Browsing by Subject "Food pattern"

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Entwicklung eines computergestützten Assessment-Tools zur Erfassung des Ernährungszustandes von Senioren
(2011) Ott-Renzer, Cornelia; Biesalski, Hans-Konrad
Introduction: Worldwide a demographic change of population is to be observed, thus also in Germany. Special expertise in geriatric diagnostics and therapy will gain in importance. Thereby, a special relevance comes up to determination of nutritional status by corresponding screening and assessment. Conventional assessment mostly equates to questionnaire methods. Purpose/Question: Focus was on developing a software (geroMAT-Malnutrition Assessment and Therapy for gerontologic patients) for identification Senior´s nutritional state, a kind of "management tool" for diagnostics and intervention. Methods: Investigation was open, cooperative and multi-centric, as well as clinical-experimentally invested. In three partial studies (I: Suitability of the MNA® as a reference method; II: Anthropo-metry, biochemistry, body composition; III: Food patterns and intake, not-nutritive factors) indicators of malnutrition were initially selected. In a final analysis Model I (prognosis of malnutritional risk) and accordingly Model II (prognosis of the MNA®) have been developed for their use in geroMAT. Results: Prevalence of malnutrition was (in this random sample) 5%, 44% were at risk and 51% were well nourished. Due to inhomogeneity in class range by assessment with the MNA®, modelling of a dichotomic risk variable ("RiskMal", homogeneous) occurred. All up 25 features and 12 (optional) additional items from the partial studies I-III could be generated and attached to further analysis. Model I prognosticated "RiskMal" reliably (auROC=.739). Although firstly Model II predicted MNA® well (r=0,5167), model quality could be improved even further by the well-chosen parametres of a feature subset selection for Models I and II (Í: r=0,822;II: r=0,6634). Discussion: The Models I/II reached the requirements made on developing geroMAT. According to the features, geroMAT would be multi-centric usable, simple to learn and operable, documentable and reproduceable, interprofessionally and without high expense, as well as modern. Advantages of geroMAT, compared with the MNA® lay in its detailedness and its choice of further options, its capture of documented information off the normal anamnesis process and the initiation or monitoring of individual interventions. Conclusions: Mean aim of the study, the identification of indicators and model development, was reached. Other model validation studies should follow before the final clinical practice of geroMAT.