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Predicting short-term survival after liver transplantation on eight score systems: a national report from China Liver Transplant Registry

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ABSTRACT

To compare the performance of eight score systems (MELD, uMELD, MELD-Na. iMELD, UKELD, MELD-AS, CTP, and mCTP) in predicting the post-transplant mortality, we analyzed the data of 6,014 adult cirrhotic patients who underwent liver transplantation between January 2003 and December 2010 from the China Liver Transplant Registry database. In hepatitis B virus (HBV) group, MELD, uMELD and MELD-AS showed good predictive accuracies at 3-month mortality after liver transplantation; by comparison with other five models, MELD presented the best ability in predicting 3-month, 6-month and 1-year mortality, showing a significantly better predictive ability than UKELD and iMELD. In hepatitis C virus and Alcohol groups, the predictive ability did not differ significantly between MELD and other models. Patient survivals in different MELD categories were of statistically significant difference. Among patients with MELD score >35, a new prognostic model based on serum creatinine, need for hemodialysis and moderate ascites could identify the sickest one. In conclusion, MELD is superior to other score systems in predicting short-term post-transplant survival in patients with HBV-related liver disease. Among patients with MELD score >35, a new prognostic model can identify the sickest patients who should be excluded from waiting list to prevent wasteful transplantation.

No MeSH data available.


Probability of 3-month death (PD3m) following liver transplantation in patients with MELD score >35.
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f4: Probability of 3-month death (PD3m) following liver transplantation in patients with MELD score >35.

Mentions: Among 515 patients with MELD > 35, 300 were selected for the construction of prognostic model and the other 215 were used as a validation group. Patients were selected according to the transplant time. Binary logistic regression analysis showed that serum creatinine, need for hemodialysis and moderate ascites were independent risk factors of 3-month mortality after transplantation (Table 3). A prognostic scoring was then established according to the multivariate analysis: risk score = −2.3090 + 0.3600 × Creatinine (mg/dl) + 0.5493 × (need for hemodialysis [0, 1]) + 0.7000 × (moderate ascites [0, 1]). Probability of Death at 3-month following liver transplantation (PD3m) = EXP (risk score)/[1 + EXP (risk score)] (Fig. 4). This model had a good fit (P = 0.521 to reject model fit) and predicted 3-month mortality after transplantation much better than MELD both in this group (AUC: 0.703 vs. 0.590, P = 0.023) and validation group (AUC: 0.737 vs. 0.589, P = 0.017). Patients in validation group with a high PD3m score (>0.5) had a 3-month mortality rate of 66.7% (24/36).


Predicting short-term survival after liver transplantation on eight score systems: a national report from China Liver Transplant Registry
Probability of 3-month death (PD3m) following liver transplantation in patients with MELD score >35.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5304182&req=5

f4: Probability of 3-month death (PD3m) following liver transplantation in patients with MELD score >35.
Mentions: Among 515 patients with MELD > 35, 300 were selected for the construction of prognostic model and the other 215 were used as a validation group. Patients were selected according to the transplant time. Binary logistic regression analysis showed that serum creatinine, need for hemodialysis and moderate ascites were independent risk factors of 3-month mortality after transplantation (Table 3). A prognostic scoring was then established according to the multivariate analysis: risk score = −2.3090 + 0.3600 × Creatinine (mg/dl) + 0.5493 × (need for hemodialysis [0, 1]) + 0.7000 × (moderate ascites [0, 1]). Probability of Death at 3-month following liver transplantation (PD3m) = EXP (risk score)/[1 + EXP (risk score)] (Fig. 4). This model had a good fit (P = 0.521 to reject model fit) and predicted 3-month mortality after transplantation much better than MELD both in this group (AUC: 0.703 vs. 0.590, P = 0.023) and validation group (AUC: 0.737 vs. 0.589, P = 0.017). Patients in validation group with a high PD3m score (>0.5) had a 3-month mortality rate of 66.7% (24/36).

View Article: PubMed Central - PubMed

ABSTRACT

To compare the performance of eight score systems (MELD, uMELD, MELD-Na. iMELD, UKELD, MELD-AS, CTP, and mCTP) in predicting the post-transplant mortality, we analyzed the data of 6,014 adult cirrhotic patients who underwent liver transplantation between January 2003 and December 2010 from the China Liver Transplant Registry database. In hepatitis B virus (HBV) group, MELD, uMELD and MELD-AS showed good predictive accuracies at 3-month mortality after liver transplantation; by comparison with other five models, MELD presented the best ability in predicting 3-month, 6-month and 1-year mortality, showing a significantly better predictive ability than UKELD and iMELD. In hepatitis C virus and Alcohol groups, the predictive ability did not differ significantly between MELD and other models. Patient survivals in different MELD categories were of statistically significant difference. Among patients with MELD score >35, a new prognostic model based on serum creatinine, need for hemodialysis and moderate ascites could identify the sickest one. In conclusion, MELD is superior to other score systems in predicting short-term post-transplant survival in patients with HBV-related liver disease. Among patients with MELD score >35, a new prognostic model can identify the sickest patients who should be excluded from waiting list to prevent wasteful transplantation.

No MeSH data available.