Identification of possible determinants of inpatient mortality using Classification and Regression Tree (CART) analysis in hospitalized oldest old patients

Butchart, Catherine, Ismailoglu, Firat, Myint, Phyo Kyaw, Musonda, Patrick, Lunt, Claire J, Pai, Yogish, Soiza, Roy L and Rayward-Smith, V J (2013) Identification of possible determinants of inpatient mortality using Classification and Regression Tree (CART) analysis in hospitalized oldest old patients. Archives of Gerontology and Geriatrics, 56 (1). pp. 188-191. ISSN 0167-4943

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Abstract

Current demographic trends suggest that there will be increasing numbers of older people in the future. Relatively little information is available regarding factors which influence mortality in the acutely unwell oldest old. This study uses the CART technique on data relating to the oldest old, to identify potential predictors of inpatient mortality in patients over 90 years old admitted acutely to the hospital due to various medical emergencies in two UK centers. The sample included 393 patients aged 90 years and older, with 67.5% females and 32.5% males and a mean age of 91.1 years. We aimed to generate hypotheses in order to identify potential acute illness prognostic indicators of inpatient mortality in this age group. The factors identified in this analysis which were associated with inpatient mortality in this patient population were raised serum urea concentration (>13.95 mmol/L), low oxygen saturation levels (17 × 10(9)/L). The predictability of using these cut off points in inpatient as well as early in-hospital death should be validated in future studies.

Item Type: Article
Additional Information: Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Uncontrolled Keywords: aged, 80 and over,female,great britain,hospital mortality,humans,inpatients,leukocyte count,male,models, statistical,oxygen,prospective studies,sodium,statistics as topic,urea
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
University of East Anglia > Faculty of Medicine and Health Sciences > Research Groups > Clinical Science and Trials
Faculty of Science > School of Computing Sciences
Depositing User: Pure Connector
Date Deposited: 20 Jan 2014 16:50
Last Modified: 25 Jul 2018 09:17
URI: https://ueaeprints.uea.ac.uk/id/eprint/46637
DOI: 10.1016/j.archger.2012.07.005

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