ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

ObjectiveTo explore the data standard system of electronic medical records in the field of rehabilitation, focusing on the terminology and coding standards, data structure, and key content categories of rehabilitation electronic medical records. MethodsBased on the Administrative Norms for the Application of Electronic Medical Records issued by the National Health Commission of China, the electronic medical record standard architecture issued by the International Organization for Standardization and Health Level Seven (HL7), the framework of the World Health Organization Family of International Classifications (WHO-FICs), Basic Architecture and Data Standards of Electronic Medical Records, Basic Data Set of Electronic Medical Records, and Specifications for Sharing Documents of Electronic Medical Records, the study constructed and organized the data structure, content, and data standards of rehabilitation electronic medical records. ResultsThe data structure of rehabilitation electronic medical records should strictly follow the structure of electronic medical records, including four levels (clinical document, document section, data set and data element) and four major content areas (basic information, diagnostic information, intervention information and cost information). Rehabilitation electronic medical records further integrated information related to rehabilitation needs and characteristics, emphasizing rehabilitation treatment, into clinical information. By fully applying the WHO-FICs reference classifications, rehabilitation electronic medical records could establish a standardized framework, diagnostic criteria, functional description tools, coding tools and terminology index tools for the coding, indexing, functional description, and analysis and interpretation of diseases and health problems. The study elaborated on the data structure and content categories of rehabilitation electronic medical records in four major categories, refined the granularity of reporting rehabilitation content in electronic medical records, and provided detailed data reporting guidance for rehabilitation electronic medical records. ConclusionThe standardization of rehabilitation electronic medical records is significant for improving the quality of rehabilitation medical services and promoting the rehabilitation process of patients. The development of rehabilitation electronic medical records must be based on the national and international standards. Under the general electronic medical records data structure and standards, a rehabilitation electronic medical records data system should be constructed which incorporates core data such as disease diagnosis, functional description and assessment, and rehabilitation interventions. The standardized rehabilitation electronic medical records scheme constructed in this study can support the improvement of standardization of rehabilitation electronic medical records data information.

ObjectiveTo analyze the data structure and standards of rehabilitation outpatient medical records, to provide data support for improving the quality of rehabilitation outpatient care and developing medical insurance payment policies. MethodsBased on the normative documents issued by the National Health Commission, Basic Standards for Medical Record Writing and Standards for Electronic Medical Record Sharing Documents, in accordance with the Quality Management Regulations for Outpatient (Emergency) Diagnosis and Treatment Information Pages (Trial), reference to the framework of the World Health Organization Family of International Classifications (WHO-FICs), the data framework and content of rehabilitation outpatient medical records were determined, and the data standards were discussed. ResultsThis study constructed a data framework for rehabilitation outpatient medical records, including four main components: patient basic information, visit process information, diagnosis and treatment information, and cost information. Three major reference classifications of WHO-FICs, International Classification of Diseases, International Classification of Functioning, Disability and Health, and International Classification of Health Interventions,were used to establish diagnostic standards and standardized terminology, as well as coding disease diagnosis, functional description, functional assessment, and rehabilitation interventions, to improve the quality of data reporting, and level of quality control in rehabilitation. ConclusionThe structuring and standardization of rehabilitation outpatient medical records are the foundation for sharing of rehabilitation data. The using of the three major classifications of WHO-FICs is valuable for the terminology and coding of disease diagnosis, functional description and assessment, and intervention in rehabilitation outpatient medical records, which is significant for sharing and interconnectivity of rehabilitation outpatient data, as well as for optimizing the quality and safety of rehabilitation medical services.

ObjectiveTo explore the standardization of inpatient rehabilitation medical record summary sheet, encompassing its structure, content and data standards, to enhance the standardization level of inpatient rehabilitation medical record summary sheet, improve data reporting quality, and provide accurate data support for medical insurance payment, hospital performance evaluation, and rehabilitation discipline evaluation. MethodsBased on the relevant specifications of the National Health Commission's Basic Norms for Medical Record Writing, Specifications for Sharing Documents of Electronic Medical Records, and Quality Management and Control Indicators for Inpatient Medical Record Summary Sheet (2016 Edition), this study analyzed the structure and content of the inpatient rehabilitation medical record summary sheet. The study systematically applied the three major reference classifications of the World Health Organization Family of International Classifications, International Classification of Diseases (ICD-10/ICD-11, ICD-9-CM-3), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), for disease diagnosis, functional description and assessment, and rehabilitation intervention, forming a standardized terminology system and coding methods. ResultsThe inpatient rehabilitation medical record summary sheet covered four major sections: inpatient information, hospitalization information, diagnosis and treatment information, and cost information. ICD-10/ICD-11 were the standards and coding tools for admission and discharge diagnoses in the inpatient rehabilitation medical record summary sheet. The three functional assessment tools recommended by ICD-11, the 36-item version of World Health Organization Disability Assessment Schedule 2.0, Brief Model Disability Survey and Generic Functioning domains, as well as ICF, were used for rehabilitation functioning assessment and the coding of outcomes. ICHI Beta-3 and ICD-9-CM-3 were used for coding surgical procedures and operations in the medical record summary sheet, and also for coding rehabilitation intervention items. ConclusionThe inpatient rehabilitation medical record summary sheet is a summary of the relevant content of the rehabilitation medical record and a tool for reporting inpatient rehabilitation data. It needs to be refined and optimized according to the characteristics of rehabilitation, with necessary data supplemented. The application of ICD-11/ICD-10, ICF and ICHI Beta-3/ICD-9-CM-3 classification standards would comprehensively promote the accuracy of inpatient diagnosis of diseases and functions. Based on ICD-11 and ICF, relevant functional assessment result data would be added, and ICHI Beta-3/ICD-9-CM-3 should be used to code rehabilitation interventions. Improving the quality of rehabilitation medical records and inpatient rehabilitation medical record summary sheet is an important part of rehabilitation quality control, and also lays an evidence-based data foundation for the analysis and application of inpatient rehabilitation medical record summary sheet.

ObjectiveTo systematically analyze the global policy framework, standard systems and application technology models of digital rehabilitation within the framework of the World Health Organization (WHO) Global Digital Health Strategy and propose policy recommendations for the future development of digital rehabilitation. MethodsBased on the policies on digital health and rehabilitation development issued by the WHO, focusing on the Global Digital Health Strategy, Rehabilitation 2030 Initiative, Rehabilitation in Health Systems, Rehabilitation in Health Systems: A Guide for Action, and World Report on Disability, a systematic review was conducted, to explore the policy architecture and core content of digital rehabilitation, the standard system for digitalizing rehabilitation, and key technological models for the development of digital rehabilitation. ResultsIn the context of global health and digital transformation, the development of digital rehabilitation services was an essential component of the global digital health strategy. Building a comprehensive policy framework and content system for digital rehabilitation was critical for strengthening rehabilitation data governance, enhancing data utilization efficiency, and ensuring data privacy and security. Empowering rehabilitation with digital technology was vital for improving the standardization, effectiveness, coverage, quality and safety of rehabilitation services. International digital rehabilitation policies primarily involved the following areas: policy and governance, digital standard systems, data privacy, security and ethics, digital talent cultivation and capacity building, and monitoring, evaluation and continuous improvement of digitally empowered rehabilitation services. The standard system for rehabilitation digitization covered the three major reference classifications of the WHO Family of International Classifications, including International Classification of Diseases Eleventh Revision (ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI), especially ICF. It also included international data interoperability standards, data security and privacy protection standards, data quality and certification standards, and health information standards, etc. The application technology models of digital rehabilitation primarily included data-driven service models, artificial intelligence -enabled models, and remote rehabilitation models combined with virtual reality, augmented reality technologies, and Internet of Things support. ConclusionThe establishment and implementation of comprehensive policies, standards and technological models for digital rehabilitation are crucial for driving the digital transformation and development of global rehabilitation services. Under the framework of the WHO Global Digital Health Strategy, it is necessary to build adaptive digital rehabilitation policy frameworks, and enhance digital governance capabilities and levels, establishing and improving digital rehabilitation standard systems, and promoting the interoperability and integration of rehabilitation data with other health big data. Meanwhile, it is essential to actively develop data-driven technological models for rehabilitation services to comprehensively improve the accessibility, availability, quality and safety of rehabilitation services.

Reproductive system diseases are among the primary contributors to the decline in social fertility rates and the intensification of aging, posing significant threats to both physical and mental health, as well as quality of life. Recent research has revealed the substantial potential of the gut microbiota in improving reproductive system diseases. Under healthy conditions, the gut microbiota maintains a dynamic balance, whereas dysfunction can trigger immune-inflammatory responses, metabolic disorders, and other issues, subsequently leading to reproductive system diseases through the gut-gonadal axis. Reproductive diseases, in turn, can exacerbate gut microbiota imbalance. This article reviews the impact of the gut microbiota and its metabolites on both male and female reproductive systems, analyzing changes in typical gut microorganisms and their metabolites related to reproductive function. The composition, diversity, and metabolites of gut bacteria, such as Bacteroides, Prevotella, and Firmicutes, including short-chain fatty acids, 5-hydroxytryptamine, γ-aminobutyric acid, and bile acids, are closely linked to reproductive function. As reproductive diseases develop, intestinal immune function typically undergoes changes, and the expression levels of immune-related factors, such as Toll-like receptors and inflammatory cytokines (including IL-6, TNF-α, and TGF-β), also vary. The gut microbiota and its metabolites influence reproductive hormones such as estrogen, luteinizing hormone, and testosterone, thereby affecting folliculogenesis and spermatogenesis. Additionally, the metabolism and absorption of vitamins can also impact spermatogenesis through the gut-testis axis. As the relationship between the gut microbiota and reproductive diseases becomes clearer, targeted regulation of the gut microbiota can be employed to address reproductive system issues in both humans and animals. This article discusses the regulation of the gut microbiota and intestinal immune function through microecological preparations, fecal microbiota transplantation, and drug therapy to treat reproductive diseases. Microbial preparations and drug therapy can help maintain the intestinal barrier and reduce chronic inflammation. Fecal microbiota transplantation involves transferring feces from healthy individuals into the recipient’s intestine, enhancing mucosal integrity and increasing microbial diversity. This article also delves into the underlying mechanisms by which the gut microbiota influences reproductive capacity through the gut-gonadal axis and explores the latest research in diagnosing and treating reproductive diseases using gut microbiota. The goal is to restore reproductive capacity by targeting the regulation of the gut microbiota. While the gut microbiota holds promise as a therapeutic target for reproductive diseases, several challenges remain. First, research on the association between gut microbiota and reproductive diseases is insufficient to establish a clear causal relationship, which is essential for proposing effective therapeutic methods targeting the gut microbiota. Second, although gut microbiota metabolites can influence lipid, glucose, and hormone synthesis and metabolism via various signaling pathways—thereby indirectly affecting ovarian and testicular function—more in-depth research is required to understand the direct effects of these metabolites on germ cells or granulosa cells. Lastly, the specific efficacy of gut microbiota in treating reproductive diseases is influenced by multiple factors, necessitating further mechanistic research and clinical studies to validate and optimize treatment regimens.

Objective:To evaluate the automatic optimization performance and clinical feasibility of the intelligent optimization engine (IOE) in the Ethos online adaptive radiotherapy platform.Methods:Clinical data of 11 patients with postoperative cervical cancer treated with Halcyon accelerator were retrospectively analyzed. Manual planning was performed for all patients using the 4 full arc volumetric modulated arc therapy (VMAT) (Manual-4Arc) in Eclipse, with a prescription dose of 45 Gy/25F. Patient images and structures were imported into the Ethos simulator, and appropriate clinical goals were added based on clinical requirements. The target coverage was normalized to 95%. Automatic plan generation was conducted using IOE, resulting in 7, 9, and 12 field intensity modulated radiotherapy (IMRT) plans (IMRT-7F、IMRT-9F、IMRT-12F), as well as 2 and 3 arc VMAT plans (VMAT-2Arc、VMAT-3Arc). Dosimetric index comparisons were made between the Manual-4Arc plans and the 5 groups of IOE-generated plans through one-way analysis of variance. Based on the analysis results, Turky post hoc multiple comparisons were performed to evaluate the automatic optimization performance of IOE.Results:In terms of the high dose area, the IMRT-12F plans showed the lowest D 1% for the planning target volume (PTV), and there were significant differences compared to the Manual-4Arc plans ( P=0.004). Regarding target coverage, all groups produced clinical target volume (CTV) plans that met the clinical requirements. Although the Ethos online adaptive plans were normalized during planning, the PTV coverage was slightly insufficient. For organs at risk (OAR) close to the target, such as the bladder, there were significant differences in V 30 Gy, V 40 Gy, and D mean among the 6 groups of plans. The dose ranking for the bladder was generally as follows: IMRT-12F

To understand Helicobacter pylori's drug resistance,genetic diversity,and relationship with clinical diseases in the Guiyang and Qiannan minority areas of Guizhou Province,we collected samples through endoscopy,and isolated and cul-tured H.pylori.The drug resistance and genotype characteristics were determined.The differences in different regions and dis-ease types were compared,and the structural characteristics of H.pylori and mixed infections with different strains of H.py-lori in Qiannan Prefecture were analyzed.A difference in the composition ratio of EPYIA typing in the cagA variable region was observed between the two areas(P=0.012),and the composition ratio of the vacA genotype differed(P=0.000).A total of 94.6％(53/56)new sequences of H.pylori strains from two regions were obtained by MLST.The rate of infection by H.pylori mixed with different strains was 44.4％in Qiannan Pre-fecture,and no significant difference was observed in the com-position of H.pylori mixed infections among patients with dif-ferent clinical diseases(P=0.349).Differences in EPI YA typ-ing and the vacA genotype composition ratio in the cagA varia-ble region of H.pylori were observed between the Qiannan Prefecture and Guiyang City.

Objective:To evaluate the robustness of fully automated adaptive planning for Ethos online adaptive radiotherapy (ART) based on the intelligent optimization engine (IOE).Methods:Clinical data of 11 stage ⅠB cervical cancer patients admitted to Peking Union Medical College Hospital between June 2021 and June 2022 were retrospectively analyzed. Original planning images and iterative cone-beam computed tomography (iCBCT) images of each radiotherapy treatment were acquired, and all patient data were imported into the Ethos simulator. IOE-based 9-field automatic plan generation was performed for 11 patients using Ethos, and the generated plans were sent to online adaptive radiotherapy simulation to obtain each online adaptive radiotherapy plan (273 fractions in total) and complete the simulated treatment. For comparison, manual plan design was performed based on the images and contoured structures used for online adaptive radiotherapy planning, and the manually plans created with evenly divided 9 fields. Dosimetric parameters, plan complexity parameters, and Mobius quality assurance (QA) pass rates were collected to compare and evaluate the robustness of the online adaptive radiotherapy plan in terms of organs at risk (OAR), target volume dosimetric parameters, and plan complexity by using paired t-test or rank sum test. Results:The online adaptive plan of cervical cancer had comparable planning target volume (PTV) coverage compared to the manual plan. For the clinical target volume (CTV) D 99%, online adaptive plan was significantly higher than the manual plan [(45.93±0.36) vs. (45.32±0.31) Gy, P<0.001]. For hot dose area, the maximum point dose (PTV D max) of adaptive plan was significantly higher than the manual plan [(49.89±1.25) vs. (48.48±0.77) Gy, P<0.001], but the PTV D 1% of adaptive plan was significantly lower than the manual plan [(47.22±0.29) vs. (47.59±0.48) Gy, P<0.001]. There was no statistical difference in the conformal index ( P=0.967). And there was significant difference in the homogeneity index, with same medians and less dispersion in adaptive plan ( P<0.001). For OAR dose, bladder D mean, rectal V 40 Gy, small intestine D mean of adaptive plan was slightly higher than that of the manual plan; the rectal D mean, small intestine D 2 cm3 of the adaptive plan was slightly lower than that of manual plan; dosimetric parameters of right and left femoral heads, spinal cord and bone marrow of the adaptive plan were better than those of manual plan. The adaptive plan had more monitor units (MU) than the manual plan, but the complexity of the adaptive plan was significantly lower than that of the manual plan (0.135±0.012 vs. 0.151±0.015, P<0.001). For Mobius γ pass rate (5%/3 mm), both adaptive and manual plans met clinical requirements. Conclusion:Ethos cervical cancer online adaptive plan, which is based on the IOE engine, demonstrates good robustness and ensures the quality of online adaptive plans generated for each treatment fraction.

Objective To study the pharmacokinetic characteristics of the test formulation of compound lidocaine cream and reference formulation of lidocaine and prilocaine cream in Chinese healthy subjects and to evaluate whether there is bioequivalence between the two formulations.Methods A single-center,single-dose,randomized,open-label,two-period,two-sequence,crossover design was used.This study included 40 healthy subjects,and in each period,test formulation or reference formulation 60 g was applied to the skin in front of both thighs(200 cm2 each side,a total of 400 cm2)under fasting conditions,and the drug was left on for at least 5 h after application.The concentrations of lidocaine and prilocaine in plasma were determined using liquid chromatography-tandem mass spectrometry(LC-MS/MS)method.Pharmacokinetic parameters were calculated using WinNonlin 8.0 software to evaluate the bioequivalence of the two formulations.Results After the application of the test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream on both thighs of the subjects,the pharmacokinetic parameters of lidocaine in plasma were as follows:Cmax were(167.27±91.33)and(156.13±66.86)ng·mL-1,AUC0-t were(1 651.78±685.09)and(1 636.69±617.23)ng·mL-1·h,AUC0-∞ were(1 669.85±684.65)and(1 654.37±618.30)ng·mL-1·h,the adjusted geometric mean ratios were 104.49％,101.88％and 101.89％,respectively,with 90％confidence intervals of 98.18％-111.20％,97.80％-106.13％and 97.87％-106.07％,all within the range of 80.00％-125.00％.The pharmacokinetic parameters of prilocaine in plasma were as follows:Cmax were(95.66±48.84)and(87.52±39.16)ng·mL-1,AUC0-t were(790.86±263.99)and(774.14±256.42)ng·mL-1·h,AUC0_m were(807.27±264.67)and(792.84±254.06)ng·mL-1 h,the adjusted geometric mean ratios were 107.34％,103.55％and 102.98％,respectively with 90％confidence intervals of 101.69％-113.31％,99.94％-107.30％and 99.65％-106.43％,all within the range of 80.00％-125.00％.Conclusion The test formulation compound lidocaine cream and the reference formulation lidocaine and prilocaine cream are bioequivalent.