Objective:To systematically review the related factors of depressive symptoms among men who have sex with men(MSM)in China.Methods:CNKI,Wanfang Data,VIP,CBM,EMbase,Pubmed,CINAHL,Web of Science and the Cochrane Library were searched from inception to February 17,2023.After literature screening and data extraction,two researchers independently assessed the quality of included studies according to the Agency for Healthcare Research and Quality.Results:A total of 21 articles with 11 822 participants were includ-ed.The results of meta-analysis showed that month income ≥3 000 yuan(OR=0.59),college degree or above(OR=0.59)and high self-esteem(OR=0.83)were protective factors,sexual role as the recipient(OR=1.68),dual sexual role(OR=1.41),multiple sexual partners(OR=1.65),sexual violence experience(OR=3.44),self-rated poor health status(OR=3.93),HIV/AIDS related discrimination(OR=1.13),HIV/AIDS related stress(OR=1.11)and suicidal tendency(OR=2.86)were risk factors for depressive symptoms.Conclusion:There are many related factors to the depressive symptoms of MSM.It is necessary to carry out early intervention on the basis of personalized assessment to reduce the occurrence of depressive symptoms among MSM.

Objective To investigate the efficacy of high-resolution computed tomography (HRCT)imaging radiomics for the classification and diagnosis of rheumatoid arthritis associated interstitial lung disease(RA-ILD).Methods A total of 261 patients diagnosed with RA-ILD admitted in our hospital from January 2019 to July 2023 were recruited in this study.There were 143 cases of usual interstitial pneumonia (UIP )and 118 cases of nonspecific interstitial pneumonia (NSIP).All the patients underwent HRCT.A U-net deep learning lung segmentation model was applied to obtain HRCT images for automatic lung segmentation,and 1688 imaging histologic features were extracted from each lung segmentation. Variance thresholding,univariate feature selection,and least absolute shrinkage and selection operator (LASSO ) were used for feature dimensionality reduction step by step,and various machine learning algorithms were conducted to construct the RA-ILD diagnostic histology model.The diagnostic value of each model was compared using receiver operating characteristic (ROC)curve and area under curve (AUC),and the accuracy,sensitivity and specificity of the models were evaluated.Results Feature screening finally identified 18 best features from the HRCT images of RA-ILD patients.Statistical difference was found in the distribution of Radiomics score (Radscore)between the UIP and NSIP patients in both the training and test sets (P<0.01 ).Among the 5 imaging histology models,the support vector machine (SVM)algorithm had an AUC value of 0.943 (95％CI:0.916～0.966),a sensitivity of 0.787 and a specificity of 0.912,respectively for the training set,and an AUC value of 0.909 (95％CI:0.849～0.969),a sensitivity of 0.625 and a specificity of 0.897,respectively for the testing set.Conclusion Our constructed RA-ILD classification and diagnosis model performs well,and the model based on SVM algorithm shows the best potential in classifying and diagnosing RA-ILD.

Objective Clinical medical record data associated with hepatitis B-related acute-on-chronic liver failure(HBV-ACLF)generally have small sample sizes and a class imbalance.However,most machine learning models are designed based on balanced data and lack interpretability.This study aimed to propose a traditional Chinese medicine(TCM)diagnostic model for HBV-ACLF based on the TCM syndrome differentiation and treatment theory,which is clini-cally interpretable and highly accurate. Methods We collected medical records from 261 patients diagnosed with HBV-ACLF,includ-ing three syndromes:Yang jaundice(214 cases),Yang-Yin jaundice(41 cases),and Yin jaun-dice(6 cases).To avoid overfitting of the machine learning model,we excluded the cases of Yin jaundice.After data standardization and cleaning,we obtained 255 relevant medical records of Yang jaundice and Yang-Yin jaundice.To address the class imbalance issue,we employed the oversampling method and five machine learning methods,including logistic regression(LR),support vector machine(SVM),decision tree(DT),random forest(RF),and extreme gradient boosting(XGBoost)to construct the syndrome diagnosis models.This study used precision,F1 score,the area under the receiver operating characteristic(ROC)curve(AUC),and accuracy as model evaluation metrics.The model with the best classification per-formance was selected to extract the diagnostic rule,and its clinical significance was thor-oughly analyzed.Furthermore,we proposed a novel multiple-round stable rule extraction(MRSRE)method to obtain a stable rule set of features that can exhibit the model's clinical in-terpretability. Results The precision of the five machine learning models built using oversampled balanced data exceeded 0.90.Among these models,the accuracy of RF classification of syndrome types was 0.92,and the mean F1 scores of the two categories of Yang jaundice and Yang-Yin jaun-dice were 0.93 and 0.94,respectively.Additionally,the AUC was 0.98.The extraction rules of the RF syndrome differentiation model based on the MRSRE method revealed that the com-mon features of Yang jaundice and Yang-Yin jaundice were wiry pulse,yellowing of the urine,skin,and eyes,normal tongue body,healthy sublingual vessel,nausea,oil loathing,and poor appetite.The main features of Yang jaundice were a red tongue body and thickened sublin-gual vessels,whereas those of Yang-Yin jaundice were a dark tongue body,pale white tongue body,white tongue coating,lack of strength,slippery pulse,light red tongue body,slimy tongue coating,and abdominal distension.This is aligned with the classifications made by TCM experts based on TCM syndrome differentiation and treatment theory. Conclusion Our model can be utilized for differentiating HBV-ACLF syndromes,which has the potential to be applied to generate other clinically interpretable models with high accura-cy on clinical data characterized by small sample sizes and a class imbalance.

{L-End}Objective To analyze the current status of post-traumatic stress disorder (PTSD) among firefighters in Chongqing City and explore its influencing factors. {L-End}Methods A total of 1 021 firefighters in Chongqing City were selected as the study subjects using the convenient sampling method. The PTSD Checklist Civilian Version was used to assess their PTSD symptom and characteristics. The Trait Coping Style Questionnaire and the Social Support Rating Scale were used to investigate coping styles and the level of social support. {L-End}Results The positive detection rate of PTSD among the study subjects was 4.6%(47/1 021), with positive detection rates of re-experiencing, avoidance/numbing, and hyperarousal symptoms of 7.0%, 9.2%, and 16.5%, respectively. The positive detection rates of re-experiencing, avoidance/numbing, and hyperarousal symptoms in the PTSD firefighters were higher than those in non-PTSD firefighters (83.0% vs 3.3%, 93.6% vs 5.1%, 100.0% vs 12.1%, respectively; all P<0.01). The results of the multivariate logistic regression analysis showed that being injured in the past six months and adopting a negative coping style were risk factors for PTSD ［odds ratio (OR) and 95% confidence interval (CI) were 2.65 (1.07-6.56) and 1.26 (1.19-1.33), respectively; both P<0.05］, while adopting a positive coping style and having a higher level of social support were protective factors for PTSD ［OR and 95%CI were 0.90 (0.85-0.95) and 0.95 (0.91-0.99), respectively; both P<0.05］. {L-End}Conclusion The incidence of PTSD among the firefighters in Chongqing City is relatively high, with symptoms mainly characterized by hyperarousal. Being injured in the past six months, coping styles, and the level of social support are influencing factors for PTSD.

Pulmonary blast injury has become the main type of trauma in modern warfare, characterized by externally mild injuries but internally severe injuries, rapid disease progression, and a high rate of early death. The injury is complicated in clinical practice, often with multiple and compound injuries. Currently, there is a lack of effective protective materials, accurate injury detection instrument and portable monitoring and transportation equipment, standardized clinical treatment guidelines in various medical centers, and evidence-based guidelines at home and abroad, resulting in a high mortality in clinlcal practice. Therefore, the Trauma Branch of Chinese Medical Association and the Editorial Committee of Chinese Journal of Trauma organized military and civilian experts in related fields such as thoracic surgery and traumatic surgery to jointly develop the Clinical treatment guideline for pulmonary blast injury ( version 2023) by combining evidence for effectiveness and clinical first-line treatment experience. This guideline provided 16 recommended opinions surrounding definition, characteristics, pre-hospital diagnosis and treatment, and in-hospital treatment of pulmonary blast injury, hoping to provide a basis for the clinical treatment in hospitals at different levels.

Interstitial lung disease (ILD) is a frequent complication of patients with connective tissue disease (CTD) and significantly affects morbidity and mortality. Disease course may vary from stable or mildly progressive to more severe, with rapid loss of lung function. At present, there are great challenges and poor prognosis in the diagnosis and treatment of CTD-ILD. Based on the evidence and guidelines from China and other countries, experts from the Chinese Rheumatology Association developed standardization of diagnosis and treatment of CTD-ILD. The aim is to strengthen the early identification of, standardize the diagnosis and treatment of CTD-ILD, and delay the progress of the disease.

Objective:To summarize the clinical characteristics of patients with coronavirus disease 2019 (COVID-19) infected with Delta variant, so as to provide further references for clinical diagnosis and treatment.Methods:A real-world study was conducted to analyze the characteristics of 166 COVID-19 patients infected with Delta variant at Guangzhou Eighth People’s Hospital, Guangzhou Medical University.Results:The study enrolled 5 asymptomatic cases, 123 non-severe cases (mild and moderate type), and 38 severe cases (severe and critical type). Among these patients, 69 (41.6%) were male and 97 (58.4%) were female, with a mean age of 47.0±23.5 years. Thirty-nine cases (23.5%) had received 1 or 2 doses of inactivated vaccine. The incidence of severe COVID-19 cases was 7.7% in 2-doses vaccinated patients, which was lower than that of 11.5% in 1-dose and 26.8% in unvaccinated patients. The proportion of severe cases in 2 dose-vaccinated patients was 7.7%, which was lower than that of 11.5% in 1-dose vaccinated patients and 26.8% in unvaccinated patients, but the difference was not significant ( P>0.05). The most common clinical symptom was fever (134 cases, 83.2%), and 39.1% of cases presented with high-grade fever (≥39 °C); other symptoms were cough, sputum, fatigue, and xerostomia. The proportion of fever in severe cases was significantly higher than that of non-severe cases (97.4% vs. 76.4%, P<0.01). Similarly, the proportion of severe cases with high peak temperature (≥39 ℃) () was also higher than that of non-severe cases (65.8% vs. 30.9%, P<0.01). The median minimal Cycle threshold (Ct) values of viral nucleic acid N gene and ORFlab gene were 20.3 and 21.5, respectively, and the minimum Ct values were 11.9 and 13.5, respectively. Within 48 h of admission, 9.0% of cases presented with decreased white blood cell counts, and 52.4% with decreased lymphocyte counts. The proportions of increased C-reactive protein, serum amyloid A, interleukin 6, and interleukin 10 were 32.5%, 57.4%, 65.3%, and 35.7%, respectively. The proportions of elevated C-reactive protein, serum amyloid A and interleukin-6 in severe cases were significantly higher than those in non-severe cases ( P<0.01). Logistic regression analysis showed that older age and higher peak temperature were associated with a higher likelihood of severe cases ( OR>3, 95% CI: 2-7, P<0.01). In terms of treatment, traditional Chinese medicine (TCM) was used in 97.6% of non-severe cases and 100% in severe cases. Other treatments included respiratory and nutritional support, immunotherapy (such as neutralizing antibodies and plasma of recovered patients). The median times from admission to progression to severe cases, of fever clearance, and of nucleic acid conversion were 5 days, 6 days and 19 days, respectively. No deaths were reported within 28 days. Conclusions:The symptoms of Delta variant infection in Guangzhou are characterized by a high proportion of fever, high peak temperature, long duration of fever, high viral load, a long time to nucleic acid conversion, and a high incidence of severe cases. The severe cases exhibit a higher percentage of elderly patients, a longer duration of fever and have a higher fever rate and a higher hyperthermia rate than non-severe cases. Age and hyperthermia are independent risk factors for progression to severe disease. The combination of TCM and Western medicine can control the progression of the disease effectively.

Objective:To examine the relationship between conflict management model, perceived social support and psychological distress in psychiatric nurses, and to analyze the mediating effect of conflict management model in the relationship between perceived social support and psychological distress in psychiatric nurses.Methods:In November 2019, a total of 208 nurses in Shandong Mental Health Center were investigated with General Demography Questionnaire, Nurses' Interpersonal Conflict Handling Form Scale, Kessler Psychological Distress Scale and Perceived Social Support Scale.Results:The total score of psychological distress of psychiatric nurses was 22.74±7.71, and the level of psychological distress was negatively correlated with the integrated conflict management model and perceived social support ( r values were -0.329--0.266, P<0.001). The most commonly used conflict management model of psychiatric nurses was "integration". The integrated conflict management model had a partial mediating effect in perceived social support and psychological distress, and the mediating effect accounted for 20.2% of the total effect. Conclusions:Psychological distress of psychiatric nurses is at a moderate to severe level, and integrated conflict management model and perceived social support play an important role in reducing psychological distress of psychiatric nurses. Nursing administrators should carry out relevant intervention studies to improve nurse-patient conflict and guide nurses to adopt integrated conflict management model to reduce psychological distress and improve mental health level.

Objective:To investigate the situation of nursing handover among psychiatric nurses, and explore the association between perceived organizational support, self-efficacy and quality of nursing handover.Methods:A total of 186 clinical nurses in Shandong Mental Health Center were enrolled by convenience sampling method. They were assessed with handover evaluation scale, perceived organizational support scale and general self-efficacy scale for the evaluation of nursing handover, perceived organizational support and self-efficacy.Results:The average score of quality of nursing handover was 5.85±1.14, and bi-variate correlations were found between perceived organizational support, self-efficacy and quality of nursing handover. Self-efficacy could mediate the relationship between organizational support and nursing handover, and the value of mediating effect was 13.4%.Conclusions:Self-efficacy might mediate the relationship between perceived organizational support and nursing handover among psychiatric nurses.

Objective: To investigate the status quo and influencing factors of work burnout of psychiatric nurses, and to provide theoretical basis for formulating intervention strategies for work burnout of psychiatric nurses. Methods: A questionnaire was conducted on 812 nurses selected from 6 tertiary A psychiatric hospitals in Shandong province as the research object by stratified random sampling, and the questionnaire was conducted by using the Maslach Burnout Inventory (MBI), the Kessler Psychological Distress Scale (K10) and Emotion regulation questionnaire (ERQ). Results: There were significant differences in job burnout among psychiatric nurses with different educational background, age, nurse-patient conflict and income level. There were significant differences in the dimensions of job burnout among psychiatric nurses with different titles (P< 0.05), There were significant differences in emotional exhaustion (F=8.417, P=0.000) and depersonalization level (F=7.918, P=0.000) between psychiatric nurses with different frequency of nurse-patient conflict.There were significant differences in affective exhaustion (F=6.426, P=0.002) and personal accomplishment (F=3.444, P=0.032) between psychiatric nurses with different monthly income levels. Psychiatric nurses' age, working years, psychological distress, cognitive reappraisal, inhibition of expression were associated with job burnout (r=0.075~0.570) . Regression analysis revealed that the factors impacting emotion exhaustion (R²=0.374, F=81.627, P=0.000) and depersonalization (R²=0.240, F=65.014, P=0.000) were psychological distress, inhibition of expression, cognitive reappraisal, conflict between nurses and patients. The factors impacting diminished personal accomplishment (R²=0.199, F=68.332, P=0.000) were psychological distress, cognitive reappraisal and age. Conclusions The work fatigue of psychiatric nurses was at the moderate level. Emotional regulation and psychological distress were the influencing factors of job burnout.Nursing administrators in psychiatric department should pay attention to the improvement of nurses' sense of burnout, improve the ability of nurses' emotional management, cultivate positive mood and behavior pattern, reduce anxiety and depression and so on, so as to effectively improve the mental health level of nurses in psychiatric department.