scholarly journals Graft survival prediction model after liver transplantation using post-transplantation aspartate aminotransferase, total bilirubin and prothrombin time: Comparison to conventional models

2021 ◽  
Vol 25 (1) ◽  
pp. S176-S176
Author(s):  
Jinsoo RHU ◽  
Jong Man KIM ◽  
Gyu-Seong CHOI ◽  
Jae-Won JOH
Keyword(s):  
Liver Transplantation ◽  
Prediction Model ◽  
Prothrombin Time ◽  
Graft Survival ◽  
Aspartate Aminotransferase ◽  
Total Bilirubin ◽  
Survival Prediction ◽  
Post Transplantation ◽  
Conventional Models

scholarly journals Prediction Model for Graft Survival After Liver Transplantation Using Aspartate Aminotransferase, Total Bilirubin and Coagulation Factor: ABC Model

2021 ◽  
Author(s):  
Jinsoo Rhu ◽  
Jong Man Kim ◽  
Kyunga Kim ◽  
Heejin Yoo ◽  
Gyu-Seong Choi ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Prediction Model ◽  
Graft Survival ◽  
Aspartate Aminotransferase ◽  
Living Donor ◽  
Total Bilirubin ◽  
Cox Regression ◽  
Coagulation Factor ◽  
Deceased Donor ◽  
Time Dependent

Abstract Background: This study was designed to build models predicting graft survival after liver transplantation.Methods: Cox regression model for predicting graft survival after liver transplantation using post-transplantation aspartate aminotransferase, total bilirubin, and international normalized ratio of prothrombin time was constructed. The model was compared with Model for Early Allograft Function Scoring (MEAF) and early allograft dysfunction (EAD) criteria.Results: The C-index of the model for living donor (0.73,CI=0.67-0.79) was significantly higher compared to those of both MEAF score (0.69,P=0.03) and EAD criteria. (0.66,P=0.001) while C-index for deceased donor (0.74,CI=0.65-0.83) was significantly higher compared to C-index of EAD criteria. (0.66,P=0.002) Time-dependent AUC at 4 weeks of living donor model (0.93,CI=0.86-0.99) was significantly higher compared to those of both MEAF score (0.87,P=0.02) and EAD criteria. (0.84,P=0.02) Time-dependent AUC at 4 weeks of deceased donor model (0.94,CI=0.89-1.00) was significantly higher compared to both MEAF score (0.82,P=0.02) and EAD criteria. (0.81,P<0.001) Internal validation for both living donor (C-index=0.68, AUC at 2 weeks=0.91, AUC at 4 weeks=0.92) and deceased donor (C-index=0.68, AUC at 2 weeks=0.86, AUC at 4 weeks=0.91) showed competent results. Conclusion: The prediction model for graft survival after liver transplantation showed high predictability and validity with higher predictability compared to traditional models.

scholarly journals Prediction model for early graft failure after liver transplantation using aspartate aminotransferase, total bilirubin and coagulation factor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jinsoo Rhu ◽  
Jong Man Kim ◽  
Kyunga Kim ◽  
Heejin Yoo ◽  
Gyu-Seong Choi ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Prediction Model ◽  
Aspartate Aminotransferase ◽  
Graft Failure ◽  
Living Donor ◽  
Total Bilirubin ◽  
Deceased Donor ◽  
Time Dependent ◽  
Early Graft ◽  
Early Graft Failure

AbstractThis study was designed to build models predicting early graft failure after liver transplantation. Cox regression model for predicting early graft failure after liver transplantation using post-transplantation aspartate aminotransferase, total bilirubin, and international normalized ratio of prothrombin time was constructed based on data from both living donor (n = 1153) and deceased donor (n = 359) liver transplantation performed during 2004 to 2018. The model was compared with Model for Early Allograft Function Scoring (MEAF) and early allograft dysfunction (EAD) with their C-index and time-dependent area-under-curve (AUC). The C-index of the model for living donor (0.73, CI = 0.67–0.79) was significantly higher compared to those of both MEAF (0.69, P = 0.03) and EAD (0.66, P = 0.001) while C-index for deceased donor (0.74, CI = 0.65–0.83) was only significantly higher compared to C-index of EAD. (0.66, P = 0.002) Time-dependent AUC at 2 weeks of living donor (0.96, CI = 0.91–1.00) and deceased donor (0.98, CI = 0.96–1.00) were significantly higher compared to those of EAD. (both 0.83, P < 0.001 for living donor and deceased donor) Time-dependent AUC at 4 weeks of living donor (0.93, CI = 0.86–0.99) was significantly higher compared to those of both MEAF (0.87, P = 0.02) and EAD. (0.84, P = 0.02) Time-dependent AUC at 4 weeks of deceased donor (0.94, CI = 0.89–1.00) was significantly higher compared to both MEAF (0.82, P = 0.02) and EAD. (0.81, P < 0.001). The prediction model for early graft failure after liver transplantation showed high predictability and validity with higher predictability compared to traditional models for both living donor and deceased donor liver transplantation.

scholarly journals Tailored Prediction Model of Survival after Liver Transplantation for Hepatocellular Carcinoma

2021 ◽  
Vol 10 (13) ◽  
pp. 2869
Author(s):  
Indah Jamtani ◽  
Kwang-Woong Lee ◽  
Yun-Hee Choi ◽  
Young-Rok Choi ◽  
Jeong-Moo Lee ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Prediction Model ◽  
Risk Group ◽  
Significant Risk ◽  
Risk Scores ◽  
Accurate Information ◽  
Survival Prediction ◽  
Good Prediction ◽  
Recurrence Rates

This study aimed to create a tailored prediction model of hepatocellular carcinoma (HCC)-specific survival after transplantation based on pre-transplant parameters. Data collected from June 2006 to July 2018 were used as a derivation dataset and analyzed to create an HCC-specific survival prediction model by combining significant risk factors. Separate data were collected from January 2014 to June 2018 for validation. The prediction model was validated internally and externally. The data were divided into three groups based on risk scores derived from the hazard ratio. A combination of patient demographic, laboratory, radiological data, and tumor-specific characteristics that showed a good prediction of HCC-specific death at a specific time (t) were chosen. Internal and external validations with Uno’s C-index were 0.79 and 0.75 (95% confidence interval (CI) 0.65–0.86), respectively. The predicted survival after liver transplantation for HCC (SALT) at a time “t” was calculated using the formula: [1 − (HCC-specific death(t’))] × 100. The 5-year HCC-specific death and recurrence rates in the low-risk group were 2% and 5%; the intermediate-risk group was 12% and 14%, and in the high-risk group were 71% and 82%. Our HCC-specific survival predictor named “SALT calculator” could provide accurate information about expected survival tailored for patients undergoing transplantation for HCC.

scholarly journals Survival and Complication of Liver Transplantation in Infants: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Yifu Hou ◽  
Xiaoxiao Wang ◽  
Hongji Yang ◽  
Shan Zhong
Keyword(s):  
Liver Transplantation ◽  
Survival Rate ◽  
Graft Survival ◽  
Patient Survival ◽  
Meta Analysis ◽  
Survival Rates ◽  
Surgical Techniques ◽  
Vascular Complications ◽  
Complication Rates ◽  
Post Transplantation

Background: Modern surgical techniques and scientific advancements have made liver transplant (LT) in infants feasible. However, there are only a small number of studies examining the short- as well as long-term outcomes of LT in this vulnerable subset of children.Methods: Comprehensive searches were done systematically through the PubMed, Scopus, and Google scholar databases. Studies that were retrospective record based or adopted a cohort approach and reported either patient survival rates or graft survival rates or complications of LT in infants were included in the meta-analysis. Statistical analysis was done using STATA version 13.0.Results: A total of 22 studies were included in the meta-analysis. The overall pooled patient survival rate at 1 year, &gt;1–5 years, and &gt;5 years post-transplantation was 85% (95% CI: 78-−92%), 71% (95% CI: 59–83%), and 80% (95% CI: 69–91%), respectively. The overall pooled graft survival rate at 1 year, &gt;1–5 years, and &gt;5 years post-transplantation was 72% (95% CI: 68–76%), 62% (95% CI: 46–78%), and 71% (95% CI: 56–86%), respectively. The overall pooled rate for vascular complications, need for re-transplantation, biliary complications, and infection/sepsis was 12% (95% CI: 10–15%), 16% (95% CI: 12–20%), 15% (95% CI: 9–21%), and 50% (95% CI: 38–61%), respectively.Conclusion: The current meta-analysis showed modest patient and graft survival rates for infant liver transplantation. However, the complication rates related to infection/sepsis were high. More comprehensive evidence is required from studies with larger sample sizes and a longer duration of follow-up.

scholarly journals Early elevated serum gamma glutamyl transpeptidase after liver transplantation is associated with better survival

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 85 ◽  
Author(s):  
Edris M Alkozai ◽  
Ton Lisman ◽  
Robert J Porte ◽  
Maarten W Nijsten
Keyword(s):  
Liver Transplantation ◽  
Aspartate Aminotransferase ◽  
Alanine Aminotransferase ◽  
Total Bilirubin ◽  
Elevated Serum ◽  
Glutathione Metabolism ◽  
Gamma Glutamyl Transpeptidase ◽  
Gamma Glutamyl ◽  
Increased Risk ◽  
Glutamyl Transpeptidase

Background: Gamma glutamyl transpeptidase (GGT) is a membrane bound enzyme that plays a key role in the synthesis of the antioxidant glutathione. Epidemiological studies have linked high GGT with an increased risk of morbidity and cardiovascular mortality. In contrast, GGT is usually elevated in liver transplant recipients that experience good outcomes.Aims: To study if and how GGT is correlated with mortality following liver transplantation.Methods: We analyzed the prognostic relevance of serum GGT levels during the early and late postoperative period after liver transplantation in 522 consecutive adults. We also studied alanine aminotransferase, aspartate aminotransferase, and total bilirubin levels.Results: Early after transplantation, the peak median (interquartile range) GGT levels were significantly higher in patients who survived more than 90 days compared to non-survivors: 293 (178-464) vs. 172 (84-239) U/l, p<0.0001. In contrast, late after transplantation, GGT levels were significantly lower in patients who survived more than 5 years than those who did not (p<0.01). The pattern of GGT levels also differed from those of alanine aminotransferase, aspartate aminotransferase, and total bilirubin early after transplantation, while these patterns were congruent late after transplantation. Kaplan-Meier survival analysis showed that early after transplantation the higher the GGT levels, the better the 90-day survival (p<0.001). In contrast, late after transplantation, higher GGT levels were associated with a lower 5-year survival (p<0.001).Conclusions:  These paradoxical findings may be explained by the time-dependent role of GGT in glutathione metabolism. Immediate postoperative elevation of GGT may indicate a physiological systemic response while chronic elevation reflects a pathological response.

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