To eat or not to eat? Indicators for reduced food intake in 91,245 patients hospitalized on nutritionDays [2006][2007][2008][2009][2010][2011][2012][2013][2014] Geneva University Hospital, Geneva, Switzerland ABSTRACT Background: Inadequate nutrition during hospitalization is strongly associated with poor patient outcome, but ensuring adequate food intake is not a priority in clinical routine worldwide. This lack of priority results in inadequate and unbalanced food intake in patients and huge amounts of wasted food. Objectives: We evaluate the main factors that are associated with reduced meal intake in hospitalized patients and the differences between geographical regions. Design: We conducted a descriptive analysis of data from 9 consecutive, annual, and cross-sectional nutritionDay samples (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) in a total of 91,245 adult patients in 6668 wards in 2584 hospitals in 56 countries. A general estimation equation methodology was used to develop a model for meal intake, and P-value thresholding was used for model selection. Results: The proportion of patients who ate a full meal varied widely (24.7-61.5%) across world regions. The factors that were most strongly associated with reduced food intake on nutritionDay were reduced intake during the previous week ( Conclusions: A set of factors that are associated with full meal intake was identified and is applicable to patients hospitalized in any region of the world. Thus, the likelihood for reduced food intake is easily estimated through access to patient characteristics, independent of world regions, and enables the easy personalization of food provision. This trial was registered at clinicaltrials.gov as NCT02820246.Am J Clin Nutr

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ObjectiveTo develop a simple scoring system to predict 30 day in-hospital mortality of in-patients excluding those from intensive care units based on easily obtainable demographic, disease and nutrition related patient data.MethodsScore development with general estimation equation methodology and model selection by P-value thresholding based on a cross-sectional sample of 52 risk indicators with 123 item classes collected with questionnaires and stored in an multilingual online database.SettingWorldwide prospective cross-sectional cohort with 30 day in-hospital mortality from the nutritionDay 2006-2009 and an external validation sample from 2012.ResultsWe included 43894 patients from 2480 units in 32 countries. 1631(3.72%) patients died within 30 days in hospital. The Patient- And Nutrition-Derived Outcome Risk Assessment (PANDORA) score predicts 30-day hospital mortality based on 7 indicators with 31 item classes on a scale from 0 to 75 points. The indicators are age (0 to 17 points), nutrient intake on nutritionDay (0 to 12 points), mobility (0 to 11 points), fluid status (0 to 10 points), BMI (0 to 9 points), cancer (9 points) and main patient group (0 to 7 points). An appropriate model fit has been achieved. The area under the receiver operating characteristic curve for mortality prediction was 0.82 in the development sample and 0.79 in the external validation sample.ConclusionsThe PANDORA score is a simple, robust scoring system for a general population of hospitalised patients to be used for risk stratification and benchmarking.

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