LSTM Home > LSTM Research > LSTM Online Archive

Prediction of hospital mortality from admission laboratory data and patient age: A simple model

Asadollahi, Khairollah, Hastings, Ian ORCID: https://orcid.org/0000-0002-1332-742X, Gill, Geoff and Beeching, Nicholas ORCID: https://orcid.org/0000-0002-7019-8791 (2011) 'Prediction of hospital mortality from admission laboratory data and patient age: A simple model'. Emergency Medicine Australasia, Vol 23, Issue 3, pp. 354-363.

Full text not available from this repository.

Abstract

Objective: To devise a simple clinical scoring system, using age of patients and laboratory data available on admission, to predict in-hospital mortality of unselected medical and surgical patients.
Methods: All patients admitted as emergencies to a large teaching hospital in Liverpool in the 5 months July-November 2004 were reviewed retrospectively, identifying all who died in hospital and controls who survived. Laboratory data available on admission were extracted to form a derivation dataset. Factors that predicted mortality were determined using logistic regression analysis and then used to construct models tested using receiver operating characteristic curves. Models were simplified to include only seven data items, with minimal loss of predictive efficiency. The simplified model was tested in a second validation dataset of all patients admitted to the same hospital in October and November 2004.
Results: The derivation dataset included 550 patients who died and 1100 controls. After logistic regression comparisons, 22 dummy variables were given weightings in discriminant analysis and used to create a receiver operating characteristic curve with area under the curve (AUC) of 0.884. The model was simplified to include the seven most discriminant variables which can each be assigned scores 2, 3 or 4 to form an index predicting outcome: a validation dataset contained 4828 patients (overall mortality 4.7%), showed this simplified scoring systems accurately predicted mortality with AUC 0.848, compared with an AUC of 0.861 in a model containing all 23 original variables.
Conclusion: A simple scoring system accurately predicts in-hospital mortality of unselected hospital patients, using age of patient and a small number of laboratory parameters available very soon after admission

Item Type: Article
Uncontrolled Keywords: acute admissions, laboratory data, mortality, outcome, scoring system
Subjects: W General Medicine. Health Professions > Health Services. Patients and Patient Advocacy > W 84 Health services. Delivery of health care
WA Public Health > Statistics. Surveys > WA 950 Theory or methods of medical statistics. Epidemiologic methods
WB Practice of Medicine > WB 100 General works
Faculty: Department: Groups (2002 - 2012) > Clinical Group
Groups (2002 - 2012) > Molecular & Biochemical Parasitology Group
Digital Object Identifer (DOI): https://doi.org/10.1111/j.1742-6723.2011.01410.x
Depositing User: Users 43 not found.
Date Deposited: 14 Jul 2011 14:41
Last Modified: 19 Sep 2019 11:29
URI: https://archive.lstmed.ac.uk/id/eprint/2102

Statistics

View details

Actions (login required)

Edit Item Edit Item