Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

Objective: To investigate the clinical characteristics, treatments and fertility recovery of rudimentary horn pregnancy (RHP). Methods: The clinical data of 12 cases with RHP diagnosed and treated in Peking University Third Hospital from January 1, 2010 to December 31, 2022 were retrospectively analyzed. Clinical informations, diagnosis and treatments of RHP and the pregnancy status after surgery were analyzed. Results: The median age of 12 RHP patients was 29 years (range: 24-37 years). Eight cases of pregnancy in residual horn of uterus occurred in type Ⅰ residual horn of uterus, 4 cases occurred in type Ⅱ residual horn of uterus; among which 5 cases were misdiagnosed by ultrasound before surgery. All patients underwent excision of residual horn of uterus and affected salpingectomy. After surgery, 9 patients expected future pregnancy, and 3 cases of natural pregnancy, 2 cases of successful pregnancy through assisted reproductive technology. Four pregnancies resulted in live birth with cesarean section, and 1 case resulted in spontaneous abortion during the first trimester of pregnancy. No uterine rupture or ectopic pregnancy occurred in subsequent pregnancies. Conclusions: Ultrasonography could aid early diagnosis of RHP while misdiagnosis occurred in certain cases. Thus, a comprehensive judgment and decision ought to be made based on medical history, physical examination and assisted examination. Surgical exploration is necessary for diagnosis and treatment of RHP. For infertile patients, assisted reproductive technology should be applied when necessary. Caution to prevent the occurrence of pregnancy complications such as uterine rupture, and application of cesarean section to terminate pregnancy are recommended.
Pregnancy ; Humans ; Female ; Young Adult ; Adult ; Cesarean Section/adverse effects* ; Retrospective Studies ; Pregnancy, Ectopic/surgery* ; Pregnancy, Cornual/surgery* ; Uterus/surgery* ; Uterine Rupture/etiology* ; Abortion, Spontaneous

Lithium(Li)salts are commonly used as psychotropic medications for the treatment of major depressive disorders.However,long-term use of Li salts poses a high risk of toxicity,necessitating continuous monitoring of Li concentration in patient blood to ensure medication safety,which is crucial for clinical treatment.Laser-induced breakdown spectroscopy(LIBS),as a rapid analytical technique,has been widely applied in the elemental analysis of complex matrices in various practical scenarios.In this study,LIBS technology combined with partial least squares(PLS)was employed for quantitative analysis of Li elements in blood matrix.A total of 45 clinical blood samples were utilized,and the quantitative models for plasma and whole blood matrices were separately investigated.The number of latent variables in the PLS algorithm was optimized using a five-fold cross-validation method.Results revealed that the PLS quantitative model constructed on the basis of plasma matrix achieved a predictive determination coefficient(R2)of 0.992,a predictive root mean square error(RMSEP)of 0.204 μg/mL,and a relative standard error(RSD)of 2.14%.In contrast,for the PLS quantitative model constructed on the basis of whole blood matrix,the R2 was 0.984,the RMSEP was 0.728 μg/mL,and the RSD was 3.45%Consequently,the LIBS model constructed on the basis of plasma calibration values demonstrated superior performance in quantitative analysis of Li element in whole blood,and LIBS technology provided a new possibility for rapid assessment of blood Li levels in clinical practice,with promising prospects for application.

Objective We aim to analyse semaglutide related adverse events in real-world,overall and by gender and age subgroups and compare the differences of different gender and age patients in adverse events,in order to supply references for security usage in the clinic.Methods OpenVigil 2.1 was used to search FDA Adverse Event Reporting System for semaglutide related adverse events from the establishment of the databases to April 2023.According to age and gender,patients were divided into 18-64 years old group and≥65 years old group,male group and female group.We selected ten adverse events which we interested(nausea,diarrhoea,vomiting,pancreatitis,cholecystitis,cholelithiasis,hypoglycaemia,diabetic retinopathy,acute kidney injury and thyroid cancer/medullary thyroid cancer)and analyzed overall and each group of semaglutide adverse events.Results A total of 5 330 cases and 15 558 adverse events were collected.2 935 patients aged 18-64 old group years with 8 553 adverse events;2 395 patients aged≥65 years old group with 7 005 adverse events.2 231 male group patients with 6 195 adverse events;3 059 female group patients with 9 277 adverse events.The sex of 40 patients was unknown.Nausea(1 089 cases/7.00％),vomiting(775 cases/4.98％)and diarrhoea(545 cases/3.50％)remained the most common adverse events.The constituent ratio of pancreatitis was significantly higher in patients aged 18-64 years old group than in patients aged 65 years old group(P＜0.05);the constituent ratio of diarrhoeaand cholelithiasis was significantly lower in patients aged 18-64 years old group than patients aged≥65 years old group(P＜0.05).The constituent ratio of diarrhoea,vomiting,pancreatitis,cholecystitis,cholelithiasis,diabetic retinopathy,and acute kidney injurywas significantly higher in male group patients than in female group(P＜0.05).Conclusion Nausea,diarrhoea and vomiting remined the most common adverse events of semaglutide.Male should be more concerned about gastrointestinal,pancreatitis,gallbladder events,retinopathy and acute kidney injury.Elderly patients should be more alert diarrhoea and cholelithiasis.

BACKGROUND:Observational studies have suggested that statins may have a protective effect against osteoarthritis,including knee osteoarthritis and hip osteoarthritis.However,the association between statins and the risk of osteoarthritis remains unclear. OBJECTIVE:To investigate the association between statins and the risk of osteoarthritis through Mendelian randomization analysis using summary data from large-scale population-based genome-wide association studies(GWAS). METHODS:Firstly,single nucleotide polymorphism data related to statins were obtained from the latest 9th edition of the FinnGen database,while data of osteoarthritis,knee osteoarthritis and hip osteoarthritis were obtained from the IEU Open GWAS,UK Biobank,and ArcOGEN(Genetics of Osteoarthritis)databases,respectively.The inverse variance weighted method was used as the primary analysis approach to evaluate the causal effects.The weighted median method,simple median method,weighted mode-based method,and MR-Egger regression were used as supplementary analyses.The causal relationship between statins and the risk of osteoarthritis,knee osteoarthritis and hip osteoarthritis was assessed using odds ratios(OR)with 95%confidence intervals(CI).Sensitivity analyses were conducted to validate the reliability of the results,including the Cochran's Q test for heterogeneity and the MR-Egger-intercept test for horizontal pleiotropy,as well as leave-one-out analysis to identify potentially influential single nucleotide polymorphisms. RESULTS AND CONCLUSION:The inverse variance weighted analysis demonstrated a negative causal relationship between genetically predicted statins and the risk of osteoarthritis(OR=0.998,95%CI:0.996-0.999,P=0.01),knee osteoarthritis(OR=0.964,95%CI:0.940-0.989,P=0.005),and hip osteoarthritis(OR=0.928,95%CI:0.901-0.955,P=4.28×10-7).MR-Egger intercept analysis did not detect potential horizontal pleiotropy(osteoarthritis:P=0.658;knee osteoarthritis:P=0.600;hip osteoarthritis:P=0.141).The results of this study provide evidence that statins reduce the risks of osteoarthritis,knee osteoarthritis and hip osteoarthritis as described in observational studies.Further research is needed to explore the specific mechanisms of statin treatment for osteoarthritis.

Objective To explore the effect of cardiac shock wave therapy(CSWT)on ST deviation of electrocardiogram and myocardial perfusion imaging in coronary artery disease(CAD)patients.Methods CAD patients who received CSWT in Cardiology Department of Beijing Hospital from December 2016 to August 2022 were enrolled.Three months of CSWT were conducted with a total of 9 times shock wave treatment.Clinical data,myocardial perfusion imaging data and stress electrocardiogram data were collected.Myocardial perfusion score,electrocardiographic data were compared before and after CSWT.Results A total of 55 patients were finally enrolled.There were 43 male and 12 female patients with an average age of(67.45±8.96)years old.ST deviation on 12 leads of electrocardiogram did not show significant difference before and after CSWT.Myocardial perfusion imaging showed global stress perfusion score(P=0.031)and reverse perfusion score(P=0.024).Global rest ischemia score reduced after CSWT(P=0.034).Target stress perfusion score(P=0.002),target reverse perfusion score(P=0.002),target reverse ischemic area(P=0.001)were improved after CSWT.Conclusions CSWT may not influence ST deviation of electrocardiogram,but may improve myocardial ischemia in CAD patients,

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.