Objective​ To evaluate the clinical characteristics and influencing factors of fatigue in patients with rheumatoid arthritis （RA）， with the aim of providing guidance for clinical treatment. Methods​ Based on the multicenter real-world cohort of the China Registry of Traditional Chinese Medicine for Rheumatism （CERTAIN） platform， patients with RA enrolled from 2019 to 2025 were included. Demographic data， disease assessment indicators， laboratory indices， and traditional Chinese medicine （TCM） syndrome patterns were collected to analyze the TCM syndromes and clinical characteristics of RA patients with fatigue. Spearman correlation analysis and logistic regression analysis were used to identify factors associated with fatigue in RA. Results​ A total of 3 021 patients with RA were included， among whom 2 007 （66.43%） had fatigue. Compared with the non-fatigue group， the fatigue group was older and had a longer disease duration， with significantly higher scores for the 28-joint Disease Activity Score （DAS28）， swollen joint count （SJC）， tender joint count （TJC）， Health Assessment Questionnaire （HAQ）， pain visual analog scale （VAS）， and patient global assessment （PGA） （P<0.01）. Among TCM syndromes， fatigue was more common in patients with dampness-heat obstruction， cold-dampness obstruction， and liver-kidney deficiency syndromes （P<0.05）. Multivariate analysis revealed that morning stiffness duration exhibited a stepwise association with fatigue， while poor appetite， insomnia with frequent dreaming， restlessness， high HAQ scores， and high pain VAS scores were identified as risk factors. ConclusionFatigue is a prominent symptom in patients with RA and is more common among those with dampness-heat obstruction， cold-dampness obstruction， and liver-kidney deficiency syndromes. It is closely associated with disease activity， pain， functional limitation， sleep， and emotional status.

ObjectiveTo evaluate the effects of Qingre Huoxue prescription combined with methotrexate （MTX） and folic acid （FA） on homocysteine （Hcy） levels and disease activity in patients with rheumatoid arthritis （RA） complicated by hyperhomocysteinemia （HHcy）. MethodsOn the basis of a multicenter real-world cohort from the China Registry of Traditional Chinese Medicine for Rheumatism （CERTAIN） platform，408 patients with RA complicated by HHcy were selected and included in this study. Treatment with Qingre Huoxue prescription was used as the exposure factor. According to whether Qingre Huoxue prescription was combined with MTX and FA，patients were assigned into an exposure group of 281 cases and a control group of 127 cases. Follow-ups were conducted every three months，with the primary outcome indicator being the achievement rate of target Hcy level. A generalized estimating equation model was adopted to analyze the dynamic changes in Hcy level under different medication regimens. Kaplan-Meier analysis was performed to evaluate the cumulative achievement rate of target Hcy level in the two groups，and Cox regression analysis was conducted to explore the predictive factors affecting the achievement rate of target Hcy level. Changes in erythrocyte sedimentation rate （ESR），C-reactive protein （CRP），28-joint disease activity score （DAS 28），and Health Assessment Questionnaire-Disability Index （HAQ-DI） scores before and after the first combined treatment with Qingre Huoxue prescription were compared between the two groups. ResultsThe Hcy level in the exposure group showed a gradual decreasing trend over time，while the decrease in Hcy level was not significant in the control group. At the 12-month follow-up，the achievement rate of target Hcy level in the exposure group （124/281，44.13%） was higher than that in the control group （23/127，18.11%，P<0.01）. Multivariable Cox regression analysis showed that treatment with Qingre Huoxue prescription ［hazard ratio（HR）=3.013，95% confidence interval （CI） 2.188-4.149， P<0.001］， absence of comorbidities （HR=2.035， 95%CI 1.352-3.061， P<0.001）， and baseline Hcy <15 μmol·L^-1 （HR=1.810， 95%CI 1.390-2.357， P<0.001） were significantly associated with an increased likelihood of achieving target Hcy levels within 6 months. In contrast， higher PGA scores were associated with a reduced likelihood of achieving target Hcy levels （HR=0.991， 95% CI 0.986-0.997， P=0.003）. After treatment，the exposure group demonstrated reductions in ESR，CRP，and DAS 28 scores （P<0.05） and had lower ESR，CRP and DAS 28 scores than the control group （P<0.05）. ConclusionEven after taking FA supplements，some RA patients undergoing MTX treatment still have high Hcy levels. When being used in conjunction with MTX and FA，Qingre Huoxue prescription can effectively lower the Hcy level and disease activity in RA patients with HHcy，outperforming Western treatment alone.

ObjectiveTo evaluate the effects of Qingre Huoxue prescription combined with methotrexate （MTX） and folic acid （FA） on homocysteine （Hcy） levels and disease activity in patients with rheumatoid arthritis （RA） complicated by hyperhomocysteinemia （HHcy）. MethodsOn the basis of a multicenter real-world cohort from the China Registry of Traditional Chinese Medicine for Rheumatism （CERTAIN） platform，408 patients with RA complicated by HHcy were selected and included in this study. Treatment with Qingre Huoxue prescription was used as the exposure factor. According to whether Qingre Huoxue prescription was combined with MTX and FA，patients were assigned into an exposure group of 281 cases and a control group of 127 cases. Follow-ups were conducted every three months，with the primary outcome indicator being the achievement rate of target Hcy level. A generalized estimating equation model was adopted to analyze the dynamic changes in Hcy level under different medication regimens. Kaplan-Meier analysis was performed to evaluate the cumulative achievement rate of target Hcy level in the two groups，and Cox regression analysis was conducted to explore the predictive factors affecting the achievement rate of target Hcy level. Changes in erythrocyte sedimentation rate （ESR），C-reactive protein （CRP），28-joint disease activity score （DAS 28），and Health Assessment Questionnaire-Disability Index （HAQ-DI） scores before and after the first combined treatment with Qingre Huoxue prescription were compared between the two groups. ResultsThe Hcy level in the exposure group showed a gradual decreasing trend over time，while the decrease in Hcy level was not significant in the control group. At the 12-month follow-up，the achievement rate of target Hcy level in the exposure group （124/281，44.13%） was higher than that in the control group （23/127，18.11%，P<0.01）. Multivariable Cox regression analysis showed that treatment with Qingre Huoxue prescription ［hazard ratio（HR）=3.013，95% confidence interval （CI） 2.188-4.149， P<0.001］， absence of comorbidities （HR=2.035， 95%CI 1.352-3.061， P<0.001）， and baseline Hcy <15 μmol·L^-1 （HR=1.810， 95%CI 1.390-2.357， P<0.001） were significantly associated with an increased likelihood of achieving target Hcy levels within 6 months. In contrast， higher PGA scores were associated with a reduced likelihood of achieving target Hcy levels （HR=0.991， 95% CI 0.986-0.997， P=0.003）. After treatment，the exposure group demonstrated reductions in ESR，CRP，and DAS 28 scores （P<0.05） and had lower ESR，CRP and DAS 28 scores than the control group （P<0.05）. ConclusionEven after taking FA supplements，some RA patients undergoing MTX treatment still have high Hcy levels. When being used in conjunction with MTX and FA，Qingre Huoxue prescription can effectively lower the Hcy level and disease activity in RA patients with HHcy，outperforming Western treatment alone.

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.

Objective: To establish a method for determining the molecular weight and molecular weight distribution of Poly(Lactide-co-Glycolide Acid) (PLGA) using Size Exclusion Chromatography-Refractive Index-Multiangle Laser Light Scattering (SEC-RI-MALLS) and Size Exclusion Chromatography-Refractive Index (SEC-RID), and to compare the results obtained from these two methods.
Methods: For SEC-RI-MALLS, tetrahydrofuran was used as the mobile phase, Shodex GPC KF-803L was employed as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, and an injection volume of 100 μL. For SEC-RID, tetrahydrofuran was also used as the mobile phase, Agilent PLgel 5 μm MIXD-D was used as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, differential detector temperature at 35 ℃, and an injection volume of 20 μL. The molecular weight and molecular weight distribution were calculated using Agilent’s GPC software. The newly established methods were validated methodologically, and the molecular weight and molecular weight distribution of 13 batches of samples were determined.
Results: The precision, accuracy, stability, and repeatability tests for SEC-RI-MALLS showed RSD values of 1.35%, 1.58%, 1.53%, and 1.26%, respectively. The SEC-RID method exhibited good linearity (r=0.999 9), with RSD values for precision, accuracy, stability, and repeatability tests (n=6) of 2.05%, 1.62%, 1.30%, and 2.97%, respectively. The results obtained from SEC-RI-MALLS were lower than those from SEC-RID, and the molecular weight distribution coefficient was smaller, but the results from the paired T-test performed with the value measured by SEC-RID method and the value measured by SEC-RI-MALLS method multiplied a conversion coefficient of 1.5 showed no significant difference between the two methods.
Conclusion: Both methods are stable and reliable, and can be used for the determination of PLGA molecular weight and molecular weight distribution based on the specific situations.

[Objective] To explore the diagnosis and treatment experience of tension hydrocele. [Methods] The clinical data of 2 patients with tension hydrocele treated in our hospital were retrospectively analyzed.Relevant literature was retrieved to analyze the clinical characteristics of this disease. [Results] Case 1 was diagnosed due to swelling and pain of the left scrotum after trauma for more than one month, which worsened for one day.Physical examination showed high tension in the left scrotum and positive light transmission test.Ultrasound examination revealed that the blood flow signal in the left testis disappeared.Emergency left scrotal exploration and hydrocelectomy were performed.There was no sign of testis torsion during the operation.Case 2 was diagnosed mainly due to hydrocele of the right testis for 1 year, which worsened for 1 week and complicated with testis distension and pain.Physical examination showed high tension in the right scrotum and positive light transmission test.Ultrasound examination revealed that the blood flow signal in the right testis decreased.After 40ml of fluid was extracted under ultrasound monitoring, the blood flow signal in the right testis recovered.Hydrocelectomy was performed the next day.During the follow-up of 8 months, there was no recurrence of hydrocele.A search of domestic and foreign literature showed that there were no reports in domestic literature, while a total of 11 cases were reported in foreign literature. [Conclusion] Tension hydrocele of the testis is a rare emergency of the scrotum.Surgery or decompression should be performed as soon as possible to restore testicular blood supply, and hydrocelectomy should be performed simultaneously or in stages to prevent recurrence.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.

Objective:To investigate the iodine nutrition status of children aged 8 - 10 and pregnant women in Xining City, Qinghai Province.Methods:From 2019 to 2021, a stratified cluster sampling method was used to divide 7 counties (districts) under the jurisdiction of Xining City, Qinghai Province into 5 sampling areas according to east, west, south, north, and center each year. One township (town, street) was selected from each area. Forty non boarding students aged 8 to 10 from each primary school (half male and half female, age balanced) and 20 pregnant women from each township (town, street) location were selected to collect edible salt samples at home and a random urine sample to measure salt iodine and urinary iodine level. B-ultrasound was used to measure thyroid volume in children and the goiter rate was calculated.Results:A total of 6 534 samples of household edible salt were collected from children and pregnant women, with an average salt iodine concentration of 25.58 mg/kg. The coverage rate of iodized salt was 97.50% (6 371/6 534), and the qualified iodized salt consumption rate was 89.46% (5 845/6 534). A total of 4 362 urine samples were collected from children, with a median urinary iodine level of 183.10 μg/L. The difference between different years was statistically significant ( H = 20.27, P < 0.001). A total of 2 169 urine samples were collected from pregnant women, with a median urinary iodine level of 168.90 μg/L. The difference between different years was statistically significant ( H = 107.09, P < 0.001). A total of 3 336 cases of thyroid gland examination were conducted in children, including 33 cases of thyroid enlargement, with a goiter rate of 0.99%. There was a statistically significant difference between different years (χ 2 = 15.00, P < 0.001). Conclusion:From 2019 to 2021, children aged 8 to 10 and pregnant women in Xining City are at an appropriate level of iodine, and the achievements in prevention and treatment of iodine deficiency disorders still need to be continuously consolidated.

AIM To establish the near-infrared spectroscopy quantitative models for moisture,23-acetylalismol B and 23-acetylalismol C in Alismatis Rhizoma decoction pieces.METHODS The near-infrared spectroscopy(NIRS)data were collected in 95 batches of decoction pieces,after which drying method was adopted in the content determination of moisture,HPLC was applied to determining the contents of 23-acetylalismol B and 23-acetylalismol C,the quantitative models were established by partial least squares method combined with feature extraction algorithms.RESULTS The model training determination coefficients were 0.952 6,0.958 1 and 0.920 8,along with the prediction determination coefficients of 0.930 0,0.905 2 and 0.906 4,the residual prediction deviations(PRD)of 4.00,3.58 and 3.46,and the root mean square error ratios of prediction values to calibration values(RMSEP/RMSEC)of 1.15,1.11 and 1.06,respectively.CONCLUSION The quantitative models based on NIRS exhibit good prediction effects,which can be used for the rapid quality detection of Alismatis Rhizoma decoction pieces.