1.Efficacy of minimally invasive transthoracic closure of atrial and ventricular septal defects
MENG Xiongwei ; YANG Siyuan ; HU Xuanyi ; JIANG Tian
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2018;25(8):715-718
Objective To evaluate the efficacy and safety of transthoracic minimally invasive occlusion operation for the treatment of congenital atrial and ventricular septal defects. Methods The clinical data of 88 patients who underwent surgical occlusion operation from December 2015 to February 2017 were summarized. There were 52 males and 36 females, aged 6.8±7.5 years ranging from 1.6 to 24.0 years. All the patients were followed up by ultrasound and electrocardiogram at postoperative 3, 6 and 12 months. The efficacy of minimally invasive thoracotomy was analyzed by statistical methods. Results The patients were followed up for 3-15 (6.8±2.3) months, and the follow-up rate was 92.0%. Ultrasound showed occluder fixed well and no residual shunt, valve regurgitation, thrombosis or other complications occurred. The heart was reduced, the ejection fraction was greater than 55%, and heart function rating for all patients was grade Ⅰ. Conclusion Transthoracic mini-invasive surgical occlusion of atrial and ventricular septal defects is safe and effective. The short and middle-term effect is satisfying. It can be widely used in clinical, but multi-center and long-term follow-up and assessment still need to be carried out.
2.Risk prediction models of dangerous behaviors among patients with severe mental disorder in community
Xuanyi HU ; Min XIE ; Siyi LIU ; Yulu WU ; Xiangrui WU ; Yuanyuan LIU ; Changjiu HE ; Guangzhi DAI ; Qiang WANG
Sichuan Mental Health 2024;37(1):39-45
BackgroundThe occurrence rate of dangerous behaviors in patients with severe mental disorders is higher than that of the general population. In China, there is limited research on the prediction of dangerous behaviors in community-dwelling patients with severe mental disorders, particularly in terms of predicting models using data mining techniques other than traditional methods. ObjectiveTo explore the influencing factors of dangerous behaviors in community-dwelling patients with severe mental disorders and testing whether the classification decision tree model is superior to the Logistic regression model. MethodsA total of 11 484 community-dwelling patients with severe mental disorders who had complete follow-up records from 2013 to 2022 were selected on December 2023. The data were divided into a training set (n=9 186) and a testing set (n=2 298) in an 8∶2 ratio. Logistic regression and classification decision trees were separately used to establish predictive models in the training set. Model discrimination and calibration were evaluated in the testing set. ResultsDuring the follow-up period, 1 115 cases (9.71%) exhibited dangerous behaviors. Logistic regression results showed that urban residence, poverty, guardianship, intellectual disability, history of dangerous behaviors, impaired insight and positive symptoms were risk factors for dangerous behaviors (OR=1.778, 1.459, 2.719, 1.483, 3.890, 1.423, 2.528, 2.124, P<0.01). Being aged ≥60 years, educated, not requiring prescribed medication and having normal social functioning were protective factors for dangerous behaviors (OR=0.594, 0.824, 0.422, 0.719, P<0.05 or 0.01). The predictive effect in the testing set showed an area under curve (AUC) of 0.729 (95% CI: 0.692~0.766), accuracy of 70.97%, sensitivity of 59.71%, and specificity of 72.05%. The classification decision tree results showed that past dangerous situations, positive symptoms, overall social functioning score, economic status, insight, household registration, disability status and age were the influencing factors for dangerous behaviors. The predictive effect in the testing set showed an AUC of 0.721 (95% CI: 0.705~0.737), accuracy of 68.28%, sensitivity of 64.46%, and specificity of 68.60%. ConclusionThe classification decision tree does not have a greater advantage over the logistic regression model in predicting the risk of dangerous behaviors in patients with severe mental disorders in the community. [Funded by Chengdu Medical Research Project (number, 2020052)]
3.Related factors of troublemaking among patients with mental disorders caused by amphetamine-type stimulants
Guojian YAN ; Li PU ; Fugui JIANG ; Xuanyi HU ; Jialing LEI ; Yuesheng CAO ; Shunzhen ZHOU ; Hua REN ; Jiajia CHEN ; Shu WAN ; Yunxi LUO ; Langbin ZHOU ; Xufeng SONG ; Jun YANG ; Wei JI
Sichuan Mental Health 2021;34(4):341-344
ObjectiveTo explore the related factors of troublemaking behaviors among patients with mental disorders induced by amphetamine-type stimulants (ATS), and to provide references for the formulation of relevant intervention measures for ATS-induced mental disorders. MethodsA total of 105 patients who met the diagnostic criteria of International Classification of Diseases, tenth edition (ICD-10) for ATS-induced mental disorders were included, and classified into troublemaking group and non-troublemaking group. The general demographic data and clinical data of the selected individuals were collected, and all patients were assessed using Social Support Rating Scale (SSRS). Then univariate analysis and multivariate Logistic regression model were used to screen the related factors of troublemaking behaviors. ResultsThe scores of SSRS, objective support dimension and social support utilization dimension were significantly lower in troublemaking group than those in non-troublemaking group, with statistical differences [(24.10±6.59) vs. (28.94±5.59), t=3.364, P=0.001; (5.50±1.96) vs. (8.20±2.13), t=5.183, P<0.01; (4.60±2.26) vs. (6.28±1.90), t=3.435, P=0.001]. Multivariate Logistic regression analysis showed that male (OR=6.061, P=0.014) was a risk factor, while high social support level (OR=0.873, P=0.018) was the protective factor for troublemaking behaviors among patients with ATS-induced mental disorders. ConclusionPatients with ATS-induced mental disorders of the males and with low social support level are at high risk of troublemaking behaviors.