Objective:To analyze the efficacy and safety of modified associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) in the treatment of patients with primary liver cancer.Methods:Clinical data of 83 patients with hepatocellular carcinoma (HCC) undergoing hemihepatectomy in the Department of Hepatobiliary and Pancreatic Tumor Surgery of Gansu Provincial Cancer Hospital between January 2022 and November 2023 were retrospectively analyzed, including 53 males and 30 females, aged (54.0±6.5) years. According to the treatment protocol, patients were divided into the control group ( n=41), in which patients underwent traditional ALPPS, and the observation group ( n=42), in which patients underwent modified ALPPS (occlusion of portal venous branch using vascular clips, combined with radiofrequency ablation for physical separation of the diseased lobe, without liver mobilization). The completion rate of staged surgery, interval between surgeries, future liver remnant (FLR) growth rate at 7 days after first-stage surgery, alanine transaminase (ALT) and aspartate transaminase (AST) levels at 5 days after fisrt-stage surgery, and postoperative complications (ascites, nausea, and vomiting, etc.) were compared between the groups. Results:The completion rate of staged surgery was 95.2% (40/42) in the observation group and 90.2% (37/41) in the control group ( χ2=0.62, P=0.431). The ALT and AST levels at 5 days after first-stage surgery were (550.4±86.0) U/L and (327.1±52.8) U/L in the observation group, respectively, which were significantly lower than those in the control group (861.6±106.3) U/L and (533.8±73.7) U/L, respectively ( t=13.13 and P<0.001, t=12.93 and P<0.001). The FLR growth rate were higher in the observation group than that in the control group [(80.4±10.3)% vs (49.3±5.7)%; t=13.13, P<0.001] and the interval between procedures were also shorter in the observation group (10.9±2.1 vs 22.4±4.8, d; t=9.65, P<0.001). The intraoperative blood loss of the first-stage surgery was lower in the observation group than that in the control group (350.5±45.2 vs 825.5±21.7, ml; t=21.43, P<0.001). The total complication rates after the first-stage surgery were 11.9% (5/42) in the observation group and 19.5% (8/41) in the control group, while after the second-stage surgery, the complication rates were 7.5% (3/40) and 18.9% (7/37), respectively, with no statistically significant differences ( χ2=0.65 and P=0.419, χ2=1.81 and 0.177, respectively). Conclusion:The modified ALPPS offers better postoperative liver function, reduced surgical trauma, accelerated FLR growth, and a shorter interval between procedures, demonstrating a favorable safety in the treatment of primary liver cancer.

Objective:To study the expression of transcription factor 12 (TCF12) in colorectal cancer cells, and to explore the effects of TCF12 on proliferation, migration, and aerobic glycolysis of colorectal cancer HT-29 cells and its mechanism.Methods:After culturing, HT-29 cells were divided into a control group and a knockdown group based on treatment conditions, and were transfected with 50 nmol/L of small interfering RNA (siRNA) and TCF12 siRNA, respectively. On the basis of the knockdown group, HT-29 cells were infected with adenovirus vector overexpressing αB-crystallin (CRYAB) with an infection multiplicity of 50, which was set as the overexpression group. The relative expression of TCF12 in HT-29 cells was detected using Western blotting. The cell survival rate, cell clone number and cell migration number of HT-29 cells were detected using cell counting kit-8, clone formation assay and cell invasion assay, respectively. Glucose uptake, relative lactic acid production and adenosine triphosphate (ATP) level of HT-29 cells were detected by related kits. The relative expression of glucose transporter 1 (GLUT1), hexokinase 2 (HK2), lactate dehydrogenase A (LDHA), CRYAB, phosphorylated phosphoinositide 3-kinase (p-PI3K)/PI3K and phosphorylated protein kinase B (p-Akt)/Akt proteins were detected by Western blotting. Data were analyzed by an independent sample t test or one-way analysis of variance. Results:The relative expression of TCF12 protein in the knockdown group was lower than that in the control group (0.14±0.03 vs 0.99±0.05, t=7.526, P<0.01). The cell survival rate, the cell clone number and the cell migration number per unit field of view in the knockdown group were all lower than those in the control group [(60.00±5.10)% vs (94.67±2.08)%, t=15.368, P<0.01; 52±5 vs 148±6, t=23.164, P<0.01; 26±4 vs 78±4, t=18.265, P<0.01]. Glucose uptake, relative lactic acid production and ATP level in the knockdown group were lower than those in the control group [(0.41±0.04) mg/ml vs (1.27±0.07) mg/ml, t=22.567, P<0.01; (55.00±6.08)% vs (98.00±4.58)%, t=18.257, P<0.01; (8.33±1.25) μmol/L vs (19.67±1.70) μmol/L, t=13.165, P<0.01]. The relative expression of GLUT1, HK2 and LDHA proteins in the knockdown group were all lower than those in the control group (0.38±0.05 vs 0.98±0.09, 0.12±0.03 vs 0.97±0.04, and 0.64±0.05 vs 0.99±0.06, all P<0.01). The relative expression of CRYAB, p-PI3K/PI3K and p-Akt/Akt proteins in the knockdown group were all lower than those in the control group (0.18±0.04 vs 0.92±0.03, t=11.265, P<0.01; 0.34±0.10 vs 0.92±0.04, t=18.257, P<0.01; 0.51±0.04 vs 1.11±0.07, t=13.165, P<0.01). The cell survival rate, the cell clone number and the cell migration number per unit field of view p in the overexpression group were all higher than those in the knockdown group [(97.00±6.56)% vs (45.67±6.03)%, t=12.762, P<0.01; 136.67±5.69 vs 44.33±6.03, t=22.585, P<0.01; 57.33±5.51 vs 24.67±4.51, t=25.312, P<0.01]. Glucose uptake, relative lactic acid production and ATP level in the overexpression group were all higher than those in the knockdown group [(1.25±0.08) mg/ml vs (0.51±0.05) mg/ml, t=22.164, P<0.01; (44.00±3.06)% vs (19.67±3.06)%, t=25.822, P<0.01; (21.00±2.00) μmol/L vs (9.33±1.53) μmol/L, t=18.876, P<0.01]. The relative expression level of CRYAB, p-PI3K/PI3K and p-Akt/Akt proteins in the overexpression group were all higher than those in the knockdown group (6.00±0.63 vs 0.96±0.24, t=12.79, P<0.01; 2.13±0.25 vs 0.10±0.03, t=13.90, P<0.01; 2.07±0.21 vs 0.46±0.04, t=13.17, P<0.01). Conclusions:TCF12 may promote the proliferation, migration and aerobic glycolysis of colorectal cancer cells by regulating CRYAB/PI3K/Akt signaling pathway.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective:To analyze the efficacy and safety of modified associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) in the treatment of patients with primary liver cancer.Methods:Clinical data of 83 patients with hepatocellular carcinoma (HCC) undergoing hemihepatectomy in the Department of Hepatobiliary and Pancreatic Tumor Surgery of Gansu Provincial Cancer Hospital between January 2022 and November 2023 were retrospectively analyzed, including 53 males and 30 females, aged (54.0±6.5) years. According to the treatment protocol, patients were divided into the control group ( n=41), in which patients underwent traditional ALPPS, and the observation group ( n=42), in which patients underwent modified ALPPS (occlusion of portal venous branch using vascular clips, combined with radiofrequency ablation for physical separation of the diseased lobe, without liver mobilization). The completion rate of staged surgery, interval between surgeries, future liver remnant (FLR) growth rate at 7 days after first-stage surgery, alanine transaminase (ALT) and aspartate transaminase (AST) levels at 5 days after fisrt-stage surgery, and postoperative complications (ascites, nausea, and vomiting, etc.) were compared between the groups. Results:The completion rate of staged surgery was 95.2% (40/42) in the observation group and 90.2% (37/41) in the control group ( χ2=0.62, P=0.431). The ALT and AST levels at 5 days after first-stage surgery were (550.4±86.0) U/L and (327.1±52.8) U/L in the observation group, respectively, which were significantly lower than those in the control group (861.6±106.3) U/L and (533.8±73.7) U/L, respectively ( t=13.13 and P<0.001, t=12.93 and P<0.001). The FLR growth rate were higher in the observation group than that in the control group [(80.4±10.3)% vs (49.3±5.7)%; t=13.13, P<0.001] and the interval between procedures were also shorter in the observation group (10.9±2.1 vs 22.4±4.8, d; t=9.65, P<0.001). The intraoperative blood loss of the first-stage surgery was lower in the observation group than that in the control group (350.5±45.2 vs 825.5±21.7, ml; t=21.43, P<0.001). The total complication rates after the first-stage surgery were 11.9% (5/42) in the observation group and 19.5% (8/41) in the control group, while after the second-stage surgery, the complication rates were 7.5% (3/40) and 18.9% (7/37), respectively, with no statistically significant differences ( χ2=0.65 and P=0.419, χ2=1.81 and 0.177, respectively). Conclusion:The modified ALPPS offers better postoperative liver function, reduced surgical trauma, accelerated FLR growth, and a shorter interval between procedures, demonstrating a favorable safety in the treatment of primary liver cancer.

Objective:To investigate the application of endoscopic ultrasound-guided liver biopsy (EUS-LB) to liver transplant recipients.Methods:In this retrospective cohort study, a total of 12 liver transplant recipients who underwent EUS-LB by the same endoscopist and specimens were diagnosed and reported by the same pathologist due to abnormal liver function or need to be evaluated for graft fibrosis in the Organ Transplantation Center of the Affiliated Hospital of Qingdao University were enrolled into the EUS-LB group from December 2021 to March 2022, meanwhile, a total of 23 patients whose PLB was completed by the same hepatologist and specimens were diagnosed by the same pathologist during the same period were enrolled in the PLB group. Acquisition of liver specimens and postoperative adverse events of the two groups were compared.Results:Patients in both groups were punctured 1-2 times on average, and the median total length of liver specimens in the EUS-LB group was significantly longer than that in the PLB group (61 mm VS 17 mm, Z=11.362, P=0.002). There was no significant difference in the length of the longest liver specimens between the two groups (17.6±6.9 mm VS 13.7±3.5 mm, t=2.382, P=0.086), while the number of liver specimens in the EUS-LB group was more than that in the PLB group (4.8±2.1 VS 2.3±1.2, t=9.271, P=0.001). The number of complete portal tracts was 11.3±4.6 in the EUS-LB group and 6.2±3.3 in the PLB group ( t=8.457, P=0.003). Abdominal pain was the only postoperative adverse event, and only 1 patient in the EUS-LB group had postoperative abdominal pain, which was fewer than that in the PLB group [8.3% (1/12) VS 43.5% (10/23), χ2=4.893, P=0.036]. Conclusion:Compared with PLB, EUS-LB delivers longer liver biopsy specimens with more complete portal tracts in liver transplant recipients, and fewer recipients complain about postoperative pain in EUS-LB group. Therefore, EUS-LB is a safer, more effective and more comfortable liver biopsy method.

Objective:To explore the decision-making experience of patients undergoing abdominoplasty in our country.Methods:A semi-structured interview was conducted with patients suffering from postpartum abdominal wall laxity who were treated at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from June to August 2023. The data were sort and analyzed using the Clolaizzi 7-step analysis method for thematic description.Results:A total of 15 patients, aged 29-53 years, were included in the study. 11 had a college education or higher, while 4 had less than a college education.Thirteen were married and two were divorced. According to the interview data, four themes were extracted: (1) negative perceptual experiences; (2) decision-making dilemmas; (3) peer support; (4) a physician-led decision-making model. According to the interview, the main decision-making dilemma faced by patients with postpartum abdominal wall laxity was lack of information and family support, and the support they get was mostly from information exchange among patients, and they had insufficient cognition of surgical knowledge, improvement degree and risk, and low participation in clinical decision making.Conclusion:Patients with postpartum abdominal wall laxity in China have an urgent psychological need for abdominoplasty, but there are many factors that have adverse effects on their decision-making experience.

Objective:To explore the decision-making experience of patients undergoing abdominoplasty in our country.Methods:A semi-structured interview was conducted with patients suffering from postpartum abdominal wall laxity who were treated at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from June to August 2023. The data were sort and analyzed using the Clolaizzi 7-step analysis method for thematic description.Results:A total of 15 patients, aged 29-53 years, were included in the study. 11 had a college education or higher, while 4 had less than a college education.Thirteen were married and two were divorced. According to the interview data, four themes were extracted: (1) negative perceptual experiences; (2) decision-making dilemmas; (3) peer support; (4) a physician-led decision-making model. According to the interview, the main decision-making dilemma faced by patients with postpartum abdominal wall laxity was lack of information and family support, and the support they get was mostly from information exchange among patients, and they had insufficient cognition of surgical knowledge, improvement degree and risk, and low participation in clinical decision making.Conclusion:Patients with postpartum abdominal wall laxity in China have an urgent psychological need for abdominoplasty, but there are many factors that have adverse effects on their decision-making experience.

Objective:To analyze the prognostic outcomes of 1 147 patients who underwent liver transplantation at Qingdao University Affiliated Hospital and to summarize measures to enhance the efficacy of liver transplantation.Methods:A retrospective analysis was conducted on the clinical and follow-up data of 1 147 liver transplant patients at Qingdao University Affiliated Hospital.Results:The overall postoperative 1-, 3-, and 5-year survival rates for the 1 147 liver transplant patients were 87.20%, 73.40%, and 65.60%, respectively. The survival rates for benign disease liver transplant recipients were 88.01%, 84.98%, and 81.39% at 1, 3, and 5 years post-transplant, respectively, compared to recipients transplanted for malignancies of 78.11%, 64.41%, and 60.06% (all P<0.001). Among the mid vs more recent period, patients' 1-year and 3-year postoperative survival rates were 84.20%, 70.80% vs 90.50%, 71.70%, respectively,significantly in favor of recently enrolled patients ( P=0.022). In the complex surgery group, patients' 1-, 3-, and 5-year survival rates were 82.70%, 65.50%, 56.70%, while in less complicated group, it was 89.00%, 76.50%, 69.20% ( P<0.001). The primary causes of death for benign disease recipients were multi-organ failure (4.1%), while in recipients with malignant disease primary cause of death was tumor recurrence (23.7%). Postoperative complications included primary graft dysfunction, delayed graft function recovery, portal vein thrombosis, hepatic artery thrombosis, biliary stricture, post-transplant lymphoproliferative disorder, and graft-versus-host disease, with occurrence rates of 1.05%, 6.89%, 1.92%, 0.44%, 2.00%, 0.61%, and 0.44%, respectively. Conclusions:With the continuous improvement in surgical techniques and perioperative care levels, the 3-year survival rate of recipients at our center has increased. Malignant diseases and complex liver transplantation remain crucial factors affecting recipient prognosis, highlighting the need to further enhance comprehensive treatment capabilities for patients with malignant diseases and complex surgeries.

Objective:To explore the impact of donor cold ischemia time(CIT)on early recovery after liver transplantation(LT).Methods:From January 2016 to December 2020, the relevant clinical data were retrospectively reviewed for 456 LT recipients.According to the value of CIT of donor liver, they were assigned into two groups of CIT >5 h and CIT≤5 h. T, Mann-Whitney U or Chi square test was employed for statistical processing.Intraoperative findings and liver function(LF)parameters of two groups were compared, including operative duration, intraoperative volume of hemorrhage, erythrocyte transfusion and anhepatic phase.LF parameters included alanine aminotransferase(ALT), aspartate aminotransferase(AST)and total bilirubin(TB)within Day 1-7 post-LT.Postoperative recovery was evaluated by postoperative stay of intensive care unit(ICU), normalization time of liver function recovery, length of postoperative hospitalization and incidence of postoperative complications.Results:Among them, 407(89.3%)patients underwent classic orthotopic LT.Median CIT of donor liver was 309 min.In CIT≤5 h and CIT >5 h groups, operative duration was[(446.3+ 76.8)vs.(526.0+ 98.1)min], anhepatic phase time[(51.9+ 13.3)vs.(62.6+ 18.9)min]and intraoperative volume of erythrocyte transfusion[(7.3+ 5.8)vs.(10.0+ 6.87)U]. And the differences were statistically significant( P<0.001, 0.001 & 0.001). Postoperative hospitalization stay was longer[(29.1±15.9)vs.(27.1±13.0)]day.And the incidence of postoperative complications was higher in CIT >5 h group[22.7%(54/238)vs.12.4%(27/218)]. And the difference was statistically significant( P=0.045 & 0.004). As compared with CIT≤5 h group, ALT, AST & TB spiked in CIT >5 h group at Day 1 post-operation and the differences were statistically significant( P=0.002, P<0.001, P=0.001). In CIT >5 h group, ALT rose at Day 2/5/6/7 post-LT( P=0.026, 0.026, 0.015 & 0.011), AST jumped from Days 2-6( P=0.002, 0.004, 0.035, 0.029 and 0.019)and TB increased from Days 2-7 post-LT and the differences were statistically significant( P=0.003, 0.014, 0.030, 0.039, 0.027 & 0.009). LF recovered at CIT≤5 h and CIT>5 h group[(10.0±3.2)vs.(10.7±3.3)day]. There were significantly statistical differences( P=0.044). Conclusions:Non-conducive to patient recovery, prolonged cold ischemic time aggravates early LF injury post-LT.