OBJECTIVE To evaluate the cost-effectiveness of finerenone combined with standard treatment regimen in the treatment of diabetic nephropathy （DN）. METHODS From the perspective of healthcare service providers， a Markov model was established to simulate the dynamic changes of each stage in DN patients who received finerenone combined with the standard treatment regimen or the standard treatment regimen alone based on the phase Ⅲ clinical trial study of finerenone for DN. Markov model was used to perform the cost-effectiveness of long-term effects and the costs of the two therapies with a simulation cycle of 4 months， a simulation period of 15 years and an annual discount rate of 5%. At the same time， one-way sensitivity analysis and probability sensitivity analysis were performed， and the stability of the results was validated. RESULTS Accumulative cost of the standard treatment regimen was 579 329.54 yuan， and the accumulative utility was 8.052 4 quality-adjusted life year （QALYs）； the accumulative cost of finerenone combined with the standard treatment regimen was 332 520.61 yuan， and the accumulative utility was 8.187 4 QALYs. Finerenone combined with the standard treatment regimen was more cost-effective. The results of one-way sensitivity analysis showed that dialysis status utility value， DN stage 3 utility value and DN stage 4 utility value had a great influence on the incremental cost-effectiveness ratio， but did not affect the robustness of the model. The results of probability sensitivity analysis showed that finerenone combined with the standard treatment regimen was more cost-effective with 100% probability. CONCLUSIONS For DN patients， finerenone combined with the standard treatment regimen is more cost-effective as an absolute advantage option.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

Objective: To explore the impact of sleep quality, experience of childhood maltreatment, and their interaction on depressive symptoms among middle school students, so as to provide the reference for early intervention of depressive symptoms among middle school students. Methods: From September to December 2023, a questionnaire survey was conducted among 1 231 students from two secondary schools in Harbin, Heilongjiang Province by a convenient sampling method. The survey included general demographic information, Childhood Trauma Questionnaire Short Form, Pittsburgh Sleep Quality Index and Short Version of Center for Epidemiological Studies Depression Scale. The Chi square test was used to analyze the differences in depressive symptom, sleep quality and childhood maltreatment among students with different demographic characteristics. Correlation analysis was conducted using Logistic regression, and interaction analysis was performed by both additive and multiplicative interaction models. Results: The detection rate of depressive symptoms among middle school students was 22.7%, and the rate for high school students (35.2%) was significantly higher than that for middle school students (17.0%) ( χ 2=50.35, P <0.01). The detection rates of depressive symptoms among middle school students with a history of childhood maltreatment and poor sleep quality were 45.8% and 44.0%, respectively. Multivariate Logistic regression analysis showed that compared to students without a history of childhood maltreatment, students with a history of childhood maltreatment had a higher risk of depressive symptoms ( OR =4.49，95% CI =3.31~ 6.09 , P <0.01);students with poor sleep quality had a higher risk of depressive symptoms than students with good sleep quality ( OR = 5.99，95% CI =4.37~8.22, P <0.01).The interaction results showed that the presence of childhood maltreatment and poor sleep quality had an additive interaction on the occurrence of depression in middle school students. Compared with students without childhood maltreatment and having good sleep quality, students with childhood maltreatment and poor sleep quality had a 22.49 times higher risk of developing depression ( OR =22.49，95% CI =14.22~35.59, P <0.01). Conclusion Depressive symptoms among middle school students are associated with childhood maltreatment and poor sleep quality, and there is an additive interaction between childhood maltreatment and poor sleep quality on the impact of depressive symptoms.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

AIM: To explore the protective effect of astragalus glycyrrhiza decoction (AGD) on arsenic trioxide (ATO)-induced QT interval prolongation and its mechanism based on metabonomics. METHODS: The model of ATO-induced QT interval prolongation in rats was established, and ECG, blood routine, and metabonomics were detected, and the key targets were collected combined with network pharmacology. The possible candidate genes and pathways for the protective effect of AGD were screened by GO and KEGG enrichment analysis and then verified by experiments in vitro. RESULTS: AGD could significantly alleviate the ATO-induced QT interval of SD rats. GO enrichment analysis was mainly related to inflammatory response, reactive oxygen species, oxidative stress, inner cell vesicles, folds, inner cell vesicles, SMAD binding, R-SMAD binding, and signal receptor activator activity. KEGG analysis showed that it was mainly concentrated in the PI3K-Akt signal pathway, lipid and arteriosclerosis, FOXO signal pathway, TNF signal pathway, HIF-1, and other signal pathways. Through the H9c2 cell model in vitro, it was verified that AGD could reverse the expression of SIRT1 and FOXO1 proteins. CONCLUSION: AGD may improve the ATO-induced QT interval prolongation and reduce the cardiotoxicity of ATO by regulating the SIRT1 / FOXO1 signal pathway.

Objective To make an epidemiological investigation on traditional Chinese medicine(TCM)dampness syndrome manifestations in the population at risk of cerebrovascular diseases in Guangdong area.Methods A cross-sectional study was conducted to analyze the clinical data related to the risk of cerebrovascular diseases in 330 Guangdong permanent residents.The diagnosis of dampness syndrome,quantitative scoring of dampness syndrome and rating of the risk of stroke were performed for the investigation of the distribution pattern of dampness syndrome and its influencing factors.Results(1)A total of 306(92.73%)study subjects were diagnosed as dampness syndrome.The percentage of dampness syndrome in the risk group was 93.82%(258/275),which was slightly higher than that of the healthy group(48/55,87.27%),but the difference was not statistically significant(χ2 = 2.91,P = 0.112).The quantitative score of dampness syndrome in the risk group was higher than that of the healthy group,and the difference was statistically significance(Z =-2.24,P = 0.025).(2)Among the study subjects at risk of cerebrovascular disease,evaluation time(χ2 = 26.11,P = 0.001),stroke risk grading(χ2= 8.85,P = 0.031),and history of stroke or transient ischemic attack(TIA)(χ2 = 9.28,P = 0.015)were the factors influencing the grading of dampness syndrome in the population at risk of cerebrovascular disease.Conclusion Dampness syndrome is the common TCM syndrome in the population of Guangdong area.The manifestations of dampness syndrome are more obvious in the population with risk factors of cerebrovascular disease,especially in the population at high risk of stroke,and in the population with a history of stroke or TIA.The assessment and intervention of dampness syndrome should be taken into account for future project of stroke prevention in Guangdong.

Objective To explore the prognostic factor and its predictive value of patients with Wilson disease-related acute-on-chronic liver failure(WD-ACLF).Methods The clinical data of 70 patients diagnosed as WD-ACLF admitted to the Department of Encephalopathy of the First Affiliated Hospital of Anhui University of Chinese Medicine from January 1,2017 to January 1,2022 were retrospectively collected.According to the 12-week prognosis,patients were divided into survival group(n=36)and death group(n=34).The data of the two groups were analyzed by univariate and multivariate logistic analysis to screen the prognostic risk factors and evaluate their predictive value.The model coefficient is omnibus tested,and the model-fitting degree is evaluated by the Hosmer-Lemeshow test.ROC curve was used to analyze the prognostic value for WD-ACLF between the new model and chronic liver failure-sequential organ failure assessment(CLIF-SOFA)score,model for end-stage liver disease(MELD)score and Child-Turcotte-Pugh(CTP)score.Results A total of 70 WD-ACLF patients were enrolled in present study,including 36 cases in survival group[22 males and 14 females with median age of 30.0(17.3,40.0)]and 34 cases in death group[25 males and 9 females with median age of 34.0(28.8,41.0)].Univariate analysis showed that the course of disease,prothrombin time(PT),activated partial thromboplastin time(APTT)were shorter in survival group than that in death group,the white blood cells(WBC),international normalized ratio(INR),aspartate transaminase(AST),total bilirubin(TBIL),blood urea nitrogen(BUN),creatinine(Cre)and ceruloplasmin(CER)levels and the proportion of infection,ascites,and upper gastrointestinal bleeding were lower in survival group than those in death group,however,the proportion of infection,ascites and upper digestive bleeding in the survival group were lower than those in the death group.Meanwhile,the red blood cells(RBC),hemoglobin(Hb),Na+ and total cholesterol(TC)level in the survival group were higher than those in the death group(P<0.05 or P<0.01).The results of multivariate logistic regression analysis showed that disease course(OR=1.176,95%CI 1.043-1.325),INR(OR=7.635,95%CI 1.767-32.980),TBIL(OR=1.012,95%CI 1.003-1.021),and upper gastrointestinal bleeding(OR=11.654,95%CI 1.029-131.980)were independent risk factors affecting the prognosis of WD-ACLF(P<0.05).Based on the results of logistic regression analysis,a joint model for predicting the prognosis of WD-ACLF was established.The AUC of the model for evaluating the prognosis of WD-ACLF was 0.941,which was greater than the CLIF-SOFA score(AUC=0.802),MELD score(AUC=0.897),and CTP score(AUC=0.722).Conclusions The course of disease,TBIL,INR,and upper gastrointestinal bleeding are risk factors that affect the prognosis of WD-ACLF.The prognosis model established based on this can more accurately predict the prognosis of WD-ACLF patients,and its predictive value is superior to CLIF-SOFA score,MELD score,and CTP score.

Objective To understand the changing trend of healthcare-associated infection(HAI)monitoring inde-xes in 50 secondary and higher grade hospitals in a city for 6 consecutive years from 2017 to 2022.Methods Infec-tion monitoring indexes from 50 secondary or higher grade hospitals in the city for 6 consecutive years were collec-ted,and changing trend of HAI monitoring indexes were compared.Results The number of full-time HAI manage-ment professionals increased from 91 in 2017 to 165 in 2022.The utilization rate of HAI information system in-creased from 17.00％in 2017 to 54.00％in 2022.In 6 consecutive years from 2017 to 2022,the incidence of HAI(0.91％vs 0.59％),prevalence rate of HAI(2.36％vs 1.08％),infection rate of class I incision surgical site in-fection(0.33％vs 0.16％)in 50 secondary or higher grade hospitals all showed downward trends,while health care workers'hand hygiene compliance rate showed an upward trend(61.03％vs 85.04％).Incidences of vascular cathe-ter-related bloodstream infection,ventilator-associated pneumonia,and catheter-associated urinary tract infection all showed downward trends.Incidence of HAI,prevalence rate of HAI,health care workers'hand hygiene compli-ance rate,and incidence of ventilator-associated pneumonia in tertiary hospitals were all higher than those in secon-dary hospitals,while surgical site infection rate of class Ⅰ incision in secondary hospitals was higher than that in tertiary hospitals,with statistically significant differences(all P＜0.001).Conclusion Standardizing the monitoring of HAI,as well as improving the prevention and control system and measures of HAI according to the monitoring results can reduce the incidence of HAI.