H.M. Kruizenga

Comparison of five malnutrition screening tools in one hospital inpatient sample

AIMS AND OBJECTIVESnThe purpose of this study is to compare five commonly used malnutrition screening tools against an acknowledged definition of malnutrition in one hospital inpatient sample.nnnBACKGROUNDnEarly identification and intervention of malnutrition in hospital patients may prevent later complications. Several screening tools have reported their diagnostic accuracy, but the criterion validity of these tools is unknown.nnnDESIGNnA cross sectional study.nnnMETHODSnWe compared quick-and easy screening tools [Malnutrition Screening Tool (MST), Short Nutritional Assessment Questionnaire (SNAQ) and Mini-Nutritional Assessment Short Form (MNA-SF)] and more comprehensive malnutrition screening tools [Malnutrition Universal Screening Tool (MUST) and Nutritional Risk Screening 2002 (NRS-2002)] to an acknowledged definition of malnutrition (including low Body Mass Index and unintentional weight loss) in one sample of 275 adult hospital inpatients. Sensitivity, specificity, positive predictive value and negative predictive value were determined. A sensitivity and specificity of ≥ 70% was set as a prerequisite for adequate performance of a screening tool.nnnRESULTSnAccording to the acknowledged definition of malnutrition 5% of patients were at moderate risk of malnutrition and 25% were at severe risk. The comprehensive malnutrition screening tools (MUST, NRS-2002) and the quick-and-easy malnutrition screening tools (MST and SNAQ) showed sensitivities and specificities of ≥70%. However, 47% of data were missing on the MUST questionnaire and 41% were missing on MNA-SF. The MNA-SF showed excellent sensitivity, but poor specificity for the older subpopulation.nnnCONCLUSIONSnThe quick-and-easy malnutrition screening tools (MST and SNAQ) are suitable for use in an hospital inpatient setting. They performed as well as the comprehensive malnutrition screening tools (MUST and NRS-2002) on criterion validity. However, MUST was found to be less applicable due to the high rate of missing values. The MNA-SF appeared to be not useful because of it low specificity.nnnRELEVANCE TO CLINICAL PRACTICEnInsight in what is the most valid and practical nutritional screening tool to use in hospital practice will increase effective recognition and treatment of malnutrition.

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

BACKGROUND & AIMSnConsensus 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.nnnMETHODSnIn 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 (<xa018.5xa0kg/m(2)) or a combination of unintentional weight loss and low FFMI or low BMI was applied to all subjects.nnnRESULTSnScreening 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%).nnnCONCLUSIONSnUsing 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.

Fructo-oligosaccharides and fibre in enteral nutrition has a beneficial influence on microbiota and gastrointestinal quality of life

Objective. Intestinal microbiota is important in health and disease. The aim of this study was to evaluate the effect of fructo-oligosaccharides (FOS) and fibre-enriched tube feeding on quality of life and intestinal microbiota (faecal Bifidobacteria). Material and methods. Nineteen out of 59 home-living, tube-feeding-dependent, adult patients and matched healthy controls were included in this randomized, double-blind study. After a washout period, patients received either no residue tube feeding (non-FOS group) or FOS and fibre-enriched tube feeding (FOS group). Quality of life as defined by the Gastrointestinal Quality of Life Index (GIQLI) and quantification of faecal Bifidobacteria were determined. Results. At baseline, GIQLI scores in controls and patients were 88±12 and 67±14, respectively (p=0.001). Following 6 weeks’ intervention, GIQLI scores remained stable (65±14 versus 67±17) in the FOS group, whereas the non-FOS group values decreased (68±17 versus 64±19). Baseline faecal samples contained 2.1×107±3.5×107 and 2.1×106±5.6×106Bifidobacteria (p=0.002) in controls and patients, respectively, with no differences between patient groups. During the intervention, this number remained stable in the FOS group (0.7×106±1.3×106 versus 1.0×106±1.3×106 baseline versus end-point), but decreased in the non-FOS group (3.6 ×1 06±8.0×106 versus 2.5×104±4.0×104). GIQLI scores were correlated with the number of faecal Bifidobacteria (r=0.41, p=0.007). Conclusions. The GIQL score for the tube-fed patients increased with the number of faecal Bifidobacteria, although in a non-linear way, and addition of FOS increased the number of Bifidobacteria. This suggests that prebiotic tube feeding may lead to a change in intestinal microbiota that could induce an increased quality of life in these patients.

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.

Weight Loss of 5% or More Predicts Loss of Fat-Free Mass During Palliative Chemotherapy in Patients With Advanced Cancer: A Pilot Study

The cutoff value of critical weight loss is still subject of discussion. In this pilot study, we investigated whether ≥5% weight loss in the past year predicts changes in nutritional status in patients with advanced cancer during treatment with palliative chemotherapy. In 20 patients with advanced cancer undergoing palliative (combination) chemotherapy, body weight, fat free mass (FFM), and cachexia were measured prior to the start and at 9 wk of treatment. History of weight loss was used to test differences in development of nutritional parameters during chemotherapy with use of independent sample t-tests. At baseline, 10 of 20 patients had lost ≥5% body weight during the past year and 5 patients were cachectic. The change in FFM in the first 9 wk of chemotherapy was significantly worse in patients with ≥5% weight loss compared to patients with <5% weight loss [mean difference: 3.5 kg (P = 0.001)]. Data also suggest that ≥5% weight loss predicts shorter survival (P = 0.03). We found that patients with ≥5% weight loss prior to chemotherapy have a deterioration in nutritional status during chemotherapy and may have a shorter survival. These results have to be confirmed in a larger study including a robust survival analysis.

Resting energy expenditure in head and neck cancer patients before and during radiotherapy

BACKGROUND & AIMSnWeight loss is a frequently observed problem in patients with head and neck cancer (HNC) during radiotherapy. It is still to be assessed whether hypermetabolism is contributing to this problem. The aim of this study was to investigate hypermetabolism before radiotherapy, and changes in resting energy expenditure (REE) in HNC patients during radiotherapy.nnnMETHODSnREE was measured by indirect calorimetry in 71 patients with HNC before radiotherapy, after 3 and 6 weeks of radiotherapy, and 3 months after radiotherapy. The association between REE and tumour stage, CRP, and prior tumour surgery was analyzed by linear regression analyses. Forty healthy control subjects were one-to-one matched to 40 patients by gender, age and fat free mass (FFM) index to compare REE.nnnRESULTSnBefore radiotherapy, REE was not significantly different between patients and controls, neither in absolute values (1568 ± 247 vs. 1619 ± 244 kcal/d; p = 0.29), nor after weight-adjustment (22.1 ± 3.5 vs. 21.5 ± 3.3 kcal/kg, p = 0.42) or FFM-adjustment (31.5 ± 4.9 vs. 30.7 ± 4.5 kcal/kg, p = 0.38). REE was independent of tumour stage, CRP, and prior tumour surgery. REE (kcal/d) decreased during radiotherapy and thereafter by 9% from pre-radiotherapy (p < 0.01). Weight and FFM also decreased significantly over time (p < 0.001). REE adjusted for FFM decreased in the first 3 weeks of radiotherapy with 4% (B = -1.39 kcal/kg FFM, p < 0.01), increased at the end of radiotherapy and decreased again 3 months after radiotherapy (B = -1.31 kcal/kg FFM, p = 0.04).nnnCONCLUSIONSnHead and neck cancer patients had normal REE before radiotherapy. During radiotherapy, REE decreased continuously with ongoing weight loss. However, weight loss is not the only explaining factor, since REE expressed per kg FFM showed a much more divergent course which is currently unexplained.

Predicting resting energy expenditure in underweight, normal weight, overweight, and obese adult hospital patients

BackgroundWhen indirect calorimetry is not available, predictive equations are used to estimate resing energy expenditure (REE). There is no consensus about which equation to use in hospitalized patients. The objective of this study is to examine the validity of REE predictive equations for underweight, normal weight, overweight, and obese inpatients and outpatients by comparison with indirect calorimetry.MethodsEquations were included when based on weight, height, age, and/or gender. REE was measured with indirect calorimetry. A prediction between 90 and 110% of the measured REE was considered accurate. The bias and root-mean-square error (RMSE) were used to evaluate how well the equations fitted the REE measurement. Subgroup analysis was performed for BMI. A new equation was developed based on regression analysis and tested.Results513 general hospital patients were included, (253xa0F, 260xa0M), 237 inpatients and 276 outpatients. Fifteen predictive equations were used. The most used fixed factors (25xa0kcal/kg/day, 30xa0kcal/kg/day and 2000xa0kcal for female and 2500xa0kcal for male) were added. The percentage of accurate predicted REE was low in all equations, ranging from 8 to 49%. Overall the new equation performed equal to the best performing Korth equation and slightly better than the well-known WHO equation based on weight and height (49% vs 45% accurate). Categorized by BMI subgroups, the new equation, Korth and the WHO equation based on weight and height performed best in all categories except from the obese subgroup. The original Harris and Benedict (HB) equation was best for obese patients.ConclusionsREE predictive equations are only accurate in about half the patients. The WHO equation is advised up to BMI 30, and HB equation is advised for obese (over BMI 30). Measuring REE with indirect calorimetry is preferred, and should be used when available and feasible in order to optimize nutritional support in hospital inpatients and outpatients with different degrees of malnutrition.

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

BACKGROUND & AIMSnWith 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.nnnMETHODSnBased 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.nnnRESULTSnTen 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 0.210xa0kg (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.nnnCONCLUSIONnCurrently, 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.

REHABILITATION PATIENTS: UNDERNOURISHED AND OBESE?

BACKGROUNDnThe aim of this study was to assess the prevalence of undernutrition in patients in Dutch rehabilitation centres and to measure the diagnostic accuracy of available screening tools.nnnMETHODSnThis cross-sectional multicentre study was conducted in 11 rehabilitation centres in The Netherlands. Patients nutritional status was determined by the amount of weight loss during the last 1, 3 and 6 months and body mass index (BMI). Diagnostic accuracy was assessed for 5 screening tools: Short Nutritional Assessment Questionnaire (SNAQ), Short Nutritional Assessment Questionnaire Residential Care (SNAQRC), SNAQ65+, Malnutrition Universal Screening Tool and Mini nutrition Assessment-short form.nnnRESULTSnTwenty-eight percent of the patients were severely undernourished and 10% were moderately undernourished. In the undernourished group, 28% were overweight (BMI 25-30) and 19% were obese (BMI >u200930). The SNAQ65+ is the recommended screening tool due to its high diagnostic accuracy (sensitivity 96%, specificity 77%, positive predictive value 62%, negative predictive value 90%) and quick and easy use. The MNA had the worst diagnostic accuracy, with a sensitivity of 44%.nnnCONCLUSIONnThe prevalence of undernutrition in patients in Dutch rehabilitation centres is high. Almost half of the undernourished patients were overweight or obese. Therefore, it is important not only to screen for undernutrition, but also carefully to assess possible overweight/obesity in every undernourished rehabilitation patient.

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

BACKGROUNDnIn 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.nnnAIMnTo study the predictive value of the new ESPEN diagnostic criteria for malnutrition on survival, with specific focus on the additional value of FFMI.nnnMETHODSnIncluded were 335 hospitalized adult patients of the VU University Medical Center Amsterdam (60% female, age 58xa0±xa018xa0y). 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.nnnRESULTSnNinety 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%; pxa0=xa00.01) and one year (76% vs 87%; pxa0=xa00.02). After adjustments, malnutrition remained significantly associated with three-months survival for the Dutch definition for malnutrition (HR:2.25, pxa0=xa00.04) and the ESPEN diagnostic criteria for malnutrition (HR:2.76, pxa0=xa00.02). Malnutrition remained significantly associated with one-year survival for the ESPEN diagnostic criteria for malnutrition (HR:2.17, pxa0<xa00.02) and the ESPEN diagnostic criteria for malnutrition without FFMI (HR:2.66, pxa0<xa00.01).nnnCONCLUSIONnThe 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.