ObjectiveTo assess the current status of medical waste management in Jinshan District of Shanghai, China, to identify existing issues, and to provide a scientific basis for formulating targeted strategies. MethodsData were collected from the routine supervision and inspection records of the Jinshan District Health Commission Supervision Institute from 2017 to 2021, covering all aspects of medical waste management, including collection, classification, transportation, storage, and administrative penalties. ResultsThe compliance rates for the establishment of institutional frameworks, staffing, internal handover, and registration in medical and healthcare institutions all exceeded 95.00%. However, only 2.31% of the medical and healthcare institutions met the 48-hour storage limit requirement for medical waste. Private institutions had significantly lower compliance rates (P<0.05) in aspects such as proper classification and collection, maintaining records for three years, adhering to the 48-hour storage limit, refraining from commercial transactions, timely disinfection and cleaning, and implementing emergency measures for waste loss. Compliance rates also varied among different types of institutions regarding the establishment of temporary storage facilities and the implementation of the transfer manifest system, with community healthcare institutions exhibiting relatively lower compliance rates (P<0.05). Over the past five years, private medical and healthcare institutions accounted for 63.33% of administrative penalty cases. ConclusionWhile medical waste management in Jinshan District, Shanghai, has gradually become more standardized, challenges remain. To address the issue of medical waste being stored for over 48 hours, medical waste transfer stations should be established to improve transfer efficiency and ensure complete waste collection. Additionally, for private and community healthcare institutions, weak links in management should be addressed by establishing medical waste quality control teams, enhancing supervision through digital tools, and optimizing management processes to comprehensively elevate medical waste management.

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 explore the effects of drug therapy combined with multi-dimensional psychological intervention on the insomnia of shift medical staff in"sunshine hospital"mode,and to provide a reference for improving the physical and mental health of shift medical staff.Methods A total of 140 cases of medical staff with insomnia in shifts in Wuhan were included and divided into study group and control group by random number table method,70 cases in each group.The control group was given drug treatment,and the study group was treated combined with multi-dimensional psychological intervention.based on"sunshine hospital"model.The scale and questionnaire of PSQI,ISI,ESS and FAS were used to evaluate sleep status and HAMD,HAMA,PHQ-9 and SAS were used to evaluate psychological status,at baseline,visit 1(baseline+intervention for 1 month)and visit 2(baseline+intervention for 3 months),respectively.Results(1)Sleep status:There were differences in 7 dimensions of PSQI score,ISI,ESS,and FAS score between the study group and the control group at different periods(P<0.05);Among them,the PSQI scores of the two groups showed significant difference between the two groups at interview 2(P<0.05);There were significant differences in sleep quality,sleep efficiency scores,ESS and FAS between the two groups at visit 1 and visit 2(P<0.05).(2)Psychological status:HAMD,HAMA,PHQ-9 and SAS scores of the study group and the control group were different in different periods(P<0.05).At interview 2,there were significant differences in HAMA and SAS scores between the two groups(P<0.05).Conclusion Based on the"sunshine hospital"model of drug therapy combined with multi-dimensional psychological intervention,it can significantly improve sleepiness,fatigue symptoms,sleep quality,sleep efficiency,and anxiety and depression of first-line shift medical staff in the short term,and significantly alleviate overall insomnia and anxiety in the long term.

Objective To explore the clinical effect of clinical observation of supplemented wendan decoction combined with Western medicine in treating insomnia accompanied by anxiety and depression in phlegm-heat internal disturbance syndrome.Methods A total of 120 cases of insomnia with anxiety and depression comorbiditis with phlegm heat disturbance syndrome were randomly divided into control group and treatment group,60 cases in each group.The control group was given escitalopram oxalate tablet combined with dexzopiclonone tablet,and the observation group was given added Wendan decoction on the basis of the control group.Both groups were treated continuously for 6 weeks.Polysomnography monitoring parameters and heart rate variability were compared between the two groups during baseline period and visit 2(baseline period+3 months).Scale scores of the two groups were compared during baseline period,visit 1(baseline period+6 weeks)and visit 2.The content of heart rate variability includes:time domain analysis(standard deviation of normal interval(SDNN),square root of the square sum of the mean of the difference between adjacent normal interval(RMSSD)and frequency domain analysis(LF,HF,LF/HF).The scale scores included the Pittsburgh Sleep Quality Index(PSQI)and Insomnia Severity Index(ISI)to assess sleep status,and the Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Self-assessment Scale for Depression(PHQ-9)and Generalized Anxiety Disorder Scale(GAD-7)to assess anxiety and depression status.Results(1)Polysomnography monitoring:the wake time of observation group was significantly shorter than that of control group,the number of awakenings was significantly less than that of control group,and the percentage of N3 and REM was significantly higher than these of control group(P＜0.05).(2)Heart rate variability:RMSSD and HF values in the observation group were significantly higher than those in the control group,and LF/HF values were significantly lower than those in the control group(P＜0.05).(3)In terms of sleep:during the interview,PSQI total score,sleep quality,hypnotic drugs and daytime dysfunction in the observation group were significantly lower than those in the control group(P＜0.05);At the 3 months,the sleep quality,hypnotic drugs and daytime dysfunction in the observation group were significantly lower than those in the control group(P＜0.05).In terms of emotion:HAMA,HAMD and GAD-7 scores were significantly lower than those of control group at 6 weeks(P＜0.05);At the 3 months,HAMA and GAD-7 scores were significantly lower than those of control group(P＜0.05).Conclusion Supplemented Wendan decoction combined with western medicine can obviously optimize the sleep structure of insomnia patients with anxiety and depressionof phlegm-heat disturbance syndrome,improve sleep continuity and deepen sleep depth,and improve parasympathetic functional activities,contribute to sympathetic parasympathetic balance,can improve insomniaand depression symptoms recently,and significantly improve anxiety symptoms in the short term,with good safety.

Objective:To investigate the clinical efficacy of liver transplantation for intra-hepatic cholangiocarcinoma.Methods:The retrospective cohort study was conducted. The clinico-pathological data of 22 patients with intrahepatic cholangiocarcinoma who underwent liver trans-plantation in the 5 medical centers, including First Hospital of Jilin University, et al, from September 2005 to December 2021 were collected. There were 18 males and 4 females, aged 57(range, 38?71)years. Observing indicators: (1) clinicopathological characteristics of patients with intrahepatic cholangiocarcinoma; (2) follow-up; (3) prognosis. Measurement data with skewed distribution were represented as M(range). Count data were described as absolute numbers or percentages. The Kaplan-Meier method was used to draw survival curves. The Log-Rank test was used for survival analysis. Results:(1) Clinicopathological characteristics of patients with intrahepatic cholangio-carcinoma. Of the 22 patients, 20 cases were diagnosed as intrahepatic cholangiocarcinoma before liver transplantation, 7 cases had viral hepatitis type B, 1 case had primary sclerosing cholangitis, 7 cases had tumor treatment before liver transplantation, 7 cases, 6 cases and 9 cases were classified as grade A, grade B and grade C of the Child-Pugh classification, 16 cases had preoperative CA19-9 >40 U/mL, 14 cases had single tumor, 11 cases with tumor located at right lobe of liver, 6 cases with tumor located at both left and right lobe of liver, 5 cases with tumor located at left lobe of liver, 9 cases with tumor vascular invasion. All 22 patients were diagnosed as moderate-poor differentiated tumor. There were 9 cases with liver cirrhosis, 4 cases with tumor lymph node metastasis, 10 cases with tumor burden within Milan criteria. The tumor diameter of 22 patients was 4.5(range, 1.5?8.0)cm. (2) Follow-up. All 22 patients were followed up for 15(range, 3?207)months. Of the 22 patients, 9 cases had tumor recurrence and 8 cases died. (3) Prognosis. The 1-year overall survival rate and 1-year disease-free survival rate of the 22 patients was 72.73% and 68.18%, respectively. Results of subgroup analysis showed there were significant differences in overall survival and disease-free survival between the 10 patients with tumor burden within Milan criteria and the 12 patients with tumor burden beyond Milan criteria who underwent liver transplantation ( hazard ratio=0.13, 0.26, 95% confidence interval as 0.03?0.53, 0.08?0.82, P<0.05). Results of further analysis of the 12 patients with tumor burden beyond Milan criteria showed there were significant differences in overall survival and disease-free survival between the 5 patients with preoperative tumor down-staging treatment and the 7 patients without preoperative tumor down-staging treatment ( hazard ratio=0.18, 0.14, 95% confidence interval as 0.04?0.76, 0.04?0.58, P<0.05). Conclusions:Intrahepatic cholangiocarcinoma patients with tumor burden within Milan criteria have a better prognosis than patients with tumor burden beyond Milan criteria after liver transplantation. For patients with tumor burden beyond Milan criteria, active tumor down-staging treatment before liver transplantation can improve the prognosis.

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.

Objective:To evaluate the effect of transfusion-free techniques on the prognosis of liver transplant patients.Methods:The recipients of adult liver transplantation at Tianjin First Central Hospital from August to December 2019 were included in the clinical observation. Liver transplantation without allogeneic blood transfusion was performed through anesthesia management techniques such as acute hemodilution or phlebotomy without volume replacement,maintaining decreased baseline central venous pressure and cell saver. According to the actual results,the patients were divided into two groups: transfusion-free group( n=21) and allogeneic transfusion group( n=28). There were 13 males and 8 females aged of (56.3±11.6) years in the transfusion-free group;and there were 16 males and 12 females aged (54.3±14.2)years in the allogeneic transfusion group. The transplant recipients who had not adopted transfusion management strategy from January to July 2019 were included as control group(27 males and 13 females,aged of (58.9±14.1)years). The clinical data of patients in perioperative period were collected to compare whether there were differences in the recovery of liver function and early complications among the three groups, one-way ANOVA test, rank-sum test, and χ 2 test were used for data analysis. Results:The amount of intraoperative blood loss in both the transfusion-free group and the transfusion group was less than that in the control group((454.2±271.3)ml vs.(673.6±333.4)ml vs.(890.3±346.7)ml; q=-6.342,-5.286,both P<0.05).The duration of stay in ICU of the transfusion-free group was less than that of the transfusion group and control group((36.4±9.1)hours vs.(44.3±14.9)hours vs.(58.2±21.1)hours; q=-4.432,-3.824,both P<0.05).The mean ALT level at 7 days after operation was significantly lower in the transfusion-free group than in the control group((56.8±32.1)U/L vs.(89.6±45.6)U/L; q=-3.358, P<0.05). Conclusions:The improvement of multi-disciplinary transfusion management technology aimed at transfusion-free liver transplantation can effectively reduce intraoperative hemorrhage and help to avoid surgical transfusion. Transfusion-free liver transplantation is beneficial to the early postoperative recovery,and its long-term clinical significance is worthy of further clinical research.

Objective:To evaluate the effect of transfusion-free techniques on the prognosis of liver transplant patients.Methods:The recipients of adult liver transplantation at Tianjin First Central Hospital from August to December 2019 were included in the clinical observation. Liver transplantation without allogeneic blood transfusion was performed through anesthesia management techniques such as acute hemodilution or phlebotomy without volume replacement,maintaining decreased baseline central venous pressure and cell saver. According to the actual results,the patients were divided into two groups: transfusion-free group( n=21) and allogeneic transfusion group( n=28). There were 13 males and 8 females aged of (56.3±11.6) years in the transfusion-free group;and there were 16 males and 12 females aged (54.3±14.2)years in the allogeneic transfusion group. The transplant recipients who had not adopted transfusion management strategy from January to July 2019 were included as control group(27 males and 13 females,aged of (58.9±14.1)years). The clinical data of patients in perioperative period were collected to compare whether there were differences in the recovery of liver function and early complications among the three groups, one-way ANOVA test, rank-sum test, and χ 2 test were used for data analysis. Results:The amount of intraoperative blood loss in both the transfusion-free group and the transfusion group was less than that in the control group((454.2±271.3)ml vs.(673.6±333.4)ml vs.(890.3±346.7)ml; q=-6.342,-5.286,both P<0.05).The duration of stay in ICU of the transfusion-free group was less than that of the transfusion group and control group((36.4±9.1)hours vs.(44.3±14.9)hours vs.(58.2±21.1)hours; q=-4.432,-3.824,both P<0.05).The mean ALT level at 7 days after operation was significantly lower in the transfusion-free group than in the control group((56.8±32.1)U/L vs.(89.6±45.6)U/L; q=-3.358, P<0.05). Conclusions:The improvement of multi-disciplinary transfusion management technology aimed at transfusion-free liver transplantation can effectively reduce intraoperative hemorrhage and help to avoid surgical transfusion. Transfusion-free liver transplantation is beneficial to the early postoperative recovery,and its long-term clinical significance is worthy of further clinical research.

Objective:To analyze the complications and outcomes during the hospitalization of extremely premature infants (EPI) and extremely low birth weight infants (ELBWI).Methods:Clinical data of 168 cases of EPI and ELBWI admitted to 4 hospitals of grade three in Shaanxi Province between January 1, 2015 and December 31, 2017 were retrospectively analyzed.The information of general data, prenatal care, complications and outcomes were summarized.Outcomes of different groups were compared according to birth weight and gestational age.Results:A total of 168 cases of EPI and ELBWI were collected.The rate of delivery in tertiary hospitals was 86.9% (146/165 cases), 86 patients (57.7%) received prenatal Dexamethasone.The mean gestational age was (27.9±1.7) weeks, and the mean birth weight was (951.6±148.9) g. The highest rates of pregnancy complications included gestational hypertension (44/149 cases, 29.5%), premature rupture of membranes (43/149 cases, 28.9%) and gestational diabetes (16/149 cases, 10.7%). The first three neonatal complications were neonatal respiratory distress syndrome (16/168 cases, 95.2%), bronchopulmonary dysplasia (73/110 cases, 66.4%) and retinopathy of prematurity (65/110 cases, 59.1%). The survival rate of EP and ELBWI in 168 cases was 61.9% (104/168 cases), the abandonment rate was 27.4% (46/168 cases), and the mortality in hospital was 10.7% (18/168 cases). According to birth weight and gestational age, there were no statistically significant differences in survival, abandonment and hospital mortality among different birth weight groups( χ2=4.361, 5.104, 1.630, all P>0.05), while there were statistically significant differences in survival, abandonment and hospital mortality among different gestational age groups( χ2=21.650, 8.164, 13.490, all P<0.05). Conclusions:There are many complications of EPI and ELBWI and the outcomes are closely related to the gestational age of birth.Improving the perinatal management level and the professional diagnosis and treatment level of neonatology are helpful to improve the survival rate and prognosis.