Source:http://linkedlifedata.com/resource/pubmed/id/15350002
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
9
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| pubmed:dateCreated |
2004-9-6
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| pubmed:abstractText |
Hepatitis C virus (HCV)-associated liver disease is the most common indication for liver transplantation (LT). There are, however, no long-term (>5 year) studies of comparative outcomes for recipients with HCV infection, and no models capable of identifying recipients with HCV infection at greatest risk for adverse outcomes. We prospectively determined: 1) long-term outcomes, and 2) whether pretransplant patient or donor variables can be used to predict death and/or graft loss in recipients with HCV infection. A total of 165 HCV-infected recipients were eligible for this study. Pretransplant donor and recipient characteristics and patient and graft survival data were prospectively collected. Model building for outcomes was carried out using logistic regression. Receiver operating characteristic curves for different models were created and compared. Median follow-up was 8.5 years. Adjusted 10 year graft survival was 64% for recipients with HCV infection and 51% for uninfected recipients. A model incorporating pretransplant HCV ribonucleic acid (RNA), cytomegalovirus immunoglobulin (CMV IgG) serostatus, creatinine, bilirubin, prothrombin time international ratio (INR), recipient age, and donor age was developed to identify recipients at greatest risk of short-term mortality or graft loss (area under receiver operating characteristic curve = .83) In conclusion, long-term outcomes following LT for recipients with HCV infection are comparable to those for recipients undergoing LT for other indications. HCV-infected recipients at greatest risk for short-term mortality and graft loss can be identified using several readily identifiable pretransplant variables. Long-term death and graft loss specifically secondary to recurrence of HCV appears, however, to be determined primarily by factors other than those included in this analysis.
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| pubmed:grant | |
| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
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| pubmed:month |
Sep
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| pubmed:issn |
1527-6465
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| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
10
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
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| pubmed:pagination |
1120-30
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| pubmed:dateRevised |
2007-11-14
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| pubmed:meshHeading |
pubmed-meshheading:15350002-Adult,
pubmed-meshheading:15350002-Female,
pubmed-meshheading:15350002-Genotype,
pubmed-meshheading:15350002-Graft Survival,
pubmed-meshheading:15350002-Hepacivirus,
pubmed-meshheading:15350002-Hepatitis C,
pubmed-meshheading:15350002-Humans,
pubmed-meshheading:15350002-Likelihood Functions,
pubmed-meshheading:15350002-Liver Transplantation,
pubmed-meshheading:15350002-Logistic Models,
pubmed-meshheading:15350002-Male,
pubmed-meshheading:15350002-Middle Aged,
pubmed-meshheading:15350002-Prospective Studies,
pubmed-meshheading:15350002-ROC Curve,
pubmed-meshheading:15350002-Risk Assessment,
pubmed-meshheading:15350002-Sensitivity and Specificity,
pubmed-meshheading:15350002-Survival Analysis,
pubmed-meshheading:15350002-Treatment Outcome
|
| pubmed:year |
2004
|
| pubmed:articleTitle |
Long-term results and modeling to predict outcomes in recipients with HCV infection: results of the NIDDK liver transplantation database.
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| pubmed:affiliation |
charlton.michael@mayo.edu
|
| pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.
|