Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin
Intensive care unit (ICU) prognostic models can be used to predict mortality outcomes for critically ill patients who require intensive treatment due to the severity of their illness. These physiological and statistical-based models stratify patients according to their severity of illness and pro...
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| Format: | Thesis |
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2017
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| Online Access: | http://studentsrepo.um.edu.my/8174/ http://studentsrepo.um.edu.my/8174/2/All.pdf http://studentsrepo.um.edu.my/8174/6/rowena.pdf |
| _version_ | 1848773586015223808 |
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| author | Rowena Wong, Syn Yin |
| author_facet | Rowena Wong, Syn Yin |
| author_sort | Rowena Wong, Syn Yin |
| building | UM Research Repository |
| collection | Online Access |
| description | Intensive care unit (ICU) prognostic models can be used to predict mortality outcomes
for critically ill patients who require intensive treatment due to the severity of their
illness. These physiological and statistical-based models stratify patients according to
their severity of illness and provide an objective approach in predicting hospital
mortality risks. These models are useful tools in assisting clinicians in decision making,
interpretation of diagnosis and prescription of appropriate treatment options to patients.
They can also be effectively used for benchmarking purposes to evaluate and compare
the clinical performances of different ICUs and assist hospital administration in making
informed changes in resource allocations. Although these models are predominantly
used in developed countries, they are not that popular in developing countries due to
costs, facilities and resources considerations. In this study, the advantages, limitations
and evolutions of three selected well-established ICU prognostic systems were reviewed
and discussed. The Acute Physiology and Chronic Health Evaluation (APACHE IV)
model was chosen as the reference model in this study due to its promising potential as
a suitable benchmarking tool. The first objective of this study is to investigate the
validity of APACHE IV model in predicting mortality risk in a Malaysian ICU. A
prospective independent observational study was conducted at a single-centre
multidisciplinary ICU in Hospital Sultanah Aminah Johor Bahru (HSA ICU). External
validation of APACHE IV involved a cohort of 916 admissions to HSA ICU in the year
2009. APACHE IV was found to be not suitable for application in HSA ICU. Although
the model exhibited good discrimination, calibration was observed to be poor. The
model overestimated risk of death in HSA ICU, especially for mid- to high- risk patient
groups. The model's lack of fit was mainly attributed to differences in case mix and
patient management between APACHE IV and HSA ICU. The second objective of this research involves investigation of the significant factors that affect mortality risk in
HSA ICU and development of a prognostic model that is suitable for application in
HSA ICU. Bayesian Markov Chain Monte Carlo and decision tree approaches were
explored as alternative methods in the modelling of ICU risk of death, where five
different types of Bayesian models and a decision tree model were proposed in this
research. Although the performance of the decision tree model was comparable to the
Bayesian models, it was not as informative as the Bayesian models, especially in
predicting individual patient mortality risk. One of the Bayesian models was chosen as
the best model to be used as the future reference model in HSA ICU. This model
comprises seven variables (age, gender, Acute Physiological Score (APS), absence of
Glasgow Coma Scale score, mechanical ventilation, presence of chronic health and ICU
admission diagnoses) that are readily available in any intensive care unit setting. This
research has shown the promising potential of the Bayesian approach as an alternative
in the analysis and modelling of ICU mortality risks. |
| first_indexed | 2025-11-14T13:44:45Z |
| format | Thesis |
| id | um-8174 |
| institution | University Malaya |
| institution_category | Local University |
| last_indexed | 2025-11-14T13:44:45Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | um-81742020-08-16T23:44:47Z Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin Rowena Wong, Syn Yin RA Public aspects of medicine Intensive care unit (ICU) prognostic models can be used to predict mortality outcomes for critically ill patients who require intensive treatment due to the severity of their illness. These physiological and statistical-based models stratify patients according to their severity of illness and provide an objective approach in predicting hospital mortality risks. These models are useful tools in assisting clinicians in decision making, interpretation of diagnosis and prescription of appropriate treatment options to patients. They can also be effectively used for benchmarking purposes to evaluate and compare the clinical performances of different ICUs and assist hospital administration in making informed changes in resource allocations. Although these models are predominantly used in developed countries, they are not that popular in developing countries due to costs, facilities and resources considerations. In this study, the advantages, limitations and evolutions of three selected well-established ICU prognostic systems were reviewed and discussed. The Acute Physiology and Chronic Health Evaluation (APACHE IV) model was chosen as the reference model in this study due to its promising potential as a suitable benchmarking tool. The first objective of this study is to investigate the validity of APACHE IV model in predicting mortality risk in a Malaysian ICU. A prospective independent observational study was conducted at a single-centre multidisciplinary ICU in Hospital Sultanah Aminah Johor Bahru (HSA ICU). External validation of APACHE IV involved a cohort of 916 admissions to HSA ICU in the year 2009. APACHE IV was found to be not suitable for application in HSA ICU. Although the model exhibited good discrimination, calibration was observed to be poor. The model overestimated risk of death in HSA ICU, especially for mid- to high- risk patient groups. The model's lack of fit was mainly attributed to differences in case mix and patient management between APACHE IV and HSA ICU. The second objective of this research involves investigation of the significant factors that affect mortality risk in HSA ICU and development of a prognostic model that is suitable for application in HSA ICU. Bayesian Markov Chain Monte Carlo and decision tree approaches were explored as alternative methods in the modelling of ICU risk of death, where five different types of Bayesian models and a decision tree model were proposed in this research. Although the performance of the decision tree model was comparable to the Bayesian models, it was not as informative as the Bayesian models, especially in predicting individual patient mortality risk. One of the Bayesian models was chosen as the best model to be used as the future reference model in HSA ICU. This model comprises seven variables (age, gender, Acute Physiological Score (APS), absence of Glasgow Coma Scale score, mechanical ventilation, presence of chronic health and ICU admission diagnoses) that are readily available in any intensive care unit setting. This research has shown the promising potential of the Bayesian approach as an alternative in the analysis and modelling of ICU mortality risks. 2017-10 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/8174/2/All.pdf application/pdf http://studentsrepo.um.edu.my/8174/6/rowena.pdf Rowena Wong, Syn Yin (2017) Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/8174/ |
| spellingShingle | RA Public aspects of medicine Rowena Wong, Syn Yin Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin |
| title | Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin |
| title_full | Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin |
| title_fullStr | Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin |
| title_full_unstemmed | Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin |
| title_short | Modelling risks of hospital mortality for critically ill patients / Rowena Wong Syn Yin |
| title_sort | modelling risks of hospital mortality for critically ill patients / rowena wong syn yin |
| topic | RA Public aspects of medicine |
| url | http://studentsrepo.um.edu.my/8174/ http://studentsrepo.um.edu.my/8174/2/All.pdf http://studentsrepo.um.edu.my/8174/6/rowena.pdf |