Published: 30 June 2015
Author(s): C.P. Launay, H. Rivière, A. Kabeshova, O. Beauchet
Section: Original Article

To examine performance criteria (i.e., sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], likelihood ratios [LR], area under receiver operating characteristic curve [AUROC]) of a 10-item brief geriatric assessment (BGA) for the prediction of prolonged length hospital stay (LHS) in older patients hospitalized in acute care wards after an emergency department (ED) visit, using artificial neural networks (ANNs); and to describe the contribution of each BGA item to the predictive accuracy using the AUROC value.

Newsletters

Stay informed on our latest news!

CAPTCHA

This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

randomness