ObjectiveTo investigate the effects of single anastomosis sleeve ileal (SASI) bypass on weight loss, metabolic improvements, and postoperative safety in patients with obesity and its metabolic comorbidities (such as type 2 diabetes and hyperlipidemia). MethodsA retrospective analysis was conducted. The clinical data of patients with obesity [body mass index (BMI) ≥32.5 kg/m² or BMI ≥27.5 kg/m² with metabolic diseases] who underwent SASI bypass in the Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School from January 2023 to December 2023. Weight loss outcomes, including the percentage of total weight loss (%TWL), percentage of excess weight loss (%EWL), and percentage of excess BMI loss (%EBMIL), were recorded at 6 and 12 months postoperatively. Metabolic disease remission and complications at 12 months postoperatively were also documented. ResultsA total of 82 patients were included in the study. At 12 months postoperatively, the reductions in %TWL, %EWL, and %EBMIL were significantly greater than those observed at 6 months postoperatively [%TWL: (27.1±4.6)% vs. (23.6±3.8)%, t=2.379, P=0.026; %EWL: (72.1±5.8)% vs. (56.6±7.3)%, t=2.593, P<0.001; %EBMIL: (71.6±6.7)% vs. (58.3±4.9)%, t=2.607, P<0.001], remission was observed in 40 out of 48 patients (83.3%) with comorbid hypertension, 49 out of 51 patients (96.1%) with comorbid type 2 diabetes mellitus, and all patients with comorbid hyperlipidemia (33 cases) and obstructive sleep apnea syndrome (29 cases) achieved complete remission. Within 12 months after SASI bypass, 3 patients (3.7%) experienced melena, 2 patients (2.4%) developed incomplete intestinal obstruction, and 10 patients (12.1%) showed malnutrition. ConclusionThe findings of this study indicate that SASI bypass demonstrates significant weight loss and metabolic improvement effects in patients with obesity and metabolic diseases, with a controllable safety profile.
ObjectiveTo evaluate the application value of three-dimensional (3D) reconstruction in preoperative surgical diagnosis of new classification criteria for lung adenocarcinoma, which is helpful to develop a deep learning model of artificial intelligence in the auxiliary diagnosis and treatment of lung cancer.MethodsThe clinical data of 173 patients with ground-glass lung nodules with a diameter of ≤2 cm, who were admitted from October 2018 to June 2020 in our hospital were retrospectively analyzed. Among them, 55 were males and 118 were females with a median age of 61 (28-82) years. Pulmonary nodules in different parts of the same patient were treated as independent events, and a total of 181 subjects were included. According to the new classification criteria of pathological types, they were divided into pre-invasive lesions (atypical adenomatous hyperplasia and and adenocarcinoma in situ), minimally invasive adenocarcinoma and invasive adenocarcinoma. The relationship between 3D reconstruction parameters and different pathological subtypes of lung adenocarcinoma, and their diagnostic values were analyzed by multiplanar reconstruction and volume reconstruction techniques.ResultsIn different pathological types of lung adenocarcinoma, the diameter of lung nodules (P<0.001), average CT value (P<0.001), consolidation/tumor ratio (CTR, P<0.001), type of nodules (P<0.001), nodular morphology (P<0.001), pleural indenlation sign (P<0.001), air bronchogram sign (P=0.010), vascular access inside the nodule (P=0.005), TNM staging (P<0.001) were significantly different, while nodule growth sites were not (P=0.054). At the same time, it was also found that with the increased invasiveness of different pathological subtypes of lung adenocarcinoma, the proportion of dominant signs of each group gradually increased. Meanwhile, nodule diameter and the average CT value or CTR were independent risk factors for malignant degree of lung adenocarcinoma.ConclusionImaging signs of lung adenocarcinoma in 3D reconstruction, including nodule diameter, the average CT value, CTR, shape, type, vascular access conditions, air bronchogram sign, pleural indenlation sign, play an important role in the diagnosis of lung adenocarcinoma subtype and can provide guidance for personalized therapy to patients in clinics.