Objective To explore the risk factors of gestational diabetes mellitus(GDM)in the first trimester(12～13+6 weeks)of pregnancy,build a prediction model and verify it.Methods 433 singleton pregnant women delivered in the First People's Hospital of Shanghai from January 2020 to December 2020 were selected.They were divided into GDM group(n=188)pregnant women and non-GDM group(n=245)pregnant women according to a 75g glucose tolerance test results at 24～28 weeks of gestation.The electrochemiluminescence method measured serum biochemical indexes in early pregnancy,and glycosylated hemoglobinAlc was measured by ion exchange high-performance liquid chromatography.Using logistic regression analysis to screen the risk factors of GDM and construct a predictive model,draw the subject's work characteristic curve to analyze the model's predictive value.Ninety-five pregnant women who underwent prenatal examinations at Shanghai First People's Hospital from January 2021 to June 2021 were selected to validate the model's effectiveness.Results Compared with the non-GDM group,the level of body mass index(BMI)(23.41±11.17 kg/m2 vs 21.18±2.88 kg/m2),gamma-glutamyl transpeptidase(γ-GGT)(16.61±10.62 U/L vs 14.00±8.35 U/L),triacylglycerol(TG)(1.90±0.58 mmol/L vs 1.57±0.55 mmol/L),glycosylated hemoglobinAlc(HbAlc)(5.25%±0.47%vs 5.07±0.34%),fasting blood glucose(FBG)(4.68±0.47 mmol/L vs 4.36±0.36 mmol/L),LDL/HDL(1.53±0.49 vs 1.41±0.50),TG/HDL(2.93±0.59 vs 2.71±0.58),and TC/HDL(1.19±0.49 vs 0.95±0.45)in GDM group was increased,and the level of highdensity lipoprotein-cholesterol(HDL)(1.69±0.39 mmol/L vs 1.77±0.41 mmol/L)was decreased,the differences were statistically significant(t=2.613,2.818,5.874,4.582,17.701,2.458,3.815,5.310,-2.187,all P＜0.05).Logistic regression analysis showed that pre-pregnancy BMI,FBG,HbAlc,TG,and TC/HDL were all independent risk factors for predicting gestational diabetes(Waldχ2=4.48～35.549,all P＜0.05).The prediction model constructed based on the selected risk factors was as follows:Logit(P)=-20.562+0.085(BMI)+1.921(FBG)+1.57(HbAlc)+2.248(TG)-2.302(TC/HDL).The model predicts that the area under the curve of GDM was 0.800(95%CI:0.757～0.842),the optimal cutoff value was 0.352,and the sensitivity and specificity were 80.00%and 66.00%,respectively.Ninety-five pregnant women validated the model,and its sensitivity,specificity,and accuracy were 84.50%,91.00%,and 85.30%,respectively.Conclusion The prediction model constructed by BMI combined with FBG,HbAlc,TG and TC/HDL in the first trimester(12～13+6 weeks)of pregnancy has a high predictive value for GDM.

Objective:To construct a real-time artificial intelligence (AI)-assisted endoscepic diagnosis system based on YOLO v3 algorithm, and to evaluate its ability of detecting focal gastric lesions in gastroscopy.Methods:A total of 5 488 white light gastroscopic images (2 733 images with gastric focal lesions and 2 755 images without gastric focal lesions) from June to November 2019 and videos of 92 cases (288 168 clear stomach frames) from May to June 2020 at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University were retrospectively collected for AI System test. A total of 3 997 prospective consecutive patients undergoing gastroscopy at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University from July 6, 2020 to November 27, 2020 and May 6, 2021 to August 2, 2021 were enrolled to assess the clinical applicability of AI System. When AI System recognized an abnormal lesion, it marked the lesion with a blue box as a warning. The ability to identify focal gastric lesions and the frequency and causes of false positives and false negatives of AI System were statistically analyzed.Results:In the image test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 92.3% (5 064/5 488), 95.0% (2 597/2 733), 89.5% (2 467/ 2 755), 90.0% (2 597/2 885) and 94.8% (2 467/2 603), respectively. In the video test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 95.4% (274 792/288 168), 95.2% (109 727/115 287), 95.5% (165 065/172 881), 93.4% (109 727/117 543) and 96.7% (165 065/170 625), respectively. In clinical application, the detection rate of local gastric lesions by AI System was 93.0% (6 830/7 344). A total of 514 focal gastric lesions were missed by AI System. The main reasons were punctate erosions (48.8%, 251/514), diminutive xanthomas (22.8%, 117/514) and diminutive polyps (21.4%, 110/514). The mean number of false positives per gastroscopy was 2 (1, 4), most of which were due to normal mucosa folds (50.2%, 5 635/11 225), bubbles and mucus (35.0%, 3 928/11 225), and liquid deposited in the fundus (9.1%, 1 021/11 225).Conclusion:The application of AI System can increase the detection rate of focal gastric lesions.

Objective:To investigate the application in the preparation of supraclavicular island flap by "point line anterograde dissection (PLAD) ".Methods:A retrospective analysis was performed on 45 flaps of 43 patients treated with supraclavicular artery island flap from the Department of Otorhinolaryngology Head and Neck Surgery, Beijing Tongren Hospital Affiliated to Capital Medical University from January 2013 to June 2019. The patients were all male, aged 35-72 years old. There were 26 cases of hypopharyngeal cancer, 4 cases of recurrent laryngeal cancer, 2 cases of cervical esophageal cancer, 1 case of tonsillar cancer, 1 case of parotid gland cancer, 3 cases of postoperative pharyngeal fistula after hypopharyngeal cancer, 2 cases of esophageal fistula after trauma, 2 cases of esophageal stricture after hypopharyngeal carcinoma operation, 1 case of autoimmune laryngeal stenosis, and 1 case of cheek defect after maxillary sinus cancer operation."Point" was the origin of the supraclavicular artery in the transverse carotid artery. "Line" was an extension line made along the starting point of the supraclavicular vessel for anterograde anatomy of 1-2 cm and the direction of the blood vessel. The extension line was used as the central axis of the designed island flap. Characteristics of flap blood supply, the time of flap preparation, flap survival, donor area recovery and clinical follow-up were recorded.Results:The arterial blood supply of the flap was constant, and the venous reflux was variable. The area of the prepared flap was (4-8) cm×(10-18) cm, and the preparation time was 30-60 min, with a median of 42 min. Skin flap survival rate was 100%. Partial necrosis of skin flap occurred in 1 patient and postoperative pharyngeal fistula occurred in 5 patients, all of whom were cured by dressing change. The donor site defects were closed and sutured directly. 3 patients had partial incision dehiscence and healed after dressing change. During the follow-up, 1 patient was lost, and the remaining 42 patients were followed up for 8 to 55 months.40 patients involved swallowing function, all of them returned to regular diet or soft fluid after operation.40 patients involved malignant tumors and local tumor recurrence in 3 patients among whom, there were 2 cases of lymph node recurrence, and 2 cases of distant metastasis, including 1 case of lung metastasis and 1 case of bone metastasis.Conclusion:PLAD is a simple, safe and efficient method for the preparation of supraclavicular island flap.