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.

Portal vein tumor thrombus(PVTT)is a common manifestation of advanced hepatocellular carcinoma(HCC),associated with poor prognosis and significant treatment challenges.Although various therapeutic options-including surgery,systemic therapies,and local treatments such as interventional procedures and radiotherapy-are available for HCC with PVTT,monotherapies often yield limited efficacy,highlighting the need for combined treatment strategies.With the advancement of radiotherapy technologies,stereotactic body radiation therapy(SBRT)has gained increasing recognition due to its high precision,ablative doses,and fewer treatment fractions.SBRT plays a crucial role in palliative care,conversion therapy,neoadjuvant,and adjuvant settings.Recent studies have demonstrated that SBRT,either alone or in combination with other modalities,significantly improves overall survival and local control rates in patients with HCC and PVTT.This review summarizes the current research progress of SBRT in the management of HCC with PVTT,emphasizing both monotherapy and combined approaches with surgery,interventional therapy,targeted agents,and immunotherapy,aiming to provide insights for clinical decision-making.

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.

Portal vein tumor thrombus(PVTT)is a common manifestation of advanced hepatocellular carcinoma(HCC),associated with poor prognosis and significant treatment challenges.Although various therapeutic options-including surgery,systemic therapies,and local treatments such as interventional procedures and radiotherapy-are available for HCC with PVTT,monotherapies often yield limited efficacy,highlighting the need for combined treatment strategies.With the advancement of radiotherapy technologies,stereotactic body radiation therapy(SBRT)has gained increasing recognition due to its high precision,ablative doses,and fewer treatment fractions.SBRT plays a crucial role in palliative care,conversion therapy,neoadjuvant,and adjuvant settings.Recent studies have demonstrated that SBRT,either alone or in combination with other modalities,significantly improves overall survival and local control rates in patients with HCC and PVTT.This review summarizes the current research progress of SBRT in the management of HCC with PVTT,emphasizing both monotherapy and combined approaches with surgery,interventional therapy,targeted agents,and immunotherapy,aiming to provide insights for clinical decision-making.

Purpose: This study aims to evaluate the efficacy and safety of a new combination treatment of vinorelbine and pyrotinib in human epidermal growth factor receptor 2 (HER2)–positive metastatic breast cancer (MBC) and provide higher level evidence for clinical practice. Materials and Methods: This was a prospective, single-arm, phase 2 trial conducted at three institutions in China. Patients with HER2-positive MBC, who had previously been treated with trastuzumab plus a taxane or trastuzumab plus pertuzumab combined with a chemotherapeutic agent, were enrolled between March 2020 and December 2021. All patients received pyrotinib 400 mg orally once daily plus vinorelbine 25 mg/m2 intravenously or 60-80 mg/m2 orally on day 1 and day 8 of 21-day cycle. The primary endpoint was progression-free survival (PFS), and the secondary endpoints included the objective response rate (ORR), disease control rate (DCR), overall survival, and safety. Results: A total of 39 patients were enrolled. All patients had been pretreated with trastuzumab and 23.1% (n=9) of them had accepted trastuzumab plus pertuzumab. The median follow-up time was 16.3 months (95% confidence interval [CI], 5.3 to 27.2), and the median PFS was 6.4 months (95% CI, 4.0 to 8.8). The ORR was 43.6% (95% CI, 27.8% to 60.4%) and the DCR was 84.6% (95% CI, 69.5% to 94.1%). The median PFS of patients with versus without prior pertuzumab treatment was 4.6 and 8.3 months (p=0.017). The most common grade 3/4 adverse events were diarrhea (28.2%), neutrophil count decreased (15.4%), white blood cell count decreased (7.7%), vomiting (5.1%), and anemia (2.6%). Conclusion Pyrotinib plus vinorelbine showed promising efficacy and tolerable toxicity as second-line treatment in patients with HER2-positive MBC.

Objective:To explore the feasibility and clinical effects of using superficial temporal artery lobulated perforator flaps in repairing skin and soft tissue defects after tumor resection in the temporal region.Methods:A retrospective observational study method was used. From March 2017 to October 2022, ten patients with temporal skin tumors were admitted to the Affiliated Hospital of Zunyi Medical University, including six women and four men, with age ranging from 42 to 87 years. Among them, three patients had squamous cell carcinoma and seven patients had basal cell carcinoma, with disease duration ranging from 6 months to 5 years. All temporal tumors underwent expanded resection, leaving wound areas of 5.4 cm×4.2 cm to 7.0 cm×4.0 cm after tumor resection. Superficial temporal artery frontal branch flaps with areas of 5.5 cm×1.2 cm to 7.0 cm×1.5 cm, superficial temporal artery descending branch flaps with areas of 4.2 cm×3.5 cm to 5.0 cm×4.0 cm, and superficial temporal artery parietal branch flaps with areas of 4.2 cm×1.0 cm to 5.0 cm×1.0 cm were designed to repair the wounds and reconstruct the hairline. The donor areas of the flaps were closed and sutured directly. The survival of the flaps was observed on 3 to 5 days after surgery, and the healing of wounds on the donor and recipient sites was observed when the stitches were removed on 5 to 7 days after surgery. During follow-up after surgery, the appearance of the temporal area, scar hyperplasia, hairline reconstruction, and tumor recurrence were observed in the temporal region on the affected side.Results:All the flaps survived well on 3 to 5 days after surgery, and all the donor and recipient site wounds healed well on 5 to 7 days after surgery. During follow-up of 3 to 6 months after surgery, the surgical incisions were concealed; the flaps were not swollen, with a consistent color to the surrounding skin; there were no obvious hypertrophic scars; the reconstructed hairline on the affected side was not significantly different from that of the healthy side; there was no tumor recurrence in the local area.Conclusions:For large areas of skin and soft tissue defects in the temporal region, the use of superficial temporal artery lobulated perforator flaps can repair the wounds in different regions and suture the donor sites in the primary stage simultaneously. The surgical operation is simple, and the facial appearance conforms to the aesthetic requirement after surgery with no tumor recurrence in the local area but a good repair effect. This method is particularly suitable for repairing large areas of skin and soft tissue defects in the temporal region in elderly patients.

Traumatic rib fractures are the most common injury in thoracic trauma. Previously，the patients with traumatic rib fractures were mostly treated non-surgically，of which 50%，especially those combined with flail chest presented chronic pain or chest wall deformities and over 30% had long-term disabilities，being unable to retain a full-time job. In the past two decades，thanks to the development of internal fixation material technology，the surgical treatment of rib fractures has achieved good outcomes. However，there are still some problems in clinical treatment，including inconsistency in surgical treatment and quality control in medical services. The current consensuses on the management of regional traumatic rib fractures published at home and abroad mainly focus on the guidance of the overall treatment decisions and plans，and relevant clinical guidelines abroad lacks progress in surgical treatment of rib fractures in recent years. Therefore，the Chinese Society of Traumatology affiliated to Chinese Medical Association and Chinese College of Trauma Surgeons affiliated to Chinese Medical Doctor Association，in conjunction with national multidisciplinary experts，formulate the Chinese Consensus for Surgical Treatment of Traumatic Rib Fractures（2021）following the principle of evidence-based medicine，scientific nature and practicality. This expert consensus puts forward some clear，applicable，and graded recommendations from aspects of preoperative imaging evaluation，surgical indications，timing of surgery，surgical methods，rib fracture sites for surgical fixation，internal fixation methods and material selections，treatment of combined injuries in rib fractures，in order to provide references for surgical treatment of traumatic rib fractures.

Objective:To evaluate the cost effectiveness of primary prophylaxis (PP) with pegylated recombinant human granulocyte colony stimulating factor (PEG-rhG-CSF), PP with recombinant human granulocyte colony stimulating factor (rhG-CSF) and no prophylaxis in women with early-stage breast cancer in China.Methods:Two phase Markov models were constructed for a hypothetical cohort of patients aged 45 with stage Ⅱ breast cancer. The first phase modelled costs and outcomes of 4 cycles docetaxel combined with cyclophosphamide [TC×4, febrile neutropenia (FN) risk>20%] chemotherapy, which assumptions based on literature reviews, including FN rates [base-case (deterministic sensitivity analysis range), 0.29 (0.24-0.35)] and related events [FN case-fatality, 3.4 (2.7-4.1)]. Second phase modelled the long term survival which was link with the relative dose intensity (RDI) [mortality hazard ratio ( HR) of RDI < 85% vs ≥85%, 1.45 (1.00-2.32)]. Clinical effectiveness, therapeutic costs, and economic utilities were estimated from peer-reviewed publications and expert opinions in case of unavailability of published evidences. Results:Compared to rhG-CSF PP and no prophylaxis, the cost of PEG-rhG-CSF PP increased to 5 208.19 RMB and 5 222.73 RMB, respectively. The quality-adjusted life-years (QALYs) enhanced to 0.066 and 0.297, respectively. Accordingly, the incremental cost effectiveness ratios (ICERs) are 79 146.3 RMB and 17 558.77 RMB per QALY, which were both below the willingness to pay (WTP) threshold of three times GDP per capita (18, 000 RMB) recommended by the WHO. Sensitivity analysis suggested that the more clinically effective the primary prophylaxis with PEG-rhG-CSF is, the more cost-effective primary prophylaxis with PEG-rhG-CSF will be. And the lower the mortality HR of RDI<85% vs ≥85% is, the more cost-effective primary prophylaxis with PEG-rhG-CSF will be. Conclusion:Although the cost of PP PEG-rhG-CSF is higher, considering the additional benefits, the administrating of PP PEG-rhG-CSF is likely to be a cost-effective alternative to PP rhG-CSF and no prophylaxis in patients with early stage breast cancer whose FN risks are more than 20% in China.

Objective:To evaluate the cost effectiveness of primary prophylaxis (PP) with pegylated recombinant human granulocyte colony stimulating factor (PEG-rhG-CSF), PP with recombinant human granulocyte colony stimulating factor (rhG-CSF) and no prophylaxis in women with early-stage breast cancer in China.Methods:Two phase Markov models were constructed for a hypothetical cohort of patients aged 45 with stage Ⅱ breast cancer. The first phase modelled costs and outcomes of 4 cycles docetaxel combined with cyclophosphamide [TC×4, febrile neutropenia (FN) risk>20%] chemotherapy, which assumptions based on literature reviews, including FN rates [base-case (deterministic sensitivity analysis range), 0.29 (0.24-0.35)] and related events [FN case-fatality, 3.4 (2.7-4.1)]. Second phase modelled the long term survival which was link with the relative dose intensity (RDI) [mortality hazard ratio ( HR) of RDI < 85% vs ≥85%, 1.45 (1.00-2.32)]. Clinical effectiveness, therapeutic costs, and economic utilities were estimated from peer-reviewed publications and expert opinions in case of unavailability of published evidences. Results:Compared to rhG-CSF PP and no prophylaxis, the cost of PEG-rhG-CSF PP increased to 5 208.19 RMB and 5 222.73 RMB, respectively. The quality-adjusted life-years (QALYs) enhanced to 0.066 and 0.297, respectively. Accordingly, the incremental cost effectiveness ratios (ICERs) are 79 146.3 RMB and 17 558.77 RMB per QALY, which were both below the willingness to pay (WTP) threshold of three times GDP per capita (18, 000 RMB) recommended by the WHO. Sensitivity analysis suggested that the more clinically effective the primary prophylaxis with PEG-rhG-CSF is, the more cost-effective primary prophylaxis with PEG-rhG-CSF will be. And the lower the mortality HR of RDI<85% vs ≥85% is, the more cost-effective primary prophylaxis with PEG-rhG-CSF will be. Conclusion:Although the cost of PP PEG-rhG-CSF is higher, considering the additional benefits, the administrating of PP PEG-rhG-CSF is likely to be a cost-effective alternative to PP rhG-CSF and no prophylaxis in patients with early stage breast cancer whose FN risks are more than 20% in China.

Understanding the effect of immunosuppressive agents on intestinal microbiota is important to reduce the mortality and morbidity from orthotopic liver transplantation (OLT). We investigated the relationship between the commonly used immunosuppressive agent cyclosporine A (CSA) and the intestinal microbial variation in an OLT model. The rat samples were divided as follows: (1) N group (normal control); (2) I group (isograft LT, Brown Norway [BN] rat to BN); (3) R group (allograft LT, Lewis to BN rat); and (4) CSA group (R group treated with CSA). The intestinal microbiota was assayed by denaturing gradient gel electrophoresis profiles and by using real-time polymerase chain reaction. The liver histopathology and the alanine/aspartate aminotransferase ratio after LT were both ameliorated by CSA. In the CSA group, the numbers of rDNA gene copies of Clostridium cluster I, Clostridium cluster XIV, and Enterobacteriaceae decreased, whereas those of Faecalibacterium prausnitzii increased compared with the R group. Cluster analysis indicated that the samples from the N, I, and CSA groups were clustered, whereas the other clusters contained the samples from the R group. Hence, CSA ameliorates hepatic graft injury and partially restores gut microbiota following LT, and these may benefit hepatic graft rejection.