Effects of oral nutrition supplements in persons with dementia: A systematic review

Objective Persons with dementia are at risk of malnutrition, evidenced by low dietary intake, which has consequences for nutritional status, activity of daily living and disease progression. The effects of oral nutrition supplements (ONS) on nutritional intake, nutritional status, and cognitive and physical outcomes in older persons with dementia were evaluated. Methods PubMed, Medline, Embase, CINAHL and the Cochrane Central Register of Controlled Trials were searched in December 2017, and this was repeated in May 2019. The Preferred Reporting Items for Systematic Reviews and Analysis (PRISMA) checklist was used. Papers were considered if they presented experimental clinical trials using oral nutritional supplements to persons diagnosed with dementia, including Alzheimer's disease and mild cognitive impairment, and conducted in hospitals, nursing homes or homes. Results We included ten articles reporting nine clinical trials. A total of 407 persons with dementia were included, of whom 228 used ONS for 7 to 180 days. Nutritional intake improved by 201 to 600 kcal/day. Energy intake from ordinary foods was not affected, thus ONS improved the persons daily intake of energy and protein. Body weight, muscle mass, and nutritional biomarkers in blood improved in the intervention groups compared with the control groups. No effects on cognition or physical outcomes were observed. Conclusion ONS increases the intake of energy and protein and improves nutritional status in persons with dementia; however, RCTs with longer intervention periods are needed to investigate the impact on cognitive and functional outcomes.publishedVersio

Prevalence of patients “at risk of malnutrition” and nutritional routines among surgical and non-surgical patients at a large university hospital during the years 2008–2018

Background & aims: Being “at risk of malnutrition”, which includes both malnutrition and the risk to be so, is associated with increased morbidity and mortality in both surgical and non-surgical patients. Several strategies and guidelines have been introduced to prevent and treat this, but the effects are scarcely investigated. This study aims to evaluate the long-term effects of these efforts by examining trends concerning: 1) the prevalence of patients «at risk of malnutrition» and 2) the use of nutritional support and diagnostic coding related to malnutrition over an 11-year period in a large university hospital. Moreover, we wanted to investigate if there was a difference in trends between surgical and non-surgical patients. Methods: From 2008 to 2018, Haukeland University Hospital, Norway, conducted 34 point-prevalence surveys to investigate the prevalence of patients «at risk of malnutrition», as defined by Nutritional Risk Screening 2002, and the use of nutritional support at the hospital. Diagnostic coding included ICD-10 codes related to malnutrition (E43, E44 and E46) at hospital discharge, which were extracted from the electronic patient journal. Trend analysis by calendar year was investigated using logistic regression models with and without adjustment for age (continuous), gender (male/female) and Charlson Comorbidity Index (none, mild, moderate or severe). Results: The number of patients included in the study was 18 933, where 52.1% were male and the median (25th, 75th percentile) age was 65 (51, 76) years. Of these, 5121 (27%) patients were identified to be «at risk of malnutrition». Fewer surgical patients (21.2%) were «at risk of malnutrition», as compared to non-surgical patients (30.9%) (p < 0.001). Adjusted trend analysis did not identify any change in the prevalence of patients «at risk of malnutrition» from 2008 to 2018. The percentage of patients «at risk of malnutrition» who received nutritional support increased from 61.6% in 2008 to 71.9% in 2018 (p < 0.001), with a range from 55.6 to 74.8%. This trend was seen for both surgical and non-surgical patients (p < 0.001 for both). Similarly, dietitians were more involved in the patients’ treatment (range: 3.8–16.7%), and there was increased use of ICD-10 codes related to malnutrition during the study period (range: 13.0–41.8%) (p < 0.001). These trends were seen for both surgical patients and non-surgical patients (p < 0.001), despite use being less common for surgical patients, as compared to non-surgical patients (p < 0.001). Conclusions: This large hospital study shows no apparent change in the prevalence of patients «at risk of malnutrition» from 2008 to 2018. However, more patients «at risk of malnutrition», both surgical and non-surgical, received nutritional support, treatment from a dietitian and a related ICD-10 code over the study period, indicating improved nutritional routines as a result of the implementation of nutritional guidelines and strategies.publishedVersio

Nutritional risk, nutrition plan and risk of death in older health care service users with chronic diseases: A register-based cohort study

Background and aims Nutritional risk in older health care service users is a well-known challenge. Nutritional risk screening and individualised nutrition plans are common strategies for preventing and treating malnutrition. The aim of the current study was to investigate whether nutritional risk is associated with an increased risk of death and whether a nutrition plan to those at nutritional risk could reduce this potential risk of death in community health care service users over 65 years of age. Methods We conducted a register-based, prospective cohort study on older health care service users with chronic diseases. The study included persons ≥65 years of age receiving health care services from all municipalities in Norway from 2017 to 2018 (n = 45,656). Data on diagnoses, nutritional risk, nutrition plan and death were obtained from the Norwegian Registry for Primary Health Care (NRPHC) and the Norwegian Patient Registry (NPR). We used Cox regression models to estimate the associations of nutritional risk and use of a nutrition plan with the risk of death within three and six months. Analyses were performed within the following diagnostic strata: chronic obstructive pulmonary disease (COPD), dementia, type 2 diabetes, stroke, osteoporosis and heart failure. The analyses were adjusted for age, gender, living situation and comorbidity. Results Of the 45,656 health care service users, 27,160 (60%) were at nutritional risk, and 4437 (10%) and 7262 (16%) died within three and six months, respectively. Among those at nutritional risk, 82% received a nutrition plan. Health care service users at nutritional risk had an increased risk of death compared to health care service users not at nutritional risk (13% vs 5% and 20% vs 10% at three and six months). Adjusted hazard ratios (HRs) for death within six months were 2.26 (95% confidence interval (CI): 1.95, 2.61) for health care service users with COPD, 2.15 (1.93, 2.41) for those with heart failure, 2.37 (1.99, 2.84) for those with osteoporosis, 2.07 (1.80, 2.38) for those with stroke, 2.65 (2.30, 3.06) for those with type 2 diabetes and 1.94 (1.74, 2.16) for those with dementia. The adjusted HRs were larger for death within three months than death within six months for all diagnoses. Nutrition plans were not associated with the risk of death for health care service users at nutritional risk with COPD, dementia or stroke. For health care service users at nutritional risk with type 2 diabetes, osteoporosis or heart failure, nutrition plans were associated with an increased risk of death within both three and six months (adjusted HR 1.56 (95% CI: 1.10, 2.21) and 1.45 (1.11, 1.88) for type 2 diabetes; 2.20 (1.38, 3.51) and 1.71 (1.25, 2.36) for osteoporosis and 1.37 (1.05, 1.78) and 1.39 (1.13, 1.72) for heart failure). Conclusions Nutritional risk was associated with the risk of earlier death in older health care service users with common chronic diseases in the community. Nutrition plans were associated with a higher risk of death in some groups in our study. This may be because we could not control sufficiently for disease severity, the indication for providing a nutrition plan or the degree of implementation of nutrition plans in community health care.publishedVersio

Nutritional risk in a university hospital. Challenges and consequences in clinical practice

Introduction: Malnutrition is present in 20-50% of hospitalised patients, leading to increased risk for adverse clinical outcomes and even mortality. Nutritional status is often ignored during hospitalisation. The Bergen Nutritional Strategy was a multi-pronged effort introduced to increase focus on improving patients’ food and mealtime routines, and the routines used by staff to evaluate nutritional risk. Another element of this strategy was to ensure proper nutritional care during patients’ hospitalisation. Guidelines were implemented and hospital staff was educated. Repeated point-prevalence surveys were introduced in 2008 to increase awareness about patients’ nutritional status and to improve nutritional care. Aims: The main objective of this dissertation research was to objectively evaluate the Bergen Nutritional Strategy. This was accomplished by conducting three studies, each addressing different aspects of the strategy. The aim of the first study was to evaluate whether the Bergen Nutritional Strategy had positive effect overall on nutritional care of patients at Haukeland University Hospital (Paper I). The aim of the second study comprised two aspects. The first was to study in detail the components of the Nutritional Risk Screening (NRS 2002) tool to determine the minimum number of components necessary to clearly classify a patient as being ‘at nutritional risk’. The intention was to simplify the screening procedure, if possible. The second aspect was to assess whether being ‘at nutritional risk’ is associated with increased morbidity, mortality, and health-care costs. This was assessed during a oneyear follow-up (Paper II). The aim of the third study was to determine the prevalence of nutritional risk as a function of patients’ age, disease category, and the hospital department in which they were treated in order to better understand in which departments and patients groups nutritional care is most crucial to monitor (Paper III). Methods: Nutritional registrations performed as point-prevalence surveys were conducted every three months during 2008 and 2009. Any changes in clinical practice at hospital units were assessed by repeated surveys. The first survey was conducted at 14 hospital units and the next seven at 51 units. NRS 2002 was used to classify patients as ‘at nutritional risk’ or ‘not at risk’, according to their nutritional status and severity of illness (See Appendix 2, section 11.2). Data on length of hospital stay, new hospital admissions, and mortality were obtained from the patient administrative system. Patients: For the eight point-prevalence surveys in 2008 and 2009, 5849 adult hospitalised patients were subject for inclusion; 3604 patients were included in study I, and 3279 patients were included in studies II and III. Results: In study I, 1230 (34%) of 3604 patients were at nutritional risk. Among these, 53% received nutritional treatment, and dieticians were involved in the treatment of only 5%. The proportion of patients who were screened increased significantly from the first to the last survey (p=0.012). However, the proportion of patients who received nutrition treatment did not increase during the study period (p=0.66). In study II, 3279 patients were followed for one year. Of these, 29% were at nutritional risk, as assessed by NRS 2002. Being at nutritional risk was strongly associated with increased morbidity and mortality. Even the initial screening robustly identified adverse outcomes. Every single item of the screening tool was found to be a significant independent risk predictor. A positive response to one or more of the initial four questions in NRS 2002 was associated with increased risk of morbidity and mortality, and positive answers to all four questions were associated with a 13 times greater risk of dying during the following year (OR 13.0, 95% CI 4.52 to 37.6). In study III, compared to well-nourished patients, those at nutritional risk were more often female (53% vs.50%); underweight (mean Body Mass Index [BMI] 21.4 vs. 25.3 kg/m²); and older (mean age: 67.8 vs. 63.0 years). The prevalence of nutritional risk increased with age, being 40% for patients ≥80 years and 21% for those 25 kg/m2), and patients with fewer than four diagnoses were frequently found to be at nutritional risk. A high prevalence of nutritional risk was found in nearly all patient groups and hospital units. However, it was most common among patients with infections, cancer, or pulmonary diseases. The greatest numbers of patients at nutritional risk were in the departments of general medicine or surgery. Nearly half (40%) of the patients who were discharged from hospital to nursing homes, and 25% of the patients who were discharged to their own home were at nutritional risk. Conclusions This comprehensive study of a university hospital patient population revealed that a high proportion of the patients in this university hospital were at nutritional risk during the study period. Far from being simply an academic finding, this risk was strongly associated with adverse outcomes, sometimes even death. Nutritional depletion is a significant risk factor for morbidity, increased use of hospital services, and premature death. Our findings support the elevated need for nutritional screening in hospitals. Patients at nutritional risk were identified in all disease categories and all ages. A screening tool is immensely valuable for categorising patients at nutritional risk, and NRS 2002 was found to be suitable for identifying high-risk patients. The initial four questions of NRS 2002 were strong predictors of hospitalisation, morbidity, and most importantly, mortality, among hospitalised patients. Thus the combined use of just these four questions would be appropriate and effective to use as an initial screening of hospitalised patients. Implementation of the Bergen Nutritional Strategy improved the screening performance among the hospital staff, but did not improve the patients’ nutritional treatment. Therefore, more intense efforts are necessary to improve nutritional practice and staff knowledge in hospitals

Evaluation of nutritional status and methods to identify nutritional risk in rheumatoid arthritis and spondyloarthritis

Patients with rheumatoid arthritis (RA) and spondyloarthritis (SpA) experience several nutritional challenges and are prone to develop malnutrition. This observational study aimed to perform a comprehensive nutritional assessment of outpatients diagnosed with RA and SpA, as well as to evaluate methods to identify nutritional risk. Nutritional status was investigated by anthropometric measures, body composition (DXA, dual energy X-ray absorptiometry), and handgrip strength (HGS). Nutritional risk was classified by Nutritional Risk Screening 2002 (NRS2002) and malnutrition was defined by the Global Leadership Initiative on Malnutrition (GLIM) criteria and fat-free mass index (FFMI; kg/m2, <16.7 (M), <14.6 (F)). Out of 71 included patients, 46 (66%) were abdominally obese, 28 (39%) were obese in terms of body mass index (BMI), and 33 (52%) were obese in terms of the fat mass index (FMI; kg/m2, ≥8.3 (M), ≥11.8 (F)). Malnutrition was identified according to FFMI in 12 (19%) patients, according to GLIM criteria in 5 (8%) patients, and on the basis of BMI (<18.5 kg/m2) in 1 (1%) patient. None were identified by NRS2002 to be at nutritional risk. Our study revealed high prevalence of abdominal obesity and low FFMI. Waist circumference was a good indicator of FMI. BMI, NRS2002, and HGS did not capture patients with malnutrition identified by DXA

Effects of oral nutrition supplements in persons with dementia: A systematic review

Objective Persons with dementia are at risk of malnutrition, evidenced by low dietary intake, which has consequences for nutritional status, activity of daily living and disease progression. The effects of oral nutrition supplements (ONS) on nutritional intake, nutritional status, and cognitive and physical outcomes in older persons with dementia were evaluated. Methods PubMed, Medline, Embase, CINAHL and the Cochrane Central Register of Controlled Trials were searched in December 2017, and this was repeated in May 2019. The Preferred Reporting Items for Systematic Reviews and Analysis (PRISMA) checklist was used. Papers were considered if they presented experimental clinical trials using oral nutritional supplements to persons diagnosed with dementia, including Alzheimer's disease and mild cognitive impairment, and conducted in hospitals, nursing homes or homes. Results We included ten articles reporting nine clinical trials. A total of 407 persons with dementia were included, of whom 228 used ONS for 7 to 180 days. Nutritional intake improved by 201 to 600 kcal/day. Energy intake from ordinary foods was not affected, thus ONS improved the persons daily intake of energy and protein. Body weight, muscle mass, and nutritional biomarkers in blood improved in the intervention groups compared with the control groups. No effects on cognition or physical outcomes were observed. Conclusion ONS increases the intake of energy and protein and improves nutritional status in persons with dementia; however, RCTs with longer intervention periods are needed to investigate the impact on cognitive and functional outcomes

Barriers and Facilitators for Implementing a Decision Support System to Prevent and Treat Disease-Related Malnutrition in a Hospital Setting: Qualitative Study

Background: Disease-related malnutrition is a challenge among hospitalized patients. Despite guidelines and recommendations for prevention and treatment, the condition continues to be prevalent. The MyFood system is a recently developed decision support system to prevent and treat disease-related malnutrition. Objective: To investigate the possible implementation of the MyFood system in clinical practice, the aims of the study were (1) to identify current practice, routines, barriers, and facilitators of nutritional care; (2) to identify potential barriers and facilitators for the use of MyFood; and (3) to identify the key aspects of an implementation plan. Methods: A qualitative study was performed among nurses, physicians, registered dietitians, and middle managers in 2 departments in a university hospital in Norway. Focus group discussions and semistructured interviews were used to collect data. The Consolidated Framework for Implementation Research (CFIR) was used to create the interview guide and analyze the results. The transcripts were analyzed using a thematic analysis. Results: A total of 27 health care professionals participated in the interviews and focus groups, including nurses (n=20), physicians (n=2), registered dietitians (n=2), and middle managers (n=3). The data were analyzed within 22 of the 39 CFIR constructs. Using the 5 CFIR domains as themes, we obtained the following results: (1) Intervention characteristics: MyFood was perceived to have a relative advantage of being more trustworthy, systematic, and motivational and providing increased awareness of nutritional treatment compared with the current practice. Its lack of communication with the existing digital systems was perceived as a potential barrier; (2) Outer settings: patients from different cultural backgrounds with language barriers and of older age were potential barriers for the use of the MyFood system; (3) Inner settings: no culture for specific routines or systems related to nutritional care existed in the departments. However, tension for change regarding screening for malnutrition risk, monitoring and nutritional treatment was highlighted in all categories of interviewees; (4) Characteristics of the individuals: positive attitudes toward MyFood were present among the majority of the interviewees, and they expressed self-efficacy toward the perceived use of MyFood; (5) Process: providing sufficient information to everyone in the department was highlighted as key to the success of the implementation. The involvement of opinion leaders, implementation leaders, and champions was also suggested for the implementation plan. Conclusions: This study identified several challenges in the nutritional care of hospitalized patients at risk of malnutrition and deviations from recommendations and guidelines. The MyFood system was perceived as being more precise, trustworthy, and motivational than the current practice. However, several potential barriers were identified. The assessment of the current situation and the identification of perceived barriers and facilitators will be used in planning an implementation and effect study, including the creation of an implementation plan

Nutritional risk profile in a university hospital population

Background & aims: The prevalence of nutritional risk varies according to several factors. We aimed to determine the nutritional risk profile in a large Norwegian hospital population, specifically by age, disease category and hospital department. Methods: Nutritional surveys are performed routinely at Haukeland University Hospital, Norway. During eight surveys in 2008-2009, 3279 patients were categorized according to the Nutritional Risk Screening tool (NRS 2002). Results: The overall prevalence of nutritional risk was 29%, highest in patients with infections (51%), cancer (44%) and pulmonary diseases (42%), and in the departments of intensive care (74%), oncology (49%) and pulmonology (43%). Further, nutritional risk was identified in 40% of patients aged ≥80 years compared to 21% of age 7 diagnoses) (45%). However it was also high in patients with BMI ≥25 kg/m² (12%) and in those with fewer than 7 diagnoses (26%). Conclusions: Nutritional risk was most common among patients with high age, low BMI, more comorbidity, and with infections, cancer or pulmonary diseases, and patients who were discharged to nursing homes. However, the highest number of patients at nutritional risk had BMI in the normal or overweight range, were 60-80 years old, and were found in departments of general medicine or surgery. Importantly, younger patients and overweight patients were also affected. Thus, nutritional risk screening should be performed in the total patient population in order to identify, within this heterogeneous group of patients, those at nutritional risk