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.

The success of implementation research is closely tied to the institution's pre-implementation readiness. This study aims to explore the organizational readiness for change (ORC) and its influencing factors on primary healthcare settings in the implementation of the "Shared Medical Appointment for Diabetes (SMART) in China: design of an optimization trial" and to enhance ORC and provide insights to support the effective implementation of the program.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Objective To screen ferroptosis genes related to the prognosis of cervical cancer and to construct a prognosis model. Methods Ferroptosis genes were obtained from FerrDb database, and cervical cancer related data were obtained from The Genome-Wide Association Study Catalog database and The Cancer Genome Atlas database. Transcriptome-Wide Association Study, colocalization analysis and differential expression analysis were conducted to screen out candidate ferroptosis genes; Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were conducted on candidate genes. Univariate Cox regression analysis was used to further screen out genes related to the prognosis of cervical cancer. Kaplan-Meier method was used to analyze the relationship between genes and the overall survival of patients. The expression levels of genes in pan-cancer were analyzed through the TIMER database. Two prognostic models were conducted, Model 1 included age and tumor stage, while Model 2 incorporated age, tumor stage, and prognostic genes. The predictive capabilities of the two models were compared. Results A total of 91 candidate genes related to ferroptosis were obtained. Univariate Cox regression analysis showed that 15 genes were associated with the prognosis of cervical cancer. CA9, SCD, TFRC, QSOX1 and CDO1 were risk factors affecting the prognosis of cervical cancer patients (P＜0.05), while PTPN6, ALOXE3, HELLS, IFNG, MIOX, ALOX12B, DUOX1, ALOX15, AQP3 and IDO1 were protective factors (P＜0.05). The mRNA expression levels of the 15 genes showed significant upregulation or downregulation in at least 7 types of cancers, among which TFRC was associated with the largest number of cancer types. Kaplan-Meier analysis showed that HELLS, DUOX1 and ALOXE3 were associated with poor prognosis in cervical cancer. The AUC of the model 1 for predicting 1-year and 3-year overall survival rates of cervical cancer patients was 0.455 and 0.478, and the AUC of Model 2 was 0.854 and 0.595. Model 2 (C-index = 0.727) had better predictive ability than Model 1 (C-index = 0.502). Conclusion The prognostic model composed of 15 prognostic-related genes selected based on bioinformatics has better predictive performance for the survival outcomes of cervical cancer patients, providing important reference value for the prognostic assessment of cervical cancer patients.

Objective: To analyze the effects of health literacy on overweight and obesity among primary school students and their parents in terms of salt, oil and sugar reduction (referred to as the "three reductions"), so as to provide a theoretical basis for the development of obesity control measures. Methods: From March to April 2024, a total of 1 022 fourthgrade primary school students and 913 parents were surveyed in 24 classes in six counties in Shandong Province using multistage cluster random sampling, and physical measurements of primary school students were conducted. Pearsons correlation analysis and ordered multivariate Logistic regression were used to investigate the associations between health literacy of primary school students and their parents with overweight and obesity among children. Results: The detection rates of overweight and obesity primary school students in Shandong Province were 14.87% and 24.66%, respectively, with significant sex difference in obesity rate (29.46% for boys and 19.76% for girls) (χ2=12.93, P<0.01). In addition to students reducing oil scores, parental reducing salt,reducing oil,reducing sugar, comprehensive health literacy scores and students reducing salt,reducing sugar and comprehensive health literacy scores showed a negative relationship with students overweight and obesity (r=-0.10, -0.08, -0.07, -0.10, -0.04, -0.07, -0.03, P<0.05). The overweight and obesity rates among primary school students with high parental reducing salt,reducing oil,reducing sugar and composite health literacy scores were lower (OR=0.69, 0.69, 0.71, 0.63, P<0.05); and the overweight and obesity rate among students with high parental and low parental and high and low parental health literacy scores were lower (OR=0.68, 0.57, P<0.05). Conclusion Improving health literacy regarding "three reductions" for parents and children, especially parents, can effectively reduce the risk of childhood overweight and obesity.

This study aimed to localize the workplace readiness questionnaire (WRQ) and validate its applicability for assessing readiness for implementation of evidence-based practices (EBP) in primary care settings in China. The localization of the instrument will provide a practical instrument for assessing organizational readiness for change (ORC).

Objective: To evaluate the application of blood conservation measures in obstetric patients with different red blood cell transfusion volumes and to assess the impact of different transfusion volumes on postpartum outcomes. Methods: A retrospective investigation was conducted on 448 obstetric patients who received blood transfusions at the Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from January 2016 to December 2022. Patients were divided into four groups (1-2 units group, 3-4 units group, 5-6 units group, and >6 units group) based on the volumes of red blood cells (RBCs) transfused during and within 7 days after delivery. The maternal physiological indicators, pre- and postpartum laboratory test indicators, obstetric complications, application of blood conservation measures, use of blood products, and postpartum outcomes were reviewed. The clinical characteristics, application of blood conservation measures, and their impact on postpartum outcomes were compared among different transfusion groups. Results: There were statistically significant differences in the multivariate logistic analysis of history of previous cesarean section (OR=1.781), eclampsia/pre-eclampsia/(OR=1.972) and postpartum blood loss>1 000 mL（OR=1.699）(P<0.05) among different transfusion groups. In terms of blood conservation measures, the more RBCs transfused, the higher the rate of mothers receiving blood conservation measures such as balloon occlusion, arterial ligation, autologous blood transfusion with a cell saver, and hysterectomy. With the increase in the volume of RBCs transfusion, the demand for fresh frozen plasma（FFP）, cryoprecipitate, and platelet transfusions also increased. The hospitalization days for the four groups of parturients were 6.0 (4.0-9.0), 7.5 (5.0-14.8), 7.0 (4.5-13.0) and 11.0 (9.0-20.5), respectively (P<0.05) and the rates of ICU transfer were 2.0% (5/250), 9.4% (12/128),18.2% (6/33) and 51.4% (19/37), respectively (P<0.05). Both increased significantly with the increase in the volume of RBCs transfusion, and the differences between groups were statistically significant. Conclusion: Parturients who received higher volume of RBCs had multiple risks factors for bleeding before childbirth, had higher postpartum blood loss, and had a higher rate of application of various blood conservation measures. In addition, an increase in the volume of RBCs transfusion may have adverse effects on postpartum recovery.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.