Objective To study the feasibility of the ultrasonic scalpel in the management of cystic blood vessels during laparoscopic cholecystectomy(LC). Methods Abdominal blood vessels of two dogs were managed by ultrasonic scalpel under the conditions of two step output power,low tension,low holding force and blunt scalpel head.The blood vessels were sealed and arteries and veins of (1～11)mm were cut.On this basis,the technique was applied to the management of cystic vessels during laparoscopic cystic and biliary operation. Results The sealing and cutting effect was good for the blood vessels of less than 9mm 140/150(93 3%).No blood oozing was found at the cutting ends of blood vessels during and after operation.In all 706 cases of laparoscopic gallbladder and biliary duct operations,no bleeding was found at the cutting ends of blood vessels during and after operation. Conclusions Ultrasonic scalpel can be directly used to seal and cut cystic artery during laparoscopic cholecystectomy.

Objective To explore the clinical value of the ten-point scale in the early diagnosis of fat embolism syndrome.Methods The data of 129 patients with fat embolism syndrome diagnosed by Gurd criteria admitted from January 1993 to February 2012 were analyzed retrospectively.At the same time,another 97 patients with single or multiple long bone fracture and/or pelvic fracture without fat embolism admitted from July 2005 to February 2012 were enrolled as control group.Patients were excluded if they had any of the following diseases:simple brain trauma,thoracic injury,spine fracture,hemorrhagic shock and the complications of cardiopulmonary cerebral resuscitation (CPCR).The patients of two groups were comparable in respect of clinical setting.The clinical data were analyzed and scored by the ten-point scale.The x2 test were applied to statistical works.Results Among all the clinical characteristics,the incidence of increased D-dimer was the highest (74.1％) in early fat embolism syndrome,followed by the progressive decrease in hemoglobin (63.6％) and hypoxemia (57.4％),and the occurrence of dyspnea was the lowest (17.8％).The percentage of total scores over ten points in patients with fat embolism syndrome group was higher than that in those without fat embolism syndrome (x2 =202.6,P ＜ 0.01).The sensitivity of tenpoint scale was 96.12％ and the specificity was 99.8％.Conclusions Ten-point scale could be used to make early diagnosis of fat embolism syndrome,thereby reducing the occurrence of misdiagnosis and misseddiagnosis.

Objective To investigate the effect of growth hormone replacement therapy on life quality of patients with growth hormone deficiency after sellar tumor surgery.Methods The data of 13 patients undergoing sellar tumor resection and suffering postoperative hypopituitarism from Jun.2009 to Dec.2010.were collected.Each of them was given daily 0.5 units growth hormone (about 0.17 mg) as replacement therapy.The life quality of patients at different time points was evaluated with QoL-GDHA scale.SPSS 17.0 software was used for statistical analysis.Results 1,3,and 6 months after treatment,QoL-GDHA score of the patients was 3.91± 2.29,3.38 + 2.43,and 3.23 + 2.28 repectively,significantly lower than before ( 8.69 ± 2.66).The difference had statistical significance (P ＜0.05 ).Conclusion Growth hormone replacement therapy can significantly improve the life quality of patients with hypopituitarism after sellar tumor surgery.

No abstract available.
Cerebral Infarction ; Infarction* ; Wrist*

Objective To investigate the prediction model of hypotension in patients with hepato-cellular carcinoma resection using controlled low central venous pressure technique(CLCVP).Methods A total of 144 patients with liver cancer admitted from January 2020 to June 2023 were retrospectively ana-lyzed,including 81 males and 63 females,aged 45-64 years,BMI 22-26 kg/m2,ASA physical status Ⅰ or Ⅱ.144 patients were randomly divided into trial set(n=96)and verification set(n=48)according to 2:1.The trial set and verification set were divided into hypotensive group and non-hypotensive group ac-cording to whether hypotension occurred after operation.Preoperative albumin,preoperative hemoglobin,op-eration method,operation time,tumor site,tumor size,hilar block time,number of hilar block times,hilar block interval time,blood loss,mean intraoperative CVP,intraoperative fluid volume,and intraoperative u-rine volume were collected.Univariate and multivariate Logistic analysis were used to analyze the risk factors of hypotension in the experimental group,and a risk prediction model was established.The risk prediction model was verified in the validation group.Results There were 29 patients(30.2％)of postoperative hy-potension in the test group and 15 patients(31.3％)of postoperative hypotension in the validation group.Compared with the non-hypotensive group,the preoperative albumin in the hypotensive group was signifi-cantly decreased(P<0.05),the operation time was significantly prolonged,the ratio of tumor diameter≥5 cm,and the amount of blood loss were significantly increased(P<0.05).Multivariate analysis showed that preoperative albumin elevation(OR=0.216,95％CI 0.164-0.665,P<0.05)was an independent protective factor for postoperative hypotension.Prolonged operative time(OR=2.649,95％CI 1.802-7.553,P<0.05),tumor diameter≥5 cm(OR=3.789,95％CI 2.011-12.458,P<0.05),in-creased blood loss(OR=8.873,95％CI 2.750-17.553,P<0.05)was an independent risk factor for postoperative hypotension.According to the results of multi-factor analysis,the risk factors of postoperative hypotension in patients with controlled low central venous pressure hepatocellular carcinoma resection were established:F=-408.64-(1.534×preoperative albumin)+(0.974×operation time)+(1.332×tumor diameter≥5 cm)+(2.183×blood loss).The risk model was validated in the validation set,and the area under the ROC curve(AUC)was0.821(0.695-0.943),the sensitivity was71.7％,and the speci-ficity was 86.5％.The Hosmer-Lemeshow goodness of fit test showed that χ2=10.654,P=0.222.Conclusion Prolonged operative time,tumor diameter≥5 cm and increased blood loss are risk factors for hypotension after hepatocellular carcinoma resection using CLCVP technique,and higher preoperative albumin is protective factor.The establishment of risk prediction model through multi-factor analysis has good forecasting value.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.