Bile duct injury caused by abdominal trauma, usually accompanied with injuries of other abdominal organs, is rarely seen. For the reason of its complexity and often delayed diagnosis and treatment, bile duct injury usually leads to severe complications such as abdominal infection. This paper reports a group of 10 cases of bile duct injury treated in our center in the recent decade.

Objective To analyze the quality of life and its influencing factors among patients with occupational coal workers' pneumoconiosis (hereinafter referred to as "coal workers' pneumoconiosis"). Methods A total of 404 coal workers' pneumoconiosis patients diagnosed in Fengjie County of Chongqing City were selected as the study subjects using the convenient sampling method, and their quality of life was investigated by the SF-36 scale. Results The total score of quality of life of the subjects was (63.1±12.1) points. Their scores in the eight dimensions of physical functioning, role-physical, bodily pain, general health subscales, vitality, social functioning, role-emotional, and mental health subscales were lower than that of norms for Chongqing City and the nation (all P<0.05). The results of multiple linear regression analysis showed that the total score of quality of life of the patients decreased with the increase of age and stage of pneumoconiosis (all P<0.01). The total score of quality of life of patients living in urban areas was higher than that of rural patients(P<0.01). The total score of quality of life of patients who had left their jobs was higher than that of retired patients (P<0.01). The total score of quality of life of smoking patients and those with complications was lower than that of non-smokers and those without complications (all P<0.01). Conclusion Age, place of residence, smoking, stage of pneumoconiosis, work status, and complications of pneumoconiosis were the main influencing factors of quality of life among coal workers' pneumoconiosis patients.

OBJECTIVE： To provide experience and reference for the study of medical insurance budget impact analysis （BIA） in China. METHODS： Retrieved from PubMed， ProQuest， CNKI， Wanfang database and CBM， related literatures about medical insurance BIA research in China and the United States were collected since the establishment of the database. The basic information， analysis results and data sources were summarized and sorted out， and descriptive analysis of the included literature was carried out on basis of seven key elements such as model design， research perspective， treatment cost， reference scenario， target population， research time limit and discount/inflation， sensitivity analysis. RESULTS： A total of 72 literatures were included in this study， involving 24 （33.33％） studies in China， 48 （66.67％） studies in the United States； the indications of 45 studies were chronic diseases （62.50％）， and those of 21 studies were acute diseases （37.50％）. Among the research methods， 49 studies （68.06％） used BIA alone and 23 studies （31.94％） adopted BIA combined with pharmaceutical economics. In terms of model design， 50 studies （69.44％） adopted cost calculation models. In terms of research perspective， 60 studies （81.94％） were based on the perspective of medical insurance department research. In the calculation of treatment cost， 69 studies （95.84％） included drug cost. In terms of reference scenarios， 61 studies （84.72％） compared the economics of different drug-based treatment groups. For target population， only 31  （43.06％） studies used real world data. In terms of research duration and discount/inflation， 14 studies （19.44％） used treatment or length of hospitalization to indicate research duration， and 19 studies （26.39％） used discount rate or inflation rate to adjust costs. As for sensitivity analysis， 62 studies （86.11％） conducted sensitivity analysis， of which 49 （68.06％） used single factor sensitivity analysis. CONCLUSIONS： There are still some limitations in medical insurance BIA research literature in China and the United States， such as unreasonable use of data， incomplete coverage of the cost， and unreasonable setting of sensitivity analysis variables. It is recommended that BIA research should standardize data sources to improve the quality of budget evidence quality， reasonably evaluate market size to improve the authenticity of prediction， scientifically set variables and their scope of change to improve the stability of results， establish BIA research paradigms or evaluating standards so as to guide BIA research scientifically.