OBJECTIVES: To explore the mediating role of sleep duration in the relationship between depression symptoms and myopia among middle school students. METHODS: This study was a cross-sectional research conducted using a stratified cluster random sampling method. A total of 1 728 middle school students were selected from two junior high schools and two senior high schools in certain urban areas and farms of the Xinjiang Production and Construction Corps. Questionnaire surveys and vision tests were conducted among the students. Spearman analysis was used to analyze the correlation between depression symptoms, sleep duration, and myopia. The Bootstrap method was employed to investigate the mediating effect of sleep duration between depression symptoms and myopia. RESULTS: The prevalence of myopia in the overall population was 74.02% (1 279/1 728), with an average sleep duration of (7.6±1.0) hours. The rate of insufficient sleep was 83.62% (1 445/1 728), and the proportion of students exhibiting depression symptoms was 25.29% (437/1 728). Correlation analysis showed significant negative correlations between visual acuity in both eyes and sleep duration with depressive emotions as measured by the Center for Epidemiologic Studies Depression Scale (with correlation coefficients of -0.064, -0.084, and -0.199 respectively; P<0.01), as well as with somatic symptoms and activities (with correlation coefficients of -0.104, -0.124, and -0.233 respectively; P<0.01) and interpersonal relationships (with correlation coefficients of -0.052, -0.059, and -0.071 respectively; P<0.05). The correlation coefficients for left and right eye visual acuity and sleep duration were 0.206 and 0.211 respectively (P<0.001). Sleep duration exhibited a mediating effect between depression symptoms and myopia (indirect effect=0.056, 95%CI: 0.029-0.088), with the mediating effect value for females (indirect effect=0.066, 95%CI: 0.024-0.119) being higher than that for males (indirect effect=0.042, 95%CI: 0.011-0.081). CONCLUSIONS Sleep duration serves as a partial mediator between depression symptoms and myopia in middle school students.
Humans ; Myopia/etiology* ; Male ; Female ; Depression/physiopathology* ; Cross-Sectional Studies ; Sleep ; Adolescent ; Students ; Child ; Time Factors ; Sleep Duration

Objective:To understand the prevalence of frailty and the importance of its influencing factors in adult population in Shaanxi Province.Methods:The data were from Shaanxi baseline survey of natural population cohort study in northwest China during 2018-2019. The frailty index (FI) was constructed to evaluate the frailty status of the population, and XGboost model combined with Shapley method was used to analyze the importance of the sociodemographic and life behavior factors affecting the prevalence of frailty by gender and age.Results:A total of 25 079 subjects were included, in whom 964 (3.8%) had frailty, and there was no significant difference in the overall prevalence of frailty between women (3.9%) and men (3.8%) ( P=0.629), but there was a gender specific difference in the distribution of FI ( P<0.001), and the proportion of the pre-frailty in men was higher than that in women. The prevalence of frailty increased with age ( P<0.001), the prevalence of frailty were 1.3%, 2.5% and 7.8% in young, middle-aged and elderly women, respectively, and 1.9%, 2.7% and 5.5% in young, middle-aged and elderly men, respectively. Sociodemographic characteristics and lifestyle patterns were both influencing factors for the prevalence of frailty, but their importance varied with gender and age. The top five contributing factors were education level, staying up late, annual family income level, sedentary time and marital status in young women, and staying up late, smoking, annual family income level, sedentary time and drinking in young men. The top five contributing factors were education level, annual family income level, passive exposure to smoking, staying up late, and sedentary time in middle-aged women, and annual family income level, education level, sedentary time, staying up late and drinking in middle-aged men. The top five contributing factors were annual family income level, passive exposure to smoking, sedentary time, marital status, and smartphone use in elderly women, and education level, annual family income level, smoking, smartphone use and sedentary time in elderly men. Conclusions:There are gender specific differences in the distribution of FI in Shaanxi. The prevalence of frailty increased with age, but young and middle-aged people also have frailty risk. The prevalence of frailty in young men was mainly related to unhealthy life behaviors, such as staying up late, smoking, sedentary behavior and drinking, while the prevalence of frailty in middle-aged and elderly men and women were more affected by sociodemographic factors, such as education level, economic status and marital status.

Objective To explore the predictive value of automated breast ultrasound(ABUS)features combined with Ki-67 in predicting pathological complete response(pCR)after neoadjuvant chemotherapy(NAC)in triple-negative breast cancer(TNBC).Methods A retrospective analysis was conducted on 127 female TNBC patients treated at Xijing Hospital,Air Force Medical University from March 2019 to December 2023.All patients underwent NAC and surgical treatment after ABUS examination.Based on postoperative pathological results,patients were divided into pCR group(n=60)and non-pathological complete response(npCR)group(n=67).Differences in various parameters before NAC were compared between the two groups.LASSO regression was used to identify independent factors influencing pCR after NAC in TNBC patients,and a predictive model was constructed using multivariate logistic regression.The prediction model was internally validated using the Bootstrap method(1000 resamples).The discriminative ability of the model was evaluated using receiver operating characteristic(ROC)curves,and the area under the curves(AUCs)of different prediction models were compared using De-long's test.The accuracy of the model was assessed using calibration curves,and the clinical benefit of the model was evaluated using clinical decision curve analysis(DCA).Results Significant differences were observed between two groups in terms of age,Ki-67,menopausal status,tumor type,posterior echo,coronal plane convergence sign,coronal plane skip sign,and coronal plane white wall sign before NAC(P<0.05).LASSO regression analysis showed that Ki-67,coronal plane convergence sign,and coronal plane white wall sign were independent influencing factors of pCR after NAC in TNBC patients(P<0.05).The AUC of the multivariate logistic regression model based on Ki-67 was 0.733(95%CI 0.646-0.819),the AUC of ABUS model was 0.777(95%CI 0.695-0.858),and the AUC of ABUS combined with Ki-67 model was 0.816(95%CI 0.741-0.890).De-long's test showed that the AUC of the combined model was higher than those of ABUS feature model and Ki-67 model,with statistically significant differences(P<0.05).There was no significant difference in the AUC between ABUS feature model and Ki-67 model(P=0.40).Hosmer-Lemeshow test indicated that the combined model had a good fit(P=0.304).Internal validation results showed that the combined model had a good stability with a consistency index(C-index)of 0.820(95%CI 0.726-0.879).The calibration curve demonstrated good consistency between the predicted and actual probabilities of the combined prediction model,and the DCA curve indicated that the model had favorable clinical benefit.Conclusion The combined ABUS feature and Ki-67 model can be used to predict the probability of pCR after NAC in TNBC patients,providing a reference for the formulation of clinical treatment plans in TNBC patients.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective:To understand the prevalence of frailty and the importance of its influencing factors in adult population in Shaanxi Province.Methods:The data were from Shaanxi baseline survey of natural population cohort study in northwest China during 2018-2019. The frailty index (FI) was constructed to evaluate the frailty status of the population, and XGboost model combined with Shapley method was used to analyze the importance of the sociodemographic and life behavior factors affecting the prevalence of frailty by gender and age.Results:A total of 25 079 subjects were included, in whom 964 (3.8%) had frailty, and there was no significant difference in the overall prevalence of frailty between women (3.9%) and men (3.8%) ( P=0.629), but there was a gender specific difference in the distribution of FI ( P<0.001), and the proportion of the pre-frailty in men was higher than that in women. The prevalence of frailty increased with age ( P<0.001), the prevalence of frailty were 1.3%, 2.5% and 7.8% in young, middle-aged and elderly women, respectively, and 1.9%, 2.7% and 5.5% in young, middle-aged and elderly men, respectively. Sociodemographic characteristics and lifestyle patterns were both influencing factors for the prevalence of frailty, but their importance varied with gender and age. The top five contributing factors were education level, staying up late, annual family income level, sedentary time and marital status in young women, and staying up late, smoking, annual family income level, sedentary time and drinking in young men. The top five contributing factors were education level, annual family income level, passive exposure to smoking, staying up late, and sedentary time in middle-aged women, and annual family income level, education level, sedentary time, staying up late and drinking in middle-aged men. The top five contributing factors were annual family income level, passive exposure to smoking, sedentary time, marital status, and smartphone use in elderly women, and education level, annual family income level, smoking, smartphone use and sedentary time in elderly men. Conclusions:There are gender specific differences in the distribution of FI in Shaanxi. The prevalence of frailty increased with age, but young and middle-aged people also have frailty risk. The prevalence of frailty in young men was mainly related to unhealthy life behaviors, such as staying up late, smoking, sedentary behavior and drinking, while the prevalence of frailty in middle-aged and elderly men and women were more affected by sociodemographic factors, such as education level, economic status and marital status.

Objective:To investigate the current status of endoscopic treatment for gastroesophageal varices in portal hypertension in China, and to provide supporting data and reference for the development of endoscopic treatment.Methods:In this study, initiated by the Liver Health Consortium in China (CHESS), a questionnaire was designed and distributed online to investigate the basic condition of endoscopic treatment for gastroesophageal varices in portal hypertension in 2022 in China. Questions included annual number and indication of endoscopic procedures, adherence to guideline for preventing esophagogastric variceal bleeding (EGVB), management and timing of emergent EGVB, management of gastric and isolated varices, and improvement of endoscopic treatment. Proportions of hospitals concerning therapeutic choices to all participant hospitals were calculated. Guideline adherence between secondary and tertiary hospitals were compared by using Chi-square test.Results:A total of 836 hospitals from 31 provinces (anotomous regions and municipalities) participated in the survey. According to the survey, the control of acute EGVB (49.3%, 412/836) and the prevention of recurrent bleeding (38.3%, 320/836) were major indications of endoscopic treatment. For primary [non-selective β-blocker (NSBB) or endoscopic therapies] and secondary prophylaxis (NSBB and endoscopic therapies) of EGVB, adherence to domestic guideline was 72.5% (606/836) and 39.2% (328/836), respectively. There were significant differences in the adherence between secondary and tertiary hospitals in primary prophylaxis of EGVB [71.0% (495/697) VS 79.9% (111/139), χ2=4.11, P=0.033] and secondary prophylaxis of EGVB [41.6% (290/697) VS 27.3% (38/139), χ2=9.31, P=0.002]. A total of 78.2% (654/836) hospitals preferred endoscopic therapies treating acute EGVB, and endoscopic therapy was more likely to be the first choice for treating acute EGVB in tertiary hospitals (82.6%, 576/697) than secondary hospitals [56.1% (78/139), χ2=46.33, P<0.001]. The optimal timing was usually within 12 hours (48.5%, 317/654) and 12-24 hours (36.9%, 241/654) after the bleeding. Regarding the management of gastroesophageal varices type 2 and isolated gastric varices type 1, most hospitals used cyanoacrylate injection in combination with sclerotherapy [48.2% (403/836) and 29.9% (250/836), respectively], but substantial proportions of hospitals preferred clip-assisted therapies [12.4% (104/836) and 26.4% (221/836), respectively]. Improving the skills of endoscopic doctors (84.2%, 704/836), and enhancing the precision of pre-procedure evaluation and quality of multidisciplinary team (78.9%, 660/836) were considered urgent needs in the development of endoscopic treatment. Conclusion:A variety of endoscopic treatments for gastroesophageal varices in portal hypertension are implemented nationwide. Participant hospitals are active to perform emergent endoscopy for acute EGVB, but are inadequate in following recommendations regarding primary and secondary prophylaxis of EGVB. Moreover, the selection of endoscopic procedures for gastric varices differs greatly among hospitals.

When skin injuries are healing, complex wound environments can be easily created, which can result in wound infection, excessive inflammation caused by neutrophil accumulation and inflammatory factors, and excessive reactive oxygen species, resulting in high levels of oxidative stress. As a result of these factors, cell membranes, proteins, DNA, etc. may become damaged, which adversely affects the repair function of normal cells around the wound, resulting in the formation of chronic wounds. The effectiveness of wound dressings as a treatment is well known. They can offer temporary skin damage protection, prevent or control wound infection, create an environment that is conducive to mending skin damage, and speed wound healing. Traditional dressings like gauze, cotton balls, and bandages, however, have the drawbacks of having no antimicrobial properties, having weak adhesive properties, having poor mechanical properties, being susceptible to inflammation, obstructing angiogenesis, needing frequent replacement, and being unable to create an environment that is conducive to wound healing. As an innovative bandage, self-assembled hydrogel has great water absorption, high water retention, superior biocompatibility, biodegradability and three-dimensional (3D) structure. With properties including hemostasis, antibacterial, anti-inflammatory, and antioxidant, the synthesized raw material itself and the loaded active compounds have a wide range of potential applications in the treatment of skin injuries and wound healing. This research begins by examining and discussing the mechanism of cross-linking in self-assembled hydrogels. The cross-linking modes include non-covalent consisting of physical interaction forces such as electrostatic interactions, π-stacking, van der Waals forces, hydrophobic interactions, and metal-ligand bonds, covalent cross-linking formed by dynamic covalent bonding such as disulfide bonding and Schiff bases. And hybrid cross-linking with mixed physical forces and dynamic covalent bonding. The next part describes the special structure and excellent functions of self-assembled hydrogels, which include an extracellular matrix-like structure, the removal of exogenous microorganisms, and the mitigation of inflammation and oxidative stress. It goes on to explain the benefits of using self-assembled hydrogels as dressings for skin injuries. These dressings are capable of controlling cell proliferation, loading active ingredients, achieving hemostasis and coagulation, hastening wound healing, and controlling the regeneration of the injured area. The development of self-assembly hydrogels as dressings is summarized in the last section. The transition from purely non-covalent or covalent cross-linking to hybrid cross-linking with multiple networks, from one-strategy action to multi-strategy synergy in exerting antimicrobial, anti-inflammatory, and antioxidant effects and from single-function to multi-functioning in a single product. Additionally, it is predicted that future developments in self-assembled hydrogels will focus on creating biomimetic gels with multi-strategy associations linkage from naturally self-assembling biomolecules peptides, lipids, proteins and polysaccharides; improving the properties and cross-linking of raw materials to enhance the storage capabilities of hydrogels and cross-linking techniques, realizing the recycling of hydrogels; conducting additional research and exploration into the cross-linking process of hydrogels; and realizing the gel’s controllable rate of degradation. Furthermore, combining 3D printing and 3D microscopic imaging technology to design and build one-to-one specialized gel dressings; using computer simulation and virtual reality to eliminate the time factor, resulting in self-assembled hydrogels that perfectly fit the ideal dressing.

Purpose::Although traditional craniotomy (TC) surgery has failed to show benefits for the functional outcome of intracerebral hemorrhage (ICH). However, a minimally invasive hematoma removal plan to avoid white matter fiber damage may be a safer and more feasible surgical approach, which may improve the prognosis of ICH. We conducted a historical cohort study on the use of multimodal image fusion-assisted neuroendoscopic surgery (MINS) for the treatment of ICH, and compared its safety and effectiveness with traditional methods.Methods::This is a historical cohort study involving 241 patients with cerebral hemorrhage. Divided into MINS group and TC group based on surgical methods. Multimodal images (CT skull, CT angiography, and white matter fiber of MRI diffusion-tensor imaging) were fused into 3 dimensional images for preoperative planning and intraoperative guidance of endoscopic hematoma removal in the MINS group. Clinical features, operative efficiency, perioperative complications, and prognoses between 2 groups were compared. Normally distributed data were analyzed using t-test of 2 independent samples, Nonnormally distributed data were compared using the Kruskal-Wallis test. Meanwhile categorical data were analyzed via the Chi-square test or Fisher’s exact test. All statistical tests were two-sided, and p < 0.05 was considered statistically significant. Results::A total of 42 patients with ICH were enrolled, who underwent TC surgery or MINS. Patients who underwent MINS had shorter operative time ( p < 0.001), less blood loss ( p < 0.001), better hematoma evacuation ( p =0.003), and a shorter stay in the intensive care unit ( p =0.002) than patients who underwent TC. Based on clinical characteristics and analysis of perioperative complications, there is no significant difference between the 2 surgical methods. Modified Rankin scale scores at 180 days were better in the MINS than in the TC group ( p =0.014). Conclusions::Compared with TC for the treatment of ICH, MINS is safer and more efficient in cleaning ICH, which improved the prognosis of the patients. In the future, a larger sample size clinical trial will be needed to evaluate its efficacy.

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.

Objective:To investigate respiratory virus infection in children with septic shock in pediatric care units (PICU) in China and its influence on clinical outcomes.Methods:The clinical data of children with septic shock in children′s PICU from January 2018 to December 2019 in 10 Chinese hospitals were retrospectively collected. They were divided into the pre-COVID-19 and post-COVID-19 groups according to the onset of disease, and the characteristics and composition of respiratory virus in the 2 groups were compared. Matching age, malignant underlying diseases, bacteria, fungi and other viruses, a new database was generated using 1∶1 propensity score matching method. The children were divided into the respiratory virus group and non-respiratory virus group according to the presence or absence of respiratory virus infection; their clinical characteristics, diagnosis, and treatment were compared by t-test, rank sum test and Chi-square test. The correlation between respiratory virus infection and the clinical outcomes was analyzed by logistic regression. Results:A total of 1 247 children with septic shock were included in the study, of them 748 were male; the age was 37 (11, 105) months. In the pre-and post-COVID-19 groups, there were 530 and 717 cases of septic shock, respectively; the positive rate of respiratory virus was 14.9% (79 cases) and 9.8% (70 cases); the seasonal distribution of septic shock was 28.9% (153/530) and 25.9% (185/717) in autumn, and 30.3% (161/530) and 28.3% (203/717) in winter, respectively, and the corresponding positive rates of respiratory viruses were 19.6% (30/153) and 15.7% (29/185) in autumn, and 21.1% (34/161) and 15.3% (31/203) in winter, respectively. The positive rates of influenza virus and adenovirus in the post-COVID-19 group were lower than those in the pre-COVID-19 group (2.1% (15/717) vs. 7.5% (40/530), and 0.7% (5/717) vs. 3.2% (17/530), χ2=21.51 and 11.08, respectively; all P<0.05). Rhinovirus virus were higher than those in the pre-Covid-19 group (1.7% (12/717) vs. 0.2% (1/530), χ2=6.51, P=0.011). After propensity score matching, there were 147 cases in both the respiratory virus group and the non-respiratory virus group. Rate of respiratory failure, acute respiratory distress, rate of disseminated coagulation dysfunction, and immunoglobulin usage of the respiratory virus group were higher than those of non-respiratory virus group (77.6% (114/147) vs. 59.2% (87/147), 17.7% (26/147) vs. 4.1% (6/147), 15.6% (25/147) vs. 4.1% (7/147), and 35.4% (52/147) vs. 21.4% (32/147); χ2=11.07, 14.02, 11.06 and 6.67, all P<0.05); and PICU hospitalization of the former was longer than that of the later (7 (3, 16) vs. 3 (1, 7)d, Z=5.01, P<0.001). Univariate logistic regression analysis showed that the presence of respiratory viral infection was associated with respiratory failure, disseminated coagulation dysfunction, the use of mechanical ventilation, and the use of immunoglobulin and anti-respiratory viral drugs ( OR=2.42, 0.22, 0.25, 0.56 and 1.12, all P<0.05). Conclusions:The composition of respiratory virus infection in children with septic shock is different between pre and post-COVID-19. Respiratory viral infection is associated with organ dysfunction in children with septic shock. Decreasing respiratory viral infection through respiratory protection may improve the clinical outcome of these children.