Undernutrition screening survey in 564,063 patients: patients with a positive undernutrition screening score stay in hospital 1.4 d longer (original) (raw)
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International journal of health sciences
Objective: To identify the risks, causes, and degree of malnutrition among admitted patients using GRAZ Malnutrition Screening tool with gender and age groups comparison among private and public hospitals. Materials & Methods: A comparative cohort study was conducted upon 385 admitted patients of two Government and private hospitals from 1st Dec- 2019 to 31st March- 2020. A standardized validated tool was used with categories of weight loss within the last 3 months, BMI, changes in appetite, the severity of the disease, and age greater than 65 with a cut-off score of 3. The data was entered and analyzed through SPSS- Version 19 by computing, frequency, percentages, and Chi-Square test, with significant cut-off limit for P-Value was set at 0.05. Results: Among the 385 admitted patients 52.2 % (n= 201) were males and 48 % (n=184) females. The vulnerable age group was 39-58 Year with 40 % (n= 157) while 33.5 % (n= 129) were among 28-38 Year. Only 6 % (n= 21) were under-weight with BMI ...
Detecting Undernutrition on Hospital Admission - Screening Tool Versus WHO Criteria
Clinical medicine research, 2017
To prevent the development of malnutrition in hospitalized children, it is important to develope an early identification of nutritional depletion, ideally at the time of admission to the hospital. In 2009 Hulst et al. proposed new guidelines for assessing the nutritional status of hospitalized children called STRONGkids questionnaire (Screening Tool Risk on Nutritional Status and Growth). This study was designed to describe the current prevalence of malnutrition on admission to a pediatric gastroenterology hospital unit and to compare the value and feasibility of STRONGkids scoring system versus anthropometric World Health Organization (WHO) criteria in identifying children at risk of developing malnutrition during hospital stay. The prospective observational study involved 124 children hospitalized at the
Nutrition, 2012
Objective: Malnourished patients suffer from higher morbidity and mortality rates than wellnourished patients do. However, few studies have controlled the outcomes for the underlying illnesses. Our aim was to determine the prevalence of malnutrition among patients admitted to the internal medicine ward and to determine whether malnutrition is an independent risk factor for adverse outcomes in these settings. Methods: Consecutive patients screened for malnutrition with the MUST (Malnutrition Universal Screening Tool), admitted to an internal medicine department, were included in this study. Demographic data, background disease, laboratory results, length of stay, and mortality rates were retrieved from the computerized file and Charlson Comorbidity Index (CCI) was calculated. Univariate and multivariate analyses were used to check for the association of malnutrition and outcome measures. Results: One thousand consecutive patients were included in the study. Mean age was 67.6 y; 25.4% of patients were found to be at high risk for malnutrition. Patients at high risk for malnutrition had significantly longer length of stay and mortality rates than well-nourished patients (9.7 d versus 6.2 d and 19.3% versus 3.2%; accordingly [P < 0.001]). On multivariate analyses, increased mortality was found to be associated with a high risk for malnutrition as well as pneumonia, acute myocardial infarction, acute renal failure, or shock on admission and a high CCI score. Conclusion: The prevalence of malnutrition among hospitalized patients, as measured by the MUST score, is common. Malnutrition is prevalent and represents an independent and significant risk factor for in-hospital mortality and increased length of stay in patients admitted to the internal medicine ward.
e-SPEN, the European e-Journal of Clinical Nutrition and Metabolism, 2007
Background & aims: A valid, quick-and-easy screening tool to detect undernutrition, is an essential requisite to treat undernutrition. In order to select quick-and-easy screening tools with high analytical accuracy for the general hospital in-, and outpatient population, a systematic review at sensitivity and specificity studies were performed. Methods: The electronic databases MEDLINE, EMBASE, CINAHL and the Cochrane Library (SR, DARE and the Central trail register) were searched. Additionally, ESPEN and ASPEN congress posters and abstracts from 2000 till 2005, reference lists and review articles, were hand-searched. There were no limitations made on language or publication date. To finally include a study there were six criteria: The study (1) determined analytical accuracy of a quick-and-easy screening tool in (2) adults with (3) the dichotomous classification: disease-related undernutrition present or absent, versus (4) an acceptable reference standard with (5) data available to abstract sensitivity and specificity. Methodological quality was formally assessed using the QUADAS (checklist for quality assessment in analytical accuracy studies) in those studies with (6) relevant sensitivity and specificity.
Clinical Nutrition, 2008
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%.