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Journal Article

Citation

Palese A, Gonella S, Lant A, Guarnier A, Barelli P, Zambiasi P, Allegrini E, Bazoli L, Casson P, Marin M, Padovan M, Picogna M, Taddia P, Salmaso D, Chiari P, Frison T, Marognolli O, Canzan F, Ambrosi E, Saiani L. Aging Clin. Exp. Res. 2015; 28(1): 139-146.

Affiliation

Udine University, Viale Ungheria 20, 33100, Udine, Italy, alvisa.palese@uniud.it.

Copyright

(Copyright © 2015, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s40520-015-0378-4

PMID

26025462

Abstract

BACKGROUND: The Conley Scale is one of the most widespread fall-risk screening tools in medical unit settings, despite the lack of data regarding its validity in patients currently admitted to these units. AIMS: Establishing the validity of the Conley Scale in identifying patients at risk of falling in an acute medical setting.

METHODS: A 6-months longitudinal study in 12 acute medical units from September 2012 to March 2013, a total of 1464 patients with ≥65 years of age were consecutively enrolled and evaluated with the Conley Scale within 24 h of admission. A construct validity, internal consistency, and a priori and a posteriori predictive validity study was performed.

RESULTS: The explorative factor analysis showed a two-factor structure explaining a total variance of 48.3 %: previous history (30.41 %), and physical and cognitive impairment (17.9 %). The scale reported a poor internal consistency (Cronbach's α = 0.465) and the capability to correctly identify 18/649 patients as being at risk of falling, whereas the negative predictive value was 98.5 %. The sensitivity and specificity values were 60.0 and 55.9 %, respectively. No difference emerged between patients scored as at risk and those scored as not at risk in the time elapsed from admission to the first fall (HR = 0.600, 95 % CI 0.289-2.247 p = .166).

DISCUSSION: The Conley Scale is not able to predict falls in elderly acute medical patients, and has reported poor internal consistency and accuracy.

CONCLUSIONS: More studies are needed to develop appropriate tools to predict the risk of falling in elderly individuals admitted to an acute medical setting.


Language: en

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