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 construction of a paperless medical record system is a new stage in the development of intelligent medical record management in hospitals.The implementation of paperless medical records has significant practical significance in impro-ving medical record management,enhancing the level of medical services,and reducing healthcare operational costs.To explore the key technological issues of paperless medical record system for inpatient care,this article first provides an overview of the po-sitioning and business process of paperless medical record system in the hospital's information system.Secondly,based on the actual application of paperless medical records in our hospital,the core difficulties and application processes of key technological aspects such as trusted electronic signatures and comprehensive verification of medical record data from all dimensions are dis-cussed.Next,the integrated application effects of paperless medical records are analyzed.Finally,the key research directions and future development models of paperless medical records are discussed.

Background: SM-like (LSM) genes a family of RNA-binding proteins, are involved in mRNA regulation and can function as oncogenes by altering mRNA stability. However, their roles in B-cell progression and tumorigenesis remain poorly understood. Methods: We analyzed gene expression profiles and overall survival data of 123 patients with mantle cell lymphoma (MCL). The LSM index was developed to assess its potential as a prognostic marker of MCL survival. Results: Five of the eight LSM genes were identified as potential prognostic markers for survival in MCL, with particular emphasis on the LSM.index. The expression levels of these LSM genes demonstrated their potential utility as classifiers of MCL. The LSM.index-high group exhibited both poorer survival rates and lower RNA levels than did the overall transcript profile. Notably, LSM1 and LSM8 were overexpressed in the LSM.index-high group, with LSM1 showing 2.5-fold increase (p < 0.001) and LSM8 depicting 1.8-fold increase (p < 0.01) than those in the LSM.index-low group.Furthermore, elevated LSM gene expression was associated with increased cell division and RNA splicing pathway activity. Conclusions The LSM.index demonstrates potential as a prognostic marker for survival in patients with MCL. Elevated expression of LSM genes, particularly LSM1 and LSM8, may be linked to poor survival outcomes through their involvement in cell division and RNA splicing pathways. These findings suggest that LSM genes may contribute to the aggressive behavior of MCL and represent potential targets for therapeutic interventions.

Background: SM-like (LSM) genes a family of RNA-binding proteins, are involved in mRNA regulation and can function as oncogenes by altering mRNA stability. However, their roles in B-cell progression and tumorigenesis remain poorly understood. Methods: We analyzed gene expression profiles and overall survival data of 123 patients with mantle cell lymphoma (MCL). The LSM index was developed to assess its potential as a prognostic marker of MCL survival. Results: Five of the eight LSM genes were identified as potential prognostic markers for survival in MCL, with particular emphasis on the LSM.index. The expression levels of these LSM genes demonstrated their potential utility as classifiers of MCL. The LSM.index-high group exhibited both poorer survival rates and lower RNA levels than did the overall transcript profile. Notably, LSM1 and LSM8 were overexpressed in the LSM.index-high group, with LSM1 showing 2.5-fold increase (p < 0.001) and LSM8 depicting 1.8-fold increase (p < 0.01) than those in the LSM.index-low group.Furthermore, elevated LSM gene expression was associated with increased cell division and RNA splicing pathway activity. Conclusions The LSM.index demonstrates potential as a prognostic marker for survival in patients with MCL. Elevated expression of LSM genes, particularly LSM1 and LSM8, may be linked to poor survival outcomes through their involvement in cell division and RNA splicing pathways. These findings suggest that LSM genes may contribute to the aggressive behavior of MCL and represent potential targets for therapeutic interventions.

ObjectiveTo systematically analyze international disability data policies and standards, as well as the application of disability data in policymaking, service optimization and inclusive social development, and to clarify the importance of international disability data policies, standard systems and disability data application for the development of disability-related services. MethodsThrough the analysis of policy content and research on the data standard system, this study explored the disability data policy framework, standard system and technical path of data interoperability and integration of international organizations including the United Nations (United Nations Statistics Division and United Nations Children's Fund), World Health Orgnization, United Nations Educational Scientific and Cultural Organization, and International Labour Organization. ResultsInternational organizations established disability data policy frameworks based on their respective mandates, involving data and service development, data standards, data governance, and data application. The international community established a disability data standard system for disability data collection, coding, exchange, interoperability, statistical analysis, data fusion and application. Building a standardized disability data standard system based on the framework of international health classification standards such as International Classification of Functioning, Disability and Health, and International Classification of Diseases, Eleventh Revision would ensure the consistency of cross-national disability data policies, and the interoperability and comparability of disability data, promoting the development of data-driven disability-related services, accurately identifying the service needs of people with disabilities, and optimizing service provision, thereby improving the quality of life and social participation of people with disabilities. ConclusionThe construction and implementation of international disability data policies and data standards have promoted the standardization and interoperability of disability data. With the application of big data, artificial intelligence and blockchain technologies in disability data, international cooperation and cross-industry data fusion in the field of disability data have been promoted, further promoting the development of data-driven disability services, ensuring equal opportunities for people with disabilities to enjoy service resources, and improving the coverage and quality of disability services.

Persistent Müllerian duct syndrome(PMDS) is a rare disorder that arises from a lack of active anti-Müllerian hormone(AMH) or type Ⅱ AMH receptor(AMHR2) deficiency in males with a normal 46, XY chromosome karyotype.It presents that the external genitalia appears normally while the Müllerian duct structure(uterus, fallopian tubes, upper vagina) persists in the body.Common pathogenic factors are mutations in the AMH and AMHR2 genes, inherited in an autosomal recessive manner.This study reported two families with PMDS.The first patient was diagnosed with PMDS due to cryptorchidism in May 2019.Gene sequencing analysis revealed a new missense mutation(c.579G>T; p.W193C) and a splicing mutation(c.622-3C>A; splicing) in the AMHR2 gene.His father had the missense mutation(c.579G>T; p.W193C), and his mother had the splicing mutation(c.622-3C>A; splicing).The second patient was diagnosed with PMDS due to bilateral cryptorchidism, transverse testis ectopia in the right testicle in March 2023.Undegraded Müllerian tube derivatives were found between the two testicles, and serum AMH levels were very high(565.00 μg/L).Gene sequencing analysis reported that the AMHR2 gene had a new deletion mutation(c.835_837del; p.Leu279del).Both his father and mother had a deletion mutation(c.835_837del; p.Leu279del).This study reports two new AMHR2 gene mutations that expand the mutation sites of this rare disease.It is recommended to consider PMDS in the differential diagnosis of cryptorchidism, undergo surgery as early as possible, and treat Müllerian duct derivatives based on individual anatomical characteristics.

Background: SM-like (LSM) genes a family of RNA-binding proteins, are involved in mRNA regulation and can function as oncogenes by altering mRNA stability. However, their roles in B-cell progression and tumorigenesis remain poorly understood. Methods: We analyzed gene expression profiles and overall survival data of 123 patients with mantle cell lymphoma (MCL). The LSM index was developed to assess its potential as a prognostic marker of MCL survival. Results: Five of the eight LSM genes were identified as potential prognostic markers for survival in MCL, with particular emphasis on the LSM.index. The expression levels of these LSM genes demonstrated their potential utility as classifiers of MCL. The LSM.index-high group exhibited both poorer survival rates and lower RNA levels than did the overall transcript profile. Notably, LSM1 and LSM8 were overexpressed in the LSM.index-high group, with LSM1 showing 2.5-fold increase (p < 0.001) and LSM8 depicting 1.8-fold increase (p < 0.01) than those in the LSM.index-low group.Furthermore, elevated LSM gene expression was associated with increased cell division and RNA splicing pathway activity. Conclusions The LSM.index demonstrates potential as a prognostic marker for survival in patients with MCL. Elevated expression of LSM genes, particularly LSM1 and LSM8, may be linked to poor survival outcomes through their involvement in cell division and RNA splicing pathways. These findings suggest that LSM genes may contribute to the aggressive behavior of MCL and represent potential targets for therapeutic interventions.

Objective:To explore the correlation between medical narrative ability, empathy ability and general self-efficacy of clinical nurses.Methods:A total of 106 clinical nurses from Jiaozuo People's Hospital were selected as the research object by convenient sampling. The Narrative Competence Scale, Empathy Ability Scale and General Self-efficacy Scale (GSES) were used to investigate and analyze the correlation of clinical nurses' medical narrative ability, empathy ability and general self-efficacy.Results:Among 106 clinical nurses, the scores of the Narrative Competence Scale, Empathy Ability Scale and GSES were (149.38±21.03) , (108.89±16.32) , and (24.31±5.17) respectively. The medical narrative ability of clinical nurses was positively correlated with empathy ability and general self-efficacy ( r=0.627, 0.569; P<0.001) , and empathy ability was positively correlated with general self-efficacy ( r=0.518, P<0.001) . Conclusions:The medical narrative ability, empathy ability and general self-efficacy of clinical nurses are positively correlated, suggesting that the training and management of clinical nurses should be strengthened to promote the improvement of their various abilities.

Objective:To investigate the predictive model construction of anastomotic thickening character after radical surgery of esophageal cancer based on computed tomogralphy(CT) radiomics and its application value.Methods:The retrospective cohort study was conducted. The clinicopathological data of 202 patients with esophageal squamous cell carcinoma (ESCC) who were admitted to The First Affiliated Hospital of Zhengzhou University from January 2013 to June 2021 were collected. There were 147 males and 55 females, aged (63±8) years. Based on random number table, 202 patients were assigned into training dataset and validation dataset at a ratio of 7:3, including 141 cases and 61 cases respectively. Patients underwent radical resection of ESCC and enhanced CT examination. Observation indicators: (1) influencing factor analysis of malignant anas-tomotic thickening; (2) construction and evaluation of predictive model; (3) performance comparison of 3 predictive models. The normality of continuous variables was tested by Kolmogorov-Smirnov method. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was analyzed using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was analyzed using the Mann-Whintney U test. Count data were represented as absolute numbers, and comparison between groups was analyzed using the chi-square test or Fisher's exact probability. The consistency between subjective CT features by two doctors and measured CT numeric variables was analyzed by Kappa test and intraclass correlation coefficient (ICC), with Kappa >0.6 and ICC >0.6 as good consistency. Univariate analysis was conducted by corresponding statistic methods. Multivariate analysis was conducted by Logistics stepwise regression model. The receiver operating characteristic (ROC) curve was drawn, and area under curve (AUC), Delong test, decision curve were used to evaluate the diagnostic efficiency and clinical applicability of model. Results:(1) Influencing factor analysis of malignant anastomotic thickening. Of the 202 ESCC patients, 97 cases had malignant anastomotic thickening and 105 cases had inflammatory anastomotic thickening. The consistency between subjective CT features by two doctors and measured CT numeric variables showed Kappa and ICC values >0.6. Results of multivariate analysis showed that the maximum thickness of anastomosis and CT enhancement pattern were independent influencing factors for malignant anastomotic thickening[ hazard ratio=1.46, 3.09, 95% confidence interval ( CI) as 1.26-1.71,1.18-8.12, P<0.05]. (2) Construction and evaluation of predictive model. ① Clinical predictive model. The maximum thickness of anasto-mosis and CT enhancement pattern were used to construct a clinical predictive model. ROC curve of the clinical predictive model showed an AUC, accuracy, sensitivity, specificity as 0.86 (95% CI as 0.80-0.92),0.77, 0.77, 0.80 for the training dataset, and 0.78 (95% CI as 0.65-0.89), 0.77, 0.77, 0.80 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=1.22, P>0.05). ② Radiomics predictive model. A total of 854 radiomics features were extracted and 2 radiomics features (wavelet-LL_first order_ Maximum and original_shape_VoxelVolume) were finally screened out to construct a radiomics predictive model. ROC curve of the radiomics predictive model showed an AUC, accuracy, sensitivity, specificity as 0.87 (95% CI as 0.81-0.93), 0.80, 0.75, 0.86 for the training dataset, and 0.73 (95% CI as 0.63-0.83), 0.80, 0.76, 0.94 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=-0.25, P>0.05). ③ Combined predictive model. Results of multivariate analysis and radiomics features were used to construct a combined predictive model. ROC curve of the combined predictive model showed an AUC, accuracy, sensitivity, specificity as 0.93 (95% CI as 0.89-0.97),0.84, 0.90, 0.84 for the training dataset, and 0.79 (95% CI as 0.70-0.88), 0.89, 0.86, 0.91 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=0.22, P>0.05). (3) Performance comparison of 3 predictive models. Results of Hosmer-Lemeshow goodness-of-fit test showed that the clinical predictive model, radiomics predictive model and combined predictive model had a good fitting degree ( χ2=4.88, 7.95, 4.85, P>0.05). Delong test showed a significant difference in AUC between the combined predictive model and clinical predictive model, also between the combined predictive model and radiomics predictive model ( Z=2.88, 2.51, P<0.05 ). There was no significant difference in AUC between the clinical predictive model and radiomics predictive model ( Z=-0.32, P>0.05). The calibration curve showed a good predictive performance in the combined predictive model. The decision curve showed a higher distinguishing performance for anastomotic thickening character in the combined predictive model than in the clinical predictive model or radiomics predictive model. Conclusions:The maximum thickness of anastomosis and CT enhancement pattern are independent influencing factors for malignant anastomotic thickening. Radiomics predictive model can distinguish the benign from malignant thickening of anastomosis. Combined predictive model has the best diagnostic efficacy.

Objective:To observe the effect of interleukin-8 (IL-8) on the adhesion and migration of retinal vascular endothelial cells (RCEC).Methods:A cell experiment. Human RCEC (hRCEC) was divided into normal control group (N group), advanced glycation end product (AGE) treatment group (AGE group), and AGE-induced combined IL-8 antagonist SB225002 treatment group (AGE+SB group). The effect of AGE on IL-8 expression in hRCEC was observed by Western blot. The effect of SB225002 on hRCEC migration was observed by cell scratch assay. The effects of SB225002 on leukocyte adhesion and reactive oxygen species (ROS) on hRCEC were detected by flow cytometry. Student- t test was performed between the two groups. Oneway analysis of variance was performed among the three groups. Results:Compared with group N, the expression level of IL-8 in cells of AGE group was significantly increased, with statistical significance ( t=25.661, P<0.001). Compared with N group and AGE+SB group, cell mobility in AGE group was significantly increased ( F=29.776), leukocyte adhesion number was significantly increased ( F=38.159, 38.556), ROS expression level was significantly increased ( F=22.336), and the differences were statistically significant ( P<0.05). Conclusion:IL-8 antagonist SB225002 may down-regulate hRCEC adhesion and migration by inhibiting ROS expression.