OBJECTIVE To build a new workflow of pharmacy intravenous admixture services （PIVAS）， effectively connect intelligent equipment， and promote the intelligent development of PIVAS. METHODS Based on intelligent auxiliary equipment， PIVAS workflow was optimized， and a process-oriented model was established. This model integrated intelligent prescription review （automatic prescription review+manual intervention mode）， intelligent labeling， intelligent allocation， intelligent sorting， and finished infusion quality inspection system. Furthermore， an assessment was conducted to examine unreasonable medical order rate of intelligent prescription review， the working efficiency and error rate of intelligent labeling machine and intelligent sorting machine， and the dispensing efficiency and accuracy of intelligent dispensing robot. RESULTS Under the intelligent prescription review mode， the rate of unreasonable medical orders decreased from 0.157% to 0.050% （P＜0.05）； automatic labeling efficiency reached 21.7 sheets/min， surpassing the manual labeling efficiency of 13.8 sheets/min （P＜0.05）， and the daily labeling error rate decreased from 6.1‰ to 2.5‰ （P＜0.05）. Simultaneously operating two dispensing robots significantly improved the efficiency of batch dispensing and reduced the residual amount of liquid medicine （P＜0.05）； additionally， a quality testing system for finished infusion was established， involving appearance， Tyndall effect， insoluble particles， turbidity， absorbance， pH and osmotic pressure， to ensure the quality of finished infusion and reduce the risk of infusion. CONCLUSIONS The new process of PIVAS connected with intelligent devices in our hospital can improve work efficiency， reduce dispensing errors， ensure the quality of finished infusion， and improve the level of pharmaceutical care.

Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

OBJECTIVE To construct a prediction model for tacrolimus trough concentration based on population pharmacokinetics （PPK） information and machine learning， evaluate its predictive performance in clinical therapeutic drug monitoring （TDM） data， and provide evidence-based support for individualized dose adjustment of tacrolimus after renal transplantation. METHODS A retrospective cohort study design was adopted， and consecutive TDM records of kidney transplant recipients treated in the First Affiliated Hospital of University of Science and Technology of China （Anhui Provincial Hospital） from January to June 2025 were included to construct the final analysis set. Based on 29 input variables including previous TDM concentration， previous concentration/dose （ C / D ） ratio， and individual predicted exposure （IPRE）， 13 commonly used regression algorithm models and 1 weighted ensemble model were systematically compared. The dataset was split into training set and test set in an 80∶20 ratio by patient. Five-fold cross-validation based on patient grouping was performed on the training set， and the model performance was evaluated on the obtained evaluation points using the coefficient of determination （ R 2 ）， mean absolute error （MAE）， root mean square error （RMSE）， Pearson correlation coefficient （Corr） and ±20%/±30% accuracy. The SHapley Additive exPlanations （SHAP） method was used for model interpretability analysis to identify core predictive features. RESULTS A total of 809 consecutive TDM records from 83 kidney transplant recipients were included， with 66 cases in the training set and 17 cases in the test set. The SVR model showed the best performance， with R 2 of 0.649 8， MAE of 1.126 0 ng/mL， RMSE of 1.478 6 ng/mL， Corr of 0.819 1， ±20% accuracy of 59.68%， and ±30% accuracy of 79.03%. The Weighted Ensemble model and Extra Trees model ranked second and third， respectively. SHAP interpretability analysis showed that the top 6 features contributing to the prediction were IPRE， previous TDM concentration， previous C/D ratio， dose-normalized concentration， hematocrit （HCT）， and concentration-dose coefficient （ θ cd ）， among which IPRE was the core predictive feature （SHAP mean value 0.915 4）. CONCLUSIONS The machine learning model incorporating PPK information demonstrates good predictive ability for tacrolimus concentration in the current TDM cohort. SVR is the optimal model， IPRE is the core predictive feature of the model， and a few core PK-derived features （IPRE， dose-normalized concentration， θ cd ） together with clinical features （previous TDM concentration， HCT， etc.） constitute the main information sources for model prediction.

OBJECTIVE To provide references for medical institutions’ outpatient pharmacies to increase the scanning rate， scanning efficiency and scanning accuracy of drug traceability codes.METHODS A total of 4 157 unscanned traceability code records from the first two‑week period of June 2025 were selected from the outpatient pharmacy of our hospital. Pareto chart was adopted to analyze the reasons for unscanned codes， and the Objective-Rules-Training-Check-Culture （ORTCC） model was utilized to carry out fine management. The traceability code scanning rate， pharmacists’ work efficiency （number of prescriptions dispensed per pharmacist per hour， number of drug boxes dispensed per pharmacist per hour）， patients’ medication-waiting time and dispensing errors were compared among four periods： before scanning implementation （June 2024）， before management intervention （June 2025）， the first phase after management （September 2025）， and the second phase after management （December 2025）， so as to evaluate the management effects.RESULTS The traceability code scanning rates in the first phase and second phase after management were remarkably higher than those before management （ P ＜0.05）， and the scanning rate in the second phase after management was obviously higher than that in the first phase after management （ P ＜0.05）. Compared with the period before scanning implementation， the number of prescriptions dispensed per pharmacist per hour， the number of drug boxes dispensed per pharmacist per hour， decreased significantly and patients’ medication-waiting time prolonged markedly before management （ P ＜0.05）. In the second phase after management， both the number of prescriptions dispensed per pharmacist per hour and the number of drug boxes dispensed per pharmacist per hour increased significantly， and patients’ medication-waiting time shortened greatly in contrast with the status before management （ P ＜0.05）. Besides， no statistically significant differences were found in the number of drug boxes dispensed per pharmacist per hour and patients’ medication-waiting time between the second phase after management and the period before scanning implementation （ P ＞0.05）.After the implementation of traceability-code scanning management， dispensing errors presented a gradually declining trend in each stage.CONCLUSIONS The fine management system for outpatient drug traceability codes constructed based on Pareto chart and ORTCC model can improve the traceability code scanning rate and pharmacists’ work efficiency of outpatient pharmacies， and reduce drug dispensing errors.

OBJECTIVE To investigate the characteristics and safety of finerenone use in hospitalized patients with acute heart failure （AHF）.METHODS A single-center retrospective cohort study was conducted， enrolling 171 AHF patients who initiated finerenone therapy during hospitalization at The First Affiliated Hospital of University of Science and Technology of China between November 2023 and April 2026. Baseline characteristics， finerenone use patterns，in-hospital major and minor safety endpoints were collected. Univariate intergroup analysis， univariate and multivariate Logistic regression were performed to identify predictive factors （Firth’s penalized likelihood method was used when events were sparse）. Propensity score matching （PSM） and stabilized inverse probability of treatment weighting （sIPTW） were employed to compare the safety differences between early initiation （≤3 d） and intermediate-to-late initiation （＞3 d） of finerenone. Sensitivity analysis was conducted to verify the robustness of the hyperkalemia-related results.RESULTS A total of 171 hospitalized patients with AHF were included， with 63.7% having heart failure with preserved ejection fraction. The median time to finerenone initiation was 2 d after admission， with early initiation accounting for 64.3%， an initial dose of 10 mg once daily accounting for 83.0%， and concomitant use of sodium-glucose cotransporter 2 inhibitor （SGLT2i） accounting for 83.6%. In the overall cohort， the incidence of hyperkalemia was 3.5%， the incidence of acute kidney injury was 13.5%， and the incidence of the composite endpoint was 21.6%. Concomitant SGLT2i use was associated with a lower risk of hyperkalemia in univariable Logistic regression （OR＝0.18， 95%CI of 0.04-0.86， P ＝0.032） and showed a trend toward a protective association after multivariable Logistic regression adjustment， although this did not reach statistical significance （OR＝0.24， 95%CI of 0.05-1.21， P ＝0.084）； after multivariable Logistic regression adjustment，baseline serum potassium was independently associated with the risk of the composite endpoint （OR＝2.01， 95%CI of 1.06-3.82， P ＝0.032）. Both PSM（OR＝0.70， 95%CI of 0.27-1.83）and sIPTW（OR＝0.70， 95%CI of 0.32-1.52）analyses showed that early initiation of finerenone did not increase the risk of the composite endpoint. Sensitivity analysis results were consistent with the overall cohort analysis.CONCLUSIONS The enrolled patients initiated finerenone early with reasonable starting doses， and a high proportion received concomitant SGLT2i therapy； early initiation did not increase the risk of in-hospital hyperkalemia or acute kidney injury， with an overall favorable safety profile， and concomitant SGLT2i use showed a protective trend with respect to hyperkalemia risk.

OBJECTIVE To analyze the non-genetic risk factors for severe cutaneous adverse reactions （SCARs） related to antiepileptic drugs （AEDs） in HLA-B*15：02 negative patients， and provide a basis for clinical precision medication. METHODS A retrospective case-control design was used to include patients who underwent HLA-B*15：02 testing at our hospital from January 2022 to December 2024. Patients were divided into SCARs group （15 cases who were HLA-B*15：02 negative and diagnosed with SCARs） and control group （38 cases who were HLA-B*15：02 negative and used AEDs）. Risk factors were evaluated using univariate analysis and a multivariable Firth penalty likelihood logistic regression model （Firth regression）， and Benjamin-Hochberg false discovery rate （FDR） and Firth regression were used for correction， and sensitivity analysis was used to quantify the impact of potential biases in carbamazepine exposure rates in the control group on the results. RESULTS Univariate analysis showed that age≥50 years， use of carbamazepine， and combination use of antibiotics/antiviral drugs were risk factors for developing AEDs- related SCARs （OR＝18.15， 7.54， 13.46， 95%CI of 4.13-79.84， 1.89-30.08， 1.36-133.18， all P＜0.05）， while taking lamotrigine was a protective factor [OR＝0.10， 95%CI of 0.02-0.39， P＜0.05]. After FDR correction， the above factors still maintained statistical significance （P＜0.05）. The results of multivariate analysis showed that age≥50 years [adjusted OR＝16.27， 95%CI of 3.98-66.55， P＜0.001] and taking carbamazepine [adjusted OR＝7.11， 95%CI of 1.82-27.85， P＝0.005] were independent risk factors for the occurrence of SCARs-related AEDs. The results of sensitivity analysis showed that the adjusted risk OR range for taking carbamazepine was between 14.2 and 28.4. CONCLUSIONS Age≥50 years and use of carbamazepine are independent non- genetic risk factors for the development of SCARs-related AEDs in HLA-B*15：02 negative patients. It is recommended that elderly patients should prioritize the use of AEDs other than carbamazepine.

OBJECTIVE To report a case of hepatitis B virus （HBV） reactivation induced by iparomlimab and tuvonralimab， summarize the clinical characteristics and potential mechanisms of such adverse reactions induced by immune-checkpoint inhibitors （ICIs）， and provide references for clinical application. METHODS From the perspective of a clinical pharmacist， a retrospective analysis was conducted on the treatment course of a patient with metastatic cervical cancer who experienced HBV reactivation after receiving iparomlimab and tuvonralimab. Additionally， an analysis of the correlation with adverse reactions was performed， and the clinical characteristics， risk factors， potential mechanisms， key points of treatment approaches and pharmaceutical care associated with HBV reactivation induced by ICIs were summarized. RESULTS & CONCLUSIONS The patient developed HBV reactivation and severe liver injury after using iparomlimab and tuvonralimab. The condition improved following drug discontinuation， and symptomatic treatment such as glucocorticoids. According to Naranjo’s Assessment Scale and China’s Measures for the Reporting and Monitoring of Adverse Drug Reactions， the association between iparomlimab and tuvonralimab and HBV reactivation was judged as “highly probable”， and it was identified as a new adverse reaction； the correlation between iparomlimab and tuvonralimab， paclitaxel and liver injury was “highly probable”. HBV reactivation in hepatitis B patients receiving standardized antiviral therapy is very rare after ICIs treatment； HBV reactivation is related to the overactivation of the immune system and disruption of immune balance induced by ICIs. For such patients， glucocorticoids should be administered for treatment， accompanied by pharmaceutical care， including pre- medication risk assessment and monitoring of relevant indicators during treatment.

[Objective] To investigate the factors associated with alanine aminotransferase (ALT) abnormalities in multi-ethnic blood donors across five Zang autonomous prefectures in the plateau regions of Qinghai Province, and to provide evidence for ensuring blood safety and formulating screening strategies. [Methods] A retrospective analysis was performed on the ALT abnormal test results of blood donors in the Zang autonomous prefectures of Qinghai from 2022 to 2024. The correlations between ALT levels and factors including gender, age, altitude, and infectious markers were investigated. [Results] The overall ALT unqualified rate among blood donors in this region was 9.01%. Significant differences in ALT levels were observed across genders and age groups (P<0.05). Variations in ALT abnormality rates were also noted among different plateau regions (P<0.05). Overall, ALT values exhibited an increasing trend with rising altitude. The average ALT unqualified rates were 11.19% in Zang donors, 7.96% in Han donors, and 4.79% in donors from other ethnic groups (P<0.05). No statistically significant association was observed between ALT abnormality and the presence of HBV/HCV infectious markers (P>0.05). [Conclusion] In the plateau areas of Qinghai, multi-ethnic blood donors have a relatively high ALT levels and ALT unqualified rates, showing distinct regional characteristics. ALT elevation in voluntary blood donors is related to non-pathological factors such as gender, age, and dietary habits, but not to infectious indicators.

Objective Based on the national drug sampling inspection program,this study aims to comprehensively and systematically evaluate the quality of Xuanmai Ganjie preparations,analyze existing quality issues,and provide references and suggestions for quality control of this variety.Methods A total of 237 batches of Xuanmai Ganjie preparations were tested using legal standards,and methods were established for detecting adulteration of Ophiopogon japonicus with counterfeit varieties,paclobutrazol residue levels,and determining the content of platycodin D in Xuanmai Ganjie preparations.These methods were applied to the quality control and evaluation of Xuanmai Ganjie preparations.Results Through statutory inspection,one batch of Xuanmai Ganjie granules was found non-compliant.Specific batches were identified to contain the following irregularities:adulteration of Ophiopogon japonicus with counterfeit varieties,paclobutrazol residue levels exceeding proposed limits,and platycodin D content below the established threshold.Conclusion The overall quality of Xuanmai Ganjie granules was average,while the overall quality of Xuanmai Ganjie capsules and lozenges was relatively good.Manufacturing enterprises should strengthen their sense of primary responsibility and enhance control over the entire drug production process.

Objective To evaluate the recognition capability of AI-enabled Cellsee CS-BM1 automatic cell morphology analyzer for pe-ripheral blood smears and its roles in assisting manual classification,and explore the application value of AI system in the diagnosis network of tiered primary medical units.Methods The blood samples which triggered the re-examination rules were collected from six primary medical units,including the Laboratory Department of Shanghai Jiahui International Hospital,and so on,from March to No-vember 2023.The smears of peripheral blood were prepared and AI analyzer was used for pre-classification to evaluate its recognition performance in identifying the samples with abnormal WBC and RBC.The sensitivity,specificity,and accuracy of WBC classification by six junior and intermediate technicians,both with and without AI assistance,were analyzed.Additionally,the roles of the AI system in tiered diagnosis of primary medical units were also evaluated.Results The sensitivity,specificity,and accuracy of AI system in recognizing malignant primitive cells were 92.86％,95.16％,and 95.10％,respectively.The sensitivities of AI system in recognizing immature granulocytes,reactive lymphocytes,and nucleated RBCs were all greater than 90％.The sensitivity of AI system in identif-ying abnormal morphology of RBCs reached 99.59％,along with rapid quantitative analysis for various anomalous types of RBCs.In AI-assisted mode,the sensitivity of recognition for all cell types was improved to varying degrees by junior and intermediate technicians,and the sensitivity for recognizing malignant primitive cells,reactive lymphocytes,and immature granulocytes increased to 58.24％,53.39％,and 62.37％for junior technicians,and to 92.06％,83.24％,and 83.12％for intermediate technicians,respectively.The improvements for junior technicians were particularly significant,with increases of 12.46％,10.61％,and 3.71％for each cell type,respectively.Both groups achieved higher specificity and accuracy.Through AI pre-classification and manual review,a variety of pe-ripheral blood cell-related diseases were accurately diagnosed in the tiered healthcare practice of primary medical units,including 339 cases(11.13％)of red blood cell diseases,5 cases(0.16％)of platelet diseases,2 343 cases(76.90％)of infection-related disea-ses,and 28 cases(0.92％)of malignant hematological diseases.In addition,332 cases(10.90％)which lacked an obvious related cause or required further examinations were identified as well.Conclusion AI pre-classification has demonstrated strong cell recogni-tion capabilities and may assist technicians in improving the sensitivity,specificity,and accuracy of blood cell classification.AI could en-hance the disease-screening capabilities in the tiered diagnosis network of primary medical units,presenting a broad application prospect.