OBJECTIVE To summarize the current situation of pharmaceutical clinic service in our hospital over the past five years， and explore sustainable development strategies for service models of pharmaceutical clinics. METHODS A retrospective analysis was conducted on the consultation records of patients who registered and established files at the pharmaceutical clinic in our hospital from January 2019 to December 2023. Statistical analysis was performed on patients’ general information， medication- related problems， and types of pharmaceutical services provided by pharmacists. RESULTS A total of 963 consultation records were included， among which females aged 20-39 years accounted for the highest proportion （66.04%）； obstetrics and gynecology- related consultations accounted for the largest number of cases. Additionally， 80 patients attended follow-up visits at our hospital’s pharmaceutical clinic. A total of 1 029 medication-related issues were resolved， including 538 cases of drug consultations （52.28%）， 453 medication recommendations （44.02%）， 22 medication restructuring（2.14%）， and 16 medication education （1.55%）； the most common types of medication-related problems identified were adverse drug events（70.07%）. CONCLUSIONS Although the pharmaceutical clinic has achieved recognition from clinicians and patients， challenges such as low awareness among healthcare providers and the public persist. Future efforts should focus on strengthening information technology construction， enhancing pharmacist training， and establishing various forms of outpatient pharmaceutical service models.

Objective:To explore the changes of serum histone deacetylase 2 (HDAC2), lonely G protein-coupled receptor ligand (Apelin) and B-type brain natriuretic peptide (BNP) in patients with chronic obstructive pulmonary disease (COPD) and the predictive value for prognosis.Methods:A retrospective selection was made of 100 COPD patients (COPD group) admitted to the Fourth People's Hospital of Langfang from May 2022 to May 2023 and 50 healthy individuals who underwent physical examinations during the same period (healthy control group) as the research subjects. The levels of serum HDAC2, Apelin and BNP in the two groups were compared. The levels of HDAC2, Apelin and BNP in COPD patients with different clinical characteristics were compared. The correlation among serum HDAC2, Apelin and BNP in COPD patients were analyzed by Spearman test. The predictive value of serum HDAC2, Apelin and BNP for the prognosis of patients with COPD was analyzed by the receiver operating characteristic (ROC) curve.Results:The level of HDAC2 in the COPD group was lower than that in the healthy control group, the levels of Apelin and BNP were higher than those in the healthy control group: (2.38 ± 0.56) U/L vs. (7.51 ± 1.33) U/L, (491.62 ± 53.82) ng/L vs. (337.19 ± 46.52) ng/L, (211.05 ± 23.46) ng/L vs. (37.52 ± 4.32) ng/L, there were statistical differences ( P<0.05). COPD patients with different clinical characteristics, including those in acute exacerbation and stable stages, mild, moderate and severe cases, COPD patients with pulmonary function grades Ⅱ, Ⅲ and Ⅳ, COPD patients with and without pulmonary hypertension, and patients with poor prognosis and good prognosis, there were statistically significant differences in the levels of HDAC2, Apelin and BNP ( P<0.05). The Spearman test results indicated that in COPD patients, serum HDAC2 was negatively correlated with Apelin ( r = - 0.469, P = 0.001), HDAC2 was negatively correlated with BNP ( r = - 0.435, P = 0.001), and Apelin was positively correlated with BNP ( r = 0.418, P = 0.001). The results of ROC curve analysis indicated that the combined detection of HDAC2, Apelin and BNP had the highest area under the curve for predicting the prognosis of COPD patients (0.954), with a sensitivity of 81.66%. Conclusions:COPD patients have lower HDAC2 and higher Apelin and BNP levels. The three indicators are correlated to a certain extent, and their levels are closely related to the clinical characteristics of patients. The combined detection of the three indicators can be used as important predictive indicators for the prognosis of COPD patients.

Objective:To investigate the current status and challenges of pediatric life support training in China and provide references for improving training quality.Methods:A cross-sectional study was conducted to collect data from pediatric life support training centers across the country，covering basic institutional information，training capacity and training faculty，training program funding，as well as existing challenges and issues.The domestic registry of training centers in 2023 was obtained through the American Heart Association's online platform.After contacting and verifying each center，an online questionnaire was distributed，and the aggregated data were statistically analyzed.Results:A total of 42 institutions participated in the survey，including 19 children's hospitals，14 general hospitals，6 maternal and child health hospitals，2 women and children’s hospitals，and 1 training institution.The distribution of training centers showed a concentration in coastal areas，with the top three provinces/municipalities being Guangdong（7/42，16.7%），Zhejiang（6/42，14.3%），and Shanghai（4/42，9.5%）.As of December 31 2023，the 42 institutions had an annual basic life support（BLS）training volume of 8 587 individuals，the median was 120 (100,200)，and an annual pediatric advanced life support（PALS）training volume of 2 448 individuals，the median was 30 (20,50).Among the 42 institutions，there were 598 BLS instructors and 306 PALS instructors.Among the surveyed institutions，24（24/42，57.1%）reported BLS instructor teams comprising fewer than 10 members，and 33（33/42，78.6%）reported PALS instructor teams comprising fewer than 10.Only 7 centers(7/42,16.7%）reported having dedicated funding support.The top three challenges were：training sessions occupying instructors’personal time（27/42，64.3%），low instructor compensation（16/42，38.1%），and issues with the data submission system（16/42，38.1%）.Conclusion:Pediatric life support training centers in China are primarily children’s hospitals，with a geographical concentration in coastal areas，which is also reflected in the distribution of training scale and instructor resources.Most centers have relatively small training scales and limited instructor capacity，with many instructors conducting training during their personal time.These issues may hinder the implementation and effectiveness of training programs.

Objective To explore the value of radiomics model and deep learning model based on unenhanced MRI in predicting microvascular invasion(MVI)of hepatocellular carcinoma(HCC)preoperatively.Methods A total of 189 patients with postopera-tive pathologically confirmed HCC from two centers were retrospectively selected,of which 119 cases from Zhujiang Hospital of Southern Medical University were used as the training set[60 cases with negative MVI,59 cases with positive MVI],and 70 cases from Shenzhen People's Hospital were used as the external test set[38 cases with negative MVI and 32 cases with positive MVI].Clinical indicators were analyzed by univariate and multivariate logistic regression analysis and the independent predictors of positive MVI were screened.Deep transfer learning(DTL)and traditional radiomics methods were used to construct radiomics model and deep learning model based on unenhanced MRI.The predictive performances of each model were compared using receiver operating charac-teristic(ROC)curves and area under the curve(AUC).DeLong test was employed to compare statistical differences in performance of the models.Results Alkaline phosphatase(ALP)and prothrombin time(PT)were independent predictors of positive MVI(P<0.05).The deep learning model based on T2WI had the best predictive efficacy,with AUC of 0.779[95%confidence interval(CI)0.696-0.863]and 0.741(95%CI 0.620-0.861)in the training set and external test set,respectively,and there were statistically significant differences compared with the radiomics model and the clinical model based on T1WI(P<0.05).Conclusion Deep learning model based on T2WI has a certain application value in preoperative noninvasive prediction of MVI status in HCC patients.

The paper reports a 32-year-old female acute myeloid leukemia patient who developed graft-versus-host disease after paternal hematopoietic stem cell transplantation, which subsequently led to renal thrombotic microangiopathy. She subsequently required a kidney transplant from the same donor 5 years later due to renal failure. Considering that both the bone marrow and kidney were from the same donor and the recovery of renal function was favorable, immunosuppressive therapy was discontinued after a short course of anti-rejection treatment, with maintained stable kidney function. This case suggests that under the condition of high chimerism, allogeneic hematopoietic stem cell transplantation and kidney transplantation from the same donor can achieve immune tolerance, potentially improving solid organ transplantation success rate. The findings provide a novel therapeutic approach for solid organ transplantation following allogeneic hematopoietic stem cell transplantation.

Objective:To construct a nomogram prediction model for the malignant risk of breast lesions based on quantitative multimodal ultrasound features and clinical indicators，and to explore its clinical application value.Methods:A total of 430 patients with breast diseases（473 lesions）confirmed by pathological examination at Kunshan Traditional Chinese Medicine Hospital from August 2018 to December 2023 were retrospectively analyzed in the study. All the patients underwent routine handheld ultrasound（HHUS），automated breast volume scanning（ABVS）and ultrasound elastography（UE）examinations before biopsy or surgery. Four hundred and seventy-three breast lesions were randomly divided into training set（ n=331）and validation set（ n=142）at a ratio of 7∶3. The ABVS ultrasound features of 331 lesions in the training set were analyzed to identify the risk features of malignant breast lesions. Based on the weight of the regression coefficients β，the ABVS risk features were assigned quantitative scores for each lesion. Using pathology results as the gold standard，ROC curves were plotted to compare the diagnostic efficacy of ABVS quantitative scoring and HHUS in the training set. The variable with higher efficacy was selected for inclusion in the multivariable logistic regression analysis. Based on the identified independent predictive factors，a nomogram was constructed to quantify the malignancy risk of breast lesions. The nomogram was evaluated and validated using the area under the ROC curve（AUC），calibration curve and clinical decision curve analysis（DCA）. Results:The AUC for ABVS quantitative scoring and HHUS in distinguishing benign and malignant breast lesions were 0.941 and 0.903，respectively，with a statistically significant difference（ Z=2.081， P=0.037）. Multivariate Logistic regression analysis showed that age，ABVS quantitative score and elasticity score were independent predictors for the identification of benign and malignant breast lesions（all P<0.05）. A nomogram was constructed based on the aforementioned independent predictive factors. The AUC for the nomogram were 0.968 in the training set and 0.943 in the validation set，indicating good discrimination. The calibration curve indicated that the predicted probabilities from the nomogram were in good agreement with the actual outcomes. DCA indicated strong clinical applicability of the nomogram. Conclusions:The nomogram based on ABVS quantitative scores，elasticity scores，and age demonstrates high diagnostic value，providing a novel method for preoperative assessment of the malignancy risk of breast lesions.