Objective:To summarize the nursing experience in the treatment of ischemic diseases of lower extremity by continu-ous arterial catheter-directed thrombolysis (CDT).Methods:From March 2010 to October 2014,99 patients with lower ex-tremity ischemic diseases were treated by continuous arterial CDT in Vascular Department,Zhongshan Hospital,Fudan Uni-versity.The routine nursing records were reviewed.The main nursing measures included the preoperative nursing of ischemic limb,postoperative nursing of thrombolytic catheter as well as the prevention and nursing of the complications.Results:A-mong the 99 patients accepted CDT treatment,there were 1 case of death resulted from septic shock,4 cases of amputation, while the ischemia situation of the remaining 94 patients were improved with good recovery.Conclusions:For the patients with ischemic diseases of lower extremity,taking reasonable and effective nursing measures in peri-operation period is one of the fac-tors to determine the efficacy of CDT.

Objective:Based on the Delphi method, the electronic intelligent kanban system for general ward nursing was constructed, and its clinical application was studied.Methods:This study was the quasi experimental research, 39 nursing staff working in the experimental ward of electronic intelligent kanban in general surgery of Zhongshan Hospital Fudan University in November 2021 and November 2022 were selected, Delphi expert consultation was used to develop the menus and detailed contents of general ward nursing electronic intelligent kanban system, and it was used in clinical practice. We used the Chinese version of the Nursing Assessment of Shift Report to evaluate the effect of nursing staff before and after the application.Results:The authority coefficients of the two rounds of expert consultation were 0.868 and 0.886 respectively, and the Kendall coordination coefficients of expert consultation were 0.068 and 0.076 respectively (all P<0.01). Finally, the electronic intelligent kanban consisted of 4 first-level menus, 8 second-level menus and 13 third-level menus. After the application of electronic intelligent kanban, the score of Nursing Assessment of Shift Report increased from (79.62 ± 7.64) to (83.51 ± 2.47), with a statistically significant difference ( t=-3.03, P<0.05). Conclusions:The constructed nursing electronic intelligent kanban system was scientific and reliable, which will be beneficial to improve the the effect of nurse shift handover.

Objective:To construct a clinical prediction model for early postoperative parastomal hernia in patients with enterostomy and to conduct internal and external validation and evaluation of clinical benefit.Methods:A total of 1 071 patients with enterostomy treated in Zhongshan Hospital Affiliated to Fudan University from October 2013 to December 2020 were selected as the research objects by the convenient sampling method. Patients from October 2013 to December 2019 were selected as the modeling group ( n=943) . The data of patients were obtained by questionnaire and other methods. The clinical prediction model of early postoperative parastomal hernia in patients with enterostomy was constructed based on Cox regression analysis and the model was internally verified by Bootstrap method. Patients from January to December 2020 were selected as the validation group ( n=128) for external validation of the model. C-statistic, area under receiver operating characteristic curve and calibration map were used to evaluate the discrimination and calibration of the model. Decision curve analysis was used to draw decision curve analysis chart to evaluate the clinical benefit of the prediction model. Results:Age, history of alcohol consumption, postoperative body mass index, diabetes mellitus, respiratory diseases, history of abdominal surgery, stoma route, stoma nature and C-reactive protein were independent influencing factors for early postoperative parastomal hernia in patients with enterostomy ( P<0.05) . The C- index value of early postoperative nomogram was 0.710 (95% CI: 0.660-0.750) . Conclusions:The clinical prediction model of early parastomal hernia in patients with enterostomy has good predictive performance, which can help clinical medical staff to screen out high-risk groups in time and guide medical staff to focus on prevention.

Objective:To construct a clinical prediction model for early postoperative parastomal hernia in patients with enterostomy and to conduct internal and external validation and evaluation of clinical benefit.Methods:A total of 1 071 patients with enterostomy treated in Zhongshan Hospital Affiliated to Fudan University from October 2013 to December 2020 were selected as the research objects by the convenient sampling method. Patients from October 2013 to December 2019 were selected as the modeling group ( n=943) . The data of patients were obtained by questionnaire and other methods. The clinical prediction model of early postoperative parastomal hernia in patients with enterostomy was constructed based on Cox regression analysis and the model was internally verified by Bootstrap method. Patients from January to December 2020 were selected as the validation group ( n=128) for external validation of the model. C-statistic, area under receiver operating characteristic curve and calibration map were used to evaluate the discrimination and calibration of the model. Decision curve analysis was used to draw decision curve analysis chart to evaluate the clinical benefit of the prediction model. Results:Age, history of alcohol consumption, postoperative body mass index, diabetes mellitus, respiratory diseases, history of abdominal surgery, stoma route, stoma nature and C-reactive protein were independent influencing factors for early postoperative parastomal hernia in patients with enterostomy ( P<0.05) . The C- index value of early postoperative nomogram was 0.710 (95% CI: 0.660-0.750) . Conclusions:The clinical prediction model of early parastomal hernia in patients with enterostomy has good predictive performance, which can help clinical medical staff to screen out high-risk groups in time and guide medical staff to focus on prevention.