OBJECTIVE To upgrade the drug traceability code management system for a pediatric hospital under the “payment by code” background， aiming to comprehensively enhance traceability integrity， efficiency， and compliance. METHODS Taking Xiamen Children’s Hospital as the implementation setting， a before-and-after control design was adopted to construct an intelligent drug traceability code management system through systematic upgrades involving the technology platform， core mechanisms， and coordination with medical insurance. Key interventions included： upgrading a traceability code management platform and designing a dynamic code pool； innovating differentiated traceability mechanisms for routine， split-dose， and special drugs； establishing a tiered early-warning and emergency response system； and constructing a data coordination and quality control system. The drug traceability code upload rate served as the primary outcome. Process indicators such as the root causes distribution of failed uploads and the duration of medication returns， and a comprehensive outcome （the number of insurance-flagged abnormal prescriptions） were also analyzed. The data between the baseline period （April 2025） and the observation period （June-August 2025） were compared and evaluated. RESULTS After the upgrade， the overall upload rate of drug traceability codes increased from 9.21% （baseline） to 99.86% （August 2025）. The upload rate of traceability codes in previously unmanaged areas， such as the inpatient pharmacy and pharmacy intravenous admixture services， soared from 0 to nearly 100%. The proportion of non-uploads due to system issues fell from 66.44% （June 2025） to 2.62% （August Additionally， the number of insurance-flagged） abnormal prescriptions dropped sharply from 2 275.00 in the first “payment by code” policy month （July 2025） to 212.00 by the end of the observation period （August 2025）， a 90.70% decrease. CONCLUSIONS The developed management system effectively addresses complex scenario challenges such as high-frequency drug splitting. It significantly enhances traceability code upload performance and ensures a high degree of compliance with medical insurance data requirements. These outcomes contribute to proactive risk mitigation against insurance claim denials and demonstrate a concurrent optimization of pharmacy operations.

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

Objective To aim at using machine learning algorithms to predict the risk of neonatal intensive care unit(ICU)mortality,providing clinicians with an early diagnosis and risk assessment tool to assist in decision-making.Methods Clinical data of preterm infants from the paediatric intensive care database retrospectively were collected.By using least absolute shrinkage and selection operator(LASSO)regression analysis and multivariate Logistic regression analysis,key clinical characteristics affecting preterm infant prognosis were screened.The study was balanced the data by using the synthetic minority oversampling technique,combined seven machine learning models to build a predictive model and evaluate its performance.The Shapley additive explanations(SHAP)was used for model interpretation.Results A total of 923 preterm infants were finally included,survival group comprised 886 infants,and death group comprised 37 infants.A total of 38 clinical characteristics were collected.LASSO screening identified 8 variables significantly associated with neonatal ICU mortality,including lactate,respiratory rate,chloride concentration,neutrophils,and red blood cell distribution width etc.Multivariate Logistic regression analysis revealed that lactate and respiratory rate were independent predictors of neonatal ICU outcomes.Internal testing and external validation showed that light gradient boosting machine model outperformed other models in terms of accuracy and precision etc.indicators.SHAP analysis indicated that respiratory rate and lactate levels had the largest predictive contribution to the risk of preterm infants mortality.Conclusion This study provides reliable tools for early identification and intervention in the prognosis of preterm infants,emphasizing the importance of key indicators.

Cardiovascular disease(CVD)is the leading cause of death among patients with non-alcoholic fatty liver disease(NAFLD),which is also recognized as an independent risk factor for CVD.Exercise has emerged as a prom-ising therapeutic approach that can ameliorate a range of conditions,including those related to the cardiovascular and en-docrine systems.Recent research has highlighted the critical role of the integrated stress response(ISR)in the mecha-nisms and manifestations of these diseases.Notably,exercise influences ISR protein markers,regulates protein expres-sion,alleviates stress levels,and ultimately impacts disease onset and progression.Current studies suggest that the effects of ISR modulation through various exercise conditions differ for the heart and liver.However,evidence indicates that un-der specific circumstances,exercise can engage the PERK and GCN2 pathways to inhibit the ISR,thereby regulating glu-cose and lipid metabolism,apoptosis,and endoplasmic reticulum stress.These actions contribute to the protection of car-diac and hepatic function,ultimately improving outcomes in CVD and NAFLD.This review aims to provide novel insights and a theoretical foundation for the role of exercise in mitigating the onset of NAFLD,CVD,and related disorders.

Objective To evaluate the effect of glucocorticoid(GC)treatment on the prognosis of patients with severe viral pneumonia,and to screen for related influencing factors and optimal beneficiary groups,providing reference for clinical medication decisions.Methods Based on the MIMIC-Ⅳ database,eligible patients with severe viral pneumonia were screened and divided into GC group and non GC group.Baseline differences were balanced using propensity score matching(PSM).Kaplan-Meier survival curves were used to analyze the cumulative survival rate of two groups of patients at 30 d,and Cox regression models were used to evaluate the association between GC use and the 30 d mortality risk in patients.Results A total of 518 severe viral pneumonia patients were included,including 43 in the GC group and 475 in the non-GC group.After PSM,there were 43 cases in the GC group and 86 cases in the non-GC group.The Kaplan-Meier survival curves showed that the 30 d cumulative survival rate of patients in the GC group was significantly higher than that in the non-GC group(P＜0.05).The results of multivariate Cox regression analysis showed that GC treatment significantly reduced the 30 d mortality risk[HR=0.35,95％CI(0.154,0.793),P=0.012],especially for patients older than 54 years,receiving mechanical ventilation,and with acute kidney injury.GC use,age＞54 years,and acute kidney injury were independent predictors of patient mortality risk(C-index=0.718 1).Subgroup analysis showed that for specific indications(age＞54 years,mechanical ventilation,no myocardial infarction,no hypertension,no hyperlipidemia,no heart failure,complicated by acute kidney failure),GC use could effectively reduce the 30 d mortality risk.Conclusion GC could effectively improve the prognosis of severe viral pneumonia patients,but individualized patient characteristics and treatment risks need to be considered comprehensively to optimize the medication regimen.

OBJECTIVE To explore the risk evaluation of healthcare workers contracting tuberculosis in a designated three-A tuberculosis hospital in Guangxi based on the failure mode and effect analysis(FMEA)method.METHODS A designated three-A tuberculosis hospital in Guangxi was selected.Healthcare workers from Jan.1,2023 to Dec.31,2023 served as the control group and received routine management,i.e.,implementing various tuberculosis prevention and control measures according to current guidelines.Healthcare workers from Jan.1,2024 to Dec.31,2024 served as the experimental group and were managed by the FMEA method.High-risk fac-tors were screened through the FMEA method,and targeted intervention strategies were formulated to priori-tize intervention for high-risk events.The incidence rate of tuberculosis among healthcare workers and the imple-mentation rate of tuberculosis infection prevention and control measures before and after FMEA intervention were compared.RESULTS The six high-risk events screened were improper use of surgical masks by patients,inade-quate respiratory hygiene practices,improper use of medical protective masks by healthcare workers,lack of full process isolation management for tuberculosis patients,unreasonable sputum collection areas and improper venti-lation and air disinfection measure setting or maintenance.After implementing a series of tuberculosis prevention and control measures,the incidence rate of tuberculosis infection among healthcare workers decreased from 1.63％before FMEA intervention to 0.30％(P=0.021).The implementation rate of tuberculosis infection prevention and control measures increased from 69.95％to 73.61％(P=0.003).CONCLUSIONS Risk evaluation based on the FMEA method can identify weaknesses in tuberculosis infection prevention among healthcare workers in desig-nated tuberculosis hospitals.Implementing multiple measures simultaneously can effectively reduce the incidence rate of tuberculosis among healthcare workers,ensure occupational safety,improve the implementation rate of tu-berculosis infection prevention and control measures and achieve scientific and precise prevention and control.

The implantation of left ventricular assist device (LVAD) has significantly improved the quality of life for patients with end-stage heart failure. However, it is associated with the risk of complications, with unplanned readmissions gaining increasing attention. This article reviews the influencing factors, prediction methods and models, and intervention measures for unplanned readmissions in LVAD patients, aiming to provide scientific guidance for clinical practice, assist healthcare professionals in accurately assessing patients' conditions, and develop rational care plans.

OBJECTIVE To investigate the construction and practice of a drug traceability code management system in pediatric hospitals， providing a reference for promoting drug traceability code collection in healthcare institutions. METHODS Taking the outpatient pharmacy of our hospital as the research subject， a drug traceability code management system was constructed through the upgrade of the hospital information system （HIS）， process optimization， and human-machine collaboration mechanism. The PDCA （plan-do-check-act） cycle management method was applied to continuously optimize this system. Based on operational data from March 2024 to February 2025， the changes in the collection rate of drug traceability codes were analyzed， and the differences in the average patient pickup time， the average pharmacist dispensing time， and the dispensing error rate were compared before and after the implementation of the system. RESULTS In the initial period of trial operation of the drug traceability code management system（June 2024）， the collection rate of drug traceability codes was 57.17%， which subsequently improved to 93.52% by February 2025 following process optimization. Compared with the pre-implementation period （March-May 2024）， there was no significant difference （P＞0.05） in the average patient pickup time during the stable run-in period （August-October 2024）； the overall average pharmacist dispensing time increased significantly （P＜0.001）， but the clinical significance of this increase （0.42 s） was limited； stratified analyses showed a significant increase in the average pharmacist dispensing time for prescriptions involving chronic disease multidrug combinations （[ 23.29±6.83） s vs. （17.87±3.64 ） s， P＜0.001]； the dispensing error rate was reduced from 0.13‰ to 0.03‰ （P＝0.038）. CONCLUSIONS By adopting the strategy of “system reconstruction-process reengineering-human-machine collaboration”， our hospital has successfully established a drug traceability code management system. While complying with national regulatory requirements， we have maintained service efficiency and reduced the medication dispensing error rate.

OBJECTIVE To evaluate the influence of pharmaceutical quality control on the efficiency and outcomes of standardized medication therapy management （MTM） services for patients with coronary heart disease by using Economic， Clinical and Humanistic Outcomes （ECHO） model. METHODS This study collected case data of coronary heart disease patients who received MTM services during January-March 2023 （pre-quality control implementation group， n＝96） and June-August 2023 （post-quality control implementation group， n＝164）. Using propensity score matching analysis， 80 patients were selected from each group. The study subsequently compared the economic， clinical， and humanistic outcome indicators of pharmaceutical services between the two matched groups. RESULTS There were no statistically significant differences in baseline data between the two groups after matching （P＞0.05）. Compared with pre-quality control implementation group， the daily treatment cost （16.26 yuan vs. 24.40 yuan， P＜0.001）， cost-effectiveness ratio [23.12 yuan/quality-adjusted life year （QALY） vs. 32.32 yuan/QALY， P＜0.001]， and the incidence of general adverse drug reactions （2.50% vs. 10.00%， P＝0.049） of post-quality control implementation group were decreased significantly； the utility value of the EuroQol Five-Dimensional Questionnaire （0.74± 0.06 vs. 0.71±0.07， P＝0.003）， the reduction in the number of medication related problems （1.0 vs. 0.5， P＜0.001）， the medication adherence score （[ 6.32±0.48） points vs. （6.10±0.37） points， P＝0.001]， and the satisfaction score （[ 92.56±1.52） points vs. （91.95±1.56） points， P＝0.013] all showed significant improvements. Neither group experienced serious adverse drug reactions. There was no statistically significant difference in the incidence of new adverse reactions between the two groups （1.25% vs. 3.75%， P＝0.310）. CONCLUSIONS Pharmaceutical quality control can improve the quality of pharmaceutical care， and the ECHO model can quantitatively evaluate the effect of MTM services， making pharmaceutical care better priced and more adaptable to social needs， thus being worthy of promotion.

Cardiovascular disease(CVD)is the leading cause of death among patients with non-alcoholic fatty liver disease(NAFLD),which is also recognized as an independent risk factor for CVD.Exercise has emerged as a prom-ising therapeutic approach that can ameliorate a range of conditions,including those related to the cardiovascular and en-docrine systems.Recent research has highlighted the critical role of the integrated stress response(ISR)in the mecha-nisms and manifestations of these diseases.Notably,exercise influences ISR protein markers,regulates protein expres-sion,alleviates stress levels,and ultimately impacts disease onset and progression.Current studies suggest that the effects of ISR modulation through various exercise conditions differ for the heart and liver.However,evidence indicates that un-der specific circumstances,exercise can engage the PERK and GCN2 pathways to inhibit the ISR,thereby regulating glu-cose and lipid metabolism,apoptosis,and endoplasmic reticulum stress.These actions contribute to the protection of car-diac and hepatic function,ultimately improving outcomes in CVD and NAFLD.This review aims to provide novel insights and a theoretical foundation for the role of exercise in mitigating the onset of NAFLD,CVD,and related disorders.