Undernutrition Screening Research Articles

Prevalence of undernutrition and risk factors of severe undernutrition among children admitted to Bugando Medical Centre in Mwanza, Tanzania

Malnutrition is a major public health problem in developing countries including Tanzania, contributing up to 50 % of under-five mortality. East Africa region was among the three United Nations (UN) subregions with the highest prevalence of stunting in 2011. In resource limited countries, the available little resources in hospitals are likely to be used focusing the primary clinical problem that led to admission of children leaving moderate and mild malnutrion unattended. This work was conducted to determine the prevalence of under-nutrition and risk factors associated with severe malnutrition among undernourished children aged 6–60 months admitted to Bugando Medical Centre (BMC) paediatric wards. This was a hospital-based cross sectional study where by 720 children were screened in order to determine their nutritional status. Data were collected through measurement of weight/length or height, mid upper arm circumference (MUAC) and interpretation was done using Z-score (mild malnutrition ≤1SD, moderate malnutrition ≤2SD and severe malnutrition ≤3SD). The socio-demographic data were obtained using a questionnaire that was completed by interviewing children’s parents/caregiver. Out of 720 screened children, 402 (55.8 %) were undernourished. Severe malnutrition was found in 178 (24.7 %) children and among these 97 (54.5 %) had marasmus. Risk factors associated with severe malnutrition were children with age less than 2 years, lack of vaccination, taking unbalanced diet, low maternal education and single parent, with p-value (<0.001, < 0.001, <0.001, 0.02, < 0.001) respectively. This study show a high prevalence of malnutrition in hospitalized children and the majority was marasmic. The risk factors associated with severe malnutrition were described. We recommend improving the screening for undernutrition in all admitted patients so that proper management of this problem can be done concurrently with the primary clinical disease that led to admission.

Developing and Validating a Renal Nutrition Screening Tool to Effectively Identify Undernutrition Risk Among Renal Inpatients

To develop and validate a nutrition screening tool that is effective to recognize renal inpatients at risk of undernutrition. A prospective, criterion validation. Adults admitted to a hospital ward with acute kidney injury, chronic kidney disease, and dialysis regardless of gender or ethnicity (n = 122) were recruited. The renal nutrition screening tool (R-NST) was developed from the Malnutrition Screening Tool and renal specific risk variables such as biochemical measures to identify renal inpatients who are at undernutrition risk. The undernutrition risk of each participant was independently assessed using the R-NST and the 7-point Subjective Global Assessment (SGA). The R-NST was autonomously used by nursing staff to determine its feasibility as a routine screening method at ward level. The SGA and R-NST tools classified 53.3% and 68.0% of participants as malnourished or at undernutrition risk, respectively. The R-NST was determined to be valid to detect undernutrition risk (sensitivity=97.3%, specificity=74.4%, positive predictive value=88.0%, and negative predictive value=93.6%) compared with the SGA. The R-NST also showed ability to recognize timely dietetic intervention required due to renal conditions. The compliance rate in the R-NST screening by the nursing staff was low (22.6%). The R-NST is a good screening tool for identifying renal inpatients at undernutrition risk. Further research is warranted to explore innovative yet effective strategies to establish undernutrition screening as standard renal ward practice.

Undernutrition screening survey in 564,063 patients: patients with a positive undernutrition screening score stay in hospital 1.4 d longer

Undernutrition is a common complication of disease and a major determinant of hospital stay outcome. Dutch hospitals are required to screen for undernutrition on the first day of admission. We sought to determine the prevalence of the screening score "undernourished" with the use of the Short Nutritional Assessment Questionnaire (SNAQ) or Malnutrition Universal Screening Tool (MUST) and its relation to length of hospital stay (LOS) in the general hospital population and per medical specialty. We conducted an observational cross-sectional study at 2 university, 3 teaching, and 8 general hospitals. All adult inpatients aged ≥18 y with an LOS of at least 1 d were included. Between 2007 and 2014, the SNAQ/MUST score, admitting medical specialty, LOS, age, and sex of each patient were extracted from the digital hospital chart system. Linear regression analysis with ln(LOS) as an outcome measure and SNAQ ≥3 points/MUST ≥2 points, sex, and age as determinant variables was used to test the relation between SNAQ/MUST score and LOS. In total, 564,063 patients were included (48% males and 52% females aged 62 ± 18 y). Of those, 74% (419,086) were screened with SNAQ and 26% (144,977) with MUST, and 13.7% (SNAQ) and 14.9% (MUST) of the patients were defined as being undernourished. Medical specialties with the highest percentage of the screening score of undernourished were geriatrics (38%), oncology (33%), gastroenterology (27%), and internal medicine (27%). Patients who had an undernourished screening score had a higher LOS than did patients who did not (median 6.8 compared with 4.0 d; P < 0.001). Regression analysis showed that a positive SNAQ/MUST score was significantly associated with LOS [SNAQ: +1.43 d (95% CI: 1.42, 1.44 d), P < 0.001; MUST: +1.47 d (95% CI: 1.45, 1.49 d), P < 0.001]. This study provides benchmark data on the prevalence of undernutrition, including more than half a million patients. One out of 7 patients was scored as undernourished. For geriatrics, oncology, gastroenterology, and internal medicine, this ratio was even greater (1 out of 3–4). Hospital stay was 1.4 d longer among undernourished patients than among those who were well nourished.

Nutritional screening: a user-friendly tool adapted from Sweden

Screening for undernutrition is highly important and may reduce morbidity and mortality. The Minimal Eating Observation and Nutrition Form Version II (MEONF-II) is a nutritional screening tool specifically developed for use by nurses. The authors describe the translation, performance and appropriateness of MEONF-II for the UK. Following translation from Swedish to British English, the user-friendliness and appropriateness of the British MEONF-II was tested by 29 registered nurses and final-year student nurses on 266 hospital inpatients. The new British MEONF-II was perceived as highly user-friendly and appropriate. Assessors found MEONF-II to compare favourably with other similar tools in terms of preference, usefulness and helpfulness in providing good nutritional care. Dependency in activities and poorer subjective health were associated with a higher risk of undernutrition. These findings support the appropriateness of the British MEONF-II version and suggest it may act as a user-friendly facilitator for good nutritional nursing care.

Malnutrition in Very Old Hospitalized Patients: A New Etiologic Factor of Anemia?

Anemia and malnutrition are highly prevalent, frequently concomitant and associated with negative outcomes and mortality in the elderly. To evaluate the association between these two entities, and test the hypothesis that protein-energy deficit could be etiology of anemia. Prospective case-control study. Geriatric and Rehabilitation Hospital, Geneva University Hospitals, Switzerland. 392 patients (mean age 84.8 years old, 68.6% female). Hematological (hemoglobin (Hb)), chemical (iron work up, cyanocobalamin, folates, renal function, C-Reactive Protein (CRP)) and nutrition (albumin, prealbumin) parameters, and mini nutritional assessment short form (MNA-SF). The prevalence of anemia (defined as Hb<120 g/l) was 39.3%. Anemic patients were more frequently malnourished or at risk of malnutrition according to the MNA-SF (p=0.047), with lower serum albumin (p <0.001) and prealbumin (p <0.001) levels. Thirty-eight percent of these patients had multiple causes and 14.3% had no cause found for anemia. Among the latter 90.9% of patients with unexplained anemia had albumin levels lower than 35g/l. After exclusion of iron,vitamin B12 and folic acid deficits, anemic patients had lower albumin (p<0.001) and prealbumin (p 0.007) levels. Albumin level explained 84.5% of the variance in anemia. In multivariate analysis albumin levels remain associated with Hb only in anemic patients, explaining 6.4% of Hb variance (adj R2) and 14.7% (adj R2) after excluding inflammatory parameters (CRP>10). Albumin levels are strongly associated with anemia in the elderly. Screening for undernutrition should be included in anemia assessment in those patients. Further prospective studies are warranted in order to explore the effect of protein and energy supplementation on hemoglobin level.

SUN-PP218: Dietary Intervention in Middle Age Obese Sarcopenic Females

Rationale: Undernutrition screening and assessment tools are made up of different components. Undernutrition has been associated with longer length of hospital stay (LOS) but it is not known which components have the greatest power in predicting LOS. We aimed to investigate the association of several under nutrition components with LOS. Methods: Demographic, clinical, anthropometric and nutritional data were obtained in 683 inpatients. LOS was determined from the date of hospital admission and discharge home (event of interest). Cox proportional hazard ratios (HR) models were adjusted for age, education, comorbidities and independence in activities of daily living. Results: Factors independently associated with lower probability of being discharged home were: weight loss >5% (HR = 0.65, 95%CI = 0.53 0.79), depletion of triceps skinfold (0.77, 0.65 0.91) or adductor pollicis (0.76, 0.59 0.98), decreased food intake in the preceding admission month (0.66, 0.55 0.80), gastrointestinal symptoms (0.71, 0.58 0.86), moderate (0.54, 0.40 0.73) and severe (0.66, 0.52 0.83) functional impairment and low handgrip strength quartiles [3rd: 0.77 (0.61 0.96); 2nd: 0.61 (0.48 0.77) and 1st (lowest): 0.50 (0.39 0.64) versus 4th]. Mid arm muscle circumference, oedema and ascites and decreased food intake in the preceding admission week were not associated with LOS. Conclusion: Weight loss, depletion of triceps skinfold and adductor pollicis, decreased food intake in the preceding admission month, gastrointestinal symptoms, functional impairment and low handgrip strength quartiles were the components of under nutrition tools that independently predicted LOS. These results are a relevant contribution in improving under nutrition tools.

Validation of a Screening Tool to Identify Undernutrition in Ambulatory Patients With Liver Cirrhosis

The prevalence of chronic liver disease is increasing in the United States. Malnutrition is common as liver disease progresses. However, an accepted method to screen these patients for malnutrition is lacking. The 6-question undernutrition screening tool was developed for professionals without nutrition training to identify a decline in the nutrition status of patients with liver cirrhosis. A 3-phase validation study was completed to assess face, content, and clinical validity of the screening tool in ambulatory patients with liver cirrhosis. In phase I, face validity was determined by surveying 13 liver disease professionals. In phase II, content validity was assessed by surveying 12 registered dietitians who specialize in liver disease. In phase III, a cross-sectional investigation was completed to compare the agreement between the undernutrition screening tool and nutrition assessment by a registered dietitian (RD). Twenty-two patients with a diagnosis of liver cirrhosis participated in phase III of the investigation. The RD assessment identified undernutrition in 82% of patients (95% CI, 60%-95%). The κ statistic indicated a fair agreement between the screening tool and RD assessment. Sensitivity and specificity of the tool were 72% and 75%, respectively, and positive predictive value was 93%. Feedback from phase I, II, and III indicate that the undernutrition screening tool is simple, is easy to use, and measures the constructs that have the strongest link with undernutrition in liver disease. Additional minor adjustments to the screening tool and a multicenter investigation are indicated to confirm clinical effectiveness and cross-validity of the tool.

Dénutrition du sujet obèse

Undernutrition and its numerous clinical consequences increase morbidity and mortality. For these reasons, undernutrition screening and its treatment must be undertaken as soon as possible for every patient at risk. However in case of obesity, the criteria for the nutritional assessment are deficient because of the clinical and biological specificities associated with excessive body fat. The purpose of this review is to discuss the limits of the parameters actually used for nutritional evaluation in order to better assess its frequency and define the situations at risk of undernutrition in obese patients.

Nutritional Screening of Pulmonology Department Inpatients

Undernutrition is associated with worse clinical outcomes and so screening is recommended. Given the paucity of information on nutritional status and on the clinical impact of undernutrition in Pulmonology patients who have been hospitalized, it is of the utmost importance that it is studied.Through a longitudinal study conducted of 323 patients consecutively admitted to a Pulmonology hospital department, undernutrition was screened using the Malnutrition Universal Screening Tool and the association between length of hospital stay, pathology type, discharge destination and undernutrition risk was quantified.There was found to be a high proportion of patients at risk of undernutrition, with 18.3% at high risk and 15.5% at moderate risk. Patients at risk of undernutrition had a higher risk of dying during hospitalization (OR=2.72, 95% CI: 1.48- 4.97).One in three patients admitted to this unit is at risk of undernutrition; chronic obstructive pulmonary disease was the pathology most strongly associated with undernutrition risk. Present data reinforces the need for screening for undernutrition on admission.

Handgrip strength cutoff values for undernutrition screening at hospital admission.

There is increasing evidence showing that handgrip strength (HGS) is an indicator of nutrition status and a promising undernutrition screening tool. However, HGS cutoff values for inpatient undernutrition screening remain to be studied. The present study aims to define gender- and age-specific HGS cutoff values for undernutrition screening of hospitalized patients at admission. A cross-sectional study was conducted in a university hospital. Gender- and age-specific receiver operating characteristic curves were constructed to evaluate the performance of HGS for correctly screening undernourished patients on the basis of their classification by Patient-Generated Subjective Global Assessment. Sensitivity, specificity, areas under the curves (AUCs) and positive likelihood ratios (LRs) were calculated. The study sample was composed of 712 participants between the ages of 18 and 91 years old, median (interquartile range) of 58 (22) years. For women, HGS cutoff values, sensitivities and specificities were as follows: 18-44 years, 20.2 kgf, 0.741 and 0.556; 45-64 years, 19.2 kgf, 0.795 and 0.522. For men, these values were as follows: 18-44 years, 41.7 kgf, 0.923 and 0.520; 45-64 years, 37.9 kgf, 0.817 and 0.402; ⩾65 years, 30.2 kgf, 0.736 and 0.567. The AUCs varied between 0.642 and 0.778 and LRs from 1.37 to 1.92. This study provides HGS cutoff values for men aged 18-91 years and for women aged 18-64 years.

PP245-MON: Screening for Under-Nutrition in Paediatric Departments: A Nationwide Survey on Current Practice and Attitude

naires on demographic characteristics, lifestyle and food frequency (FFQ) were completed. Data were analyzed by SPSS. Results: Evaluation of anthropometric indices in obese children showed that although weight and height increased significantly in both groups, Weight increased more slowly in intervention group. The largest decline in waist and hip. Among biochemical indices, only blood triglyceride and cholesterol decreased significantly. Evaluation of food group consumption showed that not only, utilization of milk, dairy and nuts group increased significantly in intervention group but also consumption of braes and cereals, butter, cream, Mayonnaise, Sugar and confectionery ingredients significantly decreased. Use of oil and fat group decreased dramatically in case group. Conclusion: Overall, if obesity interventions were done in longer periods including all family and school members, weight control and lifestyle modification would be more efficient. It is obvious that Government policy and organization support are also effective ways to control children obesity in order to have a healthy society in the future. Disclosure of Interest: None Declared.

Nutritional Screening of Pulmonology Department Inpatients

Undernutrition is associated with worse clinical outcomes and so screening is recommended. Given the paucity of information on nutritional status and on the clinical impact of undernutrition in Pulmonology patients who have been hospitalized, it is of the utmost importance that it is studied.Through a longitudinal study conducted of 323 patients consecutively admitted to a Pulmonology hospital department, undernutrition was screened using the Malnutrition Universal Screening Tool and the association between length of hospital stay, pathology type, discharge destination and undernutrition risk was quantified.There was found to be a high proportion of patients at risk of undernutrition, with 18.3% at high risk and 15.5% at moderate risk. Patients at risk of undernutrition had a higher risk of dying during hospitalization (OR=2.72, 95% CI: 1.48- 4.97).One in three patients admitted to this unit is at risk of undernutrition; chronic obstructive pulmonary disease was the pathology most strongly associated with undernutrition risk. Present data reinforces the need for screening for undernutrition on admission.

The economic burden of disease-related undernutrition in selected chronic diseases

Undernutrition is a common and aggravating problem in people suffering from various chronic diseases as well as a source of material costs. The aim of this study was to investigate the prevalence of disease-related undernutrition among adults in Croatia in the year 2012, as well as the cost of undernutrition associated with tumour cachexia, chronic pancreatitis, inflammatory bowel disease, hepatic encephalopathy, chronic obstructive pulmonary disease, chronic renal insufficiency requiring dialysis, cerebrovascular insult, pressure ulcers, and femoral fractures in the elderly. A cost-of-illness analysis was conducted, including direct costs only. The study employed the dominant cost-of-illness method, which restricts the summation of medical expenditure to the disease of interest. The bottom-up, prevalence-based approach was used. The budget holder perspective was employed, and data sources include the list of reimbursed drugs, clinical opinions, and literature. The prevalence of disease-related undernutrition in people over the age of 20 in Croatia in the year 2012 was estimated to be 33.7/1000. The total cost of adult malnutrition for selected diagnoses was 97.35 million EUR, accounting for 3.38% of the total Croatian national health care budget. The largest share was used for medications (43%), followed by 34% for hospitalizations, 13% for community health nursing, while parenteral and enteral nutrition contributed with 6% and 1% respectively. The average cost per patient was estimated at 1640.48 EUR. The cost of malnutrition for the selected diagnoses in Croatia was substantial. These health costs will increase due to population ageing, which calls for undernutrition screening in people at risk as well as for effective approaches in nutrition supplementation.

Systematic screening for undernutrition in hospitals: Predictive factors for success

Since 2007, systematic screening for undernutrition has become a performance indicator (PI) for hospitals within the National Benchmarks on Quality of Care of the Dutch Health Care Inspectorate (HCI). Its introduction was guided by a national implementation program. The aim of this study was to evaluate the screening results from 2007 to 2010 and to identify predictive factors for achieved screening results. All 97 Dutch hospitals were obliged to report screening results to the HCI. An additional questionnaire was developed to determine hospital characteristics, including hospital type, size, participation in implementation program, screening tool used, use of electronic records, presence of hospital-wide or ward task forces, and protocol-defined referral. Multivariate linear regression analysis was used to identify predictive factors for the obtained screening results in 2010. The mean screening percentage increased from 51 ± 28% in 2007 (n = 75 hospitals, n = 340,000 patients) to 72 ± 17% in 2010 (n = 97; n = 1,050,000) (p < 0.01). Eighty-one hospitals returned the questionnaire. A higher screening percentage was associated with more clinical admissions (highest vs. lowest tertile: β = 14.0, 95% CI 3.9-20.5; p < 0.01; middle vs. lowest: β = 7.3, -0.8 to 15.6; p = 0.05), presence of protocol-defined referral to a dietician (β = 10.5, 2.9-18.0; p < 0.01), and use of the SNAQ screening tool (vs. MUST: β = 9.1, 1.7-16.6; p = 0.02). Screening percentages have increased significantly since the introduction of the PI. Screening was more frequent in hospitals which have more patient admissions, protocol-defined referral to a dietician, and who use the SNAQ screening tool. This information may assist in improving Dutch screening rates and in implementation in other countries.

Validity of nutritional screening with MUST and SNAQ in hospital outpatients

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. 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). 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). 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.

Cardiac Surgery–Specific Screening Tool Identifies Preoperative Undernutrition in Cardiac Surgery

Loss of body tissue resulting in undernutrition can be caused by reduced food intake, altered metabolism, ageing, and physical inactivity. The predominant cause of undernutrition before cardiac operations is unknown. First, we explored the association of reduced food intake and inactivity with undernutrition in patients before elective cardiac operations. Second, we assessed if adding these reversible, cause-based items to the nutritional screening process improved diagnostic accuracy. A prospective observational study was performed. Undernutrition was defined by low fat-free mass index (LFFMI) measured by bioelectrical impedance spectroscopy and/or unintended weight loss (UWL). Reduced food intake was defined as the patient having a decreased appetite over the previous month. Patients admitted to hospital preoperatively were assumed to be less physically active than patients awaiting cardiac operations at home. Using these data, we developed a new tool and compared this with an existing cardiac surgery-specific tool (Cardiac Surgery-Specific Malnutrition Universal Screening Tool [CSSM]). A total of 325 patients who underwent open cardiac operations were included. Reduced food intake and inactivity were associated with undernutrition (odds ratio [OR], 4.2; 95% confidence interval [CI], 2.1-8.5 and OR, 2.0; 95% CI, 1.0-4.0). Reduced food intake and inactivity were integrated with body mass index (BMI) and UWL into a new scoring system: the Cardiac Surgery-Specific Undernutrition Screening Tool (CSSUST). Sensitivity in identification of undernourished patients was considerably higher with the CSSUST (90%) than with the CSSM (71%) (receiver operating characteristic [ROC] curve-based area under the curve [AUC], 0.79; 95% CI, 0.73-0.86 and ROC AUC, 0.71; 95% CI, 0.63-0.80). Results suggest that reduced food intake and inactivity partly explain undernutrition before cardiac operations. Our new cause-based CSSUST, which includes reduced food intake and inactivity, is superior to existing tools in identifying undernutrition in patients undergoing cardiac operations.

CONFIRMANDO LA VALIDEZ DEL SISTEMA CONUT PARA LA DETECCIÓN PRECOZ DE LA DESNUTRICIÓN CLÍNICA; COMPARACIÓN CON DOS MODELOS DE REGRESIÓN LOGÍSTICA DESARROLLADOS USANDO EL SGA COMO GOLD STANDARD

Aim: To ratify previous validations of the CONUT nutritional screening tool by the development of two probabilistic models using the parameters included in the CONUT, to see if the CONUT’s effectiveness could be improved. Methods: It is a two step prospective study. In Step 1, 101 patients were randomly selected, and SGA and CONUT was made. With data obtained an unconditional logistic regression model was developed, and two variants of CONUT were constructed: Model 1 was made by a method of logistic regression. Model 2 was made by dividing the probabilities of undernutrition obtained in model 1 in seven regular intervals. In step 2, 60 patients were selected and underwent the SGA, the original CONUT and the new models developed. The diagnostic efficacy of the original CONUT and the new models was tested by means of ROC curves. Both samples 1 and 2 were put together to measure the agreement degree between the original CONUT and SGA, and diagnostic efficacy parameters were calculated. Results: No statistically significant differences were found between sample 1 and 2, regarding age, sex and medical/surgical distribution and undernutrition rates were similar (over 40%). The AUC for the ROC curves were 0.862 for the original CONUT, and 0.839 and 0.874, for model 1 and 2 respectively. The kappa index for the CONUT and SGA was 0.680. Conclusions: The CONUT, with the original scores assigned by the authors is equally good than mathematical models and thus is a valuable tool, highly useful and efficient for the purpose of Clinical Undernutrition screening.

Confirming the validity of the CONUT system for early detection and monitoring of clinical undernutrition: comparison with two logistic regression models developed using SGA as the gold standard.

To ratify previous validations of the CONUT nutritional screening tool by the development of two probabilistic models using the parameters included in the CONUT, to see if the CONUT´s effectiveness could be improved. It is a two step prospective study. In Step 1, 101 patients were randomly selected, and SGA and CONUT was made. With data obtained an unconditional logistic regression model was developed, and two variants of CONUT were constructed: Model 1 was made by a method of logistic regression. Model 2 was made by dividing the probabilities of undernutrition obtained in model 1 in seven regular intervals. In step 2, 60 patients were selected and underwent the SGA, the original CONUT and the new models developed. The diagnostic efficacy of the original CONUT and the new models was tested by means of ROC curves. Both samples 1 and 2 were put together to measure the agreement degree between the original CONUT and SGA, and diagnostic efficacy parameters were calculated. No statistically significant differences were found between sample 1 and 2, regarding age, sex and medical/surgical distribution and undernutrition rates were similar (over 40%). The AUC for the ROC curves were 0.862 for the original CONUT, and 0.839 and 0.874, for model 1 and 2 respectively. The kappa index for the CONUT and SGA was 0.680. The CONUT, with the original scores assigned by the authors is equally good than mathematical models and thus is a valuable tool, highly useful and efficient for the purpose of Clinical Undernutrition screening.

Accuracy of Quick and Easy Undernutrition Screening Tools—Short Nutritional Assessment Questionnaire, Malnutrition Universal Screening Tool, and Modified Malnutrition Universal Screening Tool—in Patients Undergoing Cardiac Surgery

The objective of this study was to compare the quick-and-easy undernutrition screening tools, ie, Short Nutritional Assessment Questionnaire and Malnutrition Universal Screening Tool, in patients undergoing cardiac surgery with respect to their accuracy in detecting undernutrition measured by a low-fat free mass index (FFMI; calculated as kg/m 2), and secondly, to assess their association with postoperative adverse outcomes. Between February 2008 and December 2009, a single-center observational cohort study was performed (n=325). A low FFMI was set at ≤14.6 in women and ≤16.7 in men measured using bioelectrical impedance spectroscopy. To compare the accuracy of the Malnutrition Universal Screening Tool and Short Nutritional Assessment Questionnaire in detecting low FFMI sensitivity, specificity, and other accuracy test characteristics were calculated. The associations between the Malnutrition Universal Screening Tool and Short Nutritional Assessment Questionnaire and adverse outcomes were analyzed using logistic regression analyses with odds ratios and 95% confidence intervals (CI) presented. Sensitivity and receiver operator characteristic-based area under the curve to detect low FFMI were 59% and 19%, and 0.71 (95% CI: 0.60 to 0.82) and 0.56 (95% CI: 0.44 to 0.68) for the Malnutrition Universal Screening Tool and Short Nutritional Assessment Questionnaire, respectively. Accuracy of the Malnutrition Universal Screening Tool improved when age and sex were added to the nutritional screening process (sensitivity 74%, area under the curve: 0.72 [95% CI: 0.62 to 0.82]). This modified version of the Malnutrition Universal Screening Tool, but not the original Malnutrition Universal Screening Tool or Short Nutritional Assessment Questionnaire, was associated with prolonged intensive care unit and hospital stay (odds ratio: 2.1, 95% CI: 1.3 to 3.4; odds ratio: 1.6, 95% CI: 1.0 to 2.7). The accuracy to detect a low FFMI was considerably higher for the Malnutrition Universal Screening Tool than for the Short Nutritional Assessment Questionnaire, although still marginal. Further research to evaluate the modified version of the Malnutrition Universal Screening Tool, ie, the cardiac surgery–specific Malnutrition Universal Screening Tool, is needed prior to implementing.

Computer‐based undernutrition screening tool for hemodialysis patients

AbstractBACKGROUNDThe purpose of this study was to develop and validate a computer‐based screening tool to identify hemodialysis (HD) patients at risk of undernutrition. The computer‐based undernutrition screening tool identifies HD patients at risk of undernutrition as accurately as subjective global assessment (SGA) carried out by an experienced dietitian.METHODSThis was an observational study of 122 HD patients from the Royal Infirmary Haemodialysis Unit and the Western General Satellite Haemodialysis Unit, Edinburgh, Scotland. SGA of all participants was carried out, and the results were compared with the results from the computer‐based screening tool, which looked at the following parameters: pre‐dialysis urea &lt;15 mmol/L, albumin &lt;35 g/L, C‐reactive protein (CRP) &gt;10 mg/L, indicating acute phase response, total cholesterol &lt;3.5 mmol/L, &gt;5% weight loss over 3 months, body mass index &lt;20 kg/m2, midarm muscle circumference (MAMC; muscle mass) &lt;10th percentile, tricep skinfold thickness (fat mass) &lt;10th percentile, sex, age, and time on dialysis.RESULTSCorrelations with SGA results were performed for pre‐dialysis urea (p &lt; 0.001), pre‐dialysis albumin (p &lt; 0.001), CRP (p = 0.005), percentage weight loss (p &lt; 0.001), BMI (p &lt; 0.001), TSF (p &lt; 0.001), and MAMC (p = 0.001). Cholesterol did not reach statistical significance. For clinical reasons, TSF and MAMC were omitted from the final version of the computer‐based screening tool, which comprised pre‐dialysis urea, albumin, CRP, percentage weight loss, and BMI and accounted for 41% of the variability of SGA.DISCUSSIONThe computer‐based screening tool correlated with SGA across the whole range of undernutrition scores (R2 = 0.3406). As the results were based on quantitative data and therefore reproducible with a minimum chance of error, this new tool provides a rapid and easy method of assessing the risk of undernutrition. An outcome study looking at its ability to predict mortality and morbidity is now underway.