Objective To explore the influencing factors of poor prognosis after clipping in patients with ruptured intracranial aneurysm and hematoma,and to construct a clinical prediction model.Methods A total of 151 patients with aneurysmal intracranial hematoma in Dongyang People's Hospital were selected from September 2017 to October 2023.3 months after operation,the patients were grouped by modified Rankin scale(mRS),with 93 cases in good prognosis group and 58 cases in poor prognosis group.Univariate analysis and multivariate Logistic regression analysis were used to explore the risk factors affecting the poor prognosis of patients with postoperative prognosis,and a poor prognostic prediction model for patients with intracranial aneurysm rupture and hematoma clamping was constructed,the discriminant validity of the area under the curve(AUC)was evaluated,and the fit of the model was established using the Hosmer-Lemeshow test.Results The Hunt-Hess gradeⅣ-Ⅴ(OR=5.339),modified Fisher grade Ⅲ-Ⅳ(OR=5.145),hematoma volume≥ 50ml(OR=7.426),hematoma clearance rate was≤50％(OR=8.381),size of the responsible aneurysm＞5mm(OR=3.053),operation time window＞5h(OR=2.659),and intraoperative vascular operation time＞3h(OR=2.305)were independent risk factors for poor prognosis after clipping in patients with intracranial aneurysm ruptured and intracranial hematoma(P＜0.05).The AUC of the poor prognosis prediction model of patients with intracranial aneurysm rupture with hematoma after clipping was 0.863(95％CI:0.781-0.946,P＜0.001),the specificity was 79.6％,the sensitivity was 86.2％,and the prediction accuracy was 82.1％.Hosmer-Lemeshow testx2=5.778,P=0.679,and there was no significant difference between the predicted value of the model and the actual observed value.Conclusion Hunt-Hess grade Ⅳ-Ⅴ,the modified Fisher grade Ⅲ-Ⅳ,hematoma volume≥50ml,hematoma clearance rate≤50％,responsible aneurysm size＞5mm,operation time window＞5h,and intraoperative vascular operation time＞3h were independent risk factors for poor prognosis after clipping in patients with intracranial aneurysm ruptured.The model constructed in this study has high predictive performance and can provide guidance for the treatment and postoperative recovery of patients undergoing craniotomy and clipping surgery in clinical practice.

Objective:To construct a diabetic foot classification prediction model based on radiomics features of fundus photographs.Methods:A total of 2 035 fundus photographs of patients with type 2 diabetes diagnosed at Nanfang Hospital between December 2011 and December 2018 were retrospectively collected [282 photographs from patients with diabetic foot(DF), and 1 753 from patients with diabetes mellitus(DM)]. All fundus photographs were randomly divided into a training set(1 424 photos) and a test set(611 photos) using a computer generated random number at 7∶3. After pre-processing the fundus photographs, a total of 4 128 texture features based on the gray matrix were extracted by the Radiomic toolkit, and 11 339 other features were extracted using the ToolboxDESC toolkit. The LASSO algorithm was used to select the 30 features most relevant to DF, and then the Bootstrap + 0.632 self-sampling method was used to further select the 7 best combinations. Logistic regression analysis was used to obtain the regression coefficients and establish the final diabetic foot classification prediction model. ROC curve was drawn, and AUC, sensitivity, specificity, and accuracy of the training and test sets were calculated to verify its prediction performance. Results:We screened 7 fundus radiomics markers for diabetic foot patients, and based on this established a DF/DM classification prediction model. The AUC, sensitivity, specificity, and accuracy of the model were 0.958 6, 0.984 0, 0.920 0, and 0.928 0 in the training set, and 0.927 1, 0.988 9, 0.881 0, and 0.896 9 in the test set, respectively.Conclusion:In this study, seven DF fundus markers were screened using radiomics technology. Based on this, a highly accurate and easy-to-use DF/DM classification model was constructed. This technology has the potential to increase the efficiency of DF screening programs.

Coronary heart disease (CHD) is a kind of cardiovascular diseases originated from atherosclerosis (AS), and chronic inflammation is one of the pathological characteristics. The peripheral blood leukocytes, especially mononuclear cells, play an important role in the AS processes. Recently, in a series of Epigenome-Wide Association Studies (EWAS), multiple DNA differential methylation sites in peripheral blood cells were found to be statistically associated with CHD, which suggested that these DNA differential methylation sites might serve as new risk factors for CHD. The recognition of the variant of DNA methylation as a common epigenetic nucleic acid modification in the occurrence and development of CHD, is ongoing. DNA methylation has the potential to become warning biomarkers, which might provide new ideas and evidences for mechanistic studies of CHD.

Objective: To investigate the expression and clinical significance of circDLGAP4 from peripheral blood in coronary heart disease (CAD). Methods: The relative expression level of circDLGAP4 in peripheral blood leukocytes (PBLs) from 142 CAD patients and 169 healthy controls were detected by real-time PCR. Logistic regression, Spearman correlation and multivariate regression analysis were used to investigate the correlation of circDLGAP4 with CAD. THP-1 macrophages were treated with oxidized low density lipoprotein (ox-LDL) to construct an atherosclerotic foam cell model. The levels of circDLGAP4 mRNA were detected at different time points. Results: The mRNA expression of circDLGAP4 in PBLs of CAD patients was significantly decreased compared with controls (P=0.019). With increased unit (2 -ΔCt ) of circDLGAP4 expression, the risk of CAD occurrence reduced by 41.6% (adjusted OR=0.584, 95% CI: 0.394-0.866, P=0.007). The expression of circDLGAP4 was negatively correlated with T2DM history (β=-0.182，P=0.030). The level of circDLGAP4 in ox-LDL-treated THP-1 macrophages was decreased in a time-dependent manner. Conclusion The expression of circDLGAP4 was significantly decreased in PBLs of CAD patients and THP-1 macrophages-derived foam cells, and might be a protective factor in the pathophysiology of CAD.