Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/92454
Author(s): R. S. Guerra
T. F. Amaral
A. S. Sousa
F. Pichel
M. T. Restivo
S. Ferreira
I. Fonseca
Title: Handgrip strength measurement as a predictor of hospitalization costs
Issue Date: 2015
Abstract: BACKGROUND: Undernutrition status at hospital admission is related to increased hospital costs. Handgrip strength (HGS) is an indicator of undernutrition, but the ability of HGS to predict hospitalization costs has yet to be studied. OBJECTIVE: To explore whether HGS measurement at hospital admission can predict patient's hospitalization costs. SUBJECTS/METHODS: A prospective study was conducted in a university hospital. Inpatient's (n = 637) HGS and undernutrition status by Patient-Generated Subjective Global Assessment were ascertained. Multivariable linear regression analysis, computing HGS quartiles by sex (reference: fourth quartile, highest), was conducted in order to identify the independent predictors of hospitalization costs. Costs were evaluated through percentage deviation from the mean cost, after adjustment for patients' characteristics, disease severity and undernutrition status. RESULTS: Being in the first or second HGS quartiles at hospital admission increased patient's hospitalization costs, respectively, by 17.5% (95% confidence interval: 2.7-32.3) and 21.4% (7.5-35.3), which translated into an increase from [SIC]375 (58-692) to [SIC]458 (161-756). After the additional adjustment for undernutrition status, being in the first or second HGS quartiles had, respectively, an economic impact of 16.6% (1.9-31.2) and 20.0% (6.2-33.8), corresponding to an increase in hospitalization expenditure from [SIC]356 (41- 668) to [SIC]428 (133-724). CONCLUSIONS: Low HGS at hospital admission is associated with increased hospitalization costs of between 16.6 and 20.0% after controlling for possible confounders, including undernutrition status. HGS is an inexpensive, noninvasive and easy-to-use method that has clinical potential to predict hospitalization costs.
Subject: Ciências da Saúde, Ciências da saúde
Health sciences, Health sciences
Scientific areas: Ciências médicas e da saúde::Ciências da saúde
Medical and Health sciences::Health sciences
URI: https://hdl.handle.net/10216/92454
Document Type: Artigo em Revista Científica Internacional
Rights: restrictedAccess
Appears in Collections:FCNAUP - Artigo em Revista Científica Internacional
FEUP - Artigo em Revista Científica Internacional

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