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Xi Chen,1 Lu Gao,1 Zhen Zhen,1 Ying Wang,1 Jia Na,1 Wen Yu,1 Xinyuan Chu,1 Yue Yuan,1 Suyun Qian2 1Department of Cardiology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, 100045, People’s Republic of China; 2Pediatric Intensive Care Unit, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, 100045, People’s Republic of ChinaCorrespondence: Yue Yuan, Department of Cardiology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, No. 56, Nanlishilu, District Xicheng, Beijing, 100045, People’s Republic of China, Email yuanyuebjdr@163.com; yuanyuebj22@sina.com Suyun Qian, Pediatric Intensive Care Unit, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, No. 56, Nanlishilu, District Xicheng, Beijing, 100045, People’s Republic of China, Email qiansuyunbj12@163.com; suyunqian1211@163.comPurpose: To explore the risk factors and develop predictive models for intravenous immunoglobulin (IVIG) resistance in children with recurrent Kawasaki disease (KD).Patients and Methods: Patients with recurrent KD were retrospectively reviewed. Clinical and laboratory data at recurrence were collected and compared between patients with and without IVIG resistance. The patients were randomly divided into training and validation cohorts for model development and validation. All variables were subjected to standard Lasso and its variant group Lasso analyses, respectively, to construct predictive models. Model performance was evaluated by receiver operating characteristics (ROC) curves, calibration curves, and Hosmer-Lemeshow tests.Results: A total of 90 children with recurrent KD were included. A total of 16 cases were IVIG resistant. The patients with IVIG resistance had higher age and IVIG resistance probability at the first episode, increased CRP levels, neutrophil count, neutrophil percentage, direct bilirubin level, prothrombin time, and international normalized ratio, and decreased lymphocyte count, lymphocyte percentage, and serum sodium levels. Five variables including age and IVIG resistance at the first episode, lymphocytes count, serum sodium levels, and CRP levels were finally selected by standard Lasso (lLasso model) and four variables including age and IVIG resistance at the first episode, neutrophil percentage, and CRP levels were selected by group Lasso (gLasso). ROC curves suggested lLasso and gLasso models had similar excellent discrimination in both the training cohort (0.895 vs 0.906) and the validation cohort (0.855 vs 0.909). Hosmer-Lemeshow tests suggested the two models exerted a good calibration. Two nomograms were also constructed to facilitate the potential application of the two models.Conclusion: Age and IVIG resistance at the first episode and some laboratory variables may be risk factors for IVIG resistance in recurrent KD. Two predictive models for IVIG resistance with excellent performance were established in recurrent KD. External validation should be performed before clinical use.Keywords: recurrent Kawasaki disease, intravenous immunoglobulin, resistance, risk factor, predictive model

Shuang Li,1,2 Jun Na,1,2 Huijuan Mu,1,2 Yanxia Li,1,2 Li Liu,1,2 Rui Zhang,1,2 Jingyan Sun,1,3 Yuying Li,1,3 Wei Sun,1,3 Guowei Pan,1,3 Lingjun Yan1,3 1Institute of Preventive Medicine, China Medical University, Shenyang, People’s Republic of China; 2Institute of Chronic Diseases, Liaoning Provincial Center for Disease Control and Prevention, Shenyang, People’s Republic of China; 3Research Center for Universal Health, School of Public Health, China Medical University, Shenyang, People’s Republic of ChinaCorrespondence: Lingjun YanResearch Center for Universal Health, School of Public Health, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning, 110122, People’s Republic of ChinaTel + 86 2431939406Email ljyan@cmu.edu.cnPurpose: Few studies have assessed the individual and joint effects of the mother’s, father’s and teacher’s mental health symptoms on schoolchildren’s behavior and emotional well-being simultaneously in the same study.Patients and Methods: A cross-sectional survey was conducted among 8488 Chinese schoolchildren aged 6– 17 years in northeast China. The Strengths and Difficulties Questionnaire (SDQ) and General Health Questionnaire (GHQ) were used to measure the mental health of the students, their parents and the teacher in charge of the class, respectively. A total of 6173 students (72.73%) with full mental health information from all three caretakers were included in the final analysis.Results: We found a significantly elevated risk of mental health symptoms in children when their mothers (odds ratios (OR)=2.30, 95% CI=1.93– 2.73), fathers (OR=2.08, 95% CI=1.73– 2.50) and teachers (OR=1.18, 95% CI=1.01– 1.39) reported poorer mental health, and the risk increased significantly with the number of the caretakers with mental symptoms. A father with poor mental health has both direct and indirect effects on a child’s emotional health, by worsening the influence of a mother’s poor mental health.Conclusion: All three caretakers have a significant negative influence on schoolchildren’s emotional well-being, in the order of mother > father > teacher. It is desirable to assess and manage students’ mental health in the both the family and school contexts.Keywords: combined effects, mental health symptoms, fathers, mothers, teachers, school children

To reconstruct deep fluid chemical composition and increase the confidence in estimated reservoir temperatures, a more integral geothermometry method was compared to other classical geothermometers. Here, we apply the integrated multicomponent geothermometry (IMG) method using the GeoT code to estimate reservoir temperatures at the Tengchong geothermal field in Southwestern China. Results show reservoir temperatures calculated using the quartz geothermometer are closest to those estimated with the IMG method. The concentrations of Al and Mg, as well as selected minerals for geothermometry computations, are key factors for successfully using the IMG. Using the IMG method together with classical geothermometers can significantly increase confidence in reservoir temperature estimations. The methods presented and simulation program used here may be useful for analysis of other geothermal fields under similar conditions.