Αρχειοθήκη ιστολογίου

Αλέξανδρος Γ. Σφακιανάκης
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5
Άγιος Νικόλαος Κρήτη 72100
2841026182
6032607174

Τρίτη 27 Φεβρουαρίου 2018

Predicting Liver Allograft Discard: The Discard Risk Index

AbstractBackgroundAn index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. Aim: to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer.MethodsUsing univariate and multivariate analyses on a training set of 72,297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables.ResultsWe identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dl (OR 25.23, CI 17.32-36.77), donation after cardiac death (OR 14.13, CI 13.30-15.01), and total bilirubin 5 – 10 mg/dl (OR 7.57, CI 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C-statistic of 0.80. We internally validated the model with a validation set of 37,243 deceased donors and also achieved a 0.80 C-statistic. At a DSRI at the 90th percentile, the discard rate was 50% (OR 32.34 CI 28.63-36.53), while at a DSRI at the 10th percentile only 3% of livers were discarded.ConclusionsThe use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers in order to maximize the donor yield and expedite allocation. Background An index that predicts liver allograft discard can effectively grade allografts and can be used to preferentially allocate marginal allografts to aggressive centers. Aim: to devise an index to predict liver allograft discard using only risk factors available at the time of initial DonorNet offer. Methods Using univariate and multivariate analyses on a training set of 72,297 deceased donors, we identified independent risk factors for liver allograft discard. Multiple imputation was used to account for missing variables. Results We identified 15 factors as significant predictors of liver allograft discard; the most significant risk factors were: total bilirubin > 10 mg/dl (OR 25.23, CI 17.32-36.77), donation after cardiac death (OR 14.13, CI 13.30-15.01), and total bilirubin 5 – 10 mg/dl (OR 7.57, CI 6.32-9.05). The resulting Discard Risk Index (DSRI) accurately predicted the risk of liver discard with a C-statistic of 0.80. We internally validated the model with a validation set of 37,243 deceased donors and also achieved a 0.80 C-statistic. At a DSRI at the 90th percentile, the discard rate was 50% (OR 32.34 CI 28.63-36.53), while at a DSRI at the 10th percentile only 3% of livers were discarded. Conclusions The use of the DSRI can help predict liver allograft discard. The DSRI can be used to effectively grade allografts and preferentially allocate marginal allografts to aggressive centers in order to maximize the donor yield and expedite allocation. Corresponding Author: Abbas Rana, MD, Michael E. DeBakey Department of Surgery, Division of Abdominal Transplantation and Division of Hepatobiliary Surgery, Baylor College of Medicine, 6620 Main Street, Suite 1425, Houston, Texas 77030, USA. Telephone: (713) 321–8423. Fax: (713) 610–2479. abbas.rana@bcm.edu Authorship Page Abbas Rana MD: Study concept and design, acquisition of data, analysis and interpretation of data, drafting of manuscript Rohini R. Sigireddi BA: Drafting of manuscript Karim J. Halazun MD: Critical revision of manuscript Aishwarya Kothare: Critical revision of manuscript Meng-Fen Wu MS: Critical revision of manuscript Hao Liu PhD: Critical revision of manuscript Michael L. Kueht MD: Critical revision of manuscript John M. Vierling MD: Drafting of manuscript Norman L. Sussman MD: Critical revision of manuscript Ayse L. Mindikoglu MD: Critical revision of manuscript Tamir Miloh MD: Critical revision of manuscript N. Thao N. Galvan MD: Critical revision of manuscript Ronald T. Cotton MD: Critical revision of manuscript Christine A. O'Mahony MD: Critical revision of manuscript John A. Goss MD: Drafting of manuscript Disclosures: None Funding: None Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

http://ift.tt/2sX1T8z

Δεν υπάρχουν σχόλια:

Δημοσίευση σχολίου