Is self-screening for 'at risk of malnutrition' feasible in a home setting?

INTRODUCTION: Despite malnutrition being established as a well-known risk for postoperative complications, the lack of screening for nutritional risk remains a challenge. The aim of this study was to investigate whether self-screening for nutritional risk prior to surgery is feasible in a home setting and if it will increase number of patients screened for nutritional risk, and secondly, to compare their screening results with the "in-hospital assessments" conducted by healthcare professionals. MATERIALS AND METHODS: This was a prospective study involving patients from six randomly selected surgical wards at two Norwegian hospitals as a part of the "Feasibility study of implementing the surgical Patient Safety Checklist the (PASC)". This checklist included a self-reported screening tool based on the Nutritional Risk Screening tool (NRS 2002) to identify "at risk of malnutrition" in patients that will undergo surgery the next 3 months or less. The original screening tool (NRS 2002) was used as a standard routine to identify "at risk of malnutrition" by healthcare professionals at hospital. The interrater reliability between these results was investigated using Fleiss multi rater Kappa with overall agreement and reported with Landis and Koch's grading system (poor, slight, fair, moderate, substantial, and almost perfect). RESULTS: Out of 215 surgical patients in the home setting, 164 (76.7%) patients completed the self-reported screening tool. A total of 123 (57.2%) patients were screened in-hospital, of whom 96 (44.7%) prior to surgery and 96 (44.7%) were screened both at hospital (pre- and post-surgery) and at home. Self-screening at home improved malnutrition screening participation by 71.9% compared to hospital screening prior to surgery (165 (76.7%) and 96 (44.7%), respectively) and by 34.1% compared to pre- and postoperative in-hospital screening, 165 (76.7%) and 123 (57.2%), respectively). The degree of agreement between patients identified to be "at risk of malnutrition" by the self-reported screening tool and healthcare professionals was poor (κ = - 0.04 (95% CI: -0.24, 0.16), however, the degrees of agreement between the patients and healthcare professionals answers to the initial NRS 2002 questions "low BMI", "weight loss", and "reduced food intake" were almost perfect (κ = 1.00 (95% CI: 0,82, 1.18)), moderate (κ = 0.55 (95% CI: 0.34, 0.75)), and slight (κ = 0.08 (95% CI: - 0.10, 0.25) respectively. CONCLUSIONS: Three out of four patients completed the self-screening form and the preoperative screening rate improved with 70%. Preoperatively self-screening in a home setting may be a feasible method to increase the number of elective surgical patients screened for risk of malnutrition. TRIAL REGISTRATION: The trial is registered in ClinicalTrials.gov ID NCT03105713. https://classic.clinicaltrials.gov/ct2/show/NCT03105713.

Malnutrition as a prognostic factor for 2-year mortality in hospitalized patients in Norway: A matched cohort study.

BACKGROUND: Risk of malnutrition and malnutrition have been previously associated with increased risk of mortality. It remains unclear, however, whether the severity of malnutrition differentiates in association with all-cause mortality. The aim was to assess the association between being at risk of malnutrition or being diagnosed with malnutrition according to the diagnostic assessment of the Global Leadership Initiative on Malnutrition (GLIM) with all-cause mortality during a 2-year follow-up in hospitalized patients. METHODS: A matched cohort study was conducted in hospitalized patients (excluding cancer, intensive care, and transmissible infections) at a university hospital in Bergen, Norway. All patients underwent nutrition screening with the Nutritional Risk Screening 2002 and a further nutrition assessment using the GLIM criteria. All-cause mortality was estimated from the Norwegian death registry after 2 years, and risk factors were calculated by Cox regression analysis. RESULTS: Among 326 patients included, 55 patients died within 2 years (17% mortality rate). Risk of malnutrition was associated with increased all-cause mortality, which disappeared after adjustment for age and sex. Malnutrition was associated with an increased risk of all-cause mortality at 2 years also after adjustment for age and sex and, additionally, for further comorbidities (hazard ratio = 2.50; 95% CI, 1.41-4.42). When analyzed separately only severe malnutrition was associated with mortality (hazard ratio = 2.73; 95% CI, 1.44-5.15). CONCLUSION: The findings highlight a strong association between inpatients with severe malnutrition, defined by the GLIM criteria, and an increased risk of all-cause mortality within a 2-year follow-up.

Effect of dietary interventions on nutritional status in patients with rheumatoid arthritis and spondyloarthritis - A systematic review and meta-analysis.

BACKGROUND & AIM: Patients with rheumatoid arthritis (RA) and spondyloarthritis (SpA) have an increased risk of developing altered body composition, such as low muscle mass, and an increased risk of developing cardiovascular diseases (CVD). Thus, investigating how to improve body composition and CVD risk factors is a relevant topic to improve management of RA and SpA. The aim of this study was to identify dietary interventions that can improve body composition, as well as reduce CVD risk factors in RA and SpA. METHODS: We searched the databases Medline, Embase and Cochrane. Duplicates were removed using Endnote and records were screened through Rayyan. The primary outcomes were muscle mass (kg) and fat mass (kg). Secondary outcomes were body weight (kg), body mass index (BMI: kg/m2), waist circumference (cm) and lipid profile (total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, mmol/L). RESULTS: A total of 4965 articles were identified, and 17 articles were included in this review, of which 15 were suitable for meta-analysis. We found a reduction in TC and LDL-C, (Mean difference, [95%CI]: -0.36, [-0.63, -0.10], I2 = 43%, and -0.20, [-0.35, -0.05], I2 = 0% respectively). Otherwise, no other significant effect was seen in either primary or secondary outcomes. The evidence was graded as moderate for TC and low for LDL-C. CONCLUSION: Dietary interventions might reduce the levels of blood lipids, and consequently, the risk of cardiovascular diseases. However, body composition did not change significantly after a 2-4 month dietary intervention. Both short intervention period and lack of reliable methods to assess body composition are possible explanations for this finding. Further studies of longer duration are needed.

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.

Comparison of nutritional risk screening with NRS2002 and the GLIM diagnostic criteria for malnutrition in hospitalized patients.

Nutritional risk screening, to identify patients at risk of malnutrition, is the first step in the prevention and treatment of malnutrition in hospitalized patients, and should be followed by a thorough nutritional assessment resulting in a diagnosis of malnutrition and subsequent treatment. In 2019, a consensus on criteria has been suggested for the diagnosis of malnutrition by the Global Leadership Initiative for Malnutrition (GLIM). This study investigates the diagnosis of malnutrition in hospitalized patients using nutritional risk screening and the diagnostic assessment suggested by GLIM. Hospitalized patients (excluding cancer, intensive care, and transmissible infections) who underwent nutritional risk screening (by NRS2002) were included. Nutritional risk screening was followed by anthropometric measurements including measurement of muscle mass, assessment of dietary intake and measurement of serum C-reactive protein (CRP) for inflammation in all patients. Malnutrition was diagnosed according to the GLIM-criteria. In total, 328 patients (median age 71 years, 47% women, median length of stay 7 days) were included. Nutritional risk screening identified 143 patients as at risk of malnutrition, while GLIM criteria led to a diagnosis of malnutrition in 114 patients. Of these 114 patients, 77 were also identified as at risk of malnutrition by NRS2002, while 37 patients were not identified by NRS2002. Malnutrition was evident in fewer patients than at risk of malnutrition, as expected. However, a number of patients were malnourished who were not identified by the screening procedure. More studies should investigate the importance of inflammation and reduced muscle mass, which is the main difference between nutritional risk screening and GLIM diagnostic assessment.

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 malnutrition¼ 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 malnutrition¼, 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 malnutrition¼. Fewer surgical patients (21.2%) were «at risk of malnutrition¼, 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 malnutrition¼ from 2008 to 2018. The percentage of patients «at risk of malnutrition¼ 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 malnutrition¼ from 2008 to 2018. However, more patients «at risk of malnutrition¼, 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.

Nutritional treatment is associated with longer survival in patients with pancreatic disease and concomitant risk of malnutrition.

BACKGROUND: Pancreatic diseases involve complex nutritional challenges. Despite this, conflicting evidence exists regarding the clinical relevance of detecting the risk of malnutrition and implementing systematic nutrition support for these patients. Thus, our aims were to investigate whether screening for malnutrition risk and initiating nutrition support are predictive of mortality for hospitalized patients with pancreatic diseases. DESIGN: From 2008 to 2018, 34 prevalence surveys of nutrition were conducted at Haukeland University Hospital (HUH), Norway. Risk of malnutrition was defined by a score of ≥3 in Nutritional Risk Screening 2002 (NRS 2002). Primary outcomes included overall, one-year, and one-month mortality, and were compared according to malnutrition risk and nutrition support for adult patients with ICD-10 codes of K85: acute pancreatitis, K86: other diseases of pancreas, and C25: malignant neoplasm of pancreas. Length of hospital stay (LOS) was included as a secondary outcome. RESULTS: Of the 283 patients investigated, risk of malnutrition was present in 61.5%. Risk of malnutrition was associated with higher overall mortality (Hazard Ratio (HR) = 1.67, 95% confidence interval (CI): 1.2-2.4, P = 0.003) and one-year mortality (HR = 1.89, 95% CI: 1.2-2.9, P = 0.004) compared to patients not at risk. Not receiving nutrition support for at-risk patients was associated with higher overall mortality (HR = 1.60, 95% CI: 1.1-2.4, P = 0.019) and one-year mortality (HR = 1.64, 95% CI: 1.04-2.6, P = 0.034) compared to patients at risk who received nutrition support. Patients at risk of malnutrition had increased LOS (20.5 nights vs 15.2 nights, P = 0.044) compared to patients not at risk of malnutrition. CONCLUSION: This study of hospitalized patients with pancreatic disease suggests that risk of malnutrition may be associated with higher mortality rates, whereas nutrition support may decrease mortality rates. CLINICAL TRIAL REGISTRY: Not registered.

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.

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.

A positive association between nutritional risk and the incidence of surgical site infections: A hospital-based register study.

Surgical site infections (SSI) are amongst the most common health care-associated infections and have adverse effects for patient health and for hospital resources. Although surgery guidelines recognize poor nutritional status to be a risk factor for SSI, they do not tell how to identify this condition. The screening tool Nutritional Risk Screening 2002 is commonly used at hospitals to identify patients at nutritional risk. We investigated the association between nutritional risk and the incidence of SSI among 1194 surgical patients at Haukeland University Hospital (Bergen, Norway). This current study combines data from two mandatory hospital-based registers: a) the incidence of SSI within 30 days after surgery, and b) the point-prevalence of patients at nutritional risk. Patients with more than 30 days between surgery and nutritional risk screening were excluded. Associations were assessed using logistic regression, and the adjusted odds ratio included age (continuous), gender (male/female), type of surgery (acute/elective) and score from The American Society of Anesthesiologists Physical Status Classification System. There was a significant higher incidence of SSI among patients at nutritional risk (11.8%), as compared to those who were not (7.0%) (p = 0.047). Moreover, the incidence of SSI was positively associated with the prevalence of nutritional risk in both simple (OR 1.76 (95% CI: 1.04, 2.98)) and adjusted (OR 1.81 (95% CI: 1.04, 3.16)) models. Answering "yes" to the screening questions regarding reduced dietary intake and weight loss was significantly associated with the incidence of SSI (respectively OR 2.66 (95% CI: 1.59, 4.45) and OR 2.15 (95% CI: 1.23, 3.76)). In conclusion, we demonstrate SSI to occur more often among patients at nutritional risk as compared to those who are not at nutritional risk. Future studies should investigate interventions to prevent both SSI and nutritional risk among surgical patients.

Norwegian PUQE (Pregnancy-Unique Quantification of Emesis and nausea) identifies patients with hyperemesis gravidarum and poor nutritional intake: a prospective cohort validation study.

OBJECTIVE: The English questionnaire Pregnancy-Unique Quantification of Emesis and nausea (PUQE) identifies women with severe Hyperemesis Gravidarum. Our aim was to investigate whether scores from the translated Norwegian version; SUKK (SvangerskapsUtløst Kvalme Kvantifisering) was associated with severity of hyperemesis and nutritional intake. DESIGN: A prospective cohort validation study. SETTING: Hospital cohort of Hyperemesis Gravidarum (HG) patients from western Norway and healthy pregnant women from Bergen, Norway. SAMPLE: 38 women hospitalized due to HG and 31 healthy pregnant controls attending routine antenatal check-up at health centers. METHODS: Data were collected May 2013-January 2014. The study participants answered the Norwegian PUQE-questionnaire (scores ranging from 3 to 15) and registered prospectively 24-hours nutritional intake by a food list form. MAIN OUTCOME MEASURES: Differences of PUQE-scores, QOL-score and nutritional intake between hyperemesis patients and controls. RESULTS: Hyperemesis patients had shorter gestational age compared to controls (median 9.7 weeks; 95% CI 8.6-10.6 versus 11.9; 95% CI 10.1-12.9, p=0.004), and larger weight-change from pre-pregnant weight (loss of median 3 kg; 95% CI 3-4 versus gain of 2 kg; 95% CI 0.5-2, p<0.001) otherwise groups were similar regarding pre-pregnant BMI, age, gravidity, and inclusion weight. Compared to controls, hyperemesis patients had significant higher PUQE-score (median 13; 95% CI 11-14 vs. 7; 95% CI 4-8), lower QOL (median score 3; 95% CI 2-4 vs. 6; 95% CI 4.5-8) and lower nutritional intake (energy intake median 990 kcal/24 hours; 95% CI 709-1233 vs. 1652; 95% CI 1558-1880 all p<0.001). PUQE-score was inversely correlated to nutritional intake (-0.5, p<0.001). At discharge PUQE-score had fallen to median 6 (95% CI 5-8) and QOL score risen to 7 (95% CI 6-8) in the HG group, (both p<0.001 compared to admission values). CONCLUSION: PUQE-scoring has been validated as a robust indicator of severe hyperemesis gravidarum and insufficient nutritional intake in a Norwegian setting.

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 <40 years and 35% of patients with emergency admissions compared to 19% with elective admissions. Related to the tool components, nutritional risk was most common in patients with low BMI (<20.5 kg/m(2)) (95%) and/or high comorbidity (>7 diagnoses) (45%). However it was also high in patients with BMI ≥25 kg/m(2) (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.

The nutritional strategy: four questions predict morbidity, mortality and health care costs.

BACKGROUND: Nutritional care for hospital in-patients is potentially important but challenging. OBJECTIVE: To investigate the association between nutritional status and clinical outcomes. METHODS: Eight prevalence surveys were performed at Haukeland University Hospital, Norway, during 2008-2009. In total 3279 patients were classified as being at nutritional risk or not according to the Nutritional Risk Screening (NRS 2002) tool. The initial four questions of NRS 2002 assess dietary intake, weight loss, body mass index (BMI) and illness severity. RESULTS: The overall prevalence of nutritional risk was 29%. Adjusted mean days for hospitalisation was 8.3 days for patients at nutritional risk and 5.0 days for patients not at risk (p < 0.001). In adjusted models, patients at nutritional risk had increased one-year mortality (OR 4.07, 95% CI 2.90-5.70), morbidity (OR 1.59, 95% CI 1.18-2.13), and were 1.24 (95% CI 1.16-1.32) times more likely to have had a new admission during the three previous years and the one subsequent year, compared to patients not at risk. A 'positive' response to the initial four questions was associated with increased risk of morbidity and mortality. Patients with a reduced dietary intake during the last weeks had OR 1.72 (95% CI 1.03-2.85) for one-year mortality. Patients with a positive answer on all the initial four questions had ten times increased risk for mortality the following year, OR 13.0 (95% CI 4.52-37.6). CONCLUSION: The four initial questions of the NRS 2002 robustly identify nutritional risk and were strong predictors of hospitalisation, morbidity and most importantly mortality among hospitalised patients. Thus, these simpler and short questions are robust indicators for subsequent poor outcomes.