OBJECTIVE:To systematically review the efficacy of ursodeoxycholic acid(UDCA)in the prevention ofulcerative colitisassociated colorectal cancer (UC-CRC) and dysplasia (UC-Dys),and provide evidence-based reference for clinic. METH-ODS:Retrieved from Cochrane Library,EMBase,PubMed,CJFD,CBM,VIP and Wanfang Database,randomized controlled tri-als(RCT)or cohort studies about UDCA(test group)versus placebo(control group)in the prevention of UC-CRC and UC-Dys were collected. Meta-analysis was performed by using Rev Man 5.3 software after quality evaluation and data extraction by Co-chrane Manual 5.1.0. RESULTS:Totally 7 studies(3 randomized controlled trials and 4 cohort studies)were included in the analy-sis,involving 672 patients. Results of Meta-analysis of 3 RCT showed that there was no significant difference in the incidence of UC-CRC and UC-Dys between 2 groups [OR=0.95,95%CI(0.17,5.12),P=0.95];results of Meta-analysis of 4 cohort studiess-howed that there was no significant difference in the incidence of UC-CRC and UC-Dys between 2 groups[OR=0.74,95%CI(0.30, 1.84),P=0.52]. Results of subgroup analysis showed,the incidence of UC-CRC and UC-Dys in test group with low-dose UDCA (<15 mg/kg) was significantly lower than control group,the difference was statistically significant [OR=0.19,95%CI(0.08, 0.49),P<0.001];there were no signifficant diferences in the incidence of UC-CRC and UC-Dys in high-dose UDCA group[OR=1.97,95%Cl(0.53,7.25),P=0.31](≥15 mg/kg). There was no significant difference in the incidence of adverse reactions(P>0.05). CONCLUSIONS:UDCA can not decease the incidence of UC-CRC and UC-Dys,it only prompts a possible trend toward decreased UC-CRC and UC-Dys risk in low-doseUDCA.

Objective To study the effective hemostatic method for treating multiple trauma accompanied with hemorrhagic shock to increase the existence rate. Methods In treating 5 patients of multiple tauma accompanied with hemorrhagic shock, We used radiological embolism to injuried parenchymatous organs and injuried vessels to arrest the bleeding at first. After shock recovered, prompt exploration was made to repair injuried hollow viscus. Results After embolism and bleeding arrested, shocks in all 5 patients were corrected in short time; and no serious active hemorrhage was found after abdominal operation to repair the hollow viscus. All 5 patients survived after the operation. Conclusions The radiological embolism is simple,and has the little trauma and a good hemostatic effect,and needs short time. The method for treating multiple trauma can improve the salvage rate of multiple trauma accompanied with hemorrhagic shock and fit the treatment principle of multiple trauma.

Objective:To investigate the application value of machine learning algorithms for gauze detection in laparoscopic pancreatic surgery.Methods:The retrospective and descriptive study was conducted. The 80 intact laparoscopic pancreatic surgery videos from Peking Union Medical College Hospital of Chinese Academy of Medical Sciences with timing of July 2017 to July 2020 were collected. The training set was used to train the neural network, and the test set was used to test the ability of neural network for gauze detection under different difficulties. Under the supervision of two superior doctors, videos that containing gauze were selected and classified according to recognition difficulty into three difficulty level including easy, normal and hard difficulty, and further divided based on random number method into training set with 61 videos and test set with 19 videos in a ratio of 3:1 roughly. The minimum enclosing rectangle of the gauze were marked frame by frame. All images were input to the neural network model for training after normalization and preprocessing. For every image, the output of neural network is the predicted minimum enclosing rectangle of gauze. The intersection over union >0.5 was identified as positive result. Observation indicators: (1) video annotation and classification; (2) test outcomes of neural network for test set.Count data were represented as absolute numbers or percentages.Results:(1) Video annotation and classification: a total of 26 893 frames of images form 80 videos were annotated, with 61 videos including 22 564 frames of images as the training set and 19 videos including 4 329 frames of images as the test set. Of the training set, 19 videos including 5 791 frames of images were classifed as easy difficulty, 38 videos including 15 771 frames of images were classifed as normal difficulty, 4 videos including 1 002 frames of images were classifed as hard difficulty, respectively. Of the test set, 4 videos including 1 684 frames of images were classifed as easy difficulty, 6 videos including 1 016 frames of images were classifed as normal difficulty, 9 videos including 1 629 frames of images were classifed as hard difficulty, respectively. (2) Test outcomes of neural network for test set: the overall sensitivity and accuracy of gauze detection by neural network in the test set were 78.471%(3 397/4 329) and 69.811%(3 397/4 866), respectively. The sensitivity and accuracy of gauze detection by neural network were 94.478%(1 591/1 684) and 83.168%(1 591/1 913) in easy difficulty test set. The sensitivity and accuracy of gauze detection by neural network were 80.413%(817/1 016) and 70.859%(817/1 153) in normal difficulty test set, 60.712%(989/1 629) and 54.944%(989/1 800)in hard difficulty test set. The frame rate reached more than or equally to 15 fps. The overall false negative rate and false positive rate of gauze detection by neural network in the test set were 21.529%(932/4 329) and 30.189%(1 469/4 866), respectively. The false negative was mainly due to the existence of blurred images, too small gauze exposure or blood immersion of gauze. The false positive was caused by the reflection of connective tissue or body fluids.Conclusion:The machine learning algorithms for gauze detection in laparoscopic pancreatic surgery is feasible, which could help medical staff identify gauze.

Objective:To explore whether deep learning could apply to recognize the recurrent laryngeal nerve (RLN) in videos of endoscopic thyroidectomy (ETE) via breast approach.Methods:Videos of ETE via breast approach in Peking Union Medical College Hospital from Feb. 2020 to Aug. 2021 were collected. Videos containing RLN were selected, and the outline of RLN was marked by two thyroid surgeons. Then data were divided into a training set and a test set in a ratio of 5:1 and classified into the high and low difficulty group according to a senior thyroid surgeon’s opinion. Those pictures were input to D-LinkNet model. Precision, sensitivity and mean dice index was calculated.Results:A total of 46 videos including 153, 520 frames of pictures were included in this study. 131,039 frames of 39 videos were in the training set and 22,481 frames of 7 videos were in the test set. When the intersection over union threshold was 0.1, the sensitivity and precision was 92.9%/72.8% and 47.6%/54.9% in high and low recognition group, respectively. When the intersection over union threshold was 0.5, the sensitivity and precision turned to 85.8%/67.2% and 37.6%/43.5% in high and low difficulty group, respectively. Mean Dice index was 0.781 and 0.663 in high and low difficulty group, respectively.Conclusions:RLN recognition based on deep learning is feasible and has potential application value in ETE, which may help surgeons reduce the risk of accidental injury of RLN and improve the safety of thyroidectomy.

Objective:To explore whether deep learning could apply to recognize the recurrent laryngeal nerve in the video of unilateral axillary approach endoscopic thyroidectomy.Methods:Videos of endoscopic thyroidectomy via unilateral axillary approach in Peking Union Medical College Hospital from Jul. 1st, 2020 to May. 1st, 2021 were collected. Videos containing the recurrent laryngeal nerve were selected, and the outline of recurrent laryngeal nerve were marked by two senior thyroid surgeons and staffs. Data were divided into training set and test set in a ratio of 5:1, and classified into high, medium and low recognition group according to difficulty of recognizing the outline of the nerve. The neuron network was based on PSPNet combined with Resnet50. All data were analyzed by R (ver. 4.0.2) .Results:A total of 38 videos including 35,501 frames of pictures were included in this study. 29, 704 frames of 32 videos were in our training set and 5797 frames of 6 videos were in the test set. When the intersection over union (IOU) threshold is 0.1, the sensitivity and precision is 100.0%/92.1%, 95.8%/80.2% and 81.0%/80.6% in high, medium and low recognition group respectively. When the IOU threshold is 0.5, the sensitivity and precision is 92.6%/85.3%, 71.7%/60.5% and 38.1%/37.9% in high, medium and low recognition group respectively, indicating that neuron network could located the outline of recurrent laryngeal nerve in high and medium recognition group. False negatives were often due to small targets and unclear boundaries.Conclusion:Recurrent laryngeal nerve recognition based on deep learning is feasible and has potential application value in endoscopic thyroidectomy, which may help surgeons reduce the risk of accidental injury of recurrent laryngeal nerve and improve the safety of thyroidectomy.

Ureteral artery fistula (UAF) is a rare complication after long-term indwelling of ureteral stent. In this study, two cases were presented. Both of them underwent pelvic tumor surgery and radiotherapy, and had a history of cutaneous terminal ureterostomy and long-term indwelling of ureteral stents. The first case, a 52-year-old female, was admitted to hospital because of intermittent bleeding from ureteral dermostomy for 1 week on April 2, 2020. CT examination revealed hematocele in the left upper urinary tract, and left nephrectomy was performed.However, bleeding still presented and the distal ureteral resection was performed at the same time, and partial ureteral was ligated. Postoperative diagnostic was ureteral artery fistula. After 8 months of follow-up, no recurrent bleeding presented. Another case, a 82-year-old male, was admitted to hospital because of bleeding at the ureteral dermostomy for an hour on June 15, 2020. Contrast enhanced CT examination revealed intersecting of the left ureter and common iliac artery, and interventional surgery was performed, by which UAF was diagnosed. Embolization of left internal iliac artery and stent implantation of common iliac artery and external iliac artery were performed intraoperatively. The bleeding stopped immediately after the operation, and there was no further bleeding during follow-up of 6 months.

Accurate classification of the acetabular injuries and appropriate treatment plan are great challenges for orthopedic surgeons because of the irregular anatomical structure of the acetabulum and aggregation of important vessels and nerves around it. Letournel-Judet classification system has been widely applied to classify acetabular fractures. However, there are several limitations, including incomplete inclusion of fracture types, difficulty in understanding and insufficient guidance for surgical treatment, etc. Serious complications such as traumatic arthritis are common due to wrong classification and diagnosis and improper selection of surgical strategy, which brings a heavy burden to the society and families. Three-column classification, based on anatomic characteristics, has advantages of containing more fracture types and being easy to understand, etc. To solve the problems existing in the diagnosis and treatment process based on Letournel-Judet classification, achieve accurate diagnosis and treatment of patients with acetabular fractures, and obtain satisfactory prognosis, the Orthopedic Trauma Emergency Center of Third Hospital of Hebei Medical University and the Trauma Orthopedic Branch of the Chinese Orthopedic Association organized experts from relevant fields to formulate the Expert consensus on the accurate diagnosis and treatment of acetabular fractures based on three-column classification ( version 2023) in terms of principles of evidence-based medicine. Based on the three-column classification, 15 recommendations were proposed, covering the diagnosis, treatment, complication prevention and management, etc, so as to provide reference for accurate diagnosis and treatment of acetabular fractures.

Chronic refractory wound (CRW) is one of the most challengeable issues in clinic due to complex pathogenesis, long course of disease and poor prognosis. Experts need to conduct systematic summary for the diagnosis and treatment of CRW due to complex pathogenesis and poor prognosis, and standard guidelines for the diagnosis and treatment of CRW should be created. The Guideline forthe diagnosis and treatment of chronic refractory wounds in orthopedic trauma patients ( version 2023) was created by the expert group organized by the Chinese Association of Orthopedic Surgeons, Chinese Orthopedic Association, Chinese Society of Traumatology, and Trauma Orthopedics and Multiple Traumatology Group of Emergency Resuscitation Committee of Chinese Medical Doctor Association after the clinical problems were chosen based on demand-driven principles and principles of evidence-based medicine. The guideline systematically elaborated CRW from aspects of the epidemiology, diagnosis, treatment, postoperative management, complication prevention and comorbidity management, and rehabilitation and health education, and 9 recommendations were finally proposed to provide a reliable clinical reference for the diagnosis and treatment of CRW.