Objective:To construct and evaluate the nomogram prediction model of spontaneous rupture of primary liver cancer (STRPLC), and make the web-based dynamic online nomogram.Methods:Clinical data of 346 patients with PLC treated in the Second Affiliated Hospital of Kunming Medical University were retrospectively analyzed, including 87 males and 15 females, aged 58.15±10.32 years. Single factor and multiple factor logistic regression analysis were used to screen the influencing factors of STRPLC, and the prediction model was constructed based on the nomogram. Receiver operating characteristic (ROC) curve, calibration curve and clinical decision analysis were used to evaluate the model. The web-based dynamic online nomogram was developed using the DynNom package in R4.3.1 software.Results:Multivariate logistic regression analysis showed that the independent risk factors for spontaneous rupture and hemorrhage of tumor were no history of systematic anti-tumor therapy, alpha-fetoprotein (AFP) level, tumor protrusion on liver surface, tumor length, invasion of major blood vessels, and moderate to large amount of ascites (all P<0.05). The area under the receiver operating characteristic curve (AUC) of the prediction model constructed by this nomogram is 0.913 (95% CI: 0.884-0.943), the best cutoff value is 0.254, with a sensitivity of 0.892, and a specificity of 0.803. The calibration curve shows a good agreement between the predicted probability and the actual probability. The decision curve of the model is above the two invalid lines of " none" and " all" in the horizontal range of 0.07-0.98, and the clinical net benefit of the model is >0. Then user-friendly web-based dynamic online nomogram is constructed. Conclusion:Large tumor size, superficial location, no history of systematic anti-tumor therapy, high AFP level, invasion of major blood vessels, and moderate to large amount of ascites are independent risk factors for STRPLC. The prediction model and dynamic online nanogram constructed by this method can effectively assess the risk of STRPLC.

Objective:To construct and evaluate the nomogram prediction model of spontaneous rupture of primary liver cancer (STRPLC), and make the web-based dynamic online nomogram.Methods:Clinical data of 346 patients with PLC treated in the Second Affiliated Hospital of Kunming Medical University were retrospectively analyzed, including 87 males and 15 females, aged 58.15±10.32 years. Single factor and multiple factor logistic regression analysis were used to screen the influencing factors of STRPLC, and the prediction model was constructed based on the nomogram. Receiver operating characteristic (ROC) curve, calibration curve and clinical decision analysis were used to evaluate the model. The web-based dynamic online nomogram was developed using the DynNom package in R4.3.1 software.Results:Multivariate logistic regression analysis showed that the independent risk factors for spontaneous rupture and hemorrhage of tumor were no history of systematic anti-tumor therapy, alpha-fetoprotein (AFP) level, tumor protrusion on liver surface, tumor length, invasion of major blood vessels, and moderate to large amount of ascites (all P<0.05). The area under the receiver operating characteristic curve (AUC) of the prediction model constructed by this nomogram is 0.913 (95% CI: 0.884-0.943), the best cutoff value is 0.254, with a sensitivity of 0.892, and a specificity of 0.803. The calibration curve shows a good agreement between the predicted probability and the actual probability. The decision curve of the model is above the two invalid lines of " none" and " all" in the horizontal range of 0.07-0.98, and the clinical net benefit of the model is >0. Then user-friendly web-based dynamic online nomogram is constructed. Conclusion:Large tumor size, superficial location, no history of systematic anti-tumor therapy, high AFP level, invasion of major blood vessels, and moderate to large amount of ascites are independent risk factors for STRPLC. The prediction model and dynamic online nanogram constructed by this method can effectively assess the risk of STRPLC.

Objective:To compare the efficacy and safety of robotic surgery and open surgery in the treatment of hilar cholangiocarcinoma.Methods:PubMed, Embase, Cochrane Library, Web of Science, CNKI and Wanfang database were searched to compare the treatment of hilar cholangiocarcinoma by robotic surgery and traditional open surgery. Literatures were searched from the establishment of the database to July 2023. Compare operation time, intraoperative blood transfusion rate, R 0 resection rate, lymph node metastasis rate, postoperative complication rate and hospital stays between the two groups. The combined odds ratio ( OR) and mean difference ( MD) and 95% confidence interval (95% CI) were calculated using RevMan 5.4 software. Results:A total of 4 studies were included, including 267 patients with hilar cholangiocarcinoma. There were 177 males and 90 females, aged (58.8±5.7) years. A total of 267 patients were divided into open surgery group ( n=165) and robotic surgery group ( n=102) according to the surgical formula. The extract results show: operative time ( MD=-103.96, 95% CI: -216.90-8.98, P=0.070) and intraoperative blood transfusion rate ( OR=1.32, 95% CI: 0.43-4.07, P=0.630), R 0 resection rate ( OR=1.41, 95% CI: 0.71-2.81, P=0.330), lymph node metastasis rate ( OR=1.62, 95% CI: 0.46-5.63, P=0.450), postoperative complications ( OR=0.60, 95% CI: 0.28-1.31, P=0.200), and postoperative hospital stay ( MD=2.17, 95% CI: -11.56-15.90, P=0.760). Conclusion:In the treatment of hilar cholangiocarcinoma, robotic surgery is as safe and feasible as open surgery. However, due to the limited number and quality of included studies, the above conclusions need to be verified by more high-quality studies.

Objective To constitute a database of chronic wounds for characterizing the patients with chronic wounds.Methods Based on the guideline of chronic wounds defined by international wound healing society,86 outpatients with chronic wounds were selected between January and October in 2013 to set up a wound database using the wound information management system.The parameters including etiology,age distribution,mean time of fracture healing and wound healing time posterior to different treatments were analyzed.Results (1) Statistical difference existed for cause distribution (P ＜0.05).Top three causes were trauma (29％),varicosity (26％) and pressure sore (19％).(2) Age distribution varied significantly among the patients with various causes of chronic wounds (P ＜ 0.05).(3) Statistical difference was observed in healing time of various types of chronic wounds (P ＜ 0.05).Diabetic wound and varicose ulcer took the longest healing time,with average 116.36 days and 88.48 days respectively.(4) Patients treated with novel dressings had shorter healing time than those managed with traditional dressings (P ＜ 0.05).Conclusions Trauma,varicosity and pressure ulcer are relatively common among the outpatients.Etiology of chronic wounds is strongly related to age and novel dressings contributed to a shortened cause of the disorder.