Outcome following valve surgery in Australia: Development of an enhanced database module

Background: Valvular heart disease, including rheumatic heart disease (RHD), is an important cause of heart disease globally. Management of advanced disease can include surgery and other interventions to repair or replace affected valves. This article summarises the methodology of a study that will...

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Main Authors: Russell, E., Reid, Christopher, Walsh, W., Brown, A., Maguire, G.
Format: Journal Article
Published: BioMed Central 2017
Online Access:http://hdl.handle.net/20.500.11937/49786
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author Russell, E.
Reid, Christopher
Walsh, W.
Brown, A.
Maguire, G.
author_facet Russell, E.
Reid, Christopher
Walsh, W.
Brown, A.
Maguire, G.
author_sort Russell, E.
building Curtin Institutional Repository
collection Online Access
description Background: Valvular heart disease, including rheumatic heart disease (RHD), is an important cause of heart disease globally. Management of advanced disease can include surgery and other interventions to repair or replace affected valves. This article summarises the methodology of a study that will incorporate enhanced data collection systems to provide additional insights into treatment choice and outcome for advanced valvular disease including that due to RHD. Methods: An enhanced data collection system will be developed linking an existing Australian cardiac surgery registry to more detailed baseline co-morbidity, medication, echocardiographic and hospital separation data to identify predictors of morbidity and mortality outcome following valve surgery. Discussion: This project aims to collect and incorporate more detailed information regarding pre and postoperative factors and subsequent morbidity. We will use this to provide additional insights into treatment choice and outcome. © 2017 The Author(s).
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institution Curtin University Malaysia
institution_category Local University
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publishDate 2017
publisher BioMed Central
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spelling curtin-20.500.11937-497862017-09-13T15:35:35Z Outcome following valve surgery in Australia: Development of an enhanced database module Russell, E. Reid, Christopher Walsh, W. Brown, A. Maguire, G. Background: Valvular heart disease, including rheumatic heart disease (RHD), is an important cause of heart disease globally. Management of advanced disease can include surgery and other interventions to repair or replace affected valves. This article summarises the methodology of a study that will incorporate enhanced data collection systems to provide additional insights into treatment choice and outcome for advanced valvular disease including that due to RHD. Methods: An enhanced data collection system will be developed linking an existing Australian cardiac surgery registry to more detailed baseline co-morbidity, medication, echocardiographic and hospital separation data to identify predictors of morbidity and mortality outcome following valve surgery. Discussion: This project aims to collect and incorporate more detailed information regarding pre and postoperative factors and subsequent morbidity. We will use this to provide additional insights into treatment choice and outcome. © 2017 The Author(s). 2017 Journal Article http://hdl.handle.net/20.500.11937/49786 10.1186/s12913-017-2002-0 http://creativecommons.org/licenses/by/4.0/ BioMed Central fulltext
spellingShingle Russell, E.
Reid, Christopher
Walsh, W.
Brown, A.
Maguire, G.
Outcome following valve surgery in Australia: Development of an enhanced database module
title Outcome following valve surgery in Australia: Development of an enhanced database module
title_full Outcome following valve surgery in Australia: Development of an enhanced database module
title_fullStr Outcome following valve surgery in Australia: Development of an enhanced database module
title_full_unstemmed Outcome following valve surgery in Australia: Development of an enhanced database module
title_short Outcome following valve surgery in Australia: Development of an enhanced database module
title_sort outcome following valve surgery in australia: development of an enhanced database module
url http://hdl.handle.net/20.500.11937/49786