Handgrip strength measurement as a predictor of hospitalization costs

• Published in: European journal of clinical nutrition Vol. 69; no. 2; pp. 187 - 192
• Main Authors: Guerra, R S, Amaral, T F, Sousa, A S, Pichel, F, Restivo, M T, Ferreira, S, Fonseca, I
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.02.2015; Nature Publishing Group
• Subjects: 692/700; 692/700/2814; Adult; Aged; Aged, 80 and over; Clinical Nutrition; Confidence intervals; Costs; Economic aspects; Economic impact; Epidemiology; Female; Grip strength; Hand Strength; Hands; Health care costs; Hospital Costs; Hospitalization; Hospitalization - economics; Humans; Impact analysis; Inpatients; Internal Medicine; Linear Models; Male; Malnutrition; Malnutrition - diagnosis; Malnutrition - economics; Measurement; Medicine; Medicine & Public Health; Metabolic Diseases; Middle Aged; Muscular system; Nutrition Assessment; Nutritional Status; original-article; Patient admissions; Patients; Prospective Studies; Public Health; Quartiles; Regression analysis; Statistical analysis; Undernutrition; Young Adult
• ISSN: 0954-3007; 1476-5640
• DOI: 10.1038/ejcn.2014.242

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 €375 (58–692) to €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 €356 (41–668) to €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.