ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.

ObjectiveTo develop and preliminarily validate a prediction model for brace treatment failure risk in patients with adolescent idiopathic scoliosis (AIS), based on information obtained before brace treatment and during initial brace fitting. MethodsA total of 191 patients with AIS who initiated thoracolumbosacral orthosis treatment at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from March, 2015 to August, 2024 and had determinable outcomes were retrospectively included. Patients were divided according to a prespecified scheme into a training set (n = 133) and a validation set (n = 58). Brace treatment failure was defined as progression of the major-curve Cobb angle by ≥ 5° from baseline during follow-up or at brace weaning, or a final major-curve Cobb angle > 45°. Logistic regression, random forest, support vector machine with radial basis function kernel, and extreme gradient boosting (XGBoost) models were developed using routinely available clinical and radiographic variables before brace treatment and during initial brace fitting. Stratified five-fold cross-validation was used for hyperparameter tuning in the training set. Model performance was evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), Brier score, calibration curves, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) was used to interpret the main explanatory model. ResultsIn cross-validation of the training set, both random forest and XGBoost showed good discriminative performance, with cross-validation-AUC values of 0.871 and 0.880, respectively. In the validation set, the AUC values of random forest and XGBoost were 0.888 and 0.899, the AUPRC values were 0.678 and 0.830, and the Brier scores were 0.086 and 0.076, respectively. Random forest was selected as the primary model for interpretation, with a calibration intercept of 0.091 and a calibration slope of 0.995. SHAP analysis indicated that the in-brace correction rate and the major-curve Cobb angle measured in the brace contributed most to the model predictions. ConclusionThe random forest model developed using routinely available pretreatment and initial-fitting variables shows preliminary predictive value for brace treatment failure risk in AIS, and may provide quantitative support for follow-up scheduling, brace-fit reassessment and early adherence-oriented management.

Background Both productive dust and noise are occupational hazards, and each can induce changes in blood glucose levels among workers. Objective To explore the potential interactive effects of exposure to productive dust and noise on the risk of hyperglycemia among automobile manufacturing workers. Methods Using a cluster sampling method, workers undergoing occupational health examination from three automobile manufacturing plants in Wuhan in 2022 were selected. Basic information was collected using a questionnaire designed by the Chinese Center for Disease Control and Prevention. Exposure history was obtained through occupational history interviews. Clinic indicators such as blood pressure, blood lipids, fasting blood glucose (FBG), and fatty liver status, were retrieved from examination records. Hyperglycemia was defined as FBG > 6.1 mmol·L^-1. Logistic regression models analyzed the independent effects of occupational noise and dust exposure, while additive and multiplicative interaction models assessed their interactive effects on hyperglycemia. Results The prevalence of hyperglycemia among the 1223 participants was 7.7%. Logistic regression showed that using workers without exposure as reference, the odds ratios (OR) and 95% confidence intervals (CI) for hyperglycemia among workers exposed only to dust, only to noise, and to both were 2.15 (1.90, 4.23), 2.23 (1.40, 5.08), and 3.75 (1.95, 7.24), respectively. A linear association was observed between the duration of noise exposure and blood glucose levels (P<0.05). Interaction analysis showed no multiplicative interaction or additive interaction. Conclusion Exposure to productive dust and noise are independent risk factors for hyperglycemia among workers. While both contribute to increased risk, no significant synergistic interaction is observed.

Objective:To analyze the clinical characteristics and cytokines expression characteristics in infants with mild and severe respiratory syncytial virus (RSV) infection.Methods:From May 2023 to December 2023, plasma samples and clinical information were collected from 16 infants with RSV infection and 14 control infants. Cytek Aurora flow cytometry (Cytek, America) and Enzyme linked immunosorbent assay (ELISA) were used to detect the expression levels of 25 cytokines after mild and severe RSV infection.Results:Cough and nasal obstruction were the main clinical manifestations in infants with mild RSV infection, accompanied by polypnea, wheezing and other symptoms. The main symptoms of severe RSV infection were cough and rales, accompanied by fever and polypnea. In comparison with the control group, the expression levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-13, IL-22, TNF-α, IFN-α, IFN-β, MIP-1β, I-TAC, ENA-78, GROα, Eotaxin, and MCP-1 in the RSV infection group all exhibited an upregulation trend. Both IP-10 and MIP-3α demonstrated a downward trend in the RSV infection group; however, there was no statistically significant difference ( P>0.05). The levels of IL-10, IFN-γ, MIP-1α, and IL-8 in the RSV infection group were significantly higher than those in the control group, whereas the levels of MIG, TARC, and RANTES in the RSV infection group were significantly lower than those in the control group ( P<0.05). The levels of IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-13, IL-22, IFN-β, IFN-γ, TNF-α, IL-8, I-TAC, MIP-1β, Eotaxin, and MCP-1 in the mild RSV infection group were significantly higher than those in the severe RSV infection group ( P>0.05). Among these, the levels of MIG, RANTES, TARC, MIP-3α, and ENA-78 in the mild infection group were all lower than those in the severe infection group. The expressions of ENA-78 and MIP-1α in the severe infection group were significantly higher than those in the mild infection group and also higher than those in the control group. There was no significant difference in IP-10 and GROα between the mild and severe RSV infection groups ( P>0.05). Conclusions:The differences in clinical features and cytokines between infants with mild and severe RSV infection provide important data support for the prevention and treatment of RSV infection in infants.

Objective:To characterize the clinical and genetic features of 2 patients with interleukin-1 receptor associated kinase (IRAK) 4 deficiency and to assess the pathogenicity of their genetic variants.Methods:This case series included two patients diagnosed with IRAK4 gene deficiency at Shenzhen Children′s Hospital and the University of Hong Kong-Shenzhen Hospital between 2019 and 2024. Six healthy children without recent infections or immunodeficiency served as controls. Peripheral blood mononuclear cells were stimulated in vitro with Toll-like receptor 4 (TLR4) agonists, and cytokine levels were quantified using a protein chip assay.Results:The 2 patients, a 5-year-old boy and a 10-year-old girl, presented with recurrent invasive or non-invasive bacterial infections and impaired acute-phase inflammatory responses. Genetic testing identified a homozygous frameshift variant (c.540delT, p.F180Lfs*26) in Patient 1 and compound heterozygous frameshift variants (c.166delT, p.F56fs and c.629delG, p.R210fs) in Patient 2, all predicted to result in truncated IRAK4 proteins. Both patients received regular infection prophylaxis with favorable clinical outcomes. Controls consists of 3 males and 3 females, aged 5-17 years. Following TLR4 stimulation, cytokine levels in Patient 1, Patient 2, and controls (tumor necrosis factor-α 68.6, 103.0, 618.7 (392.7, 824.1); interleukin (IL)-1β 39.8, 10.8, 1 975.5 (1 556.0, 2 096.5); interferon-γ 8.6, 6.2, 13.5 (12.7, 14.9); granulocyte colony-stimulating factor 17.6, 15.9, 2 890.0 (1 622.0, 4 692.8); IL-6 140.1, 352.7, 7 222.5 (5 768.5, 8 043.5); and IL-17 47.5, 44.5, 59.7 (43.4, 69.5), respectively.Conclusions:IRAK4 deficiency should be suspected in patients with early-onset recurrent bacterial infections and attenuated inflammatory response. Homozygous and compound heterozygous frameshift variants in IRAK4 gene lead to truncated IRAK4 proteins and impared innate immune signaling.

Objective:To investigate the clinical significance of monitoring SIL::TAL1 fusion transcripts in the evaluation of treatment response and prognosis of children with T-acute lymphoblastic leukemia (T-ALL).Methods:A retrospective cohort study was conducted to analyze the clinical data of 46 newly diagnosed pediatric T-ALL with SIL::TAL1 fusion transcripts treated at Beijing Children′s Hospital Capital Medical University from November 2004 to December 2022. The SIL::TAL1 fusion transcripts were quantitatively detected at the initial diagnosis (TP0) and early stage of induction therapy (TP1), at the end of induction remission therapy (TP2), before consolidation therapy (TP3) and subsequent treatment. Patients were divided into negative and positive groups on SIL::TAL1 fusion transcripts level, differences of clinical features and survival among groups at TP0 to TP3 were analyzed. The χ2 test or Fisher exact test or Mann-Whitney U test was used to compare the clinical difference. Survival analysis was estimated by Kaplan-Meier method with Log-Rank testing. Multivariate analysis was conducted by Cox proportional hazards models. Results:Among the 46 children with SIL::TAL1 fusion transcripts, 36 were males and 10 were females, with the onset age of 6.8 (3.4, 9.5) years. The negative rates of SIL::TAL1 fusion transcripts for TP1,TP2, TP3, before delayed intensification Ⅰ treatment (TP4), before maintenance therapy (TP5) were 36% (13/36), 78% (32/41), 76% (32/42), 15/16, and 12/12, respectively. No significant difference was found on clinical features and prednisone response between groups at TP0-TP3 (all P>0.05). The 5-year events free survival (EFS) rate of patients classified as negative (32 cases) and positive (9 cases) groups at TP2 was (78±8)% and (33±16)%, respectively ( χ2=9.86, P=0.002), the 5-year overall survival (OS) rate was (81±7)% and (44±17)%, respectively ( χ2=6.40, P=0.011). The 5-year EFS rate of patients classified as negative (32 cases) and positive (10 cases) groups at TP3 was (78±8)% and (30±15)%, respectively ( χ2=13.04, P<0.001) and the 5-year OS rate was (84±6)% and (30±15)%, respectively ( χ2=15.95, P<0.001). Cox multivariate regression showed that positive of SIL::TAL1 transcript at TP3 was adverse independent prognostic factors for EFS and OS (EFS: HR=6.70, 95% CI 2.01-22.35, P=0.002; OS: HR=10.73, 95% CI 2.50-46.09, P=0.001). Conclusions:Monitoring SIL::TAL1 fusion transcripts can reflect the clinical treatment response. The level of SIL::TAL1 fusion transcripts at early period can predict long-term outcomes of these patients.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.