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Qu, Z; Gwiasda, J; Schrem, H; Kaltenborn, A; Harries, L; Beneke, J; Amelung, V; Krauth, C.
Evaluation of published assessment tools for comorbidity in liver transplantation: a systematic review protocol.
BMJ Open. 2018; 8(6): e021181-e021181.
Doi: 10.1136/bmjopen-2017-021181
[OPEN ACCESS]
Web of Science
PubMed
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- Co-authors Med Uni Graz
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Schrem Harald Heinrich
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- Abstract:
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Liver transplantation is considered the best therapy option for end-stage liver disease. Different factors including recipient comorbidity at time of transplantation are supposed to have substantial impact on outcomes. Although several studies have focused on comorbidity assessment indices for liver transplant recipients, there is no systematic review available on the methodological details and prognostic accuracy of these instruments. The aim of this study is to systematically review recipient comorbidity assessment indices in the context of liver transplantation.
PubMed, Embase, Web of Science and PsyINFO databases will be searched. Studies describing, using or evaluating specific assessment tools to predict the effect of comorbidity on clinical outcomes after liver transplantation will be included. The selection will be conducted independently by two reviewers. The study characteristics and methodological information on published comorbidity assessment tools will be extracted into a predefined structural table. This approach will be deployed to systematically extract information on the validity, reliability and practical feasibility of investigated comorbidity assessment tools for comparative evaluation. Narrative information synthesis will be conducted, and additional meta-analytical comparison will be performed, if appropriate.
All data are collected from published literature. Thus, formal ethics review for the research is not required. The findings of this systematic review will be published in a peer-reviewed journal and presented at relevant conferences. The results of this systematic review will be highly relevant for further research on prognostic models, clinical decision making and optimisation of donor organ allocation.
CRD42017074609.
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