Risk stratification modelling in post-operative abdominal aortic aneurysm patients

Introduction: the aim of the project was to test the hypothesis that 'the principles of risk stratification modelling can be successfully applied in a combined group of both elective and emergency AAA patients in the immediate post-operative setting'. Methods: the applicability of two exis...

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Main Author: Hadjianastassiou, Vassilis Georgiou
Published: University of Oxford 2006
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Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491903
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spelling ndltd-bl.uk-oai-ethos.bl.uk-4919032017-12-24T15:53:22ZRisk stratification modelling in post-operative abdominal aortic aneurysm patientsHadjianastassiou, Vassilis Georgiou2006Introduction: the aim of the project was to test the hypothesis that 'the principles of risk stratification modelling can be successfully applied in a combined group of both elective and emergency AAA patients in the immediate post-operative setting'. Methods: the applicability of two existing generic risk stratification models as predictors of in-hospital mortality was assessed in a combined group of elective and emergency post-operative abdominal aortic aneurysm patients, from 24 Intensive Care Units in the North-Thames. The better of the two models was chosen to develop a disease-specific risk stratification model (the APACHE-AAA) in this group of patients, using hierarchical logistic regression. The accuracy of this new model was compared to that of artificial neural networks and clinician predictions on the same patient population. The APACHE-AAA model was then externally validated in a patient population (from the Oxford/Lewisham Intensive Care Units) independent from the one used to develop it and the model's prognostic accuracy was also compared with existing risk stratification models (POSSUM or VBHOM based) advocated for use in abdominal aortic aneurysm patients. Results: The two generic risk stratification models did not predict outcome accurately when applied to the North-Thames population of patients. The disease-specific APACHE-AAA model subsequently developed, successfully predicted outcome in this patient population, as evidenced by all measures of internal validity such as callibration and discrimination properties and subgroup analyses. The APACHE-AAA and the corresponding artificial neural network models were found to be more accurate than Intensive Care resident doctors in quantifying prognosis. The artificial neural network model had inferior calibration properties to the logistic regression model. The APACHE-AAA model was successfully externally validated in the Oxford/Lewisham patient population. Existing POSSUM- and VBHOM-based risk stratification models did not model outcome accurately in this population. Conclusions: the principles of risk stratification modelling were successfully applied in post-operative abdominal aortic aneurysm patients. The APACHE-AAA model exemplifies the methodology required to formulate a national reference system for reliable assessments of the quality of intensive care, for evaluative research and in prognostication in this group of patients.616.1University of Oxfordhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491903Electronic Thesis or Dissertation
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topic 616.1
spellingShingle 616.1
Hadjianastassiou, Vassilis Georgiou
Risk stratification modelling in post-operative abdominal aortic aneurysm patients
description Introduction: the aim of the project was to test the hypothesis that 'the principles of risk stratification modelling can be successfully applied in a combined group of both elective and emergency AAA patients in the immediate post-operative setting'. Methods: the applicability of two existing generic risk stratification models as predictors of in-hospital mortality was assessed in a combined group of elective and emergency post-operative abdominal aortic aneurysm patients, from 24 Intensive Care Units in the North-Thames. The better of the two models was chosen to develop a disease-specific risk stratification model (the APACHE-AAA) in this group of patients, using hierarchical logistic regression. The accuracy of this new model was compared to that of artificial neural networks and clinician predictions on the same patient population. The APACHE-AAA model was then externally validated in a patient population (from the Oxford/Lewisham Intensive Care Units) independent from the one used to develop it and the model's prognostic accuracy was also compared with existing risk stratification models (POSSUM or VBHOM based) advocated for use in abdominal aortic aneurysm patients. Results: The two generic risk stratification models did not predict outcome accurately when applied to the North-Thames population of patients. The disease-specific APACHE-AAA model subsequently developed, successfully predicted outcome in this patient population, as evidenced by all measures of internal validity such as callibration and discrimination properties and subgroup analyses. The APACHE-AAA and the corresponding artificial neural network models were found to be more accurate than Intensive Care resident doctors in quantifying prognosis. The artificial neural network model had inferior calibration properties to the logistic regression model. The APACHE-AAA model was successfully externally validated in the Oxford/Lewisham patient population. Existing POSSUM- and VBHOM-based risk stratification models did not model outcome accurately in this population. Conclusions: the principles of risk stratification modelling were successfully applied in post-operative abdominal aortic aneurysm patients. The APACHE-AAA model exemplifies the methodology required to formulate a national reference system for reliable assessments of the quality of intensive care, for evaluative research and in prognostication in this group of patients.
author Hadjianastassiou, Vassilis Georgiou
author_facet Hadjianastassiou, Vassilis Georgiou
author_sort Hadjianastassiou, Vassilis Georgiou
title Risk stratification modelling in post-operative abdominal aortic aneurysm patients
title_short Risk stratification modelling in post-operative abdominal aortic aneurysm patients
title_full Risk stratification modelling in post-operative abdominal aortic aneurysm patients
title_fullStr Risk stratification modelling in post-operative abdominal aortic aneurysm patients
title_full_unstemmed Risk stratification modelling in post-operative abdominal aortic aneurysm patients
title_sort risk stratification modelling in post-operative abdominal aortic aneurysm patients
publisher University of Oxford
publishDate 2006
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491903
work_keys_str_mv AT hadjianastassiouvassilisgeorgiou riskstratificationmodellinginpostoperativeabdominalaorticaneurysmpatients
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