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.

Objective:To systematically evaluate the actual experience and needs of family caregivers for cardiac arrest patients.Methods:Qualitative research on the real experience and needs of family caregivers in patients with cardiac arrest was electronically searched in databases such as PubMed, CINAHL, and Embase. Two researchers independently screened the literature, evaluated its quality, and integrated the research results. The search period was from database establishment to May 1, 2023.Results:A total of 15 articles were included, and 51 research results were extracted. The similar results were summarized into nine categories and integrated into three results, including sudden changes in life and substantial impacts; challenges in controlling complex emotions, and multiple psychological experiences; multidimensional needs.Conclusions:Family caregivers' actual experiences and requirements for cardiac arrest patients are diverse. Medical and nursing staff need to pay attention to the emotional experiences of family caregivers and meet their multidimensional needs.

Objective:To explore the caregiving feelings and needs of caregivers of children with β-thalassemia major.Methods:A semi-structured interview was conducted with 14 caregivers of children with β-thalassemia major who were treated at the Affiliated Hospital of Youjiang Medical University for Nationalities from December 2022 to March 2023, and the data were analyzed using the Colaizzi 7-step analysis method.Results:Caregivers of children with β-thalassemia major felt a greater burden of care, including declining physical and mental health, disruption of daily life rhythms and heavy financial burden. And their caregiving needs included psychological and emotional support, guidance on the physical and mental health of children, assurance of a stable blood supply and medical and social support.Conclusions:Caregivers of children with β-thalassemia major have a heavy burden of care and face various nursing difficulties in the daily care of children. Medical staff should actively take measures to meet their care needs and improve their care quality and quality of life.

Objective To systematically evaluate the rumination in stroke patients and identify the influencing factors.Methods A mixed-methods systematic review was carried out by searching databases,such as CNKI,WanFang Data,VIP,CBM,PubMed,Web of Science,the Cochrane Library,Embase and Scopus databases,from the inception to 27th October,2023,for literature on the influencing factors of rumination in stroke patients.The researchers evaluated quality of the literature according to the mixed methods appraisal tool developed by McGill University of Canada.Then the data were collected,analysed and integrated using the convergent integration method proposed by the JBI Evidence-Based Health Care Research Centre of Australia.Results A total of 22 studies were included with an involvement of 4 949 patients.Then a total of 45 research topics were extracted and grouped into 8 categories.The influence factors of rumination were integrated,including individual factors,external support and coping strategies.Conclusions Stroke patients have different levels of rumination.Individual factors may affect rumination in patients.Harmonious interpersonal relationships and positive thinking with coping strategies can promote deliberate rumination.However,the effects of age,place of residence and household income on rumination in stroke patients are required to be further explored.

Objective The evaluation of lymph node properties before lung cancer surgery has a great impact with the choice of surgical methods.Although there are various examination methods,many methods have invasive or accuracy problems.In order to improve the accuracy of diagnosis,we mainly discuss the value of wide-body spectral CT in the differential diagnosis of mediastinal metastatic lymph nodes,non-metastatic lymph nodes in lung cancer patients and reactive hyperplastic lymph nodes.Methods The clinical and imaging data of 64 patients with lung cancer and 28 patients with pulmonary inflammatory lesions were retrospectively analyzed.All patients underwent plain scan and enhanced dual-phase spectral CT scan.The size,density,three-phase IC,NIC,and λHU of lymph nodes in metastatic,non-metastatic and inflammatory reactive hyperplasia groups were measured on 70 keV single-energy images and iodine-based images,respectively.The single-factor variance and Kruskal-Wallis H rank sum test were used to analyze and compare the differences.Results The short diameter of metastatic lymph nodes was larger than that of non-metastatic lymph nodes and reactive hyperplastic lymph nodes(P<0.001).The plain scan density of reactive hyperplastic lymph nodes was higher than that of metastatic lymph nodes(P<0.001),but there was no significant difference between non-metastatic lymph nodes(P=0.325).The CT values of reactive hyperplastic lymph nodes in arterial phase and venous phase were higher than those of metastatic and non-metastatic lymph nodes(P<0.05).Except for NIC in arterial phase,IC,NIC and λHU in plain scan,IC and λHU in arterial phase,IC,NIC and λHU in venous phase of reactive hyperplastic lymph nodes and metastatic lymph nodes were statistically significant(all P<0.05).There was no significant difference in IC,NIC and λHU between reactive hyperplastic lymph nodes and non-metastatic lymph nodes in plain scan,arterial phase and venous phase(all P>0.05).Conclusion The quantitative and spectral curve slope of iodine in mediastinal metastatic lymph nodes of lung cancer were basically lower than those in reactive hyperplastic lymph nodes.The quantitative parameters of spectral CT had certain diagnostic efficacy in differentiating metastatic lymph nodes and reactive hyperplastic lymph nodes,while the spectral parameters of non-metastatic lymph nodes and reactive hyperplastic lymph nodes were not statistically significant.

Objective To develop deep learning-based auxiliary diagnostic models for diverse pulmonary diffuse cystic diseases,and subsequently evaluate their classification performance to identify the optimal model for clinical diagnosis.Methods A total of 288 patients diagnosed with idiopathic pulmonary fibrosis(IPF),pulmonary lymphangioleiomyomatosis(PLAM),and pulmonary Langerhans cell histiocytosis(PLCH)were prospectively enrolled from the First Affiliated Hospital of Guangzhou Medical University between January 2010 and October 2022,comprising 76 cases of IPF,179 cases of PLAM,and 33 cases of PLCH.A total of 877 CT cases were collected,comprising 232 cases of IPF,557 cases of PLAM,and 88 cases of pulmonary PLCH.Based on the cutoff date of December 31,2019,the CT scans were divided into two datasets:dataset A consisted of 500 CT scans including 185 IPF cases,265 PLAM cases,and 50 PLCH cases;while dataset B comprised 377 CT scans with a distribution of 47 IPFcases,292 PLAMcases,and 38 PLCH cases.The Dataset A was randomly partitioned into training set,validation set,and test set in a ratio of 7∶1∶2.Subsequently,six distinct deep learning neural networks were employed for training after preprocessing and data augmentation.Receiver operating characteristic curves were generated to assess the model performance using metrics such as area under the curve(AUC),accuracy,sensitivity,specificity,and F1 score in order to identify the optimal model.Furthermore,a test set B comprising 30 randomly selected cases from dataset B for each disease type was utilized to evaluate the trained optimal model by employing the same aforementioned metrics.Results In test A,six well-established diagnostic models demonstrated superior classification performance for IPF and LAM,with an AUC greater than 0.9.For LCH,EfficientNet exhibited low classification efficiency with an AUC between 0.6 and 0.7,while Vgg11 showed an AUC between 0.8 and 0.9;the other four models displayed excellent classification efficiency with an AUC greater than 0.9.Except for Inception V3,the remaining five diagnostic models performed poorly in identifying and classifying LCH lesions.Considering multiple indicators,the InceptionV3 model showcased optimal comprehensive performance among the six models,achieving high evaluation parameters such as overall accuracy(94.90%),precision(93.49%),recall(90.84%),and specificity(96.91%).TestB was conducted using the trained InceptionV3 model resulting in an accuracy of 81%,precision of 82%,recall of 81%,and specificity of 90%.Conclusions Six recognition and classification models,developed using deep learning technology in conjunction with pulmonary CT images,demonstrate effective discrimination between LAM,LCH,and IPF.Notably,the model constructed utilizing the InceptionV3 neural network exhibits superior efficiency in accurately recognizing and classifying IPF and LAM.

Objective To systematically evaluate the risk factors of contrast medium extravasation(CME).Methods The rele-vant literature on the risk factors of CME were searched from CNKI,WanFang,VIP,CBM,Cochrane Library,ProQuest,PubMed,Ovid,Web of Science,and Embase via computer.Meta-analysis was performed via RevMan5.4.Results A total of 10 articles were included,involving 17 risk factors.The results of the Meta-analysis showed that contrast medium(CM)concentration[odds ratio(OR)=2.02],age(OR=2.22),combined tumor(OR=2.87),puncture site(OR=2.73),nursing experience(OR=2.78),osmotic pressure(OR=3.29),combined circulatory disease(OR=4.56)were the statistically significant factors.Conclusion The independ-ent risk factors of CME include CM concentration,age,combined tumor,puncture site,nursing experience,osmotic pressure,and combined circulatory disease.

Objective:To analyze the genus, drug resistance/virulence and phylogenetic characteristics of Brucella strains isolated from brucellosis surveillance sentinels in Henan Province from 2013 to 2022, and provide baseline data for the surveillance, early warning and outbreak tracing of brucellosis. Methods:Blood samples were collected from patients with Brucella infection for strain isolation, culture and species identification, drug susceptibility test, whole genome sequencing, splicing and assembly, functional/virulence/resistance gene prediction analysis and phylogenetic tree drawing based on single nucleotide polymorphism (SNP). Results:In 36 brucellosis patients, the majority were men (86.11%, 31/36), young adults aged 18-50 (88.89%, 32/36) and farmers/herdsmen (72.22%, 26/36). A total of 36 strains of Brucella melitensis were isolated, and average 1 305 functional proteins of 21 categories were predicted by strain genome; all the strains carried four main virulence factors (pmm, VirB group, BtpA/BtpB, BvrS/BvrR). The drug sensitivity rate was 100.00% to six types of antibiotics including levofloxacin, rifampicin, doxycycline, streptomycin, tetracycline and gentamicin, they showed different resistances to three antibiotics including compound trimethoprim-sulfamethoxazole, ciprofloxacin and ampicillin. The strains carried four types of resistance genes and two clusters of resistance genes, with four combinations of genotypes, the resistance mechanisms included antibiotic degradation/modification enzymes, resistant nodular cell differentiation (RND) efflux pumps, 16S/23S ribosomal rRNA binding site mutations, etc. The number of SNP differed in the genomes of 36 Brucellamelitensis strains ranged from 0 to 454 and phylogenetic tree was divided into three major branches, with relative branch distances between 0.000 0 and 0.498 6 for each strain. Conclusions:Human Brucellamelitensis strains isolated from surveillance sentinels in Henan from 2013 to 2022 carried multiple virulence and antibiotic resistance genes and had different drug resistance phenotypes. Single nucleotide polymorphism analysis and phylogenetic tree analysis showed significant differences in phylogenetic relationships among different strains.