BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

Objective To explore the dynamic changes of gut microbiota metabolites in septic patients following admission, as well as the correlations between these metabolites, the gut microbiota, and the prognosis of septic patients. Methods A total of 119 fecal samples were collected from 23 septic patients, 16 non-septic patients admitted to the Emergency Intensive Care Unit (ICU), and 20 healthy controls at Zhongshan Hospital, Fudan University, from January to August 2019. The 16S rRNA gene sequencing technology was applied to analyze the microbiome, while ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) was used for metabolomics research. The R software was used to analyze the gut microbiota and metabolite data. Based on 180-day survival status after admission, the sepsis group was divided into the survival group (n＝15) and the death group (n＝8) to analyze differential metabolites between the two groups. Spearman correlation coefficients were used to assess correlations between gut microbiota and metabolites. Results In the first week of ICU stay, gut microbiota metabolites such as nicotinic acid, methylsuccinic acid, and glutaric acid were significantly lower in septic patients than in healthy controls (P＜0.05), whereas tryptophan, histidine, valine, and pyroglutamic acid were higher in septic patients (P＜0.05). The methylsuccinic acid and phenylacetic acid levels in the first week were lower in the death group than those in the survival group (P＜0.05), and the levels of methylsuccinic acid, phenylacetic acid, and glutaric acid were lower in the third week (P＜0.05). Further analysis indicated that methylsuccinic acid was closely associated with sepsis prognosis. These differential metabolites involved in metabolic pathways such as phenylalanine metabolism and β-alanine metabolism. Most differential amino acids were positively correlated with opportunistic pathogens but negatively correlated with normal gut microbiota. Conversely, metabolites such as nicotinic acid, phenylacetic acid, methylsuccinic acid, and glutaric acid were negatively correlated with opportunistic pathogens and positively correlated with normal gut microbiota. Conclusions Significant dynamic changes occur in gut microbiota metabolites in septic patients, with methylsuccinic acid, phenylacetic acid, and glutaric acid potentially playing important roles in determining patient prognosis.

OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.

Irritable bowel syndrome with diarrhea （IBS-D）， as a prototypical disorder involving the microbiota-gut-brain axis， remains poorly understood in terms of its pathogenesis， posing ongoing challenges for clinical diagnosis. Omics technologies， leveraging their high-throughput detection and systematic analysis advantages， has emerged as a critical tool for deciphering the complex mechanisms underlying traditional Chinese medicine （TCM） treatment of IBS-D. This systematic review summarizes the research progress of transcriptomics， proteomics， metabolomics， microbiomics， and multi-omics integration techniques in TCM interventions for IBS-D. In single-omics studies， transcriptomics using techniques like RNA-seq， reveals the regulatory mechanisms of TCM on IBS-related signaling pathways. Proteomics， leveraging quantitative technologies such as 2D-difference gel electrophoresis and tandem mass tag， identifies differentially expressed proteins and elucidates the action targets of TCM in treating IBS-D. Metabolomics， employing methods like UPLC-Q-TOF-MS and LC-MS/MS， discovers metabolic pathways regulated by TCM to improve metabolic disturbances in IBS-D. Microbiomics， based on 16S rRNA sequencing， confirms that TCM can reshape the gut microbiota structure and restore the intestinal microecological balance， thereby improving IBS-D. Multi-omics integration further overcomes the limitations of single-omics approaches by synthesizing information from transcriptomics， proteomics， metabolomics， and microbiomics， enabling a more comprehensive and systematic elucidation of the complex mechanisms underlying TCM treatment for IBS-D. In the future， research related to IBS-D should be advanced from three aspects： stratified clinical research based on TCM syndrome types， multi-omics integration verification mechanisms， and emerging omics to explore new mechanisms， providing more innovative ideas for the precise diagnosis and treatment of this disease.

OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

Objective To address the safety challenges arising from the rapid development of nuclear energy and technology, assess the current status of health emergency response capabilities in nuclear radiation emergencies, and promote capacity enhancement. Methods A preliminary evaluation system for health emergency response capability in nuclear radiation emergencies was developed based on a literature review. Two rounds of Delphi expert consultation (n = 20) were conducted, and the analytic hierarchy process was employed to establish judgment matrices for assigning indicator weights. Results The finalized system included six primary indicators (radiation protection capability, triage capability, decontamination and evacuation capability, medical treatment capability, radiation detection capability, and radiation dose estimation capability), along with 29 secondary indicators, such as capability for setting up emergency zones, capability for protecting personnel from internal and external contamination, on-site first aid capability, and personal dose monitoring capability. The expert response rate was 0.95, and the expert authority coefficient reached 0.80. The Kendall’s coefficient of concordance was W = 0.288 (P<0.01) for the first round of expert consultation and W = 0.308 (P<0.01) for the second round. Both rounds demonstrated high agreement among experts, and the consultation questionnaires passed reliability and validity tests. Conclusion By integrating qualitative analysis and quantitative calculation, this study developed a scientifically sound and operationally feasible evaluation system. This system will help identify gaps in health emergency response capabilities and provide scientific guidance and a decision-making basis for optimizing emergency plans and improving the level of health emergency response in nuclear radiation emergencies.

Dialisis merupakan rawatan yang lazim bagi pesakit kegagalan buah pinggang. Dari tahun ke tahun, bilangan pesakit yang menjalani dialisis semakin meningkat dengan kadar yang membimbangkan. Tahap keupayaan fungsi pesakit dialisis adalah lebih rendah berbanding pesakit diabetes yang tidak menjalani dialisis. Kajian ini bertujuan untuk mengenal pasti bagaimana dialisis mempengaruhi prestasi Aktiviti Kehidupan Seharian (ADL) dalam kalangan pesakit diabetes di Kuala Selangor serta faktor-faktor yang mempengaruhi prestasi ADL mereka. Kajian berkaitan prestasi ADL dalam kalangan pesakit dialisis yang menghidap diabetes masih terhad. Oleh itu, kajian ini menggunakan kaedah kualitatif melalui sesi temu bual bersemuka secara separa berstruktur. Seramai sepuluh peserta telah direkrut berdasarkan kriteria kemasukan yang ditetapkan. Lima tema utama telah dikenal pasti daripada temu bual, iaitu: (i) meningkatkan kualiti kehidupan seharian: perspektif baharu terhadap aktiviti harian; (ii) kesan diabetes terhadap aktiviti kehidupan seharian; (iii) kesan dialisis terhadap aktiviti kehidupan seharian; (iv) prestasi fungsi dalam aktiviti asas kehidupan seharian; dan (v) aktiviti harian yang dianggap penting. Hasil kajian menunjukkan bahawa pelbagai jenis aktiviti kehidupan seharian telah terjejas akibat kelemahan fizikal yang dialami oleh peserta. Kajian ini dapat memberi pemahaman yang lebih mendalam kepada ahli terapi cara kerja dan bidang pemulihan lain mengenai keupayaan fizikal pesakit diabetes yang menjalani hemodialisis

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

Objective To investigate the feasibility, safety, and clinical value of endoscopic-assisted skin-sparing mastectomy combined with immediate implant-based breast reconstruction performed as day surgery for breast cancer, aiming to provide a reference for major hospitals seeking to implement a day surgery model for breast cancer treatment. Methods We retrospectively analyzed the patients who underwent endoscopic-assisted skin-sparing mastectomy combined with immediate implant-based breast reconstruction for breast cancer at West China Hospital of Sichuan University from June 2021 to December 2022, and they were divided into a day surgery group and a conventional inpatient group based on their admission model. The operative indicators, Breast-Q scores, preoperative waiting time, length of hospital stay, hospitalization costs and complications of the two groups were analyzed. Results Except for intraoperative bleeding (P=0.007), the difference between the two groups in comparison of the rest of the operative indicators was not statistically significant (all P>0.05); there was no significant difference between the two groups in preoperative and postoperative Breast-Q scores (all P>0.05); the preoperative waiting time and length of stay in hospital of the day surgery group were 4.0 (3.0, 11.0) days and 1.0 (1.0, 1.0) days, respectively, which were significantly shorter than that of the conventional inpatient group; the postoperative pain score in the day surgery group [1.0 (1.0, 1.0) points] was lower than that in the conventional inpatient group [3.0 (3.0, 3.0) points], with a statistically significant difference between the two groups (P<0.001). Additionally, the total hospitalization costs for the day surgery group and conventional inpatient group were 50 656.5 (48 145.3, 62 597.3) RMB and 53 689.3 (50 469.1, 64 826.5) RMB, respectively.The total hospitalization cost in the day surgery group was significantly lower than that in the conventional inpatient group, with a statistically significant difference between the two groups (P=0.001). There was no statistically significant difference in complications between the two groups (all P>0.05). Conclusion Endoscopic-assisted skin-sparing mastectomy combined with immediate implant-based breast reconstruction in day surgery is feasible and safe. Without increasing postoperative complications, it effectively reduces hospitalization costs and shortens medical care time, demonstrating significant clinical value.