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Erschienen in: Supportive Care in Cancer 1/2016

01.01.2016 | Original Article

Prevalence of hospital malnutrition in cancer patients: a sub-analysis of the PREDyCES® study

verfasst von: Mercè Planas, Julia Álvarez-Hernández, Miguel León-Sanz, Sebastián Celaya-Pérez, Krysmarú Araujo, Abelardo García de Lorenzo, on behalf of the PREDyCES® researchers

Erschienen in: Supportive Care in Cancer | Ausgabe 1/2016

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Abstract

Purpose

In oncology patients, hospital malnutrition is associated with a greater risk of morbidity and mortality. The objective of this study was to determine the prevalence of nutritional risk and the clinical and economic consequences of hospital malnutrition in oncology patients hospitalised in Spanish centres.

Methods

This was an observational, cross-sectional, multicentre study. The prevalence of nutritional risk was determined using the Nutrition Risk Screening®-2002 (NRS®-2002).

Results

Four hundred one oncology patients were included; 33.9 % (136/401) were at nutritional risk (NRS®-2002 ≥ 3) at admission and 36.4 % (135/371) at discharge. On average, patients at nutritional risk were more elderly and had lower weights, body mass indices and arm and calf circumferences, as well as lower serum albumin levels than patients not at risk. Mean duration of hospitalisation and healthcare costs were greater in patients at nutritional risk at discharge (12.1 days; 95 % confidence interval (CI) 10.83–13.39) than in well-nourished patients (8.6 days; 95 % CI 7.86–9.40). Only a third of the patients at risk of malnutrition at discharge had received any kind of nutritional support.

Conclusions

This study shows that hospital malnutrition is a prevalent and undertreated condition in oncology patients that is associated with longer hospital stays and increased healthcare costs.
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Metadaten
Titel
Prevalence of hospital malnutrition in cancer patients: a sub-analysis of the PREDyCES® study
verfasst von
Mercè Planas
Julia Álvarez-Hernández
Miguel León-Sanz
Sebastián Celaya-Pérez
Krysmarú Araujo
Abelardo García de Lorenzo
on behalf of the PREDyCES® researchers
Publikationsdatum
01.01.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Supportive Care in Cancer / Ausgabe 1/2016
Print ISSN: 0941-4355
Elektronische ISSN: 1433-7339
DOI
https://doi.org/10.1007/s00520-015-2813-7

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Krebserkrankungen unbekannten Ursprungs (CUP) sind eine diagnostische Herausforderung. KI-Systeme können Pathologen dabei unterstützen, zytologische Bilder zu interpretieren, um den Primärtumor zu lokalisieren.

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