Background: Malignant vasovagal syncope (VVS) is characterized by cardiac arrest lasting more than 3 seconds during a syncope episode or head-up tilt test (HUTT). We aim to conduct a risk assessment for potential malignant VVS before the HUTT by using economic, simple and convenient demographic data, in order to prevent adverse outcomes for pediatric VVS.Purpose: To explore the correlation between demographic factors and pediatric malignant VVS, and verify the value of these factors in early risk assessment for malignant VVS before HUTT, so as to optimize test safety and reduce adverse events. Methods: We conducted a retrospective analysis of the clinical data of 3,734 children who were initially diagnosed with VVS due to unexplained syncope and presyncope. Finally, 122 children who met the diagnostic criteria for malignant VVS were included in the malignant VVS group, and 661 children who did not meet the criteria during the same period were matched as the control group. By analyzing demographic data and other factors, we attempted to clarify the association between these factors and malignant VVS. Results: Linear relationship: age and body mass index (BMI) have independent protective effects on malignant VVS. For every 1-year increase in age and every 1 kg/m2 increase in BMI, the risk of malignant VVS decreases by 12% and 9%, respectively. Nonlinear relationship: When the age is <12.9 years old, for every additional year of age, the risk of malignant VVS decreases by 20%. For ages 12.9 years and above, the efficacy is not significant. There is no significant nonlinear relationship between BMI and malignant VVS. Conclusion Age and BMI are independent protective factors for pediatric malignant VVS. Before the age of 12.9 years, the incidence of malignant VVS gradually decreases with the increase in age, and thereafter there is no significant impact.

Signal detection is a critical task in drug safety regulation. However, it inevitably generates irrelevant or false signals, posing challenges for resource allocation by marketing authorization holders. To reasonably assess these signals, different countries have established various principles for prioritizing the evaluation of risk signals. This study systematically compares these principles and finds that the U.S. Food and Drug Administration(FDA) focuses on practical issues, such as identifying drug confusion or drug interactions. However, China's Good Pharmacovigilance Practices and the European Medicines Agency(EMA) emphasize a comprehensive evaluation framework. The Council for International Organizations of Medical Sciences(CIOMS) emphasizes the consistency of multiple data sources, highlighting the reliability of signal evaluation. China practices a multidisciplinary approach combining traditional Chinese and western medicine, and the risk signals related to traditional Chinese medicine(TCM) have unique characteristics, including complex components, cumulative toxicity, specific theoretical foundations, and drug interactions. The different priorities in risk signal evaluation principles across countries suggest that China should strengthen clinical trial research, emphasize corroboration with evidence of multiple sources, and pay particular attention to the risks of drug interactions in the TCM regulatory science. Establishing the risk signal prioritization principles that align with the characteristics of TCM enables more precise and efficient scientific regulation of TCM.
Humans ; Medicine, Chinese Traditional/standards* ; China ; Drugs, Chinese Herbal/adverse effects* ; United States ; United States Food and Drug Administration

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Objective:To explore the distant metastatic characteristics of metastatic hormone-sensitive prostate cancer (mHSPC) and metastatic castration-resistant prostate cancer (mCRPC) based on prostate-specific membrane antigen (PSMA) PET-CT.Methods:This is a retrospective cohort study. Ultimately, data from 227 patients with metastatic prostate cancer who underwent PSMA PET-CT examinations at Xiangya Hospital, Central South University between March 2016 and May 2025 were retrospectively reviewed, including 117 mHSPC patients with an age of (68.8±7.6) years (range:53 to 89 years) and 110 mCRPC patients with an age of (69.4±7.5) years (range: 49 to 88 years). Clinical and pathological data, along with metastatic characteristics identified via PSMA PET-CT, were collected and compared. Intergroup comparisons were performed using χ 2 tests. Results:The incidence rates of lymph node metastasis, bone metastasis, and visceral metastasis in the mHSPC group were 71.8% (84/117), 89.7% (105/117), and 11.1% (13/117), respectively, while those in the mCRPC group were 52.7% (58/110), 91.8% (101/110), and 15.5% (17/110), respectively. The incidence of lymph node metastasis in the mHSPC group was significantly higher than that in the mCRPC group ( χ2=8.800, P=0.003). Among patients with bone metastasis, the rates of osteoblastic metastasis, osteolytic metastasis, and mixed metastasis in the mHSPC group were 76.2% (80/105), 8.6% (9/105), and 15.2% (16/105), respectively, while the corresponding rates in the mCRPC group were 74.3% (75/101), 7.3% (8/101), and 16.4% (18/101), respectively, all indicating a relatively high probability of osteolytic and mixed bone metastases ( χ2=0.260, P=0.878). Among patients with mHSPC and mCRPC who tested positive for visceral metastasis, lung metastasis (9/13 and 8/17) and liver metastasis (4/13 and 9/17) were the most common sites of metastasis, but there was no significant difference in the composition of visceral metastasis between the two groups ( χ2=0.933, P=0.564). In this study, among 20 patients who progressed from mHSPC to mCRPC, 35.0% (7/20) had persistent or progressive activity at the original metastatic site, 35.0% (7/20) developed new metastatic lesions, and 30.0% (6/20) showed inhibitory changes in the original metastatic lesions. Among patients with imaging progression, 1/14 of patients with osteoblastic metastatic lesions at the mHSPC stage exhibited osteolytic changes upon progression to mCRPC. Conclusion:Compared with the mCRPC group, the mHSPC group has a higher lymph node metastasis rate,and both groups have common rates of osteolytic and mixed bone metastases and visceral metastasis.

Objective:To analyze the key factors in quality control for clinical laboratory instrument by constructing an analysis framework of the model that entropy weight method(EWM)combines with decision laboratory analysis(DEMATEL),so as to obtain the key factors of quality control for clinical laboratory instrument,and provide a basis in formulating targeted quality control strategies for clinical laboratory instruments.Methods:Based on EWM,the entropy weight values of various factors of quality control for clinical laboratory instruments that produced influence on quality control for clinical laboratory instruments were obtained,and the DEMATEL was combined to determine the value of influence degree among different factors.The combined weight values of each factor were calculated to construct the analysis framework of the model that EWM combined with DEMATEL.Then,the main influencing factors were determined to formulate the model of management system of quality control for clinical laboratory instruments.Results:The management system of quality control for clinical laboratory instruments included 23 key factors of 5 aspects:performance and design of instruments,operators'training and skills,environmental factors,maintenance management,and mechanism of quality feedback.The combined weights of 10 factors,which included maintenance for instrument,operators'experience and proficiency,repair for instrument,operators'understanding for instrument performance,accuracy of instrument,mechanism of quality control and continuous feedback,stability of instrument,data security,suggestions of analyzing and optimizing data,and calibration for instrument,has a relatively high weight,and they were extremely key factors in the quality control for clinical laboratory instruments.Conclusion:The analysis framework of EWM combined with DEMATEL model can improve the accuracy and reliability of analyzing key factors of quality control for clinical laboratory instrument,and provide scientific basis in formulating targeted quality control strategies for clinical laboratory instrument,and help to promote continuous improvement and enhancement of quality control for clinical laboratory instrument.

Objective:To characterize the epidemiology, antimicrobial susceptibility, and molecular mechanisms of carbapenem-resistant Enterobacterales (CRE) carrying multiple carbapenemase genes in China, and to provide evidence for infection control and antibiotic stewardship.Methods:From 2016 to 2023, 115 CRE isolates harboring at least two carbapenemase genes were collected from 41 hospitals in 18 provinces across China. Species identification, antimicrobial susceptibility testing, and whole-genome sequencing were performed. Multilocus sequence typing (MLST) and capsular typing were conducted using Kleborate, plasmid replicon types were identified with PlasmidFinder, and a core genome phylogenetic tree was constructed.Results:The majority of isolates belonged to Klebsiella spp. (80.0%, 92/115), followed by E. cloacae (8.7%, 10/115) and E. coli (6.1%, 7/115). The isolates were mainly from Hebei, Beijing, Shandong, and Hunan (60.9%, 70/115), and sputum was the predominant specimen (43.5%, 50/115). The most common genotype was bla KPC+bla NDM (73.0%, 84/115), primarily in Klebsiella spp. (79.8%, 67/84), followed by bla NDM+bla IMP (15.7%, 18/115). The prevalent plasmid replicon types were IncFII (77.5%, 86/111), IncFIB (68.5%, 76/111), IncR (51.4%, 57/111), and IncX3 (20.7%, 23/111). Notably, 88.6% (31/35) of ST11-KL64 K. pneumoniae strains co-harbored IncFII, IncFIB, and IncR plasmids simultaneously. Between 2016 and 2022, the dominant subtype among Klebsiella spp. isolates was bla KPC-2+bla NDM-1 (56.2%, 36/64). In 2023, the bla KPC-2+bla NDM-13 subtype (29.5%, 19/64) emerged and exhibited clonal transmission (single nucleotide polymorphism 2?74 bp) in Hebei, Beijing, and Jilin. Susceptibility testing showed widespread resistance to β-lactams (90.2%-100%). Aztreonam-avibactam, tigecycline, and colistin retained high activity, with susceptibility rates of 90.16%-98.36%. Conclusions:In China, the majority of clinical Enterobacteriaceae strains that harbor multiple carbapenemases are Klebsiella spp. co-producing KPC and NDM enzymes. Dissemination is driven by both clonal expansion of ST11-KL64 and horizontal transfer of IncFII, IncFIB, and IncR plasmids. The recent emergence and regional clonal spread of the bla KPC-2+bla NDM-13 genotype underscore the urgent need for strengthened surveillance and containment measures.

Vasculature injury occurs rarely in traumatic brain injury but increases lifetime risk of ischemic or hemorrhage stroke. The diverse and nonspecific clinical manifestations make the diagnosis and treatment of these injuries highly challenging. With advancements in device design, endovascular treatments have become widely adopted, playing an increasingly vital role in the management of vascular diseases. The purpose of this review is to introduce and summarize endovascular treatments of traumatic cerebrovascular injury and other related pathological states after traumatic brain injury. Given the innovations of neuroendovascular devices and improvements in the techniques over the past decade, this review will outline several recent advancements in endovascular treatment strategies for cerebrovascular pathologies. Popularizing more treatment options to clinicians will benefit in dealing with a variety of clinical scenarios and reduce the overall morbidity of traumatic cerebrovascular injury.
Humans ; Endovascular Procedures/methods* ; Brain Injuries, Traumatic/complications* ; Cerebrovascular Trauma/therapy*