The association of weight loss with one-year mortality in hospital patients, stratified by BMI and FFMI subgroups.

BACKGROUND: The European Society for Clinical Nutrition and Metabolism (ESPEN) has recently published consensus-based criteria for the diagnosis of malnutrition; in subjects identified at nutritional risk the diagnosis is confirmed by either BMI <18.5 kg/m2 or weight loss in combination with low BMI or low FFMI. Concerns have been raised whether this definition correctly classifies malnutrition in patients with normal weight or overweight and concomitant weight loss. Therefore, the aim of this research is to assess the association between weight loss and one-year mortality in hospitalized patients, stratified by BMI and FFMI subgroups. METHODS: This prospective study included 769 patients admitted to the VU University Medical Center. Critical weight loss (CWL) was defined as >5% weight loss in the previous month or >10% weight loss in the previous six months. The association between CWL and one-year mortality was analyzed with a priori stratification by BMI cut-off values (

The new ESPEN diagnostic criteria for malnutrition predict overall survival in hospitalised patients.

BACKGROUND: In 2015 the European Society for Clinical Nutrition and Metabolism (ESPEN) presented new consensus criteria for the diagnosis of malnutrition. Whereas most previous definitions were based on involuntary weight loss and/or a low BMI, the ESPEN definition added Fat Free Mass Index (FFMI) to the set of criteria. AIM: To study the predictive value of the new ESPEN diagnostic criteria for malnutrition on survival, with specific focus on the additional value of FFMI. METHODS: Included were 335 hospitalized adult patients of the VU University Medical Center Amsterdam (60% female, age 58 ± 18 y). Three sets of criteria for malnutrition were used to study the predictive value for survival: Dutch definition for malnutrition, ESPEN diagnostic criteria for malnutrition and ESPEN diagnostic criteria for malnutrition without FFMI criterion. The association between malnutrition and three-months and one-year overall survival was analyzed by log rank tests and Cox regression. In multivariate analyses, adjustments were made for gender, age, care complexity and length of stay. RESULTS: Ninety patients (27%) were classified as malnourished by any of the sets of criteria; malnourished patients had significant lower survival rates than non-malnourished patients at three months (84% vs 94%; p = 0.01) and one year (76% vs 87%; p = 0.02). After adjustments, malnutrition remained significantly associated with three-months survival for the Dutch definition for malnutrition (HR:2.25, p = 0.04) and the ESPEN diagnostic criteria for malnutrition (HR:2.76, p = 0.02). Malnutrition remained significantly associated with one-year survival for the ESPEN diagnostic criteria for malnutrition (HR:2.17, p < 0.02) and the ESPEN diagnostic criteria for malnutrition without FFMI (HR:2.66, p < 0.01). CONCLUSION: The new ESPEN definition for malnutrition is predictive for both three-months and one-year survival in a general hospital population, whereas definitions without FFMI are predictive for either three-months or one year survival.

Predictors for achieving adequate protein and energy intake in nursing home rehabilitation patients.

BACKGROUND: Adequate energy and protein intake could be essential for contributing significantly to the rehabilitations process. Data on the actual nutritional intake of older nursing home rehabilitation patients have not yet been investigated. AIMS: To investigate the nutritional intake and predictors for achieving protein and energy requirements on the 14th day of admission in nursing home rehabilitation patients. METHODS: Fifty-nine patients aged 65+ years newly admitted to nursing home rehabilitation wards were included. Data on potential variables were collected on admission. On the fourteenth day nutritional intake was assessed. Intake was considered 'adequate' if patients had achieved ≥ 1.2 g of protein/kg bodyweight and ≥ 85% of their energy needs according to Harris and Benedict + 30%. Multiple logistic regression analyses were performed to select predictors for adequate intake. RESULTS: Protein and energy intake was assessed in 79 patients [67% female, mean age 82 ± (SD) 8 years, BMI 25 ± 6 kg/m2]. Mean energy intake was 1677 kcal (± 433) and mean protein intake was 68 g (± 20). Fourteen patients (18%) achieved an adequate protein and energy intake. Predictors for adequate intake were use of sip/tube feeding (OR = 7.7; 95% CI = 1.35-44.21), BMI (0.68; 0.53-0.87) and nausea (8.59; 1.42-52.01). CONCLUSION: Only 18% of older nursing home rehabilitation patients had an adequate protein and energy intake at 14 days after admission. Patients with higher BMI were less likely, while those using sip/tube feeding or feeling nauseous were more likely to achieve an adequate protein and energy intake.

Undernutrition in nursing home rehabilitation patients.

OBJECTIVE: To examine the prevalence of undernutrition, received dietetic treatment and self-perception of nutritional status in older patients admitted to Dutch nursing home rehabilitation wards. METHODS: Between December 2012-February 2014, we included 190 patients (≥65 y) admitted to seven nursing home rehabilitation wards. Nutritional status in the first week of admission was characterized as: severely undernourished (>10% unintentional weight loss in the past six months and/or >5% unintentional weight loss in the past month and/or BMI < 20 kg/m2), moderately undernourished (5-10% unintentional weight loss in the past 6 months and/or BMI 20-22 kg/m2), well-nourished (<5% unintentional weight loss in the past 6 months and BMI 22-28 kg/m2) and overweight (BMI>28 kg/m2). Primary diagnosis was categorized as: trauma, elective orthopaedics, stroke and other. Perceived nutritional status was determined with the question: 'Do you currently consider yourself undernourished?' (yes/no). Information regarding dietetic treatment was obtained from medical records. RESULTS: A complete dataset was obtained from 179 patients (70% female, age 81 ± 8 y). 26% of the patients was found to be severely undernourished and 14% moderately undernourished. Prevalence of undernutrition did not differ by sex or age. Of all undernourished patients, 56% had been treated by a dietitian. Only one out of five of undernourished patients considered themselves undernourished. Elective orthopaedics patients had the lowest prevalence of undernutrition (19%) while patients categorised as 'other' had the highest prevalence (51%). CONCLUSION: More than one in three older patients in Dutch nursing home rehabilitation wards are moderately to severely undernourished. Out of these patients the majority does not consider themselves undernourished and almost half has not received dietetic treatment. More attention to undernutrition in nursing home rehabilitation patients seems necessary.

A critical appraisal of nutritional intervention studies in malnourished, community dwelling older persons.

BACKGROUND & AIMS: With the rapidly increasing number of malnourished older persons in the community, this review aims to summarize the effects of nutritional intervention studies for this target group. METHODS: Based on 2 previous reviews (2009, 2011) an update of the literature was performed. Selected were higher quality studies which included malnourished community dwelling older adults who received dietetic counselling and/or oral nutritional supplements. RESULTS: Ten studies were included. Six studies showed (trends towards) weight gain. Meta-analysis showed a modest effect of the intervention on weight gain, standardized mean difference 0.210 kg (95% CI 0.03-0.40). Effects on other relevant functional and clinical outcomes were inconsistent. Studies were hampered by low sample sizes, low adherence to the interventions, and participants not meeting nutritional requirements. CONCLUSION: Currently, nutritional intervention studies for malnourished community dwelling older adults show limited effects, which may be caused by methodological shortcomings and participants not meeting treatment goals. High quality studies are eagerly awaited to be able to identify (sub)groups of older persons who are most likely to benefit from nutritional support.

The prevalence of malnutrition according to the new ESPEN definition in four diverse populations.

BACKGROUND & AIMS: Consensus on the definition of malnutrition has not yet been reached. Recently, The European Society for Clinical Nutrition and Metabolism (ESPEN) proposed a consensus definition of malnutrition. The aim of the present study was to describe the prevalence of malnutrition according to the ESPEN definition in four diverse populations. METHODS: In total, 349 acutely ill middle-aged patients, 135 geriatric outpatients, 306 healthy old individuals and 179 healthy young individuals were included in the study. Subjects were screened for risk of malnutrition using the SNAQ. The ESPEN definition of malnutrition, i.e. low BMI (< 18.5 kg/m(2)) or a combination of unintentional weight loss and low FFMI or low BMI was applied to all subjects. RESULTS: Screening identified 0, 0.5, 10 and 30% of the healthy young, the healthy old, the geriatric outpatients and the acutely ill middle-aged patients as being at risk of malnutrition. The prevalence of malnutrition ranged from 0% in the healthy young, 0.5% in healthy old individuals, 6% in the geriatric outpatients to 14% in the acutely ill middle-aged patients. Prevalence of low FFMI was observed in all four populations (14-33%), but concurred less frequently with weight loss (0-13%). CONCLUSIONS: Using the ESPEN definition, 0%-14% malnutrition was found in the diverse populations. Further work is needed to fully address the validity of a two-step approach, including risk assessment as an initial step in screening and defining malnutrition. Furthermore, assessing the predictive validity of the ESPEN definition is needed.

The view of European experts regarding health economics for medical nutrition in disease-related malnutrition.

Health-care systems are currently facing tremendous budget constraints resulting in growing pressure on decision makers and health-care providers to obtain the maximum possible health benefits of the resources available. Choices have to be made, and health economics can help in allocating limited health-care resources among unlimited wants and needs. Attempts to achieve cost reductions often focus on severe pathologies and chronic diseases as they commonly represent high health-care expenditures. In this context, awareness of the considerable financial burden caused by disease-related malnutrition (DRM) is lacking. Possibilities of reducing costs by optimising the management of DRM through medical nutrition will mostly not even be taken into account. During a European expert meeting, the total evaluation of medical nutrition was viewed and discussed. The aim of this meeting was to gain an experts' outline of the key issues relating to the health economic assessment of the use of medical nutrition. This article provides a summary of the observations per discussed item and describes the next steps suggested.

Critical weight loss is a major prognostic indicator for disease-specific survival in patients with head and neck cancer receiving radiotherapy.

BACKGROUND: Pre-treatment weight loss (WL) is a prognostic indicator for overall survival (OS) in head and neck cancer (HNC) patients. This study investigates the association between WL before or during radiotherapy and disease-specific survival (DSS) in HNC patients. METHODS: In 1340 newly diagnosed HNC patients, weight change was collected before and during (adjuvant) radiotherapy with curative intent. Critical WL during radiotherapy was defined as >5% WL during radiotherapy or >7.5% WL until week 12. Differences in 5-year OS and DSS between WL groups were analysed by Cox's regression with adjustments for important socio-demographic and tumour-related confounders. RESULTS: Before radiotherapy, 70% of patients had no WL, 16% had ≤5% WL, 9% had >5-10% WL, and 5% had >10% WL. Five-year OS and DSS rates for these groups were 71%, 59%, 47%, and 42% (P<0.001), and 86%, 86%, 81%, and 71%, respectively (P<0.001). After adjustment for potential confounders, >10% WL before radiotherapy remained significantly associated with a worse OS (HR 1.7; 95% CI 1.2-2.5; P=0.002) and DSS (HR 2.1; 95% CI 1.2-3.5; P=0.007).The 5-year OS and DSS rates for patients with critical WL during radiotherapy were 62% and 82%, compared with 70% and 89% for patients without critical WL (P=0.01; P=0.001). After adjustment, critical WL during radiotherapy remained significantly associated with a worse DSS (HR 1.7; 95% CI 1.2-2.4; P=0.004). CONCLUSION: Weight loss both before and during radiotherapy are important prognostic indicators for 5-year DSS in HNC patients. Randomised studies into the prognostic effect of nutritional intervention are needed.

Validity of nutritional screening with MUST and SNAQ in hospital outpatients.

BACKGROUND/OBJECTIVES: The majority of hospital outpatients with undernutrition is unrecognized, and therefore untreated. There is a need for an easy and valid screening tool to detect undernutrition in this setting. The aim of this study was to determine the diagnostic accuracy of the MUST (Malnutrition Universal Screening Tool) and SNAQ (Short Nutritional Assessment Questionnaire) tools for undernutrition screening in hospital outpatients. METHODS: In a large multicenter-hospital-outpatient population, patients were classified as: severely undernourished (body mass index (BMI) <18.5 (<65 years) or <20 ( ≥ 65 years) and/or unintentional weight loss >5% in the last month or >10% in the last 6 months), moderately undernourished (BMI 18.5-20 (<65 years) or 20-22 ( ≥ 65 years) and/or 5-10% unintentional weight loss in the last 6 months) or not undernourished. Diagnostic accuracy of the screening tools versus the reference method was expressed as sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV). RESULTS: Out of the 2236 outpatients, 6% were severely and 7% were moderately undernourished according to the reference method. MUST and SNAQ identified 9% and 3% as severely undernourished, respectively. MUST had a low PPV (Se=75, Sp=95, PPV=43, NPV=98), whereas SNAQ had a low Se (Se=43, Sp=99, PPV=78, NPV=96). CONCLUSIONS: The validity of MUST and SNAQ is insufficient for hospital outpatients. While SNAQ identifies too few patients as undernourished, MUST identifies too many patients as undernourished. We advise to measure body weight, height and weight loss, in order to define undernutrition in hospital outpatients.

The SNAQ(RC), an easy traffic light system as a first step in the recognition of undernutrition in residential care.

OBJECTIVE: Development and validation of a quick and easy screening tool for the early detection of undernourished residents in nursing homes and residential homes. DESIGN: Multi-center, cross sectional observational study. SETTING: Nursing homes and residential homes. PARTICIPANTS: The screening tool was developed in a total of 308 residents (development sample; sample A) and cross validated in a new sample of 720 residents (validation sample) consisting of 476 nursing home residents (Sample B1) and 244 residential home residents (sample B2). MEASUREMENTS: Patients were defined severely undernourished when they met at least one of the following criteria: BMI or= 5% unintentional weight loss in the past month and/or >or= 10% unintentional weight loss in the past 6 months. Patients were defined as moderately undernourished if they met the following criteria: BMI 20.1-22 kg/m2 and/or 5-10% unintentional weight loss in the past six months. The most predictive questions (originally derived from previously developed screening instruments) of undernourishment were selected in sample A and cross validated in sample B. In a second stage BMI was added to the SNAQRC in sample B. The diagnostic accuracy of the screening tool in the development and validation samples was expressed in sensitivity, specificity, and the negative and positive predictive value. RESULTS: The four most predictive questions for undernutrition related to: unintentional weight loss more than 6 kg during the past 6 months and more than 3 kg in the past month, capability of eating and drinking with help, and decreased appetite during the past month. The diagnostic accuracy of these questions alone was insufficient (Se=45%, Sp=87%, PPV=50% and NPV=84%). However, combining the questions with measured BMI sufficiently improved the diagnostic accuracy (Se=87%, Sp=82%, PPV=59% and NPV=95%). CONCLUSION: Early detection of undernourished nursing- and residential home residents is possible using four screening questions and measured BMI.

Screening malnutrition in hospital outpatients. Can the SNAQ malnutrition screening tool also be applied to this population?

BACKGROUND & AIMS: It is known from earlier studies that only 15% of the malnourished hospital outpatient population is recognized and receives nutritional treatment. To increase this number, a quick and easy malnutrition screening tool would be helpful. Because such a tool is lacking, we developed one by using the SNAQ (Short Nutritional Assessment Questionnaire) as a basis. The aim of this study was to develop a quick and easy malnutrition screening tool and to measure its diagnostic accuracy in malnourished hospital outpatients. METHODS: First, an optimal set of questions was selected for the preoperative outpatient population. Secondly, the diagnostic accuracy for the preoperative outpatients was determined (979 patients) and finally, the diagnostic accuracy for general hospital outpatients was established (705 patients). RESULTS: The three original SNAQ questions proved to be the best set of questions for the outpatient population as well. In the preoperative and general outpatient population the diagnostic accuracy resulted respectively in a sensitivity of 53% and 67%, a specificity of 97% and 98%, a positive predictive value of 69% and 72% and a negative predictive value of 94% and 97%. CONCLUSIONS: With an acceptable diagnostic accuracy it may be concluded that the original SNAQ malnutrition screening tool is valid for the hospital outpatient population.

Are malnourished patients complex patients? Health status and care complexity of malnourished patients detected by the Short Nutritional Assessment Questionnaire (SNAQ).

BACKGROUND: This article describes the characteristics of patients identified as malnourished using the Short Nutritional Assessment Questionnaire (SNAQ) in terms of health status (quality of life, functional capacity, and body composition) and care complexity. We expected that by using the quick and easy SNAQ method of screening on malnutrition, inferences could be made about general health status and care complexity. This information can be used for optimal multi-disciplinary treatment of the malnourished patient. METHODS: The research population consisted of a group of 588 patients admitted to internal medicine and surgery wards of the VU university medical center. Patients with a SNAQ score of at least 3 points were considered malnourished. The SNAQ score was compared to the health status, which was determined by serum albumin, hand grip strength, quality of life, body composition, and estimated care complexity. RESULTS: At admission, 172 patients (29%) had a SNAQ score of at least 3 points. These patients had a significantly poorer quality of life, poorer physical functioning, a lower fat free mass index, and higher care complexity. CONCLUSION: These findings confirm our assumption that a considerable proportion of malnourished patients should be considered as complex patients and that malnutrition is an important aspect and indicator of overall health status of the patients. The SNAQ is a simple malnutrition screening tool, applicable in the current complex hospital situation, to identify these complex, malnourished patients.

Development and validation of a hospital screening tool for malnutrition: the short nutritional assessment questionnaire (SNAQ).

OBJECTIVE: For the early detection and treatment of malnourished hospital patients no valid screening instrument for the Dutch language exists. Calculation of percentage weight loss and body mass index (BMI) by the nurse at admission to the hospital appeared to be not feasible. Therefore, the short, nutritional assessment questionnaire (SNAQ), was developed. RESEARCH, DESIGN AND METHODS: Two hundred and ninety one patients on the mixed internal and surgery/oncology wards of the VU University medical center were screened on nutritional status and classified as well nourished (<5% weight loss in the last 6 months and BMI>18.5), moderately malnourished (5-10% weight loss in the last 6 months and BMI>18.5) or severely malnourished (>10% weight loss in the last 6 months or >5% in the last month or BMI<18.5). All patients were asked 26 questions related to eating and drinking difficulties, defecation, condition and pain. Odds ratio, binary and multinomial logistic regression were used to determine the set of questions that best predicts the nutritional status. Based on the regression coefficient a score was composed to detect moderately (2 points) and severely (3 points) malnourished patients. The validity, the nurse-nurse reproducibility and nurse-dietitian reproducibility was tested in another but similar population of 297 patients. RESULTS: The questions 'Did you lose weight unintentionally?'. 'Did you experience a decreased appetite over the last month?' and 'Did you use supplemental drinks or tube feeding over the last month?' were most predictive of malnutrition. The instrument proved to be valid and reproducible. CONCLUSION: SNAQ is an easy, short, valid and reproducible questionnaire for early detection of hospital malnutrition.

Why do diabetic patients not attend appointments with their dietitian?

PURPOSE: Determining the prevalence of and possible reasons for nonattendance of diabetic nutritional care clinics. METHODS: Data were collected by means of a telephone survey and a review of patient records among 293 (166 attendees and 127 nonattendees) patients undergoing outpatient treatment at a university hospital. The t-tests, chi-square tests and logistic regression analysis were used to identify potential determinants of nonattendance. The theoretical framework was primarily based on the Health Belief Model. RESULTS: In univariate analysis, nonattendance at the clinic was associated with a number of factors such as not visiting other care givers, risk perceptions, body-mass index, self-rated health, health locus of control, satisfaction with the dietitian, feelings of obligation to attend, and beliefs about the effectiveness of the treatment. In multivariate analysis only health locus of control and obligation to attend the visit were significant predictors of attendance. A significant number of respondents further reported that they perceived their visits to the dietitian to be of little use. CONCLUSION: One in three diabetic patients undergoing outpatient treatment skipped one or more visits to their dietitian. Patient education to improve attendance should focus primarily on convincing patients that they can contribute to their own health, and may stress the obligation the patients have when making an appointment with the dietitian.

Screening of nutritional status in The Netherlands.

BACKGROUND AND AIMS: In 2001, the Dutch Dietetic Association conducted a national screening on malnutrition. The goal of this screening was to determine the prevalence of disease-related malnutrition in The Netherlands in all fields of medical care and to investigate the involvement of the dietitian in the treatment of malnutrition. METHODS: Eight thousand five hundred and twenty nine patients were screened of which data of 7606 patients could be analysed. Eighty one per cent (6150) of the patients were hospital patients. Eleven per cent (808) of the patients lived in a nursing home. Seven per cent (533) of the patients were home-care patients, who were measured at home or at the general practitioner's office. The origin of 115 patients (2%) was not registered. Age, height, weight, unintentional weight loss, kind of illness and intervention by a dietitian were registered. Malnutrition was defined as >10% unintentional weight loss during the past 6 months and risk of malnutrition was defined as 5-10% unintentional weight loss during the past 6 months. RESULTS: Twelve per cent (884) of all patients appeared to be malnourished. Thirteen per cent (962) were at risk of malnutrition and 75% (5760) were well nourished. Fifty four per cent of the malnourished patients were referred to a dietitian. Oncological disease was more associated with malnutrition than non-oncological disease (in particular in the head and neck, lung and intestinal areas). Also, non-oncological gastro-intestinal and lung disease patients were often categorised as malnourished. Elderly patients (>75 years) were more at risk of malnutrition. BMI and unintentional weight loss did not correlate well. CONCLUSION: In this national survey conducted by dietitians, including a convenience sample of mainly institutionalised patients, approximately 25% of patients in all medical fields were categorised as moderately or severely malnourished. About half of these patients were seen by a dietitian.