TY - JOUR
T1 - The combination of indocyanine green clearance test and model for end-stage liver disease score predicts early graft outcome after liver transplantation
AU - Yunhua, Tang
AU - Weiqiang, Ju
AU - Maogen, Chen
AU - Sai, Yang
AU - Zhiheng, Zhang
AU - Dongping, Wang
AU - Zhiyong, Guo
AU - Xiaoshun, He
N1 - Funding Information:
Acknowledgements This study was supported by the National High Technology Research and Development Program of China (863 Program) (2012AA021007 & 2012AA021008), the Research Fund for the Doctoral Program of Higher Education of China by Ministry of Education (20110171120077), the National Natural Science Foundation of China (81373156 and 81471583), the Special Fund for Science Research by Ministry of Health (201302009), the Key Clinical Specialty Construction Project of National Health and Family Planning Commission of the People’s Republic of China, the Guangdong Provincial Key Laboratory Construction Projection on Organ Donation and Transplant Immunology (2013A061401007), Guangdong Provincial international Cooperation Base of Science and Technology (Organ Transplantation) (2015B050501002), Guangdong Provincial Natural Science Funds for Distinguished Young Scholars (2015A030306025), Special support program for training high level talents in Guangdong Province (2015TQ01R168), and Pearl River Nova Program of Guangzhou (201506010014).
Publisher Copyright:
© 2017, Springer Science+Business Media B.V.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - Early allograft dysfunction (EAD) and early postoperative complications are two important clinical endpoints when evaluating clinical outcomes of liver transplantation (LT). We developed and validated two ICGR15-MELD models in 87 liver transplant recipients for predicting EAD and early postoperative complications after LT by incorporating the quantitative liver function tests (ICGR15) into the MELD score. Eighty seven consecutive patients who underwent LT were collected and divided into a training cohort (n = 61) and an internal validation cohort (n = 26). For predicting EAD after LT, the area under curve (AUC) for ICGR15-MELD score was 0.876, with a sensitivity of 92.0% and a specificity of 75.0%, which is better than MELD score or ICGR15 alone. The recipients with a ICGR15-MELD score ≥0.243 have a higher incidence of EAD than those with a ICGR15-MELD score <0.243 (P <0.001). For predicting early postoperative complications, the AUC of ICGR15-MELD score was 0.832, with a sensitivity of 90.9% and a specificity of 71.0%. Those recipients with an ICGR15-MELD score ≥0.098 have a higher incidence of early postoperative complications than those with an ICGR15-MELD score <0.098 (P < 0.001). Finally, application of the two ICGR15-MELD models in the validation cohort still gave good accuracy (AUC, 0.835 and 0.826, respectively) in predicting EAD and early postoperative complications after LT. The combination of quantitative liver function tests (ICGR15) and the preoperative MELD score is a reliable and effective predictor of EAD and early postoperative complications after LT, which is better than MELD score or ICGR15 alone.
AB - Early allograft dysfunction (EAD) and early postoperative complications are two important clinical endpoints when evaluating clinical outcomes of liver transplantation (LT). We developed and validated two ICGR15-MELD models in 87 liver transplant recipients for predicting EAD and early postoperative complications after LT by incorporating the quantitative liver function tests (ICGR15) into the MELD score. Eighty seven consecutive patients who underwent LT were collected and divided into a training cohort (n = 61) and an internal validation cohort (n = 26). For predicting EAD after LT, the area under curve (AUC) for ICGR15-MELD score was 0.876, with a sensitivity of 92.0% and a specificity of 75.0%, which is better than MELD score or ICGR15 alone. The recipients with a ICGR15-MELD score ≥0.243 have a higher incidence of EAD than those with a ICGR15-MELD score <0.243 (P <0.001). For predicting early postoperative complications, the AUC of ICGR15-MELD score was 0.832, with a sensitivity of 90.9% and a specificity of 71.0%. Those recipients with an ICGR15-MELD score ≥0.098 have a higher incidence of early postoperative complications than those with an ICGR15-MELD score <0.098 (P < 0.001). Finally, application of the two ICGR15-MELD models in the validation cohort still gave good accuracy (AUC, 0.835 and 0.826, respectively) in predicting EAD and early postoperative complications after LT. The combination of quantitative liver function tests (ICGR15) and the preoperative MELD score is a reliable and effective predictor of EAD and early postoperative complications after LT, which is better than MELD score or ICGR15 alone.
KW - Early allograft dysfunction
KW - Early postoperative complications
KW - ICGR15
KW - Liver transplantation
KW - MELD score
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U2 - 10.1007/s10877-017-0051-x
DO - 10.1007/s10877-017-0051-x
M3 - Article
C2 - 28831767
AN - SCOPUS:85027887234
VL - 32
SP - 471
EP - 479
JO - Journal of Clinical Monitoring and Computing
JF - Journal of Clinical Monitoring and Computing
SN - 1387-1307
IS - 3
ER -