Objective To analyze the main causes and risk factors of unplanned reoperation after liver transplantation. Methods The clinical data of 242 liver transplant recipients in the First Affiliated Hospital of Anhui Medical University from January 2015 to December 2024 were retrospectively analyzed. According to whether unplanned reoperation was performed during the same hospitalization after surgery, the recipients were divided into the reoperation group (n=36) and the non-reoperation group (n=206). The preoperative, intraoperative and postoperative data of the two groups, as well as donor and graft-related data, were compared to analyze the risk factors of unplanned reoperation after liver transplantation and the survival status of the two groups. Results Among the 242 liver transplant recipients, 36 underwent unplanned reoperations, with a total of 54 procedures including various laparotomies, endoscopic and interventional surgeries, among which there were 20 laparotomies, 18 endoscopic surgeries and 16 interventional surgeries. The most common cause of unplanned reoperation was biliary complications (20 times), followed by vascular complications (17 times). Compared with the non-reoperation group, the reoperation group had longer graft cold ischemia time, higher postoperative fatality rate of recipients, longer length of stay in the intensive care unit and postoperative hospital stay, and higher total hospitalization costs (all P<0.05). The incidence of unplanned reoperation was higher in recipients who underwent split liver transplantation (P<0.05). Multivariate analysis showed that intraoperative blood loss ≥1 000 mL, positive culture of graft perfusate and split liver transplantation were independent risk factors for unplanned reoperation (all P<0.05). The postoperative 7-day, 1-month, 3-month and 6-month survival rates of recipients in the reoperation group and the non-reoperation group were 100% vs. 98.1%, 88.9% vs. 94.2%, 69.4% vs. 90.8% and 66.7% vs. 90.8%, respectively, and the postoperative survival rate of recipients in the reoperation group was lower than that in the non-reoperation group (P<0.05). Conclusions The main causes of unplanned reoperation after liver transplantation are biliary complications, vascular complications, abdominal incision infection and intra-abdominal hemorrhage. Intraoperative massive blood loss, positive culture of graft perfusate and split liver transplantation are the risk factors associated with unplanned reoperation after liver transplantation.

Background and Aims:Pancreatic cancer is a highly malignant digestive system tumor characterized by poor prognosis and limited therapeutic response.The tumor microenvironment plays a crucial role in its progression,where oxidative stress and lactate metabolism are two tightly interconnected processes influencing tumor growth,immune escape,and therapeutic resistance.However,their combined prognostic impact remains poorly understood.This study aimed to integrate oxidative stress-and lactate metabolism-related genes to establish and validate a robust prognostic model for pancreatic cancer,and to explore its association with immune microenvironment characteristics.Methods:Transcriptomic and clinical data of 177 pancreatic cancer patients were obtained from TCGA database and an external validation was performed using the GEO dataset(GSE57495).Differentially expressed genes associated with oxidative stress and lactate metabolism were identified using the"limma"package.Univariate Cox regression was used to screen prognostic genes,followed by LASSO regression to construct a multi-gene risk model.Model performance was evaluated by Kaplan-Meier survival analysis,receiver operating characteristic(ROC)curves,concordance index(C-index),nomogram calibration,and decision curve analysis(DCA).The CIBERSORT and ssGSEA algorithms were used to analyze immune cell infiltration and immune functional differences between risk groups.Results:A six-gene signature(MUC1,KRT18,SDC1,AREG,DDC,and ATPAF2)was identified to construct the prognostic model.Based on the calculated risk score,patients were stratified into high-and low-risk groups.Kaplan-Meier analysis revealed significantly worse overall survival in the high-risk group(P<0.01).The model showed good predictive accuracy with 1-,2-,and 3-year AUCs of 0.710,0.674,and 0.649,respectively.The C-index and calibration curves confirmed its reliability,and multivariate Cox regression indicated that the risk score was an independent prognostic factor.External validation using GEO data demonstrated consistent predictive performance.Immune infiltration analysis revealed that M0 macrophages were markedly enriched in the high-risk group,while cytotoxic and effector T-cell populations were reduced,suggesting that an immunosuppressive microenvironment may contribute to poor outcomes.Conclusion:This study developed and validated a novel prognostic model for pancreatic cancer based on oxidative stress and lactate metabolism-related genes.The model accurately predicts patient survival,reflects immune microenvironment heterogeneity,and provides new molecular insights for risk stratification and individualized therapeutic strategies in pancreatic cancer management.

Objective:To explore the clinical efficacy of double tract reconstruction and single flap valvuloplasty technique in laparoscopic proximal gastrectomy.Methods:A retrospective cohort study was adopted to analyze the clinical data of 65 patients with gastric cancer who underwent radical proximal gastrectomy at Taizhou People's Hospital Affiliated to Nanjing Medical University from July 2019 to April 2024. According to the different reconstruction methods, the patients were divided into the double tract reconstruction group (double tract; n=43) and oblique anastomosis of esophageal-gastric mucosal window with single flap valvuloplasty technique group (single flap n=22). The baseline data, surgical and postoperative recovery indicators, postoperative pathological results, gastroesophageal reflux at postoperative 6 months, and nutritional status at postoperative 1 year were compared between the two groups. Results:Comparisons of operative time, gastrointestinal reconstruction time, number of lymph nodes dissected, postoperative intestinal function recovery time, total protein, plasma albumin, hemoglobin, and lymphocyte count at 1 week postoperatively, prognostic nutritional index (PNI), time to normalization of postoperative white blood cell count and C-reactive protein, length of hospital stay, hospital costs, and incidence of postoperative pulmonary infection or anastomotic leakage between the two groups showed no statistically significant differences (all P>0.05). However, compared with the double tract group, the single muscle flap group had significantly higher intraoperative blood loss ( P<0.001), higher maximum postoperative body temperature ( P=0.004), and a significantly higher proportion of patients with pleural effusion ≥2 cm ( P=0.029).No statistically significant differences were observed between the two groups in terms of tumor length, length of esophageal involvement, Siewert classification, tumor differentiation degree, neural invasion, lymphovascular invasion, number of metastatic lymph nodes, tumor T stage and N stage, or UICC TNM staging for gastric cancer (all P>0.05). Nevertheless, the minimum distance of the lower resection margin in the double tract group was significantly longer than that in the single muscle flap group, with a statistically significant difference between the groups ( P<0.001). At 6 months postoperatively, results from the Quality of Life Questionnaire-Core 30 (QLQ-C30), Quality of Life Questionnaire-Stomach 22 (QLQ-ST022), Reflux Symptom Index scores, Visick grading, and gastroscopy (Los Angeles classification) all indicated that the incidence of reflux esophagitis in the double tract group was significantly lower than that in the single muscle flap group (all P<0.001). Gastrointestinal contrast examination showed no anastomotic stenosis in either group; gastroesophageal reflux occurred in 5 cases (11.6%) in the double tract group and 4 cases (18.2%) in the single muscle flap group, with no statistically significant difference (χ2=0.524, P=0.469). Gastroscopy results revealed that the incidence of reflux esophagitis at 6 months postoperatively was 9.3% (4/43) in the double tract group and 59.1% (13/22) in the single muscle flap group, with a statistically significant difference between the two groups (χ2=18.680, P<0.001).At 1 year postoperatively, the dual-chamber group showed better performance in body mass index(BMI), proportion of a decrease in BMI, plasma albumin, and PNI compared with the single muscle flap group, with statistically significant differences (all P<0.05). There were no statistically significant differences in hemoglobin or lymphocyte count between the two groups (all P>0.05). During 1 year of follow-up, one case of anastomotic recurrence occurred in each group, with no statistically significant difference between the groups ( P=0.624). Conclusions:Both proximal gastrectomy with double-tract anastomosis and esophagogastric mucosal window oblique anastomosis combined with single muscular flap valvuloplasty for digestive tract reconstruction are safe and feasible. However, double-tract anastomosis can better prevent the occurrence of postoperative reflux esophagitis, improve the patient's postoperative nutritional status, and enhance the patient's quality of life.

Background and Aims:Pancreatic cancer is a highly malignant digestive system tumor characterized by poor prognosis and limited therapeutic response.The tumor microenvironment plays a crucial role in its progression,where oxidative stress and lactate metabolism are two tightly interconnected processes influencing tumor growth,immune escape,and therapeutic resistance.However,their combined prognostic impact remains poorly understood.This study aimed to integrate oxidative stress-and lactate metabolism-related genes to establish and validate a robust prognostic model for pancreatic cancer,and to explore its association with immune microenvironment characteristics.Methods:Transcriptomic and clinical data of 177 pancreatic cancer patients were obtained from TCGA database and an external validation was performed using the GEO dataset(GSE57495).Differentially expressed genes associated with oxidative stress and lactate metabolism were identified using the"limma"package.Univariate Cox regression was used to screen prognostic genes,followed by LASSO regression to construct a multi-gene risk model.Model performance was evaluated by Kaplan-Meier survival analysis,receiver operating characteristic(ROC)curves,concordance index(C-index),nomogram calibration,and decision curve analysis(DCA).The CIBERSORT and ssGSEA algorithms were used to analyze immune cell infiltration and immune functional differences between risk groups.Results:A six-gene signature(MUC1,KRT18,SDC1,AREG,DDC,and ATPAF2)was identified to construct the prognostic model.Based on the calculated risk score,patients were stratified into high-and low-risk groups.Kaplan-Meier analysis revealed significantly worse overall survival in the high-risk group(P<0.01).The model showed good predictive accuracy with 1-,2-,and 3-year AUCs of 0.710,0.674,and 0.649,respectively.The C-index and calibration curves confirmed its reliability,and multivariate Cox regression indicated that the risk score was an independent prognostic factor.External validation using GEO data demonstrated consistent predictive performance.Immune infiltration analysis revealed that M0 macrophages were markedly enriched in the high-risk group,while cytotoxic and effector T-cell populations were reduced,suggesting that an immunosuppressive microenvironment may contribute to poor outcomes.Conclusion:This study developed and validated a novel prognostic model for pancreatic cancer based on oxidative stress and lactate metabolism-related genes.The model accurately predicts patient survival,reflects immune microenvironment heterogeneity,and provides new molecular insights for risk stratification and individualized therapeutic strategies in pancreatic cancer management.

During the career life cycle, workers may face various health problems such as occupational injuries, occupational diseases, and work-related diseases. How to comprehensively protect the health of workers is a crucial scientific issue that needs to be solved urgently. Workers show the characteristics of co-exposure to multiple occupational risks or co-existence of multiple health conditions in their occupational activities. Occupational injuries are closely related to occupational diseases and work-related diseases. To carry out prevention and control of occupational injuries in the context of "big health", we should further strengthen the systematic approach and highlight the concept of "overall process" and "all-round". That is to establish an occupational injury surveillance system covering the whole process of surveillance-assessment-intervention and the evaluation of intervention effects, and to set up the joint prevention and control strategy of occupational injuries, occupational diseases, and work-related diseases. This will promote the implementation of efficient and intensive health management at government, society, employers, workers and other levels to achieve all-round protection of workers' health. When exploring the possible effects of job burnout, occupational stress, comorbidity, and other factors on occupational injuries, the introduction of machine learning methods provides a new approach to identifying and analyzing the influencing factors of occupational injuries and to exploring potential underlying mechanisms.

Background Workers in the cable manufacturing industry are exposed to high-speed machinery and equipment for a long time, coupled with heavy workload, which poses significant risks to their physical health. However, the issue of occupational injuries in this industry has not received enough attention yet. Objective To understand the incidence of occupational injury of workers in cable manufacturing industry and to analyze the influencing factors. Method A basic information questionnaire and an occupational injury questionnaire were developed to investigate the occupational injuries of 1 343 workers in a cable manufacturing enterprise in the past year, and a total of 1 225 valid questionnaires were recovered, with an effective rate of 91.2%. Descriptive statistics were used to characterize the causes, injury locations, injury types, and other characteristics of employees’ occupational injuries. Chi-square test was used to analyze the occupational injury status of groups with different demographic characteristics, occupational characteristics, lifestyles, and interpersonal relationships. Logistic regression was used to analyze the influencing factors of occupational injuries. Result The incidence of occupational injuries among workers in a cable manufacturing enterprise in the past year was 8.6%, which mainly happened in male workers (80.0%) and occurred from May to July in summer (45.7%). The main causes were mechanical injuries (32.4%) and object blows (27.6%). The main sources of damage were machinery and equipment (36.2%) as well as raw materials and products (15.2%). The main injuries were located in upper limbs (53.3%) and lower limbs (22.9%). The main types of injuries were fractures (33.3%) and abrasions/contusions/puncture wounds (19.0%). The results of univariate analysis showed that there were statistically significant variations in the incidence of occupational injuries by gender, overtime, pre-job training, years of service in current position, alcohol consumption, physical exercise per week, and co-worker relationship (P<0.05). The logistic regression model showed that workers who exercised less than twice a week, did not participate in pre-job training, worked overtime, and had fair/poor/very poor colleague relationship had a higher risk of occupational injury, while women had a lower risk of occupational injury. Conclusion The distribution of occupational injury population is mainly male, and the time distribution is mainly from May to July. Gender, physical exercise, pre-job training, overtime, and colleague relationship are the influencing factors of occupational injuries. We should strengthen pre-job training, arrange work hours reasonably, and create a good working atmosphere to reduce the occurrence of occupational injuries.

Background Social psychological factors have emerged as a key area of research in occupational injury prevention. Occupational stress, a significant component of social psychology, has garnered widespread attention due to its potential impact on occupational injury. Objective To analyze the factors influencing occupational stress among cable manufacturing workers and explore the relationship between occupational stress and occupational injury, and to provide scientific evidence for reducing occupational stress and injury. Methods A questionnaire on basic demographics, occupational injury, and occupational stress (Effort-Reward Imbalance, ERI) was used to investigate 1343 workers in a cable enterprise. Chi-square test was employed to analyze the distribution of occupational stress across different worker characteristics. Logistic regression was used to identify factors influencing occupational stress, and a decision tree model was applied to assess the impact of occupational stress on injury risk. Results A total of 1225 valid questionnaires were collected, yielding a response rate of 91.2%. The positive rate of occupational stress was 28.7%, while the incidence of occupational injury in the past year was 8.6%. The results of univariate analysis revealed that workers who had experienced occupational injuries had a higher positive rate of occupational stress compared to those without injuries (P<0.05), and there were significant differences in the distribution of occupational stress by genders, overtime work, shift work, daily working hours, fatigue levels, sleep duration, family relationships, and colleague relationships (P<0.05). The logistic regression results showed that individuals who worked shifts, had fair/poor/very colleague relationships, and frequently worked overtime had a higher risk of occupational stress (P<0.05). The final decision tree model confirmed that occupational stress was a risk factor for occupational injury. Additional factors influencing occupational injury included physical exercise, colleague relationships, pre-job training participation, and gender. Workers who exercised less than twice per week and experienced occupational stress had a significantly higher risk of injury (23.6%) compared to those without occupational stress (10.9%). Conclusion Shift work, colleague relationships, and overtime work are correlated with the positive rate of occupational stress among cable manufacturing workers. Implementing a reasonable work schedule and fostering a positive work environment are recommended. Reducing occupational stress may help lower the risk of occupational injuries in this industry.

Background Light gradient boosting machine (LightGBM) has become a popular choice in prediction models due to its high efficiency and speed. However, the "black box" issues in machine learning models lead to poor model interpretability. At present, few studies have evaluated the severity of occupational injuries from the perspective of LightGBM model and model interpretability. Objective To evaluate the application value of LightGBM models and model interpretability methods in occupational injury prediction. Methods The Mine Safety and Health Administration (MSHA) occupational injury data set of mining industry workers from 1983 to 2022 was used. Injury severity (death/fatal occupational injury and permanent/partial disability) was used as the outcome variable, and the predictor variables included the month of occurrence, age, sex, time of accident, time since beginning of shift, accident time interval from shift start, total experience, total mining experience, experience at this mine, cause of injury, accident type, activity of injury, source of injury, body part of injury, work environment type, product category, and nature of injury. Feature sets were screened using least absolute shrinkage and selection operator (Lasso) regression. A LightGBM model was then employed to predict occupational injury, with area under curve (AUC) of the model serving as the primary evaluation metric; an AUC closer to 1 indicates better predictive performance of the model. The interpretability of the model was evaluated using Shapley additive explanations (SHAP). Results Through Lasso regression, 7 key influencing factors were identified, including accident time interval from shift start, experience at this mine, cause of injury, accident type, body part of injury, nature of injury, and work environment type. A LightGBM model, constructed based on feature selection via Lasso regression, demonstrated good predictive performance with an AUC value of 0.9941 (95%CI: 0.9917, 0.9966), accuracy of 0.9743, specificity of 0.9781, and sensitivity of 0.9640. The predicted probability of fatal occupational injuries showed high consistency with the actual probability of fatal occupational injuries. In the occupational injury prediction model, the importance of each indicator was analyzed through its SHAP value, and it was found that the body part of injury and the nature of injury were the two main features that affected the prediction results of the model, and the impacts of other features were relatively small. The distribution of SHAP values across body part of injury was broad, with significant impacts on the model's prediction of fatal risk, particularly for injuries to the head and neck, as well as multi-part injuries. The nature of injury also exerted influences on the model in different directions, with suffocation/drowning, crushing, and multi-part injuries having a greater impact on the risk of fatal occupational injuries. Conclusion LightGBM model is capable of efficiently processing large-scale data and providing high-precision prediction results. Research on model interpretability aids in more accurately exploring and analyzing various key risk factors for fatal occupational injuries among mining workers, and further reveals the complex interactions among these factors. This, in turn, enables better preventive intervention and protection measures, as well as optimal resource allocation for labor workers.

The traditional medical quality management model has many problems,such as excessive reliance on experience,poor coordination among departments,and lagging supervision,innovating medical quality management models has become an essential issue for the high-quality development of hospitals.A tertiary Grade A general hospital built a"data element multiplier"ecological chain for medical quality management,and established a complete closed-loop management system for medical quality management under the"Internet plus"model.Finally,the mobile medical quality management platform was built.Jointly driven by"Internet plus"and"data element multiplier",the level of lean management has been significantly improved,providing practical reference for hospitals at the same level.

Objective: To assess the dynamic changes of microcirculation at acupoints in patients with primary dysmenorrhea and cold congelation and blood stasis syndrome using laser speckle blood flow imaging. Methods: Patients with primary dysmenorrhea and cold coagulation and blood stasis syndrome (primary dysmenorrhea group, n=53) and healthy female college students(control group, n=57) who met the inclusion and exclusion criteria from October 2020 to July 2022 were enrolled at Hebei University of Chinese Medicine. On the premenstrual and first day of menstruation, a laser speckle blood flow imaging system was used to measure the microcirculation blood flow perfusion on the surface of acupoints related to the conception, thoroughfare, and governor vessels, and stomach, spleen, and bladder meridians in the abdomen and lumbosacral regions. The dynamic changes in microcirculation were calculated based on the difference in average blood flow perfusion at each acupoint before and after menstruation. Receiver operating curve (ROC) analysis was used to analyze the diagnostic efficacy of dynamic changes in microcirculation on the surface of each acupoint. The microcirculation sensitization rate of acupoints was calculated. Results: Compared with the control group, the dynamic changes in microcirculation at the following acupoints in the primary dysmenorrhea group were increased (P<0.05): conception vessel (Yinjiao[CV7], Qihai[CV6], Shimen[CV5], Guanyuan[CV4]); left thoroughfare vessel (left Huangshu[KI16], left Zhongzhu[KI15], left Siman[KI14], left Qixue[KI13], left Dahe[KI12], left Henggu[KI11]); left stomach meridian (left Tianshu[ST25], left Wailing[ST26], left Qichong[ST30]); left spleen meridian (left Daheng[SP15], left Fujie[SP14]); right thoroughfare vessel (right Huangshu[KI16], right Zhongzhu[KI15], right Siman[KI14], right Qixue[KI13], right Dahe[KI12], right Henggu[KI11]); right stomach meridian (right Wailing[ST26], right Daju[ST27], right Shuidao[ST28], right Guilai[ST29], right Qichong[ST30]); and right spleen meridian (right Fujie[SP14]). The area under the ROC curve of conception vessel (Yinjiao[CV7], Qihai[CV6], Shimen[CV5], Guanyuan[CV4]), thoroughfare vessel (right Siman[KI14], left Huangshu[KI16], right Qixue[KI13], right Zhongzhu[KI15], right Dahe[KI12], left Zhongzhu[KI15], left Siman[KI14], right Huangshu[KI16], left Qixue[KI13], right Henggu[KI11], left Henggu[KI11], left Dahe[KI12]); stomach meridian (left Tianshu[ST25], right Guilai[ST29], left Wailing[ST26], right Shuidao[ST28], right Daju[ST27], right Wailing[ST26], right Qichong[ST30], left Qichong[ST30]), and spleen meridian (left Daheng[SP15], left Fujie[SP14], right Fujie[SP14]) was 0.610-0.682 (P<0.05). Compared with the control group, the sensitization rate of some acupoints in the primary dysmenorrhea group increased (P<0.05). Conclusion With the onset of menstruation, the blood flow perfusion of some acupoints in the abdomen (thoroughfare, and conception vessels, and stomach and spleen meridians) of patients with primary dysmenorrhea and cold blood coagulation and blood stasis syndrome increased, and the status of acupoints changed from a resting state to an active state. These acupoints are sensitive in patients with primary dysmenorrhea and cold blood coagulation and blood stasis syndrome and have a certain diagnostic efficacy, providing a basis for further analyzing the efficacy and mechanism of acupuncture and moxibustion to treat primary dysmenorrhea with cold blood coagulation and blood stasis syndrome.