OBJECTIVE To systematically analyze the compatibility stability of commonly used intravenous antibiotics in the intensive care unit （ICU）， and to provide evidence-based support for rational clinical drug use. METHODS Medication data from the ICU of Hebei General Hospital between January and December 2024 were extracted from the Prescription Automatic Screening System. Commonly used intravenous antibiotics and other intravenous drugs in the ICU were selected through consultations with critical care and pharmacy experts in Hebei province， drug package inserts and compatibility information retrieved from Micromedex， Trissel’s Injectable Drug Handbook and PubMed. The physicochemical stability of drug combinations was analyzed. In addition， Cytoscape 3.10.2 software was used to construct a drug compatibility network for identifying high-risk drugs. RESULTS &CONCLUSIONS A total of 904 pairwise drug combinations involving 16 antibacterial agents and 65 intravenous drugs were collected. Among them， 549 combinations （60.7%） were compatible， 88 combinations （9.7%） were incompatible， 82 combinations （9.1%） had conflicting evidence， and 185 combinations （20.5%） lacked valid data support. High-risk combination drugs primarily involved Amphotericin B for injection， Ceftazidime for injection， Imipenem-cilastatin for injection， Ceftriaxone sodium for injection， Vancomycin hydrochloride for injection， etc. The main risk factors for drug-drug incompatibility included drug concentration， temperature， mixing rate， pH， and chemical structure. In clinical practice， drugs and diluents should be selected rationally based on specific compatibility data， and research and monitoring of drug compatibility should be further strengthened.

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.

Objective To develop a Self-Report Scale of Symptoms for Post Intensive Care Syndrome-Family(PICS-F)and validate its reliability and validity,providing a scientific tool for healthcare professionals to comprehensively assess post intensive care syndrome-family.Methods Based on the symptom experience dimension of Symptom Management Theory,a preliminary version of the scale was developed through literature analysis,semi-structured interviews,expert consultations,and a pilot survey.A convenience sampling method was used to conduct the pre-trial version of the scale questionnaire survey on 442 family members of ICU patients at a tertiary A comprehensive hospital in Wuhan from June to September 2024.The test of the validity and reliability was conducted.Results The developed scale consists of 4 dimensions and 20 items.Exploratory factor analysis identified 4 factors,with a cumulative variance contribution rate of 70.921％.The content validity index at the scale level was 0.941,and the content validity indices for individual items ranged from 0.809 to 1.000.Confirmatory factor analysis indicated that the model fit indices were within acceptable ranges.The overall Cronbach's αcoefficient for the scale was 0.941,and the split-half reliability was 0.832.Conclusion The Self-Report Scale of Symptoms for PICS-F demonstrates good reliability and validity.It can comprehensively reflect the primary symptoms of PICS-F,and can serve as an effective measurement tool for clinicians to assess PICS-F in family members of ICU patients.

Objective:To explore the formulation patterns and potential targets of traditional Chinese medicine (TCM) in the treatment of pneumoconiosis using data mining, network pharmacology, and Mendelian randomization (MR) .Methods:In November 2023, prescription data for TCM compound treatments of pneumoconiosis from the past five years were retrieved from the China National Knowledge Infrastructure (CNKI), Wanfang, and VIP databases. The formulation patterns of TCM for pneumoconiosis were analyzed based on drug frequency, association rules, and cluster analysis, followed by the identification of core drugs. Network pharmacology and MR analysis were then applied to determine the potential targets for pneumoconiosis treatment.Results:A total of 100 TCM prescriptions were included, involving 182 herbs, with 15 high-frequency herbs. A total of 24 strong association rules were identified, including 16 herbs. Cluster analysis identified three groups of drug combinations. The core drug combination, "Astragalus Root-Codonopsis Root-Tangkuei-Chinese Magnolia Vine Fruit-Danshen Root-Prepared Rehmannia Root" was determined, which interacted with 47 common targets associated with pneumoconiosis. Further protein-protein interaction (PPI) analysis identified 18 core targets, and MR analysis confirmed that Caspase-3 (CASP3) and Cathepsin B (CTSB) were risk factors for pneumoconiosis ( OR=1.35, 1.44; P=0.038, 0.038) . Conclusion:The core drug combination for the treatment of pneumoconiosis with TCM is "Astragalus Root-Codonopsis Root-Tangkuei-Chinese Magnolia Vine Fruit-Danshen Root-Prepared Rehmannia Root". The medication mainly focuses on tonifying lung qi, moistening dryness and stopping coughing, circulating blood and transforming stasis, which are supplemented with herbs for nourishing yin and moistening dryness, warming yang and dissipating cold. Finally, the key targets for treating pneumoconiosis are screened out, providing an important basis for the development of therapeutic drugs for it.

Objective:To assess the preliminary efficacy and safety of modified Société Internationale d′Oncologie Pédiatrique Epithelial Liver Tumor Study Group (SIOPEL)-4 protocol for pediatric hepatoblastoma (HB) with lung metastases.Methods:This prospective cohort study enrolled 27 newly diagnosed pediatric HB with lung metastases who received the modified SIOPEL-4 protocol at Shanghai Children′s Medical Center, Shanghai Jiao Tong University School of Medicine, and Shanghai Children′s Hospital between January 2020 to December 2023. Clinical characteristics, lung response rates to induction chemotherapy, treatment outcomes, prognostic factors and sever chemotherapy toxicities at different stages were analyzed. Survival analysis was performed by Kaplan-Meier method. Univariate prognostic analysis was conducted by Log-Rank test.Results:Of the 27 patients, there were 17 males and 10 females, with the age of 21 (15, 33) months. During the follow-up of 31 (12, 45) months for 17 continuous complete remission patients, 4 cases disease progression (2 cases death) and 6 cases relapse were observed. The 2-year event free survival (EFS) and overall survival (OS) rate was (58±11)% and (89±7)%, respectively. All the 27 patients had response to block 1-3 induction chemotherapy (cisplatin+doxorubicin), with 14 cases (52%) achieving complete response and 13 cases (48%) achieving partial response of lung metastatic lesions, the 2-year EFS rate was (81±12)% and (34±14)%, respectively ( χ 2=6.76, P=0.009), the 2-year OS rate was 100% and (79±13)%, respectively ( χ2=2.12, P=0.145). Patients with caudate lobe tumors or ≥10 pulmonary metastatic nodules had significantly lower EFS rates ( χ2=5.36, 7.84, P=0.021, 0.005, respectively). The incidence of grade 3/4 neutropenia after block 1-3 induction chemotherapy, CD (carboplatin+doxorubicin), and VI (vincristine+irinotecan) consolidation chemotherapy was 90% (73/81), 75% (58/77), and 31% (11/35), respectively. The incidence of grade 3/4 thrombocytopenia was 77% (62/81), 69% (53/77), and 14% (5/35), respectively. The incidence of grade 3/4 infections was 64% (52/81), 25% (19/77), and 20% (7/35), respectively. The differences between the groups were statistically significant ( χ2=43.51, 42.69, 33.00, all P<0.001). Two patients (10%) of the 20 evaluable patients for ototoxicity occurred grade 3 and higher hearing impairment, with 1 patient requiring a hearing aid. Conclusions:The modified SIOPEL-4 regimen shows good preliminary efficacy and safety in treating pediatric HB with lung metastases. The prognosis for patients with residual lesions in the lungs after induction chemotherapy needs to be improved. Attention should be given to the ototoxicity induced by high-dose cisplatin chemotherapy.

BACKGROUND:In recent years,with the rapid development of biomedicine,the study of brain aging and exosomes has attracted more and more attention,but there is no bibliometrics analysis in this field. OBJECTIVE:To objectively analyze domestic and foreign literature on brain aging and exosomes in the past 15 years,to summarize the research status,hot spots,and development trends in this field. METHODS:Using the core database of Web of Science as a search platform,we downloaded the literature on brain aging and exosomes published from the establishment of the database to December 28,2022,and analyzed the data from the aspects of country or region,institution,author,keywords,and co-cited literature using CiteSpace 6.1.R6 visualization software. RESULTS AND CONCLUSION:A total of 1 045 research articles were included,and the number of publications on brain aging and exosomes research both domestically and internationally was showing an increasing trend year by year.The United States ranked first with 429 papers,and China ranked second with 277 papers.Louisiana State University ranked first with 16 articles.Professor Lukiw Walter J from Louisiana State University in the United States was the author with the highest number of publications,and Professor Bartel DP from the Massachusetts Institute of Technology was the author with the most citations.The most prolific Journal was the International Journal of Molecular Sciences.Alzheimer's disease,microRNA,gene expression,extracellular vesicles,exosomes,oxidative stress,and biomarkers are the most relevant terms.According to the research on hot topics,biomarkers have become a new research hotspot.The above results indicate that the research on brain aging and exosomes has gradually increased in the past 15 years.The research direction has gradually shifted from the initial exploration of the expression of miRNAs in central nervous system diseases related to brain aging to the search for biomarkers that can identify and diagnose neurodegenerative diseases.The study of exocrine miRNAs to protect central nervous system from damage has emerged as promising therapeutic strategy.

Objective:To analyze the clinical characteristics of adverse reactions caused by dinutuximab β for the treatment of neuro-blastoma(NB)in China and to provide safety evidence for the rational use of dinutuximab β in clinical practice.Methods:Clinical data were retrospectively collected from 16 pediatric patients with NB who had been treated with dinutuximab β at Shanghai Children's Medical Center Affiliated to Shanghai Jiao Tong University School of Medicine from January 2022 to November 2023,and the adverse reactions caused by dinutuximab β were summarized and analyzed.Results:The male-to-female ratio was 5:3 among the 16 children with NB.The retroperitoneum was the main initial site of involvement,accounting for 75%.Thirteen(81.25%)patients had high-risk NB.The adverse reactions caused by dinutuximab β mainly included decreased hemoglobin,fever,vomiting,and diarrhea.The inci-dence of adverse reactions was highest in the first course of treatment,and the median time of adverse reactions was 2-5 days.Conclu-sion:Targeted monitoring should be carried out at an early stage during dinutuximab β administration.Adverse reactions should be de-tected and managed early to ensure the safety of medication for children.

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.

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.

Objective:To investigate the predictive value of machine learning-based CT radiomics model for radioresistance in patients with esophageal squamous cell carcinoma (ESCC).Methods:Clinical data of 185 patients with ESCC treated with radical radiotherapy in the First Affiliated Hospital of Anhui Medical University from December 2015 to July 2022 were retrospectively analyzed, and all patients were randomly divided into a training set ( n=129) and a validation set ( n=56) at a ratio of 7 : 3. The radiomics parameters of the primary lesion of esophageal cancer and the surrounding 5 cm region in the patients' CT arterial phase images were extracted, and 6 machine learning methods were used to screen the optimal radiomics model to obtain the optimal radiomics score (Radscore). Independent prognostic predictors of radioresistance in ESCC were obtained by univariate and multivariate logistic regression analyses, which was used as the basis for constructing the nomogram. The predictive performance of different models was compared by the area under the receiver operating characteristic (ROC) curve (AUC). The predictive efficacy and clinical value of the combined model were evaluated using calibration curve, decision curve analysis and clinical impact curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results:The combined intratumoral and peritumoral radiomics model based on naive Bayesian classifier yielded the optimal prediction performance, with AUC of 0.859 and 0.936 in the training set and validation set, respectively. Multivariate logistic regression analysis showed that Radscore and T stage were the independent prognostic predictors of radioresistance in ESCC patients, and the AUC of the combined model constructed based on these predictors in the training and validation sets were 0.942 and 0.959, respectively. Calibration curve, decision curve analysis and clinical impact curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) all indicated higher clinical benefit and more consistent predictive efficacy of the combined model.Conclusions:Machine learning-based CT radiomics model is useful for the prediction of radioresistance in ESCC. The nomogram of radiomics and clinical parameters can further improve the prediction accuracy and provide novel reference for individualized treatment of patients with ESCC.