BackgroundIn recent years， the incidence of depression among adolescents has been increasing steadily， posing a serious threat to their physical and mental health and even leading to severe consequences such as self-harm and suicide. At the same time， the detection rate of subclinical depression symptoms among adolescents is even higher. Although these symptoms do not meet the clinical diagnostic criteria， they have significantly affected their quality of life， and their persistence over time may further develop into depression. Therefore， in-depth exploration of adolescent depression symptoms and the predictive factors holds significant practical significance and research value. However， up to now， no large-scale investigation and research on depression symptoms among children and adolescents has been conducted in Inner Mongolia Autonomous Region. ObjectiveTo understand the prevalence of depressive symptoms among children and adolescents in Inner Mongolia Autonomous Region， in order to provide references for formulating scientific and effective prevention strategies and intervention measures. MethodsBy using the cluster stratified random sampling method， 6 281 students from the third grade of primary school to the second grade of high school in 12 leagues and cities of Inner Mongolia Autonomous Region were selected in March 2024. A self-designed questionnaire and the Self-rating Depression Scale （SDS） were used for on-site investigation. ResultsA total of 6 058 （96.45%） children and adolescents completed the valid questionnaire survey， and 2 728 cases （45.03%） were found to have depressive symptoms. There were statistically significant differences in the detection rates of depressive symptoms among children and adolescents of different genders， ages， whether they were only children， different family types， family monthly income， parents' educational levels， and whether the mother was employed （χ²=33.769， 40.618， 48.593， 29.972， 142.648， 195.999， 168.190， 5.445， P<0.05 or 0.01）.The results of the Logistic regression analysis showed that for children and adolescents， being female， aged between 12 and 16， over 16 years old， not being an only child， living in a reconstituted family， having a monthly family income of less than 5 000 yuan， and having parents with an education level of primary school or below were predictors of depressive symptoms （OR=1.241， 1.427， 1.273， 1.177， 1.549， 1.278， 1.462， 1.417， 1.514， 1.929， 1.660， 1.528， P<0.05 or 0.01）. ConclusionThe detection rate of depressive symptoms among children and adolescents in Inner Mongolia Autonomous Region is relatively high. Factors that may predict depressive symptoms in children and adolescents include female gender， ages between 12 and 16， ages over 16 years old， non-only children， families with a restructured structure， monthly family income of less than 5 000 yuan， and parents with an education level of primary school or below. ［Funded by Science and Technology Planning Project of the Inner Mongolia Autonomous Region （number， 2022YFSH0119）］

Objective:To explore the application value of radiomics models based on MRI of vertebrae and paravertebral muscles in identifying potential vertebral fragility fracture risk in osteoporosis and osteopenia.Methods:This cross-sectional study collected data from patients who underwent both dual-energy X-ray absorptiometry (DXA) and lumbar MRI at the Third Affiliated Hospital of Southern Medical University between January 2014 and December 2023,retrospectively. Based on DXA results, patients were categorized into osteoporosis group ( n=302) and osteopenia group ( n=264), with fracture and non-fracture patients matched at 1∶1 ratio by propensity score matching based on age, gender, and body mass index. The fourth lumbar vertebra was selected as the region of interest (ROI) for the vertebral body, and the bilateral psoas major, erector spinae, and multifidus muscles were selected as the ROIs for the paraspinal muscles. A total of 7 259 radiomics features were extracted from these ROIs. The dataset was divided into a training set and a test set in an 8∶2 ratio by simple random sampling (osteoporosis group 241 and 61 cases, osteopenia group 211 and 53 cases). The T-score was used to establish the clinical model. After feature normalization and dimensionality reduction, logistic regression was applied to build three radiomics models: vertebral model, paraspinal muscle model, and vertebral-paraspinal muscle model. The T-score was then combined with the radiomics model that achieved the highest area under the receiver operating characteristic curve (AUC) in the test set to construct a clinical-radiomics combined model. Model performance was evaluated using the AUC. The DeLong test was used to compare the diagnostic efficacy between models. Results:In the test set, the vertebral-paravertebral muscle model achieved the highest AUC among radiomics models and was selected for combination with the T-score. In identifying potential vertebral fragility fractures of osteoporosis group, the AUC (95% CI) of the clinical model, vertebral model, paraspinal muscle model, vertebral-paraspinal muscle model, and clinical-radiomics model were 0.523 (0.373-0.672), 0.869 (0.779-0.959), 0.608 (0.464-0.752), 0.876 (0.791-0.961), and 0.860 (0.769-0.952), respectively. For osteopenia group, the corresponding AUC(95% CI) were 0.625 (0.467-0.783), 0.696 (0.547-0.845), 0.706 (0.563-0.848), 0.816 (0.702-0.930), and 0.820 (0.710-0.930). The DeLong test showed that the vertebral model for identifying the potential vertebral fracture risk in osteoporosis group had better performance than the paraspinal muscle model ( Z=3.28, P=0.001). While for osteopenia group, there was no significant difference in diagnostic performance between the vertebral model and the paraspinal muscle model ( Z=0.09, P=0.932). The recognition efficacy of the clinical model and the vertebral-paraspinal muscle model was significantly different ( Z=3.69, 1.98; P<0.001, P=0.047), while there was no significant difference between the clinical-radiomics combined model and the vertebral-paraspinal muscle model ( Z=1.51, 0.12; P=0.131, 0.904). Conclusion:The MRI-based vertebral-paraspinal muscle radiomics model can effectively identify osteoporosis or osteopenia patients with potential fragility fracture risk. In osteopenia group, the efficacy of the MRI radiomics models based on the vertebra and paraspinal muscles in identifying potential vertebral fragility fracture risk is comparable.

OBJECTIVE: To screen the optimal regimen of acupuncture and moxibustion for obstructive sleep apnea hypopnea syndrome (OSAHS), so as to provide the evidences for clinical decision-making. METHODS: From 7 databases in Chinese and English i.e. the Full-Text Database of China Journal Network (CNKI), Wanfang Data Knowledge Service Platform (Wanfang), VIP Information Chinese Journal Service Platform (VIP), Chinese Biomedical Literature Database (SinoMed), PubMed, Web of Science (WOS) and Cochrane Library, randomized controlled trial (RCT) articals of OSAHS treated with acupuncture and moxibustion were searched. The quality of evidence was evaluated with the modified Jadad scale, the evaluation index was established and the optimal regimen of acupuncture and moxibustion for OSAHS was screened by multi-index decision analysis. RESULTS: A total of 10 RCTs were included, and the filiform needling therapy was optimal in treatment of OSAHS. The acupoints included Lianquan (CV23), Danzhong (CV17), Zhongwan (CV12), and bilateral Kongzui (LU6), Pishu (BL20), Fenglong (ST40), Zusanli (ST36), Yinlingquan (SP9) and Zhaohai (KI6). Zusanli (ST36) received the reinforcing method, Pishu (BL20) and Fenglong (ST40) were stimulated with the reducing technique, and the rest acupoints with the uniform reinforcing-reducing. Each acupoint was manually manipulated once every 10 min during the needle retention for 30 min. Acupuncture was delivered once a day, 5 times a week and for consecutive 4 weeks. Among the included literature, the severity of disease was not reported in detail, the filiform needling was the dominant intervention, the local acupoints such as Lianquan (CV23) and Panglianquan (Extra) were mainly selected. The apnea-hypopnea index and the minimum oxygen saturation were taken as the evaluation indexes, and the effect was evaluated in reference to the generally accepted standards. The attention to safety evaluation was insufficient, the report on methodology was not adequate and the quality was low. CONCLUSION Filiform needling is the dominant therapy of acupuncture and moxibustion for OSAHS, and the local acupoints are considered specially. But the quality of clinical research should be improved.
Humans ; Moxibustion ; Acupuncture Therapy ; Sleep Apnea, Obstructive/therapy* ; Acupuncture Points ; Randomized Controlled Trials as Topic

Objective:To analyze the changes in the levels of inflammatory factors in gingival crevicular fluid of the patients with periodontal disease underwent invisible appliance,and to provide the reference for clinical practice.Methods:PubMed,Embase,Cochrane Library,China National Knowledge Infrastructure(CNKI),Chinese Biology Medicine(CBM),Wanfang and VIP Databases were used for literature collection about the treatment using invisible appliance and fixed appliance for periodontal disease.The retrieval time was limited from January 1997 to November 2023.Two researchers independently screened the literatures and extracted data based on the inclusion and exclusion criteria,and conducted quality evaluation.Review Manager 5.4 software was used to analyze the changes in the levels of inflammatory cytokines including tumor necrosis factor-α(TNF-α),C-reaction protein(CRP),interleukin-6(IL-6),interleukin-1β(IL-1β)and interleukin-2(IL-2)before and 6 months after appliance placement.Results:Six randomized controlled trials were included in this study with a total sample size of 601 cases.Subgroup analysis was conducted based on the type of brackets.The results of Meta-analysis showed that compared with fixed appliance group,the changes in the levels of TNF-α(MD=-1.32,95％CI:-1.87--0.77,P＜0.001),IL-6(MD=-0.78,95％CI:-1.22--0.35,P＜0.001),CRP(MD=-1.03,95％CI:-1.30--0.76,P＜0.001)and IL-1β(MD=-1.45,95％CI:-2.21--0.70,P＜0.001)in invisible appliance group were significantly decreased,while the change in IL-2 level(MD=0.74,95％CI:0.61-0.87,P＜0.001)was significantly increased.Conclusion:Compared with fixed appliance,the invisible appliance can better control the levels of inflammatory factors in gingival crevicular fluid of the patients with periodontal disease,which is beneficial to the periodontal tissue health of these patients.

Objective:To construct a matching model between difficulty grading of peripheral venipuncture in infants and nurse's venipuncture competence, and to evaluate its effectiveness.Methods:Convenience sampling was used to select pediatric patients who were treated with peripheral venous infusion in the infusion room of the Affiliated Xuzhou Children's Hospital of Xuzhou Medical University from March to June 2024, and to establish a model for matching the difficulty grading of peripheral venipuncture in infants and the nurse's venipuncture competence. Pediatric patients before the implementation of the matching model (March to April 2024) were set up as control group, and pediatric patients after the implementation of the matching model (May to June 2024) were set up as observation group. The success rate of first peripheral venipuncture was counted and compared between the two groups.Results:The per capita first puncture success rate of the nurses in control group was (93.94±4.67) %, and the per capita first puncture success rate of the nurses in observation group was (96.10±2.65) %, and the difference was statistically significant ( P<0.05) . Conclusions:The establishment of a matching model between difficulty grading of peripheral venipuncture in infants and nurse's venipuncture competence can improve the success rate of first pediatric peripheral venipuncture and promote a steady improvement in the technical competence of pediatric venipuncture nurses.

Objective:To describe the prevalence of anxiety disorders and its distribution in Inner Mongolia Autonomous Region,and to explore the relevant factors of anxiety disorders.Methods:From June 2019 to Decem-ber 2019,representative multi-stage disproportionate stratified sampling procedure was used to sample in residents aged 18 and over in the Inner Mongolia Autonomous Region.All respondents were face-to-face interviewed by trained interviewers.Composite International Diagnostic Interview-3.0(CIDI-3.0)was used to diagnose anxiety disorders according to the criteria and definition of the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ).Chi-square test and multivariate logistic regression analysis were used for statistical anal-ysis.Results:Totally 12 315 people were interviewed in the survey.The weighted 12-mouth prevalence rate of any anxiety disorder was 4.64％,and the lifetime prevalence rate was 6.25％.The weighted 12-month prevalence rate of anxiety disorders was higher in female than that in male(5.38％vs.3.92％).The rate was higher in rural resi-dents than that in urban residents(5.67％vs.3.95％).The rate was higher in people with chronic diseases than that in people without chronic diseases(6.81％vs.2.29％).Logistic regression analysis showed that unmarried(OR=2.32,95％CI:1.31-4.10),separated/divorced(OR=2.49,95％CI:1.33-4.67),in debt(OR=1.55,95％CI:1.04-2.32),chronic disease(OR=2.22,95％CI:1.39-3.53),family history of anxiety disorders(OR=12.05,95％CI:8.78-16.53),poor sleep(OR=2.64,95％CI:1.97-3.54)were risk factors of occurrence of anxiety disorders,while junior high school(OR=0.65,95％CI:0.44-0.96)was protective factor of anxiety disor-ders.Conclusion:Adults with chronic diseases,poor sleep,unmarried or separated/divorced,family history of anxi-ety disorders,and financial debt are at higher risk groups of anxiety disorder in Inner Mongolia Autonomous Re-gion.

Objective:To describe the prevalence and distributions of mood disorder in Inner Mongolia Au-tonomous Region,and analyze the related risk factors.Methods:The multistage stratified sampling method with un-equal probability was used to select permanent residents aged 18 years and over in Inner Mongolia Autonomous Re-gion.The Composite International Diagnostic Interview 3.0 was used as a diagnostic tool.Mood disorders were di-agnosed according to the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition(DSM-Ⅳ).Single and multivariate analyses were used to investigate the related factors of mood disorders.Results:Totally,12 315 community residents were interviewed in the survey.The weighted 12-month prevalence and lifetime prevalence of mood disorder were 5.4％and 8.7％,respectively.Weighted 12-month prevalence of depressive disorder was 4.9％,and that of bipolar disorder was 0.3％.Among all subtypes of mood disorder,the 12-month prevalence rate of major depressive disorder(3.1％)was the highest.Multivariate logistic regression analysis showed that female,unmarried,separated or divorced,unemployment,family history,other mental disorders,sleep disorders and chronic diseases(OR=1.56,2.80,2.07,1.42,13.46,7.97,3.23,2.13)were risk factors of mood disorder,while aged 65 years and over(OR=0.44)was protective factor of mood disorders.The lifetime consultation rate in patients with mood disorders was 15.5％,the rate of psychiatric consultation was 3.7％,the rate of medication was 1.8％.Con-clusion:It indicates that female residents and people who are unmarried,separated and divorced,unemployed,with family history,suffering from other mental disorders,suffering from sleep disorders,and suffering from chronic dis-eases may be high risk groups of mood disorders,and the utilization rate of health services is rather low in Inner Mongolia Autonomous Region.

Objective:To describe the prevalence of anxiety disorders and its distribution in Inner Mongolia Autonomous Region,and to explore the relevant factors of anxiety disorders.Methods:From June 2019 to Decem-ber 2019,representative multi-stage disproportionate stratified sampling procedure was used to sample in residents aged 18 and over in the Inner Mongolia Autonomous Region.All respondents were face-to-face interviewed by trained interviewers.Composite International Diagnostic Interview-3.0(CIDI-3.0)was used to diagnose anxiety disorders according to the criteria and definition of the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ).Chi-square test and multivariate logistic regression analysis were used for statistical anal-ysis.Results:Totally 12 315 people were interviewed in the survey.The weighted 12-mouth prevalence rate of any anxiety disorder was 4.64％,and the lifetime prevalence rate was 6.25％.The weighted 12-month prevalence rate of anxiety disorders was higher in female than that in male(5.38％vs.3.92％).The rate was higher in rural resi-dents than that in urban residents(5.67％vs.3.95％).The rate was higher in people with chronic diseases than that in people without chronic diseases(6.81％vs.2.29％).Logistic regression analysis showed that unmarried(OR=2.32,95％CI:1.31-4.10),separated/divorced(OR=2.49,95％CI:1.33-4.67),in debt(OR=1.55,95％CI:1.04-2.32),chronic disease(OR=2.22,95％CI:1.39-3.53),family history of anxiety disorders(OR=12.05,95％CI:8.78-16.53),poor sleep(OR=2.64,95％CI:1.97-3.54)were risk factors of occurrence of anxiety disorders,while junior high school(OR=0.65,95％CI:0.44-0.96)was protective factor of anxiety disor-ders.Conclusion:Adults with chronic diseases,poor sleep,unmarried or separated/divorced,family history of anxi-ety disorders,and financial debt are at higher risk groups of anxiety disorder in Inner Mongolia Autonomous Re-gion.

Objective:To describe the prevalence and distributions of mood disorder in Inner Mongolia Au-tonomous Region,and analyze the related risk factors.Methods:The multistage stratified sampling method with un-equal probability was used to select permanent residents aged 18 years and over in Inner Mongolia Autonomous Re-gion.The Composite International Diagnostic Interview 3.0 was used as a diagnostic tool.Mood disorders were di-agnosed according to the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition(DSM-Ⅳ).Single and multivariate analyses were used to investigate the related factors of mood disorders.Results:Totally,12 315 community residents were interviewed in the survey.The weighted 12-month prevalence and lifetime prevalence of mood disorder were 5.4％and 8.7％,respectively.Weighted 12-month prevalence of depressive disorder was 4.9％,and that of bipolar disorder was 0.3％.Among all subtypes of mood disorder,the 12-month prevalence rate of major depressive disorder(3.1％)was the highest.Multivariate logistic regression analysis showed that female,unmarried,separated or divorced,unemployment,family history,other mental disorders,sleep disorders and chronic diseases(OR=1.56,2.80,2.07,1.42,13.46,7.97,3.23,2.13)were risk factors of mood disorder,while aged 65 years and over(OR=0.44)was protective factor of mood disorders.The lifetime consultation rate in patients with mood disorders was 15.5％,the rate of psychiatric consultation was 3.7％,the rate of medication was 1.8％.Con-clusion:It indicates that female residents and people who are unmarried,separated and divorced,unemployed,with family history,suffering from other mental disorders,suffering from sleep disorders,and suffering from chronic dis-eases may be high risk groups of mood disorders,and the utilization rate of health services is rather low in Inner Mongolia Autonomous Region.

Objective:To explore the application value of radiomics models based on MRI of vertebrae and paravertebral muscles in identifying potential vertebral fragility fracture risk in osteoporosis and osteopenia.Methods:This cross-sectional study collected data from patients who underwent both dual-energy X-ray absorptiometry (DXA) and lumbar MRI at the Third Affiliated Hospital of Southern Medical University between January 2014 and December 2023,retrospectively. Based on DXA results, patients were categorized into osteoporosis group ( n=302) and osteopenia group ( n=264), with fracture and non-fracture patients matched at 1∶1 ratio by propensity score matching based on age, gender, and body mass index. The fourth lumbar vertebra was selected as the region of interest (ROI) for the vertebral body, and the bilateral psoas major, erector spinae, and multifidus muscles were selected as the ROIs for the paraspinal muscles. A total of 7 259 radiomics features were extracted from these ROIs. The dataset was divided into a training set and a test set in an 8∶2 ratio by simple random sampling (osteoporosis group 241 and 61 cases, osteopenia group 211 and 53 cases). The T-score was used to establish the clinical model. After feature normalization and dimensionality reduction, logistic regression was applied to build three radiomics models: vertebral model, paraspinal muscle model, and vertebral-paraspinal muscle model. The T-score was then combined with the radiomics model that achieved the highest area under the receiver operating characteristic curve (AUC) in the test set to construct a clinical-radiomics combined model. Model performance was evaluated using the AUC. The DeLong test was used to compare the diagnostic efficacy between models. Results:In the test set, the vertebral-paravertebral muscle model achieved the highest AUC among radiomics models and was selected for combination with the T-score. In identifying potential vertebral fragility fractures of osteoporosis group, the AUC (95% CI) of the clinical model, vertebral model, paraspinal muscle model, vertebral-paraspinal muscle model, and clinical-radiomics model were 0.523 (0.373-0.672), 0.869 (0.779-0.959), 0.608 (0.464-0.752), 0.876 (0.791-0.961), and 0.860 (0.769-0.952), respectively. For osteopenia group, the corresponding AUC(95% CI) were 0.625 (0.467-0.783), 0.696 (0.547-0.845), 0.706 (0.563-0.848), 0.816 (0.702-0.930), and 0.820 (0.710-0.930). The DeLong test showed that the vertebral model for identifying the potential vertebral fracture risk in osteoporosis group had better performance than the paraspinal muscle model ( Z=3.28, P=0.001). While for osteopenia group, there was no significant difference in diagnostic performance between the vertebral model and the paraspinal muscle model ( Z=0.09, P=0.932). The recognition efficacy of the clinical model and the vertebral-paraspinal muscle model was significantly different ( Z=3.69, 1.98; P<0.001, P=0.047), while there was no significant difference between the clinical-radiomics combined model and the vertebral-paraspinal muscle model ( Z=1.51, 0.12; P=0.131, 0.904). Conclusion:The MRI-based vertebral-paraspinal muscle radiomics model can effectively identify osteoporosis or osteopenia patients with potential fragility fracture risk. In osteopenia group, the efficacy of the MRI radiomics models based on the vertebra and paraspinal muscles in identifying potential vertebral fragility fracture risk is comparable.