Objective To predict the potential suitability distribution of Vitex negundo in China;To analyze the key environmental factors influencing its suitability distribution.Methods Based on the geographic distribution data of Vitex negundo from 196 sites across China and 55 environmental variables,the Maximum Entropy(MaxEnt)model and ArcGIS 10.2 were employed to predict the potential distribution of suitable habitats for Vitex negundo in China.Results The constructed MaxEnt prediction model demonstrated high reliability.The primary environmental factors influencing the suitable distribution of Vitex negundo included the average temperature from June to October,precipitation in April and November,the mean temperature of the warmest season,soil type,and vegetation type.The predicted suitable habitats for Vitex negundo would be widely distributed,primarily concentrated in Jiangxi,central and southern Anhui,northwestern Zhejiang,eastern and northeastern Hunan,as well as eastern and southeastern Hubei.Conclusion The predicted potential distribution of Vitex negundo in China can provide a valuable reference for the conservation and sustainable utilization of this medicinal resource.

With the widespread promotion of patient-centered care models,narrative medicine,as a medical practice that emphasizes patients'personal stories and experiences,has garnered increasing attention in the medical field.Through a systematic literature review and field observations,this paper analyzed the ethical challenges faced by narrative medicine in reconstructing doctor-patient relationships,which mainly include information asymmetry and uneven distribution of medical resources,insufficient informed consent and privacy protection of patients,and difficulties in ensuring the authenticity and completeness of narrative content.In response,this paper proposed strategies such as enhancing patients'understanding of their rights and narrative medicine,promoting continuous ethical evaluations of narrative medicine practices,and exploring interdisciplinary collaborations to foster harmonious doctor-patient relationships.It also emphasized the importance of establishing multidisciplinary cooperation mechanisms and strengthening ethical training for medical personnel,as well as the necessity of ensuring information security through technological means,aiming to promote harmonious doctor-patient relationships,better realize the ethical practices of narrative medicine,optimize doctor-patient relationships,and improve the quality of medical services.

Objective:This study empirically analyzes the relationship between outpatient and inpatient services under the impact of healthcare payment reform,and evaluates the effects of the reform.Methods:Data from healthcare services and basic medical insurance payments in eight districts of Jinhua City from 2020 to 2022 were used.A fixed-effects model for outpatient and inpatient services was constructed to analyze the impact of healthcare payment reforms and outpatient services on inpatient services.Results:The DRG-based payment had a significant positive effect on inpatient visits and a significant negative effect on employee basic medical insurance inpatient costs.The"capitation+APG"outpatient payment policy had a significant negative effect on inpatient visits and a significant negative effect on residents'basic medical insurance inpatient costs.The interaction between outpatient payment and outpatient visits had a significant negative effect on employee basic medical insurance inpatient visits,while the interaction between outpatient payment and outpatient costs had a significant negative effect on both overall and employee inpatient costs.Conclusions:The DRG payment reform led to an increase in inpatient visits and a reduction in employee basic medical insurance inpatient costs.The outpatient"capitation+APG"payment reform reduced inpatient visits and lowered residents'basic medical insurance inpatient costs,thereby slowing down the complementary effect between outpatient and inpatient services.

Objective To explore the research hotspots and development trends in the field of cancer treatment in the past decade. Methods The CNKI and Web of Science Core Collection databases were searched for Chinese and English articles related to cancer treatment published over the last 10 years. Bibliometric research methods were employed, including keyword cluster analysis of published literature. Results A total of 45 455 Chinese articles and 866 958 English articles were retrieved. Combining the visualization analysis results and the current research dilemma of tumor treatment revealed that the current research hotspots of tumor treatment domestically and internationally can primarily focus on four key areas. In the realm of targeted therapy, efforts are directed towards the discovery of new drug targets, overcoming resistance to targeted therapy, and the development of monoclonal antibodies and antibody–drug conjugates. In the field of immunotherapy, the emphasis lies in enhancing the response rate to immune checkpoint inhibitors, determining the mechanisms behind resistance to immunotherapy, and improving the safety of treatment. The research in traditional Chinese medicine (TCM) covers evidence-based evaluation studies on TCM treatment, the identification of populations that can gain the most benefit from TCM, and strategies for improving the quality of life. In the area of novel drug development, cutting-edge technologies, such as organoid-based screening for anticancer drugs, synthetic biology, and artificial intelligence, are under investigation. Conclusion New targeted drugs, immune efficacy improvement, multidisciplinary integration, nano-delivery, and TCM innovation are the key research directions in the field of tumor therapy in the future.

Objective To analyze the disease burden of chronic kidney diseases (CKD) attributed to high body mass index (BMI) in China from 1992 to 2021 and predict the disease burden for the next decade, and to provide evidence for the prevention and treatment of CKD. Methods Using the Global Burden of Disease (GBD) database and the Joinpoint model, the average annual percentage rate change (AAPC) of the mortality rate and disability-adjusted life year (DALY) rate was calculated to describe and analyze the CKD disease burden attributed to high BMI in China from 1992 to 2021. The ARIMA model was employed to predict and analyze the change trend of the CKD disease burden. Results From 1992 to 2021, the mortality rate and DALY rate attributed to high BMI-induced chronic kidney disease showed an upward trend. Compared to 1992, the attributed number of deaths increased by 324.38%, and DALYs increased by 268.56%; the mortality rate increased by 64.00%, and the DALY rate grew by 51.62%. From 1992 to 2021, the mortality rate and DALY rate for males were lower than those for females, but the growth rate for males exceeded that of females. From 1992 to 2021, the mortality rate and DALY rate of chronic kidney disease attributed to high BMI in China increased with age. The average annual change rate of chronic kidney disease attributed to high BMI in China from 1992 to 2021 (mortality rate: 1.40 per 100,000 (95% CI: 1.04–1.76), DALY rate: 1.43 per 100 000 (95% CI: 1.17–1.70)) was higher than thHuaiyin Normal University, Huai'anher social demographic index (SDI) regions. The ARIMA model predicted that the age-standardized mortality rate increased from 2.91 per 100 000 in 2022 to 3.05 per 100 000 in 2026, and the age-standardized DALY rate increased from 69.65 per 100 000 in 2022 to 73.58 per 100 000 in 2026. Conclusion Chronic kidney disease attributed to high BMI in China is on the rise, and it will continue to grow in the future. The focus of CKD prevention and control should be on males and the elderly, while active measures should be taken to reduce the occurrence and progression of chronic kidney disease.

Objective To construct a nomogram prediction model for predicting hemoglobin A1c(HbA1c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021 to January 2022 were selected as the research objects and divided into the non-standard group(HbA1c≥7%,n=801)and the standard group(HbA1c<7%,n=135).Univariate analysis was used to screen the related factors of HbA1c failure.Logistic regression multivariate model was used to analyze the influencing factors of HbA1c failure in T2DM patients.The R language was used to construct a nomogram,and the area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictive ability of the model.The C-index and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Results There were statistically significant differences in triglyceride(TG),low-density lipoprotein cholesterol,direct bilirubin,urinary albumin/creatinine ratio(UACR),self-monitoring of blood glucose(SMBG),meat and vegetable pairing,hot pot,whole grain and animal viscera consumption between the two groups(P<0.05).Logistic regression analysis showed that TG(OR 1.699,95%CI 1.298～2.222),UACR(OR 1.003,95%CI 1.001～1.005),SMGB(OR 0.480,95%CI 0.313～0.735),more meat and less vegetables(OR 1.432,95%CI 1.062～1.931)were the influencing factors of HbA1c failure.The AUC of the nomogram prediction model based on the influencing factors was 0.711,with C-index 0.710(95%CI 0.663～0.758)and good calibration(χ2=11.185,P=0.191).Conclusions The nomogram prediction model for HbA1c failure in T2DM patients established based on TG,UACR,SMGB,meat and vegetarian mix has good discrimination and calibration,which can provide certain reference value for warning of poor blood glucose control.

Objective:To explore the influence of different scanning positions based on chest phantom of computed tomography(CT)scan on chest on image quality and radiation dose.Methods:A thermoluminescent dosimeter(TLD)was placed at the breast area of simulating anthropoid chest phantom.GE Revolution evo CT was used to conduct scan on the conventional supine position(supine group)and prone position(prone group)for chest phantom.Different noise indexes(NI=10-23)were adjusted to control ration doses,and other parameters were fixed,and each group collected 12 sequence images.The average value(AV),standard deviation(SD)of the CT scan at region of interest(ROI)under different scanning positions were recorded to calculate the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the image.The radiation dose at the breast area was measured by TLD,and the volume CT dose index(CTDIvol)and dose-length product(DLP)were recorded.Results:Under different scanning positions,the radiation dose of breast organs in the prone group was lower than that in the supine group,there was a statistically significant difference between the two groups(t=6.57,P<0.05),while there were not statistically significant differences in CTDIvol and DLP between the two groups(P>0.05).There were not statistically significant differences in the CT values,SD,SNR,CNR of lung tissue,and the CT values of breast tissue between the two groups of images(P>0.05).The SD,SNR and CNR of breast tissue in the prone group were lower than those in the supine group,and the differences were statistically significant(t=-13.33,-10.59,6.70,P<0.05).There were no statistically significant differences in the subjective scores of the clarity of the edge of the tissue within lung,the layers of soft tissue of the breast,noise,and artifacts in the bone tissue between the two groups of images(P>0.05).Conclusion:When low-dose CT physical examination on chest is conducted in clinical practice,the scanning of prone position during undergoing CT scan on chest can obtain image quality that can meet the requirements in diagnosing lung,and reduce the radiation dose on the breast,and conform to the technical principle of optimal radiation protection.

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 construct a nomogram prediction model for predicting hemoglobin A1c(HbA1c)failure in type 2 diabetes mellitus(T2DM)patients.Methods A total of 936 inpatients with T2DM admitted to the Department of Endocrinology of the Affiliated Hospital of Shandong Second Medical University from January 2021 to January 2022 were selected as the research objects and divided into the non-standard group(HbA1c≥7%,n=801)and the standard group(HbA1c<7%,n=135).Univariate analysis was used to screen the related factors of HbA1c failure.Logistic regression multivariate model was used to analyze the influencing factors of HbA1c failure in T2DM patients.The R language was used to construct a nomogram,and the area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictive ability of the model.The C-index and Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model.Results There were statistically significant differences in triglyceride(TG),low-density lipoprotein cholesterol,direct bilirubin,urinary albumin/creatinine ratio(UACR),self-monitoring of blood glucose(SMBG),meat and vegetable pairing,hot pot,whole grain and animal viscera consumption between the two groups(P<0.05).Logistic regression analysis showed that TG(OR 1.699,95%CI 1.298～2.222),UACR(OR 1.003,95%CI 1.001～1.005),SMGB(OR 0.480,95%CI 0.313～0.735),more meat and less vegetables(OR 1.432,95%CI 1.062～1.931)were the influencing factors of HbA1c failure.The AUC of the nomogram prediction model based on the influencing factors was 0.711,with C-index 0.710(95%CI 0.663～0.758)and good calibration(χ2=11.185,P=0.191).Conclusions The nomogram prediction model for HbA1c failure in T2DM patients established based on TG,UACR,SMGB,meat and vegetarian mix has good discrimination and calibration,which can provide certain reference value for warning of poor blood glucose control.

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.