OBJECTIVE To construct a closed-loop management model for externally dispensed intravenous prescriptions， and to provide reference for standardized management of externally dispensed intravenous prescriptions. METHODS Based on the Expert Consensus on Closed-loop Management of Externally Dispensed Intravenous Prescriptions in Guangxi Zhuang Autonomous Region previously formulated by our hospital， risk points during the entire process were systematically identified through multidisciplinary team brainstorming and a fishbone diagram. A series of strategies were subsequently formulated and implemented， including qualifying designated external dispensing pharmacies and the drug catalogs， operating and maintaining the hospital information system and the Pharmacy Intravenous Admixture Service （PIVAS） intelligent management platform， and strengthening differentiated training for staff in the whole workflow. A whole-process closed-loop management system was constructed with PIVAS as the co re hub and the daytime chemotherapy center as the safety terminal. RESULTS A total of 3 cooperating pharmacies and an initial drug list comprising 35 product specifications were selected. A closed‑loop management process encompassing hospital outpatient prescribing， patient drug purchase in designated pharmacies， PIVAS drug dispensing， and medication use in daytime chemotherapy center was successfully established. This system enabled the mandatory grouping and association of externally dispensed intravenous prescriptions with in-hospital diluents， full-process verification based on drug traceability codes， intelligent monitoring of infusion parameters， and whole-process data traceability. CONCLUSIONS The constructed model effectively resolves the coordination and safety oversight during the use of externally dispensed intravenous drugs from out-of-hospital circulation to in-hospital use， and has preliminarily enabled procedural standardization， whole-process information traceability， and proactive control of medication risks.

Objective:To comprehensively evaluate the application of Common Data Model (CDM) of Observational Medical Outcomes Partnership (OMOP) in China, and provide reference for the implementation of data standardization and evidence sharing in China.Methods:PubMed, Embase, Web of Science, CNKI, VIP, WanFang and SinoMed databases were used for literature retrieval to collect the research papers of OMOP CDM application for data standardization in China until March 15, 2023. The information about institutions, types and numbers of patients were extracted.Results:A total of 14 research papers, including 9 in English and 5 in Chinese, were selected. The research papers published since 2018 were collected, which focused on patients with hypertension, diabetes, and depression. A total of 12 institutions or platforms transformed data into OMOP CDM. Jiangsu Provincial People's Hospital was the first one to apply the CDM and demonstrated its feasibility in China. Additionally, the regional information system in Yinzhou District of Ningbo, Zhejiang Province, standardized the multi-dimensional data of patients with diabetes and hypertension. Based on this platform, a series of prediction models for complications in patients with diabetes were constructed. Another major database in Beijing Anding Hospital applied OMOP CDM to analyze the characteristics of patients with late-life depression and dementia.Conclusions:This study analyzed the application of OMOP CDM in China. Through in-depth analysis of specific cases, the study provided guidance for the future cross-regional evidence sharing and collaboration.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.

Standardized research reporting is crucial for the translation of pharmacoepidemiology research findings,and visual reporting can significantly enhance the clarity,understandability,and transparency of research results.Based on the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition),this article systematically explains the key points for writing each component of a research report(including title,abstract,introduction,research methods,research results,discussion and conclusions,acknowledgments,conflict of interest statement,and references).This article also summarizes recognized international and domestic standards for pharmacoepidemiology research reporting,providing a reference for researchers.Furthermore,real-world cases will be used to demonstrate common forms of visualized reports and their interpretation methods.Finally,it further explores strategies for communicating research results.This study aims to provide pharmacoepidemiology researchers with detailed guidance on visually presenting research results and writing high-quality research reports,thereby enhancing the integrity and impact of their research.

Objective:To analyze the characteristics of Hashimoto thyroiditis(HT)and Graves disease(GD),two autoimmune thyroid diseases aged 10-59 in Qingdao City from 2022 to 2024,and to provide scientific basis for making targeted prevention and treatment measures.Methods:A cross-sectional study design was adopted,based on the data of the Regional Health Information Platform in Qingdao,the con-firmed cases of HT and GD from 2022 to 2024 were included,and combined with the data of the seventh population census,the three-year and annual prevalence rates of HT and GD were calculated,and the time trend of annual prevalence was analyzed by Cochran-Armitage trend test.The distribution characte-ristics of HT and GD prevalence in different age groups and regions were analyzed,and Chi-square test was used to compare the differences between the groups.Results:The total number of HT patients among women aged 10-59 in Qingdao City from 2022 to 2024 was 40 362.The proportion of HT patients in 30-34 years old was the highest(19.83％).The proportion of HT patients in Huangdao District was the highest(17.72％).The three-year prevalence of HT was 1 206.53/100 000.In 2022-2024,the annual prevalence of HT increased significantly(P＜0.001),from 385.32/100 000 in 2022 to 1 206.32/100 000 in 2024.The three-year prevalence of HT was significantly different in age distribution(P＜0.001).The three-year prevalence of HT in 25-29 years(2 354.44/100 000)and 35-39 years(2 022.20/100 000)was higher than that in other age groups,showing a bimodal distribution.There were significant differences in the three-year prevalence of HT in different regions(P＜0.001),among which the three-year prevalence of HT in Shinan District was the highest(2 392.90/100 000),followed by Licang Dis-trict(1 492.41/100 000),and Laixi City was the lowest(659.940/100 000).The total number of GD patients was 2 095,among which the proportion of GD patients in the 35-39 age group was the highest(15.42％),and the proportion of GD patients from Jimo District was the highest(12.27％).From 2022 to 2024,the three-year prevalence rate of GD was 62.63/100 000,and the annual prevalence rate of GD showed an increasing trend(P＜0.001),from 20.33/100 000 in 2022 to 62.63/100 000 in 2024.There were significant differences in the prevalence of GD by age(P＜0.001).The three-year prevalence of GD reached the highest value in the 25-29 age group(98.90/100 000),followed by the 35-39 age group(85.21/100 000),and the lowest in the 10-14 age group(14.43/100 000).In the regional distribution,there were significant differences in the 3-year prevalence of GD(P＜0.001).Laoshan District had the highest three-year prevalence of GD(107.58/100 000),followed by Shinan District(97.83/100 000)and Huangdao District(28.92/100 000).Conclusion:The three-year pre-valence of HT and GD in females aged 10-59 years in Qingdao City from 2022 to 2024 is low,but the annual prevalence is on the rise,and the three-year prevalence of HT and GD in females aged 25-39 years is higher than that in other age groups,so it is necessary to strengthen the screening and monitoring of this population.

Objective To investigate the labeling of dialysis-related information in the instructions of drugs for systemic use in patients with end-stage renal disease undergoing hemodialysis,and to provide reference for further standardization and im-provement of drug instructions.Methods Collected the information on pharmacokinetics and drug dose adjustment in hemodi-alysis patients with end-stage renal disease from the instructions of chemicals and biologics used systemically in XuanWu hospital's formulary from January to March 2023.Classified and compared the labeling rates of the corresponding information of the originally developed drugs and generic drugs,imported drugs and domestic drugs;Drugs eliminated by non-renal route,or with mo-lecular weight≥5 000,or binding rate of plasma protein ≥ 60％,or drug distribution volume＞360L were classified as"non-dialysis group",and other drugs were classified as"dialysis group",compared the labeling rate of corresponding information of drugs in"dialysis group"and"non-dialysis group";and compared the labeling rate and content with relevant information in Lexicomp and Micromedex.Results Among the 930 drug instructions,the labeling rates of drug dialysis clearance,drug adjustment,and ex-plicit drug adjustment plan were 16.67％,25.16％,and 24.52％.There was no significant difference in the labeling rate of dialysis-related information between original and generic drugs,and imported and domestic drugs.There was a significant difference in the labeling rate of dialysis-related information between the"dialyzable group"and the"non-dialyzable group"(P＜0.01).The differ-ence in the labeling rate of dialysis related information between the investigated drug instructions and the corresponding drugs in Lexicomp or Micromedex was statistically significant(P＜0.01).Conclusion Attention should be paid to the lack of informa-tion and unclear labeling of hemodialysis patients with end-stage renal disease in the drug instructions by relevant departments.

Objective:To comprehensively evaluate the application of Common Data Model (CDM) of Observational Medical Outcomes Partnership (OMOP) in China, and provide reference for the implementation of data standardization and evidence sharing in China.Methods:PubMed, Embase, Web of Science, CNKI, VIP, WanFang and SinoMed databases were used for literature retrieval to collect the research papers of OMOP CDM application for data standardization in China until March 15, 2023. The information about institutions, types and numbers of patients were extracted.Results:A total of 14 research papers, including 9 in English and 5 in Chinese, were selected. The research papers published since 2018 were collected, which focused on patients with hypertension, diabetes, and depression. A total of 12 institutions or platforms transformed data into OMOP CDM. Jiangsu Provincial People's Hospital was the first one to apply the CDM and demonstrated its feasibility in China. Additionally, the regional information system in Yinzhou District of Ningbo, Zhejiang Province, standardized the multi-dimensional data of patients with diabetes and hypertension. Based on this platform, a series of prediction models for complications in patients with diabetes were constructed. Another major database in Beijing Anding Hospital applied OMOP CDM to analyze the characteristics of patients with late-life depression and dementia.Conclusions:This study analyzed the application of OMOP CDM in China. Through in-depth analysis of specific cases, the study provided guidance for the future cross-regional evidence sharing and collaboration.

Objective:To systematically review the progress in the method development and application of distributed learning in the estimation of epidemiological effect and provide methodological reference for multi-center studies.Methods:We conducted a literature retrieval for English papers published up to December 31, 2023 by using keywords of "health/medical big data" and "distributed/federated learning". After consulting experts, we set criteria of paper inclusion and exclusion and created a framework for data extraction. We collected information about basic study details, including method, application, and evaluation. Two researchers independently screened the papers and extracted information. We used EndNote 20 for the management of literatures and EpiData for the management of data.Results:A total of 3 444 papers were collected, and 29 papers were included in the final analysis. Most of the papers (25, 86.2%) were published in or after 2019, and the papers were mainly from the United States (21/29, 72.4%). For the estimation of epidemiological effects, 22 distributed learning methods had been developed, including methods for logistic regression (8), Cox regression (8), Poisson regression (2), and generalized linear mixed model (GLMM) (4), as well as three platforms for distributed analysis (VLP, Vantage6, AusCAT). The 29 papers described 45 applications, with 20 (44.4%) focusing on the establishment of prediction model and 25 (55.6%) on association analysis. Importantly, except for GLMM, current distributed learning methods can estimate effects with little bias in 1-3 rounds of communication. These methods show less bias compared with meta-analysis, especially in the address of data heterogeneity and rare outcomes. However, less studies examined how differences in data structure and sparse data affect results, an area that requires further research.Conclusion:While distributed learning shows promise in epidemiological effect estimation, it is still in early development, requiring further research on data heterogeneity handling and communication efficiency improvement.

Objective To investigate the labeling of dialysis-related information in the instructions of drugs for systemic use in patients with end-stage renal disease undergoing hemodialysis,and to provide reference for further standardization and im-provement of drug instructions.Methods Collected the information on pharmacokinetics and drug dose adjustment in hemodi-alysis patients with end-stage renal disease from the instructions of chemicals and biologics used systemically in XuanWu hospital's formulary from January to March 2023.Classified and compared the labeling rates of the corresponding information of the originally developed drugs and generic drugs,imported drugs and domestic drugs;Drugs eliminated by non-renal route,or with mo-lecular weight≥5 000,or binding rate of plasma protein ≥ 60％,or drug distribution volume＞360L were classified as"non-dialysis group",and other drugs were classified as"dialysis group",compared the labeling rate of corresponding information of drugs in"dialysis group"and"non-dialysis group";and compared the labeling rate and content with relevant information in Lexicomp and Micromedex.Results Among the 930 drug instructions,the labeling rates of drug dialysis clearance,drug adjustment,and ex-plicit drug adjustment plan were 16.67％,25.16％,and 24.52％.There was no significant difference in the labeling rate of dialysis-related information between original and generic drugs,and imported and domestic drugs.There was a significant difference in the labeling rate of dialysis-related information between the"dialyzable group"and the"non-dialyzable group"(P＜0.01).The differ-ence in the labeling rate of dialysis related information between the investigated drug instructions and the corresponding drugs in Lexicomp or Micromedex was statistically significant(P＜0.01).Conclusion Attention should be paid to the lack of informa-tion and unclear labeling of hemodialysis patients with end-stage renal disease in the drug instructions by relevant departments.

A 61-year-old patient was admitted in November 2024 with the chief complaint of “marked enlargement of uterine myoma for 2 months after menopause”. This patient was diagnosed with uterine myoma 8 years ago and underwent modified radical mastectomy for right breast cancer in April 2023. Postoperative pathology revealed invasive carcinoma (SBR grade Ⅲ). Upon admission, examination results showed a cystic-solid mass in the posterior wall of the uterus and an elevated CA153 level of 273 U/mL. Transabdominal total hysterectomy and bilateral adnexectomy were performed. HE staining postoperatively indicated uterine myoma with involvement of invasive lobular carcinoma. Immunohistochemistry showed positivity for pan-cytokeratin (CKpan, ＋), GATA3 (＋), desmin (muscle＋), and estrogen receptor (ER, 90%＋ ＋ ＋), confirming the diagnosis of breast cancer metastasis to the uterine myometrium. CDK4/6 inhibitor, anastrozole, and zoledronic acid were used after surgery. Metastasis of invasive lobular carcinoma to the uterine myometrium is rare. Rapid enlargement of uterine myoma in breast cancer patients should alert clinicians to consider the possibility of metastasis, which must be confirmed by pathological examination.