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.

OBJECTIVE: To explore the relationship between serum complement levels at diagnosis and prognosis in patients with aggressive non-Hodgkin lymphoma(NHL). METHODS: The clinical data of 102 patients with aggressive non-Hodgkin lymphoma diagnosed in the First Hospital of Lanzhou University from February 2017 to March 2023 were selected to analyze the correlation between serum complement C3 and C4 levels and prognosis of patients with aggressive NHL at the time of initial diagnosis. The optimal cut-off point of C3 and C4 were obtained by calculating the Jorden index through the receiver operating characteristic（ROC） curve, and 102 patients were divided into low C3 group (C3< 1.07) and high C3 group (C3≥1.07), low C4 group (C4< 0.255) and high C4 group (C4≥0.255). The effects of serum C3 and C4 levels on the prognosis of these patients were analyzed. RESULTS: ROC curve analysis showed that the area under the curve (AUC) of C3 and C4 in predicting the prognosis of aggressive NHL patients was 0.634 (95%CI ：0.525-0.743；P =0.025) and 0.651 (95%CI ：0.541-0.761；P =0.012), respectively. The optimal cut-off points for C3 and C4 were 1.07 and 0.255, respectively. K-M survival analysis showed that groups with high C3 and C4 levels had shorter progression-free survival (PFS) (P =0.0079; P =0.0092) and overall survival (OS) (P =0.021; P =0.021). Multivariate Cox analysis showed that high level serum complement C3 (HR=2.37, 95%CI : 1.07-5.24, P =0.034) and age ≥60 years (HR=2.34, 95%CI : 1.11-4.95, P =0.025) were independent risk factors for PFS in patients with aggressive NHL. High level complement C3 (HR=2.37, 95%CI : 1.09-5.13, P =0.029) and age ≥60 years at diagnosis (HR=2.40, 95%CI : 1.13-5.13, P =0.024) were independent risk factors for OS in patients with aggressive NHL. CONCLUSION The level of serum complement C3 at diagnosis is one of the prognostic factors in patients with aggressive NHL.
Humans ; Lymphoma, Non-Hodgkin/blood* ; Prognosis ; Complement C3/metabolism* ; Complement C4/metabolism* ; ROC Curve ; Male ; Female ; Middle Aged ; Adult ; Aged

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

OBJECTIVE To evaluate the effectiveness and safety of Panlongqi tablets in the treatment of fractures based on real-world research. METHODS From September 2021 to September 2023， fracture patients admitted to 33 medical institutions were collected retrospectively. Patients who received conventional treatment were divided into control group （n＝3 750）， and patients who received combination of Panlongqi tablets on the basis of conventional treatment were divided into observation group （n＝ 3 706）. Self-reported indicators of patients were collected through telephone follow-up at 0， 4， 7 and 14 days after treatment. The improvement values of pain score， swelling score and health utility value， as well as effective rate and adverse drug reactions were compared between 2 groups. The propensity matching score （PSM） method was adopted to perform baseline matching on patient’s age， gender， fracture site， fracture severity， surgical type， type of hospital， and other indicators. Statistical analysis was performed on each therapeutic effect indicator. RESULTS After PSM， a total of 6 425 patients were included， of which 3 055 were in the observation group and 3 370 were in the control group. After 14 days of treatment， the observation group showed significant improvement in pain score （4.768 vs. 4.353）， swelling fangshiyuan2008@126.com grading score （2.979 vs. 2.391）， and life quality utility value （0.430 vs. 0.363）， as well as effective rate （87.20% vs.75.99%） compared to the control group （P＜0.05）. The results of subgroup analyses conducted by gender， age， hospital type， and fracture site were consistent with the aforementioned results. In terms of safety， the observation group had no serious adverse reactions， with a total of 29 cases of mild adverse reactions such as dizziness， stomach pain， and allergies， with an incidence rate of 0.78%. CONCLUSIONS Panlongqi tablets combined with conventional treatment are significantly better than conventional treatment in improving pain， swelling， quality of life， and effective rate in patients with fractures， and have good safety.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Objective:To evaluate the association between preoperative serum β 2-microglobulin (β 2MG) concentrations and postoperative delirium (POD) in elderly patients. Methods:The study selected patients who underwent knee or hip arthroplasty under spinal-epidural anesthesia on an elective basis at Qingdao Municipal Hospital from May 2021 to November 2022. The patients were divided into a POD group and a non-POD group based on the occurrence of POD. The study was conducted as part of the Perioperative Neurocognitive Impairment and Biomarkers Lifestyle Cohort, which was a nested case-control study. The study collected baseline data from two groups of patients and analyzed the differences between them. Logistic regression was used to identify the risk factors for POD. The stability of the regression model was tested using sensitivity analysis. The mediation model was used to examine whether cerebrospinal fluid (CSF) biomarkers mediated the relationship between β 2MG and POD. The receiver operating characteristic curve was drawn and the area under the curve was calculated to evaluate the accuracy of preoperative β 2MG concentrations and CSF biomarker concentration in predicting POD. Results:There were 57 cases in POD group and 449 cases in non-POD group. The results of logistic regression analysis showed that the increased β 2MG and CSF total tau protein (t-tau) concentrations were risk factors for POD, and the increased CSF β-amyloid 42 concentration was a protective factor for POD after adjustment for multiple confounders such as age, gender, education, Mini-Mental State Examination, history of hypertension and infusion volume ( P<0.05). The results of mediation analysis showed that the serum β 2MG′s effect on POD was partly mediated by t-tau (18.1%). The results of the receiver operating characteristic curve showed that the area under the curve of the β 2MG concentration combined with the CSF biomarker concentration was 0.742. Conclusions:Elevated preoperative serum β 2MG concentration is a risk factor for POD in elderly patients, and the relationship may be partly mediated by CSF t-tau.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease is associated with coronary artery lesion development.Purpose: This study aimed to explore the factors associated with IVIG-resistance and construct and validate an interpretable machine learning (ML) prediction model in clinical practice. Methods: Between December 2014 and November 2022, 602 patients were screened and risk factors for IVIG-resistance investigated. Five ML models are used to establish an optimal prediction model. The SHapley Additive exPlanations (SHAP) method was used to interpret the ML model. Results: Na+, hemoglobin (Hb), C-reactive protein (CRP), and globulin were independent risk factors for IVIG-resistance. A nonlinear relationship was identified between globulin level and IVIG-resistance. The XGBoost model exhibited excellent performance, with an area under the receiver operating characteristic curve of 0.821, accuracy of 0.748, sensitivity of 0.889, and specificity of 0.683 in the testing set. The XGBoost model was interpreted globally and locally using the SHAP method. Conclusion Na+, Hb, CRP, and globulin levels were independently associated with IVIG-resistance. Our findings demonstrate that ML models can reliably predict IVIG-resistance. Moreover, use of the SHAP method to interpret the established XGBoost model's findings would provide evidence of IVIG-resistance and guide the individualized treatment of Kawasaki disease.