Objective:To understand the usage situation of e-cigarettes among residents aged 18-65 in Beijing, explore the relationship between e-cigarette use and cigarette smoking as well as smoking cessation behaviors, and provide scientific support for the developing and improving policies and measures related to e-cigarettes.Methods:Using 19 684 residents data from the Beijing Non-communication Chronic Disease and Risk Factors Surveillance in 2022, complex sampling weighted methods were used to estimate proportions, and complex sampling logistic regression analysis was applied to explore the relationship between e-cigarette use, cigarette smoking, and smoking cessation.Results:Among all study participants, the proportion of those who had ever used e-cigarettes was 3.36%, with the current e-cigarette use at 1.26%. The proportion of current e-cigarette users (1.87%) and the former e-cigarette users (3.47%) were higher ( χ2=64.70, P<0.001) among males compared to females (0.60% and 0.64% respectively). The top three reasons for using e-cigarettes were wanting to quit smoking, perceiving e-cigarettes as less harmful, and enjoying the flavors of e-cigarettes. 83.54% of e-cigarette users started with cigarettes. The results of the complex sampling multivariable logistic regression analysis showed that current smoking ( OR=61.35, 95% CI: 36.98-101.76) and former smoking ( OR=31.20, 95% CI: 15.52-62.71) were positively associated with e-cigarette, while current e-cigarette use ( OR=0.13, 95% CI: 0.04-0.39) was negatively associated with quitting cigarette smoking. Conclusions:The proportion of e-cigarette use in Beijing was relatively low. E-cigarette use was associated with cigarette use and was not conducive to smoking cessation. Therefore, stronger regulatory measures and health education campaigns regarding the risks of e-cigarettes should be implemented.

Objective:To analyze the prevalence trends and epidemiological characteristics of cardiometabolic multimorbidity(CMM) in Beijing from 2005 to 2022.Methods:A series of representative cross-sectional surveys were conducted in Beijing between 2005 and 2022 using a stratified multistage cluster random sampling method. A total of 110 496 permanent residents aged 18-79 years participated in face-to-face interviews, physical examinations, and laboratory testing. Complex sampling logistic regression models were employed to identify factors associated with CMM, and Joinpoint regression was used to assess temporal trends in prevalence. Results:The prevalence of CMM was 22.3% in 2005 and 24.3% in 2022, with an average annual percent change of 0.1%(95% CI -1.3%-1.3%, P>0.05). In rural areas, the prevalence increased by 1.3% per year(95% CI 0.2%-2.6%, P<0.05), while among obese individuals, it decreased by 1.0% annually( P<0.05). The most common CMM patterns were hypertension combined with dyslipidemia(13.2%), hypertension combined with diabetes(7.0%), and diabetes combined with dyslipidemia(5.8%). The prevalence of hypertension and dyslipidemia comorbidity showed a long-term decline among females, those aged 60-79 and obese individuals( P<0.05). In contrast, the prevalence of hypertension and diabetes comorbidity increased over time in rural residents and individuals with normal body weight( P<0.05). Furthermore, diabetes and dyslipidemia comorbidity rates increased significantly among males, adults aged 18-59 years, those with a college education or above, rural residents and individuals with normal body weight( P<0.05). Multivariable logistic regression indicated that male, older age, overweight, obese, and lower education level were independently associated with a higher risk of CMM( P<0.05). Conclusion:From 2005 to 2022, the prevalence of CMM remained high among adults in Beijing. While prevalence decreased among obese individuals, it increased significantly in rural areas. Hypertension combined with dyslipidemia was the most common multimorbidity pattern throughout the study period.

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

Permanent left superior vena cava aneurysm is a rare mediastinal venous lesion，the majority of the literature is in the form of case reports. In this article，a 50-year-old female with an incidental permanent left superior vena cava aneurysm discovered on echocardiography in Nanjing Gulou Hospital，and the right heart contrast-enhanced echocardiographic played an important role in the process of clear diagnosis. The patient was observed without intervention. No complications were attributable to the permanent left superior vena cava aneurysm during follow-up.

Objective:To understand the usage situation of e-cigarettes among residents aged 18-65 in Beijing, explore the relationship between e-cigarette use and cigarette smoking as well as smoking cessation behaviors, and provide scientific support for the developing and improving policies and measures related to e-cigarettes.Methods:Using 19 684 residents data from the Beijing Non-communication Chronic Disease and Risk Factors Surveillance in 2022, complex sampling weighted methods were used to estimate proportions, and complex sampling logistic regression analysis was applied to explore the relationship between e-cigarette use, cigarette smoking, and smoking cessation.Results:Among all study participants, the proportion of those who had ever used e-cigarettes was 3.36%, with the current e-cigarette use at 1.26%. The proportion of current e-cigarette users (1.87%) and the former e-cigarette users (3.47%) were higher ( χ2=64.70, P<0.001) among males compared to females (0.60% and 0.64% respectively). The top three reasons for using e-cigarettes were wanting to quit smoking, perceiving e-cigarettes as less harmful, and enjoying the flavors of e-cigarettes. 83.54% of e-cigarette users started with cigarettes. The results of the complex sampling multivariable logistic regression analysis showed that current smoking ( OR=61.35, 95% CI: 36.98-101.76) and former smoking ( OR=31.20, 95% CI: 15.52-62.71) were positively associated with e-cigarette, while current e-cigarette use ( OR=0.13, 95% CI: 0.04-0.39) was negatively associated with quitting cigarette smoking. Conclusions:The proportion of e-cigarette use in Beijing was relatively low. E-cigarette use was associated with cigarette use and was not conducive to smoking cessation. Therefore, stronger regulatory measures and health education campaigns regarding the risks of e-cigarettes should be implemented.

Objective:To analyze the prevalence trends and epidemiological characteristics of cardiometabolic multimorbidity(CMM) in Beijing from 2005 to 2022.Methods:A series of representative cross-sectional surveys were conducted in Beijing between 2005 and 2022 using a stratified multistage cluster random sampling method. A total of 110 496 permanent residents aged 18-79 years participated in face-to-face interviews, physical examinations, and laboratory testing. Complex sampling logistic regression models were employed to identify factors associated with CMM, and Joinpoint regression was used to assess temporal trends in prevalence. Results:The prevalence of CMM was 22.3% in 2005 and 24.3% in 2022, with an average annual percent change of 0.1%(95% CI -1.3%-1.3%, P>0.05). In rural areas, the prevalence increased by 1.3% per year(95% CI 0.2%-2.6%, P<0.05), while among obese individuals, it decreased by 1.0% annually( P<0.05). The most common CMM patterns were hypertension combined with dyslipidemia(13.2%), hypertension combined with diabetes(7.0%), and diabetes combined with dyslipidemia(5.8%). The prevalence of hypertension and dyslipidemia comorbidity showed a long-term decline among females, those aged 60-79 and obese individuals( P<0.05). In contrast, the prevalence of hypertension and diabetes comorbidity increased over time in rural residents and individuals with normal body weight( P<0.05). Furthermore, diabetes and dyslipidemia comorbidity rates increased significantly among males, adults aged 18-59 years, those with a college education or above, rural residents and individuals with normal body weight( P<0.05). Multivariable logistic regression indicated that male, older age, overweight, obese, and lower education level were independently associated with a higher risk of CMM( P<0.05). Conclusion:From 2005 to 2022, the prevalence of CMM remained high among adults in Beijing. While prevalence decreased among obese individuals, it increased significantly in rural areas. Hypertension combined with dyslipidemia was the most common multimorbidity pattern throughout the study period.

Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.

Permanent left superior vena cava aneurysm is a rare mediastinal venous lesion，the majority of the literature is in the form of case reports. In this article，a 50-year-old female with an incidental permanent left superior vena cava aneurysm discovered on echocardiography in Nanjing Gulou Hospital，and the right heart contrast-enhanced echocardiographic played an important role in the process of clear diagnosis. The patient was observed without intervention. No complications were attributable to the permanent left superior vena cava aneurysm during follow-up.

Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1 250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAXGv).The videos were divided into development set(245 A4C,155 PLAX,225 PSAXGV),semi-automated training set(98 A4C,62 PLAX,90 PSAXGV)and test set(147 A4C,93 PLAX,135 PSAXGV)at the ratio of 5:2:3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33％,97.26％,97.26％and 97.26％to 99.73％,99.65％,99.77％and 99.71％,respectively,while the overall accuracy for assessing A4C,PLAX and PSAXGV TTE as standard views in test set improved from 89.12％,83.87％and 90.37％to 93.20％,90.32％and 93.33％,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.

Life science and medical research involving human beings cannot be separated from the support of research participants.The safety,health,and rights and interests of research participants are the primary considerations in clinical research,and their rights and interests include the right of compensation,privacy protection,health and so on.Protecting the compensation rights of research participants is a necessary responsibility of the research-related departments and personnel.Based on laws and regulations and literature review,and combined with practical experience,this paper made an in-depth discussion on compensation rights.It puts forward the types of compensation(conventional compensation,research-related damage compensation),compensation principles(necessity,timeliness,appropriateness,fairness),compensation elements(method,amount,plan,consent,notification,and reference of compensation),compensation under special circumstances(compensation for participants without or with limited informed consent ability and withdraw from the study midway),protection measures of compensation right(sponsor/contract research organizations,research institutions,research management departments,(main)researchers and research teams,ethics(review)committee).The compensation rights should be implemented to protect research participants.