Objective To develop and compare prediction models for hyperuricemia(HUA)in perim-enopausal and postmenopausal women using Lasso regression,random forest,and multivariate logistic regres-sion.Methods A multi-stage,stratified cluster sampling method was used to select 12 790 subjects from An-ning City,Yunnan Province.Prediction models for HUA were constructed using Lasso regression,random for-est,and multivariate logistic regression.The efficacy of the model was evaluated by accuracy,sensitivity,speci-ficity,F1 score,and area under the curve(AUC).Results LASSO regression analysis screened 19 variables for inclusion in the model,such as age,waist circumference,diastolic blood pressure,BMI,HDL-C,fasting blood glucose(FBG),etc.The accuracy rate was 0.701,the sensitivity was 0.703,the specificity was 0.680,and the F1 score was 0.806.The AUC(95%CI)was 0.770(0.748-0.792).The results of the random forest model show that variables such as creatinine,triglyceride-glucose index(TyG),TG,BMI,TC,Urea nitrogen(Urea),and ALT were relatively important,with an accuracy rate of 0.663,a sensitivity of 0.653,a specificity of 0.738,and an F1 score of 0.774.The AUC(95%CI)was 0.763(0.741-0.785).Multivariate logistic re-gression results showed that 11 variables including creatinine(Cr),TyG,BMI,Urea,and ALT were included in the model,with an accuracy rate of 0.705,a sensitivity of 0.707,a specificity of 0.686,an F1 score of 0.809,and an AUC(95%CI)of 0.771(0.749-0.793).Conclusion The overall performance of LASSO re-gression and multivariate logistic regression models is better.The random forest model has a strong variable screening ability and high specificity,and can be used as a supplement to provide more accurate predictions.

Objective:To investigate the status quo and influencing factors of social isolation of parents of children with autism spectrum disorder in order to provide theoretical basis for clinical intervention measures.Methods:A total of 340 parents of children with autism spectrum disorder who visited the Children′s Developmental Behavior Center of Third Affiliated Hospital of Sun Yat sen University were selected by the convenience sampling method as research objects during July to November 2023. A cross-sectional survey was investigated by a general information questionnaire, General Alienation Scale, Social Avoidance and Distress Scale, Affiliate Stigma Scale, Family APGAR Index, Chinese Simplified Version of Social Support Scale, and Social Responsiveness Scale.Results:A total of 323 valid questionnaires were collected, including 235 mothers and 88 fathers; 33 individuals aged 25-29 years, 233 individuals aged 30-39 years, and 57 individuals aged 40-60 years. The subjective social isolation score of parents of children with autism spectrum disorder was 33.24 ± 4.92 and the objective social isolation score was 4.00(2.00,7.00). The results of multiple linear regression analysis showed that the subjective social isolation of parents of children with autism spectrum disorder was influenced by factors including self-assessed health status, whether they worked full-time or not, whether they were satisfied with the division of labor in the family caring for their children, affiliate stigma, family care, and social support (all P<0.05); and the objective social isolation of parents was influenced by factors including the severity of autism symptoms, self-assessed health status, affiliate stigma, and family care (all p<0.05). Conclusions:Parents of children with autism spectrum disorder had some degree of social isolation, and the level of subjective social isolation was higher than objective social isolation. Healthcare professionals should pay attention to parents of autistic children who have high levels of symptom severity, poor self-rated health, do not work full-time, and are dissatisfied with the division of labor in the family caring for their child, and take measures to reduce the affiliate stigma, and to increase the level of family care and social support, so as to improve the social isolation of parents of children with autism spectrum disorder.