OBJECTIVE To ensure the safety of patients’ drug use and control the risk of medical insurance expenditure by upgrading the pre-prescription review system to conduct pre-review on prescriptions from internet hospitals and external prescriptions， as well as to review the payment methods of drugs （including in-hospital and external drug dispensing）. METHODS The data interfaces of prescriptions from internet hospitals and external prescriptions were integrated to achieve real-time rational drug use intervention. Additionally， an intelligent review project for payment method was added to precisely intervene in the medical insurance payment methods of drugs. The effect of the system upgrade was evaluated by comparing the qualification rates of prescriptions from internet hospitals and external prescriptions and the suspected amounts of drug violations from January to April 2025 （before the system upgrade） and May to August 2025 （after the system upgrade）. RESULTS After the upgrade of the pre-prescription review system， the qualification rates of prescriptions from internet hospitals and external prescriptions increased by 3.5% [95% confidence interval （CI）＝0.3%-6.7%， P ＝0.037 ] ； the suspected amounts of drug violations decreased to 52.9% of the pre-upgrade level （95%CI＝31.6%-88.5%， P ＝0.026）， and the average monthly sequential decrease was 29.5% （95%CI＝12.2%-43.4%， P ＝0.012）. Moreover， the addition of the intelligent review project for payment methods promoted the management of off-label drug use in our hospital. After the upgrade， a total of 79 filling valid applications for off-label drug use were received and archived. CONCLUSIONS The upgrade of the pre-prescription review system effectively improves the review qualification rates of prescriptions from internet hospitals and external prescriptions and the accuracy of medical insurance payment for drugs， and strengthens the supervision of off-label drug use， achieving dual guarantees of clinical rationality and medical insurance compliance.

Objective: To evaluate the practical effectiveness of confidential unit exclusion (CUE) in ensuring blood safety in Zhengzhou, analyze its application characteristics and existing problems, and provide a basis for optimizing blood safety management strategies. Methods: A retrospective analysis was conducted on CUE data handled by Henan Red Cross Blood Center from January 2019 to December 2024. Parameters such as the number of cases, demographic characteristics, reasons for exclusion, and time of report were statistically analyzed and compared with those of non-CUE. Results: From 2019 to 2024, the CUE reporting rate in Zhengzhou was 0.002 6% (40/1 547 666). CUE donors were predominantly male (65.00%, 26/40), aged 18-34 years (47.50%, 19/40), had college degree orabove (50.00%, 20/40), and were employees of enterprises or public institutions (32.50%, 13/40). Among the 40 CUE blood units, only one was reactive for anti-TP, while all others were qualified. The main reasons for CUE were recent vaccination (32.50%, 13/40), medical conditions unsuitable for donation (27.50%, 11/40), and high-risk sexual behavior (17.50%, 7/40). A total of 70.00% of reports occurred within 24 hours after donation, during which none of the corresponding blood units had been released; all units reported after more than 7 days had already been issued for clinical use, with no adverse transfusion reactions reported upon follow-up. Conclusion: The confidential unit exclusion program has played an active role in establishing a supplementary information feedback channel for blood donors. The procedure can be optimized by strengthening interactive communication and confirmation before donation, improving the accuracy of donors' self-assessment, and expanding convenient and rapid information-based reporting channels.

OBJECTIVE To develop a pharmacist-led intervention model for reducing drug-related medical insurance claim denial risks， so as to provide practical references for healthcare institutions in fulfilling their primary responsibility for medical insurance fund supervision. METHODS A risk matrix method was employed by the pharmacists to assess the risks associated with drug‑related medical insurance claim rejections in our hospital during 2024. Intervention measures were developed targeting high‑risk factors (including inappropriate indications for medical insurance coverage, exceeding the covered treatment course, and inappropriateness of gender and age) from three dimensions, namely organizational structure, technical prevention and control, and closed‑loop management. Changes in drug‑related claim rejection data were compared between 2024 (pre‑intervention) and 2025 (post‑intervention), and the interception effect of the pre‑prescription review system was evaluated after the intervention. RESULTS After the intervention, the total amount of drug‑related medical insurance claim rejections in our hospital was reduced by 57.24% compared with that before the intervention, and the number of rejected items decreased from 10 108 to 2 892. Specifically, the number of rejected items due to inappropriate indications, exceeded treatment course, inappropriate gender, and inappropriate age was reduced by 70.94%, 74.26%, 83.86%, and 96.70%, respectively. Throughout the year following the intervention, a total of 5.605 yuan million in outpatient prescription drug amounts and 4.683 million yuan in inpatient medication order amounts that did not meet the insurance‑limited payment requirements were intercepted by the pre‑prescription review system. The proportion of drug‑related claim rejection amount to the total medical service claim rejection amount of our hospital decreased to 19.7%. CONCLUSIONS The pharmacist-led multi-department collaborative， technical prevention and control， and dynamic optimization integrated full-process intervention model is highly operable and has significant practical effects. It has important promotion value in reducing drug-related medical insurance claim denial risks.

The occurrence and progression of diseases constitute a complex dynamic process, and cross-sectional data from a single time point are insufficient to fully characterize their evolutionary patterns. In contrast, longitudinal time-series data can capture the dynamic evolution of diseases over time, which is key to achieving precise disease prediction. In recent years, breakthroughs in deep learning have driven significant progress in intelligent predictive models based on longitudinal time-series data. However, challenges inherent to such data-including irregular sampling, high missing rates, and heterogeneity-also impose specific requirements on model design. This paper provides a systematic review of research advances in intelligent models for disease prediction based on time-series data. We conduct an in-depth analysis from three perspectives: data processing and representation, representative model architectures, and time-series modeling strategies, aiming to provide a reference for building more efficient and robust longitudinal disease prediction models.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

A novel analytical method was developed in this study by combining online solid phase extraction with ultra performance liquid chromatography-tandem mass spectrometry(Online SPE-UPLC-MS/MS)for simultaneous determination of 50 kinds of steroid hormones in surface water.Specifically,after high-speed centrifugation of 4 mL water samples,the supernatant was directly injected into an Oasis HLB online SPE column for enrichment and purification.Subsequently,the target compounds were transferred to the analytical column via valve switching for separation and analysis.The chromatographic separation was performed on a Thermo Acclaim RSLC C18 column(100 mm×2.1 mm,2.2 μm),using a mobile phase composed of 5 mmol/L ammonium fluoride aqueous solution and acetonitrile.Mass spectrometric detection was conducted in positive ion mode,utilizing multiple reaction monitoring(MRM)with quantification achieved by the internal standard method.The method validation demonstrated that the limits of detection(LOD)for the 50 kinds of steroid hormones ranged from 0.02 to 0.50 ng/L,while the limits of quantification(LOQ)were between 0.08 and 1.67 ng/L.The average recoveries in surface water samples at spiked concentrations of 5,20 and 200 ng/L were between 74.1％and 119％,with relative standard deviations(RSDs)of 0.2％to 9.9％.This method was applied to analyze 11 surface water samples collected from sites surrounding a pharmaceutical and chemical industrial park.A total of 44 kinds of steroid hormones were detected,with concentrations ranging from 0.11 to 88.6 ng/L,revealing the presence of hormone contamination in the environmental waters surrounding industrial areas.Compared with the traditional offline SPE methods,the proposed online SPE technique significantly reduced sample volume requirements and pretreatment time,while minimizing the loss of target compounds during the pretreatment process.Moreover,compared to reported online SPE techniques,this method achieved high-throughput analysis of multiple classes of steroid hormones,with lower detection limits and higher recoveries.Overall,this method provided rapid sample preparation,high sensitivity,and excellent stability,making it suitable for the direct analysis of trace steroid hormones in surface water.

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 explore the differences in early clinical features between Kawasaki disease shock syndrome (KDSS) and septic shock (SS).Methods:A retrospective case-control study was conducted. Clinical data was collected from 64 children who were diagnosed with KDSS or SS and admitted to the Department of Critical Care Medicine of Capital Center for Children′s Health, Capital Medical University from January 2018 to February 2025. Mann-Whitney U test, χ2 test, or Fisher′s exact test were used to compare the differences in clinical features, treatment, and outcomes between children with KDSS and SS. Lasso regression was applied to screen predictive variables, and multivariable logistic regression analysis was performed to identify factors associated with KDSS. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of parameters for KDSS. Results:Among the 64 children (30 males and 34 females), the age was 3.6 (1.2, 6.5) years. There were 51 cases in the SS group and 13 cases in the KDSS group. Compared to children with SS, children with KDSS had a longer pre-shock fever duration, lower lactate levels and serum albumin levels, and higher soluble interleukin-2 receptor (sIL-2R) levels (all P<0.05). Additionally, they exhibited a higher incidence of coronary involvement, pericardial effusion, and ascites, a higher utilization rate of intravenous immunoglobulin, and a lower utilization rate of invasive mechanical ventilation (all P<0.05). There was no significant difference in in-hospital mortality between KDSS and SS ( P=0.574). Multivariate logistic regression analysis identified pre-shock fever duration and sIL-2R as independent factors associated with KDSS ( OR=1.52 and 1.54 per 1 000 U increase, 95% CI 1.12-2.05 and 1.06-2.24, respectively; both P<0.05). ROC curve analysis showed that the areas under the curve for pre-shock fever duration and sIL-2R in identifying KDSS were 0.83 (95% CI 0.73-0.94, P=0.001) and 0.70 (95% CI 0.53-0.87, P=0.042), respectively. The optimal cutoff values were 3.5 d and 3.8×10 6 U/L, with sensitivities of 0.91 and 0.82, and specificities of 0.71 and 0.62, respectively. Conclusions:Children with KDSS have higher incidences of coronary involvement, pericardial effusion, and ascites compared to those with SS. Pre-shock fever duration and sIL-2R may serve as potential early indicators for distinguishing KDSS from SS.

Objective To assess the effectiveness of the Gasdermin D C-terminal fragment(GSDMD-CT)as a novel plasma biomarker for the clinical diagnosis of sepsis.Methods Between July 2021 and November 2024,245 patients from Tangshan Gongren Hospital were enrolled in this study.In accordance with the diagnostic criteria for sepsis and the systemic inflammatory response syndrome(SIRS),patient samples were classified into the sepsis group and the SIRS group.Meanwhile,healthy individuals were selected as the healthy control(HC)group.Sepsis patients were further categorized into the Gram-positive bacterial group,the Gram-negative bacterial group,and the fungal group based on the type of pathogen infection.The levels of GSDMD-CT,C-reactive protein(CRP),and procalcitonin(PCT)were measured in all subjects.Nonparametric tests were employed to compare the differences in various indices among different groups.The diagnostic value of GSDMD-CT in sepsis was evalu-ated by constructing the receiver operating characteristic(ROC)curve.Spearman's correlation analysis was used to examine the relationships among GSDMD-CT,CRP,and PCT.Results The plasma GSDMD-CT levels in the sepsis group 23.02(16.71,33.01)pg/mL and in the SIRS group 16.52(11.26,22.22)pg/mL were significantly higher than those in the healthy control group 7.02(4.42,11.43)pg/mL(U=-10.175,-7.890,P<0.001).Moreover,the plasma GSDMD-CT levels in the sepsis group were significantly higher than those in the SIRS group(U=-2.941,P<0.05).In the Gram-positive bacterial group,the Gram-negative bacterial group,and the fungal group,the GSDMD-CT levels were 23.01(17.16,27.51)pg/mL,23.41(16.78,35.50)pg/mL,and 16.29(14.53,56.27)pg/mL,respectively.When compared with the healthy control group,the GSDMD-CT levels in these three groups were all significantly higher(P<0.05).However,there were no significant differences in GSDMD-CT levels among these three groups(P>0.05).The area under the curve(AUC)of plasma GSDMD-CT for diagnosing sepsis was 0.881(95%confidence interval:0.833～0.929),with a Youden index(YI)of 0.695,a sensitivity of 85.0%,and a specificity of 84.5%.Spearman correlation analysis indicated a weak correlation between GSDMD-CT and C-reactive protein(CRP)(r=0.32,P<0.001)and a positive correlation between GSDMD-CT and procalci-tonin(PCT)(r=0.65,P<0.001).Conclusion GSDMD-CT exhibits significant clinical value in the diagnosis of sepsis and holds great potential as a biomarker in the diagnostic process of sepsis.

BACKGROUND:Intertrochanteric fractures of the femur are particularly common in elderly and osteoporosis patients,and treatment often requires internal fixation surgery to stabilize the fracture and promote healing. However,internal fixation surgery may occasionally fail,leading to serious problems such as nonunion of fractures,malunion,or re-fracture.OBJECTIVE:To explore the effect of artificial total hip arthroplasty on postoperative failure of internal fixation for intertrochanteric fractures of the femur and the influencing factors of postoperative occult blood loss.METHODS:Totally 86 patients with failed internal fixation of intertrochanteric fractures of the femur who were treated in First People's Hospital of Yangquan City from May 2019 to September 2022 and had complete follow-up data were collected. Using artificial total hip arthroplasty for treatment,relevant clinical indicators of the patient were recorded,and Harris score,visual analog scale score,and SF-36 score were compared and analyzed before and after surgery. Univariate and multivariate logistic regression analysis was conducted on the factors affecting occult blood loss after total hip arthroplasty. Logistic regression models and neural network models were established to predict occult blood loss. The predictive performance and accuracy of the two models were compared by drawing receiver operating characteristic curves.RESULTS AND CONCLUSION:(1) Totally 86 patients with intertrochanteric fractures of the femur were successfully treated with artificial total hip arthroplasty after internal fixation failure. (2) There were statistically significant differences in Harris score,visual analog scale score,SF-36 score,and hip active range of motion between patients before and 3,6,and 12 months after surgery (P<0.05). (3) The age,hypertension ratio,diabetes ratio,osteoporosis ratio,operation time,total blood loss,intraoperative blood loss,postoperative drainage volume,and hemoglobin decrease in the high occult blood loss group were significantly higher than those in the low occult blood loss group (P<0.05). The proportion of bone cement type prostheses,anterior approach,and 2-3 grade hip jointspace in the low occult blood loss group were higher than those in the high occult blood loss group (P<0.05). There was no statistically significant difference between the two groups in terms of gender ratio,body mass index,proportion of chronic bronchitis,proportion of sides,anesthesia method,and acetabular cup diameter (P>0.05). (4) Through multivariate logistic regression analysis,age,diabetes,osteoporosis,prosthesis type,surgical approach,hip joint space,total blood loss,intraoperative blood loss,postoperative drainage volume,and hemoglobin decrease were the risk factors for high occult blood loss after total hip arthroplasty (P<0.05). (5) After incorporating influencing factors into the logistic regression model and neural network model for predicting occult blood loss,the receiver operating characteristic curves of the two models were plotted with area under curve values of 0.882 and 0.923,sensitivity values of 0.879 and 0.886,specificity values of 0.854 and 0.908,Youden index values of 0.733 and 0.794,and accuracy values of 0.867 and 0.897,respectively. The area under curve,Youden index,and accuracy of both models were higher than those of neural network models. (6) It is concluded that total hip arthroplasty has a significant clinical effect on treating postoperative failure of internal fixation for intertrochanteric fractures of the femur,with good recovery of hip joint range of motion. Age,diabetes,osteoporosis,prosthesis type,surgical approach,hip joint space,total blood loss,intraoperative blood loss,postoperative drainage volume,and hemoglobin decrease are important factors for the high risk of occult blood loss after total hip arthroplasty. Logistic regression model and neural network model based on risk factors have little difference in the prediction results of occult blood loss,and neural network model is higher.