Objective: To evaluate the effect of community comprehensive management model intervention among patients with dyslipidemia, so as to provide the reference for optimizing community management strategies and improving the target achievement rate for blood lipids among this population. Methods: From May to June 2023, a multi-stage stratified random sampling method was employed to select patients with dyslipidemia from primary healthcare institutions in Jiaxing City, Zhejiang Province. Eligible participants were randomly assigned to either a control group or an intervention group. The control group received routine management, while the intervention group was subjected to a community comprehensive management model in addition to the routine care. Both groups were followed up for 24 months. Data on demographic characteristics, lifestyle behaviors, physical examination indices, and blood biochemical indicators were collected at baseline and after the intervention through questionnaires, physical examinations, and laboratory tests. Changes in obesity rate, central obesity rate, target achievement rates for blood lipids, blood pressure, and blood glucose, as well as lifestyle modifications, were analyzed. Differences between the two groups before and after the intervention were assessed using generalized estimating equations (GEE). Results: The control group consisted of 560 patients, including 303 females (54.11%) and 430 individuals aged ≥65 years (76.79%). The intervention group also included 560 patients, with 300 females (53.57%) and 431 individuals aged ≥65 years (76.96%). Before the intervention, no statistically significant differences were observed between the two groups in terms of gender, age, educational level, history of chronic diseases, and atherosclerotic cardiovascular disease risk stratification (all P>0.05). After 24 months of intervention, interaction effects between group and time were observed for obesity rate, central obesity rate, target achievement rate for blood lipids, target achievement rate for blood glucose, composite target achievement rate, physical activity rate, and medication adherence (all P<0.05). Specifically, the intervention group demonstrated lower rates of obesity and central obesity, and higher target achievement rate of blood lipids, target achievement rate of blood glucose, composite target achievement rate, physical activity rate, and medication adherence compared to the control group. Conclusion The community comprehensive management model contributed to improvements in multiple metabolic parameters (including body weight, waist circumference, blood lipids, and blood glucose) among patients with dyslipidemia, and was associated with increased physical activity rate and medication adherence.

To conduct a bibliometric and keyword analysis on the domestic and international literature of medical artificial intelligence （AI） ethics， explore the research frontiers， hotspots， and development trends in this field， and provide references for promoting the construction of China’s ethical governance system on medical AI. Utilizing CiteSpace software， a comparative analysis was conducted between the reviewed domestic and international literature regarding their publication volume， author and institutional collaboration networks， as well as keyword co-occurrence， clustering， timeline graph， and burst， to explore the research hotspots and development trends in the field. A total of 2 393 Chinese and English publications were included. In recent years， research topics in medical AI ethics both domestically and internationally focused on three aspects， encompassing their theoretical research， emerging domains and their ethical risks， as well as the ethical governance and regulation of medical AI. International research hotspots included federated learning， computer-aided detection， informed consent， and other aspects， whereas domestic research hotspots were smart healthcare， responsibility ethics， ethical values， and other aspects. Internationally， greater attention was placed on ethical issues concerning population health and healthcare in the public health domain， whereas domestic research topics tended to focus more on theoretical discussions and the establishment of ethical principles. The ethical governance of medical AI represents a shared global challenge， necessitating enhanced research into both the variances and commonalities in this field.

The construction of a training system for visiting physicians in the department of rare diseases in China is an important measure to improve the overall diagnosis and treatment capacity for rare diseases and address the critical challenge of insufficient knowledge and skills among clinicians in practice. This article systematically describes the visiting physician training system established by the Department of Rare Diseases at Peking Union Medical College Hospital. It summarizes the training objectives and positioning, design logic, and learning modules of the system, aiming to provide a reference for the construction of the specialized talent team for rare diseases in China.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

The Compilation Instructions for Expert Consensus on Clinical Application of Dieda Huoxue capsules systematically expound the development methods and evidence-based basis of this consensus. In view of the weak clinical application evidence and ambiguous indications of Dieda Huoxue capsules， the Institute of Basic Research in Clinical Medicine of the China Academy of Chinese Medical Sciences and Wangjing Hospital took the lead and collaborated with 33 experts from 28 medical institutions nationwide. They strictly followed the World Health Organization （WHO） guideline-making norms and the Grading of Recommendations Assessment， Development and Evaluations （GRADE） evidence-grading system and completed the compilation through multidisciplinary cooperation. The workflow included constructing clinical questions （19 items were screened by the nominal group technique）， retrieving evidence （from Chinese and English databases and grey literature）， assessing safety （integrating drug monitoring data and clinical investigations）， and forming recommendations and consensus suggestions （3 recommendations were reached via the GRADE grid method， and 16 consensus suggestions were reached by the majority vote rule）. The results indicate that the consensus clearly states that this medicine （Dieda Huoxue capsules） is applicable to conditions like traumatic injury， blood stasis-induced pain， and sudden lumbar sprains. The recommended dose is 6 capsules each time， twice a day. Combining oral administration with external application can enhance the efficacy， and elderly patients should take the medicine at intervals. Safety monitoring suggests that it should be used with caution in people with a bleeding tendency and those with an allergic constitution. The compilation process involved three rounds of reviews by internal and external experts. Literature analysis， the Delphi method， and clinical applicability tests were employed to ensure methodological rigor. The compilation instructions comprehensively present key aspects such as project approval and registration， conflict-of-interest statements， and evidence evaluation through 12 appendices， providing methodological support for the clinical translation of the consensus. In the future， it will be continuously improved through a dynamic revision mechanism.

Objective: To explore the laboratory testing methods and clinical management strategies for immune hemolytic anemia induced by Ceftizoxime sodium drug-dependent antibodies. Methods: Patient blood samples were subjected to blood typing, direct antiglobulin test, and unexpected antibody identification. Ceftizoxime sodium drug-dependent antibodies were detected using the immune complex method and drug-sensitized red cell method. The properties and titers of the drug antibodies were further assessed. Flow cytometry was used to assess the complement activation capacity of the drug antibodies in vitro. Results: Direct antiglobulin tests (IgG and C3d) were positive. Ceftizoxime sodium drug-dependent antibodies were identified using both the immune complex method and the sensitized red cell method, their titers significantly increased following the addition of the drug. Flow cytometry confirmed the complement activation capability of these antibodies and identified 30 minutes as the optimal time for activation in vitro. The patient's condition improved rapidly after drug withdrawal and supportive transfusion, resulting in a favorable outcome. Conclusion: Ceftizoxime sodium can cause drug-induced immune hemolytic anemia via complement activation mediated by drug-dependent antibodies. Serological testing is essential for diagnosing drug-induced hemolytic anemia. Clinicians should be vigilant for this adverse reaction. The offending drug must be promptly discontinued, and supportive care should be initiated upon the onset of symptoms.

Objective: To investigate the current status and influencing factors of overweight and obesity among adults in Jiaxing City, Zhejiang Province, so as to provide a basis for developing targeted weight management measures. Methods: In 2024, a multistage stratified random cluster sampling method was employed to recruit permanent residents aged ≥18 years from Jiaxing City for questionnaire surveys. Data on basic information, lifestyle behaviors, and history of chronic diseases were collected. Height and body weight were measured, and overweight and obesity were determined based on body mass index (BMI). The influencing factors of overweight and obesity among adults were analyzed by a multivariable logistic regression model. Results: Totally 10 509 questionnaires were allocated, and 9 802 valid questionnaires were recovered, with an effective recovery rate of 93.27%. Among the respondents, 4 808 (49.05%) were males and 4 994 (50.95%) were females, with a mean age of (51.27±17.26) years. A total of 4 884 overweight and obesity individuals were identified, with a detection rate of 49.83%. Multivariable logistic regression analysis showed that gender (male, OR=1.719, 95%CI: 1.578-1.873), age (≥60 years, OR=0.802, 95%CI: 0.652-0.986), educational level (bachelor and above, OR=0.640, 95%CI: 0.518-0.791), marital status (being married/cohabiting, OR=1.224, 95%CI: 1.009-1.486), adequate nut intake (OR=0.910, 95%CI: 0.832-0.995), hypertension (OR=2.462, 95%CI: 2.219-2.732), and dyslipidemia (OR=1.629, 95%CI: 1.444-1.837) were statistically associated with overweight and obesity among adults. Conclusion The detected rate of overweight and obesity among adults in Jiaxing City was relatively high, and was mainly associated with gender, age, education level, marital status, nut intake, hypertension, and dyslipidemia.

Objective: To investigate the association between overweight, obesity, central obesity and hypertension, so as to provide the basis for formulating targeted hypertension prevention and control strategies. Methods: Permanent residents aged ≥18 years were selected in Wenzhou City, Zhejiang Province from June 2023 to August 2024 by a multistage cluster random sampling method. Data on demographic information, lifestyle, height, weight, waist circumference (WC), blood pressure, and blood biochemical indicators were collected through questionnaire surveys, physical examinations, and laboratory tests. The prevalence of hypertension was calculated and standardized using the data of the Sixth National Population Census in 2010. Body mass index (BMI) was calculated to determine overweight and obesity, while WC was used to identify central obesity. The association between overweight, obesity, central obesity and hypertension were analyzed using multivariable logistic regression models. Results: A total of 38 593 residents were surveyed, including 19 481 (50.48%) males and 19 112 (49.52%) females. The median age was 46.00 (interquartile range, 26.00) years. The rates of overweight, obesity, and central obesity were 32.74% (12 634 individuals), 10.27% (3 963 individuals), and 27.87% (10 755 individuals), respectively. There were 11 813 cases of hypertension, with a prevalence and standardized prevalence of 30.61% and 24.41%, respectively. Multivariable logistic regression analysis showed that after adjusting for demographic information, lifestyle, diabetes and dyslipidemia, the likelihood of hypertension in the overweight and obesity groups was 1.927 (95%CI: 1.815-2.045) times and 3.724 (95%CI: 3.404-4.073) times that of the normal BMI group, respectively. The likelihood of hypertension in the central obesity group was 2.346 (95%CI: 2.214-2.486) times that of the normal WC group. The likelihood of hypertension in the central obesity only, overweight only, overweight with central obesity, obesity only and obesity with central obesity groups was 1.586 (95%CI: 1.391-1.809), 1.704 (95%CI: 1.582-1.835), 2.433 (95%CI: 2.254-2.626), 1.768 (95%CI: 1.424-2.194), and 4.466 (95%CI: 4.053-4.921) times that of the normal BMI and WC group, respectively. Conclusions Overweight, obesity and central obesity were all associated with hypertension among adult residents. The highest likelihood of hypertension was observed among adult residents with both general obesity and central obesity.