BackgroundCurrently， the incidence of depression among teenagers is on the rise， and the related academic problems are becoming increasingly serious. Short video addiction has a negative impact on teenagers' emotional issues and academic achievements. However， few studies have explored the relationship between this addiction and the learning burnout of teenagers with depression， and even fewer have focused on the role paths of impulsivity and coping disposition in this process. ObjectiveTo explore the relationship between short video addiction and learning burnout in adolescent patients with depression， as well as the pathway of impulsivity and coping disposition， so as to provide references for the intervention of learning burnout in adolescent patients with depression. MethodsA total of 191 adolescent patients who were hospitalized at The Affiliated Brain Hospital of Guangzhou Medical University from December 2024 to April 2025 and met the diagnostic criteria for depression according to the International Classification of Diseases， tenth edition （ICD-10） were selected consecutively. The Short Video Addiction Measurement Scale （SVAMS）， the Brief Barratt Impulsiveness Scale （BBIS）， the Simplified Coping Style Questionnaire （SCSQ）， and the Adolescent Student Burnout Inventory （ASBI） were used for assessment. Pearson correlation analysis was employed to examine the correlations of the scores of each scale. Model 6 of the SPSS macro Process 4.2 was employed to analyze the chained mediation pathway of impulsivity and coping disposition between short video addiction and learning burnout. ResultsA total of 173 cases （90.58%） of adolescent patients with depression completed the valid questionnaire survey. Correlation analysis showed that SCSQ coping disposition score was negatively correlated with the SVAMS score， the BBIS score， and the ASBI score （r=-0.282， -0.341， -0.431， P<0.01）， the SVAMS score was positively correlated with the BBIS score and the ASBI score （r=0.339， 0.262， P<0.01）， and the BBIS score was positively correlated with the ASBI score （r=0.486， P<0.01）. The pathway analysis showed that the direct effect of short video addiction on learning burnout was not statistically significant， but the total effect and the indirect effect were statistically significant. The effect values were 0.275 （95% CI： 0.207–0.343） and 0.193 （95% CI： 0.143–0.246）， respectively， with the indirect effect accounting for 70.18%. Impulsivity and coping disposition both played independent mediating roles between short video addiction and learning burnout， with effect values of 0.122 （95% CI： 0.090–0.156） and 0.054 （95% CI： 0.032–0.079）， accounting for 44.36% and 19.64% of the total effect， respectively. The chained mediation effect of impulsivity and coping disposition was significant， with an effect value of 0.017 （95% CI： 0.011–0.026）， accounting for 6.18% of the total effect. ConclusionAlthough short video addiction does not directly affect learning burnout in adolescent patients with depression， it may indirectly influence learning burnout through independent and chain paths of impulsivity and coping disposition. ［Funded by Guangzhou Key Clinical Specialty （Clinical Medical Research Institute）］

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Background Prehospital emergency medical personnel (PEMP) are exposed to long-term high-pressure work, which can exacerbate psychological distress and impair job satisfaction and sleep quality. However, in-depth research on the interactions among these factors is lacking. Objective To assess the status of psychological distress, job satisfaction, and sleep quality of PEMP in Guangzhou and to explore the mediating role of sleep quality in the relationship between psychological distress and job satisfaction. Methods From February to May 2025, 1085 PEMP from "120" emergency network hospitals in Guangzhou were selected using convenience sampling. Data were collected via the General Information Questionnaire, Kessler Psychological Distress Scale, Minnesota Satisfaction Questionnaire, and Pittsburgh Sleep Quality Index. Statistical analyses were performed using SPSS 25.0, and The mediation model of sleep quality in linking psychological distress and job satisfaction was constructed using AMOS 28.0. The bias-corrected Bootstrap method was employed to assessed the significance of the mediating effect. Results A total of 1063 valid responses were received (97.97% valid response rate). The mean scores were: psychological distress (27.99±10.75), job satisfaction (69.45±15.84), and sleep quality (9.82±4.47). Significant differences in the three scores were found across gender, age, monthly night shift frequency, and hospital grade (P<0.05). Higher job satisfaction was linked to lower psychological distress and better sleep quality and its dimensions, while psychological distress directly correlated with poorer sleep quality (P<0.01). Sleep quality partially mediated the relationship between psychological distress and job satisfaction, with a mediating effect of −0.195, accounting for 43.62% of the total effect. Conclusion The participants report moderate psychological distress, moderate-to-high job satisfaction, and poor sleep quality. Psychological distress directly affects job satisfaction and indirectly through its impact on sleep quality. Interventions aimed at improving sleep health and mental health are essential to improve personnel well-being and work efficiency.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Background Prehospital emergency medical personnel (PEMP) are exposed to long-term high-pressure work, which can exacerbate psychological distress and impair job satisfaction and sleep quality. However, in-depth research on the interactions among these factors is lacking. Objective To assess the status of psychological distress, job satisfaction, and sleep quality of PEMP in Guangzhou and to explore the mediating role of sleep quality in the relationship between psychological distress and job satisfaction. Methods From February to May 2025, 1085 PEMP from "120" emergency network hospitals in Guangzhou were selected using convenience sampling. Data were collected via the General Information Questionnaire, Kessler Psychological Distress Scale, Minnesota Satisfaction Questionnaire, and Pittsburgh Sleep Quality Index. Statistical analyses were performed using SPSS 25.0, and The mediation model of sleep quality in linking psychological distress and job satisfaction was constructed using AMOS 28.0. The bias-corrected Bootstrap method was employed to assessed the significance of the mediating effect. Results A total of 1063 valid responses were received (97.97% valid response rate). The mean scores were: psychological distress (27.99±10.75), job satisfaction (69.45±15.84), and sleep quality (9.82±4.47). Significant differences in the three scores were found across gender, age, monthly night shift frequency, and hospital grade (P<0.05). Higher job satisfaction was linked to lower psychological distress and better sleep quality and its dimensions, while psychological distress directly correlated with poorer sleep quality (P<0.01). Sleep quality partially mediated the relationship between psychological distress and job satisfaction, with a mediating effect of −0.195, accounting for 43.62% of the total effect. Conclusion The participants report moderate psychological distress, moderate-to-high job satisfaction, and poor sleep quality. Psychological distress directly affects job satisfaction and indirectly through its impact on sleep quality. Interventions aimed at improving sleep health and mental health are essential to improve personnel well-being and work efficiency.

Despite of the widespread use of hydrogen and methane breath test, the variability in testing protocols, gas measurement techniques, and interpretation criteria continues to challenge the reproducibility and comparability across centers, especially in the Asia-Pacific region. The Asian Neurogastroenterology and Motility Association hence presents the first Asian monograph guiding application and interpretation of breath test. The monograph was formulated according to the framework of indications, preparatory process, performance, and interpretation of results, as well as future direction for research.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

With the rapid advancements in surgical and interventional therapies, over 90% of children with congenital heart disease can now survive into adulthood with appropriate treatment. As a rapidly expanding population, adult congenital heart disease (ACHD) patients often present with complex anatomical abnormalities and post-procedural complications, posing significant long-term management challenges for clinicians. The American College of Cardiology and American Heart Association jointly released the 2025 guidelines for the management of adult congenital heart disease, which represents a comprehensive and fundamental update following the inaugural 2008 edition. This new guideline not only integrates the latest evidence-based data but also marks a paradigm shift in ACHD management, from a disease-centered approach to a patient-centered lifelong continuum of care. This article aims to provide an interpretation of the guidelines from the perspective of a cardiac surgeon to provide references for the management of various disease subtypes.

Objective To construct and compare logistic regression and decision tree models for predicting systemic inflammatory response syndrome (SIRS) in patients with type B aortic dissection (TBAD) after interventional surgery. Methods A retrospective analysis was conducted on clinical data of TBAD patients at Peking University Shenzhen Hospital from 2020 to 2024. The patients were divided into a SIRS group and a non SIRS group based on whether SIRS occurred within 24 hours after surgery. Multivariate logistic regression was used to analyze the influencing factors of SIRS occurrence in TBAD intervention patients, and a decision tree model was constructed using SPSS Modeler to compare the predictive performance of the two models. Results A total of 742 patients with TBAD were included, including 579 males and 163 females, aged 27-97 (58.85±10.79) years. Within 24 hours after intervention, a total of 506 patients developed SIRS, with an incidence rate of 68.19%. Logistic regression analysis showed that the extensive involvement of the dissection, the surgical time≥2 hours, PET coated stents implanted, serum creatinine, white blood cell count, C-reactive protein, monocyte (MONO), neutrophil count levels elevated, estimated glomerular filtration rate and decreased albumin levels were independent risk factors for SIRS (P<0.05). The decision tree model selected a total of 10 explanatory variables and 6 layers with 37 nodes, among which MONO was the most important predictor. The area under the decision tree model curve was 0.829 [95%CI (0.800, 0.856)], which was better than the logistic regression model's 0.690 [95%CI (0.655, 0.723)], and the difference was statistically significant (P<0.001). Conclusion The incidence of SIRS after TBAD intervention is high, and the decision tree model has better predictive performance than logistic regression. It can identify high-risk patients with higher accuracy and provide a practical tool for early clinical intervention.

AIM: To evaluate the reliability of a digital multimedia system for measuring near-distance horizontal heterophoria.METHODS: This cross-sectional diagnostic study enrolled patients with refractive errors who visited Shantou Aier Eye Hospital from May 2023 to August 2025, presenting with symptoms of visual fatigue, undergoing myopia management, or receiving routine ophthalmic examinations, and who completed heterophoria testing during this period. All patients wearing full refractive correction underwent near-distance(0.4 m)horizontal heterophoria measurement in a random order using the digital multimedia system, the Von Graefe method, and the Maddox rod method. Two consecutive measurements were performed for each method. The intraclass correlation coefficient(ICC)was used to analyze the measurement repeatability of each method, and Bland-Altman analysis and Spearman correlation analysis were employed to evaluate the consistency between the digital multimedia system and the two traditional methods.RESULTS: A total of 60 patients(120 eyes)were included, comprising 27 males and 33 females, with a mean age of 21.03±7.24 y. Repeatability analysis showed that the ICC for the digital multimedia system was 0.960(95%CI: 0.934-0.976), for the Von Graefe method was 0.979(95%CI: 0.964-0.987), and for the Maddox rod method was 0.956(95%CI: 0.926-0.973), all indicating excellent repeatability. Bland-Altman analysis revealed a mean difference of 0.367△ [95% limits of agreement(LoA): -2.97△ to 3.70△] between the Von Graefe method and the digital system, and a mean difference of 0.067△(95% LoA: -3.05△ to 3.19△)between the Maddox rod method and the digital system. Both differences were within the clinically acceptable range(difference <4△). Spearman correlation analysis showed positive correlations between the digital system and the Von Graefe method(rs=0.867)and between the digital system and the Maddox rod method(rs=0.777, all P<0.001).CONCLUSION: The digital multimedia system demonstrates high repeatability and good consistency with the traditional Von Graefe and Maddox rod methods for measuring near-distance horizontal heterophoria. It shows promise as a new and effective tool for clinical near-distance horizontal heterophoria measurement.