nutritional risk or malnourished, and their nutritional condition is often further impaired during hospitalization. After discharge, a "nutrition gap" often occurs in which the patient does not receive enough nutrition to ensure an optimal recovery. METHODS: The study is a randomized controlled study ongoing over 112 days. At discharge, the intervention group receives guidance from a clinical dietitian, and an individualized nutrition plan is made. The dietitian will perform telephone follow-up after 4 and 30 days. It will also be possible for the participant, the participant's relatives, or the participant's municipality to contact the dietitian if nutritional questions arise. At the time of discharge, the intervention group will receive a package containing foods and drinks that will cover their nutritional needs on the first day after discharge. They will also receive a goodie bag containing samples of protein-rich, milk-based drinks. Data are collected on quality of life, appetite, physical function, dietary intake, weight, height, energy and protein needs, and experience of discharge and cooperation with the municipality. Information about nutrition status will be sent to the municipality so that the municipality can take over nutritional treatment. The control group receives a standard treatment. DISCUSSION: This study is the first to combine previously successful single nutritional interventions into a multimodal intervention whose aim is to obtain an effect on patient-related outcomes. We hope that the results will prove beneficial and help to ensure the cross-sector quality of nutritional support to older patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03488329. April 5, 2018.

From Evidence to Clinical Practice: Positive Effect of Implementing a Protein-Enriched Hospital Menu in Conjunction With Individualized Dietary Counseling.

BACKGROUND: The aim of this study was to investigate if a protein-enriched menu in conjunction with individualized dietary counseling would increase energy and protein intake in hospitalized patients at nutrition risk compared with providing the protein-enriched menu as a stand-alone intervention. METHOD: Data from medical and surgical hospitalized patients were prospectively collected and compared with a historical intervention group (HIG). Primary outcome was the number of patients achieving >75% of energy and protein requirements. Secondary outcomes included mean energy and protein intake (adjusted for body weight [ABW]), readmission rate, and the number of patients with a baseline intake <50% of energy and protein requirement, who increased to ≥50%. RESULTS: In the intervention group (IG), 92% vs 76% in the HIG reached >75% of energy requirements ( P = .04); 90% in the IG vs 66% in the HIG reached >75% of protein requirements ( p = <0.01). The IG had a significantly higher mean intake of energy and protein compared with the HIG: ABW, 31 kcal kg-1 vs 25 kcal kg-1 ( P < .01) and 1.2 g protein kg-1 vs 0.9 g protein kg-1 ( P < .001). More than 85% of the patients with a baseline <50% of the EP requirement achieved ≥75% of the energy and protein requirement. No difference between readmission rates was found. CONCLUSION: Providing a protein-enriched menu in conjunction with individualized dietary counseling significantly increased protein and energy intake in hospitalized patients at nutrition risk.