Background: Owing to the development of double-balloon enteroscopy (DBE) and video capsule endoscopy (VCE) in recent years, direct visualization of the entire small intestinal mucosa has become possible. Because of the nonspecific symptoms and the anatomic location of the small bowel, diagnosis of isolated small bowel Crohn’s disease (CD) remains a challenge. The aim of this research was to explore the value of DBE for isolated small bowel CD in situations where routine tests cannot confirm the diagnosis. Methods: This study included patients with suspected isolated small bowel CD who were hospitalized in Shengjing Hospital from April 2014 to June 2018. We included patients presenting with chronic diarrhea, abdominal pain, abdominal mass, perianal lesions, and systemic symptoms including weight loss, fever, and anemia after excluding infection factors. Patients with purely colonic CD were excluded from this cohort. Patients with suspected isolated small bowel CD underwent DBE. Results: In 16/18 patients, pathological findings were detected by DBE. In 12 of the cases, small bowel CD was confirmed. The remaining four patients were diagnosed with small bowel inflammation, duodenal carcinoma, ileum inflammation and small bowel ulcers. However, the diagnosis of CD was confirmed in 14/18 (78%) patients by taking into account the clinical presentation, endoscopic and histological results as well as the experimental treatment. DBE assisted in the diagnosis in 86% (12/14) of the patients. Conclusions: In the diagnosis of small bowel CD, DBE is a helpful tool. Before assessment with DBE, clinical features, colonoscopy, and CT were used to initially assess the intestine. According to the lesions indicated by CT, we chose the most appropriate endoscope insertion route, and combined the endoscopic characteristics and pathological results of DBE to confirm the diagnosis.

Purpose: This study was to investigate the diagnostic efficacy of radiomics models based on the enhanced CT images in differentiating the malignant risk of gastrointestinal stromal tumors (GIST) in comparison with the clinical indicators model and traditional CT diagnostic criteria.Materials and methods: A total of 342 patients with GISTs confirmed histopathologically were enrolled from five medical centers. Data of patients wrom two centers comprised the training group (n=196), and data from the remaining three centers constituted the validation group (n=146). After CT image segmentation and feature extraction and selection, the arterial phase model and venous phase model were established. The maximum diameter of the tumor and internal necrosis were used to establish a clinical indicators model. The traditional CT diagnostic criteria were established for the classification of malignant potential of tumor. The performance of the four models was assessed using the receiver operating characteristics curve.Reuslts: In the training group, the area under the curves(AUCs) of the arterial phase model, venous phase model, clinical indicators model, and traditional CT diagnostic criteria were 0.930 [95% confidence interval (CI): 0.895-0.965), 0.933 (95%CI 0.898-0.967), 0.917 (95%CI 0.872-0.961) and 0.782 (95%CI 0.717-0.848), respectively. In the validation group, the AUCs of the models were 0.960 (95%CI 0.930-0.990), 0.961 (95% CI 0.930-0.992), 0.922 (95%CI 0.884-0.960) and 0.768 (95%CI 0.692-0.844), respectively. No significant difference was detected in the AUC between the arterial phase model, venous phase model, and clinical indicators model by the DeLong test, whereas a significant difference was observed between the traditional CT diagnostic criteria and the other three models.Conclusion: The radiomics model using the morphological features of GISTs play a significant role in tumor risk stratification and can provide a reference for clinical diagnosis and treatment plan.

Background: This study aims to explore the influence of off-pump coronary artery bypass grafting (OPCABG) on coagulation function and the effects of diabetes on coagulation function during OPCABG. Methods: Patients who met the inclusion and exclusion criteria were divided into two groups: diabetes mellitus (DM) and non-diabetes mellitus (NDM) groups. Thromboelastography (TEG) was tested at the following time points: T0, five days after aspirin and clopidogrel therapy, and before OPCABG; T1, returning to care unit after OPCABG; T2, 5 days after aspirin and clopidogrel therapy, and after OPCABG. Results: A total of 56 patients were involved. There were no deaths, or no early postoperative thrombotic events and abnormal bleeding after OPCABG. Intra-group comparison: Compared with T0, the R and K value decreased, while the α angle and MA value increased at T1 and T2, in both groups (P<0.05). A significantly statistical difference was found in the multiple comparison at T0, T1 and T2 (P0.05). Conclusions: The coagulation function of patients was at a hypercoagulable state at the early stage after OPCABG. The coagulation function was affected by diabetes at the day of OPCABG. However, there was no statistical difference after 5 days of aspirin and clopidogrel therapy following OPCABG.

Background: Emerging research suggests that epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) agents are not universally effective in patients with EGFR-mutant non-small cell lung cancer (NSCLC), with many developing varying degrees of acquired resistance. Studies have found that such resistance is significantly associated with certain imaging features. Therefore, this study aimed to examine the application value of combining texture analysis techniques with computed tomography (CT) images in predicting the efficacy of targeted adjuvant therapy in patients with EGFR-mutant NSCLC following surgery. Methods: The basic clinical data of patients with EGFR-mutant NSCLC who underwent surgery followed by targeted therapy with first-generation EGFR-TKIs at the First Affiliated Hospital of Hebei North University between January 2019 and September 2024 were retrospectively collected. Texture features of the tumor were extracted from chest CT images via 3D Slicer software, and after standardization, feature dimensionality reduction and selection were performed through correlation analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Univariate and multivariate logistic regression analyses were then conducted on clinical and texture features to identify independent prognostic factors. A clinical model, a radiomics texture model, and a joint model were developed with R software (The R Foundation for Statistical Computing). Model performance was assessed with the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). A nomogram was constructed based on the combined model. Results: In this study, 150 texture features were extracted, and dimensionality reduction was conducted with the LASSO algorithm. At the optimal l-value of 0.0753, three candidate features were preliminarily selected. These three features were then subjected to univariate and multivariate logistic regression analyses, ultimately yielding one significant texture feature. Smoking was found to be an independent prognostic factor for patients with EGFR-mutant NSCLC (P<0.05). The AUC for predicting poor prognosis in patients with EGFR-mutant NSCLC was 0.756 for the clinical model, 0.771 for the texture-analysis model, and 0.90 for the combined model. The combined model demonstrated significantly better predictive performance than the individual models (P<0.05). DCA further confirmed the superior clinical utility of the combined model. A nomogram was constructed to provide an intuitive and quantitative tool for evaluating treatment efficacy in individual patients. Conclusions: CT texture-based analysis demonstrated favorable predictive performance in assessing the efficacy of postoperative adjuvant targeted therapy in patients with EGFR-mutant NSCLC. The proposed model offers an intuitive and reliable reference for individualized treatment planning.