OBJECTIVE To establish a high-risk medication list and preventive and therapeutic measures for drug-induced hypofibrinogenemia， and to provide a reference for the prevention and treatment of this condition. METHODS By integrating domestic and international case reports， retrospective case-control studies， and spontaneous adverse drug reaction reporting databases， 19 domestically marketed high-risk drugs for drug-induced hypofibrinogenemia were identified. Based on the clinical characteristics and mechanisms of these drugs， relevant risk factors were systematically reviewed， and existing treatment options were summarized， leading to the preliminary development of recommended preventive and therapeutic measures. A two-round Delphi consultation was conducted to evaluate， revise， and ultimately reach consensus on the preliminary findings， using a mean importance score of ≥3.5 points for indicators and a coefficient of variation ＜0.3 as screening criteria. RESULTS The coefficient of expert authority for both rounds of expert consultation was 0.904. In the first round， the Kendall coordination coefficients （Kendall’s W ） for the high-risk medication list and the proposed preventive and therapeutic measures were 0.390 and 0.223 （ P ＜0.05）， respectively. In the second round， the Kendall’s W were 0.227 and 0.200 （ P ＜0.05）， respectively. After two rounds of expert consultation and discussion， 11 high-risk drugs for drug-induced hypofibrinogenemia， represented by hemocoagulase and certain anti-infective agents， were ultimately identified， along with 5 preventive and therapeutic measures spanning the entire process of “pre-medication assessment， intra-medication monitoring， and bleeding event management”. CONCLUSIONS This study has established a scientific and reliable high-risk medication list， and corresponding preventive and therapeutic measures for drug-induced hypofibrinogenemia， providing a theoretical basis and practical support for the early identification， stratified management， and precise intervention of this condition.

Objective To identify key influencing factors for comorbidity between myopia and depressive symptoms among middle school students, and to construct a nomogram predictive model capable of quantitatively assessing their comorbidity risk. Methods A total of 13 976 middle school students aged 11-20 from 14 counties (cities, districts) in Yichang City were selected as study subjects through cluster random sampling. On-site surveys were conducted using the Student Health Status and Influencing Factors Questionnaire and the Depression Assessment Scale. Chi-square test and multivariate logistic regression analysis were employed to investigate the comorbidity association between myopia and depressive symptoms and their influencing factors, and to construct a nomogram model for risk prediction. Results The myopia screening rate among middle school students was 68.67%, the depression detection rate was 23.31%, and the comorbidity detection rate was 16.59%. Logistic regression analysis revealed that boarding school (OR=1.207), smoking history (OR=1.504), alcohol consumption (OR=2.016), outdoor activity time <1 h (OR=1.293), internet addiction (OR=4.008), school bullying (OR=4.358), school absence due to illness within one year (OR=1.712), and severe injury within one year (OR=1.356) were risk factors for myopia-depression comorbidity. Protective factors included male gender (OR=0.578), junior high school students (OR=0.670), nuclear family (OR=0.862), moderate-to-high intensity exercise ≥1 h/d (OR=0.852), screen time <2h (OR=0.803), adequate sleep duration (OR=0.602), and homework time after school <2 h/d (OR=0.766). The nomogram model constructed based on the above variables exhibited excellent discriminant power (AUC = 0.712) and calibration (Hosmer-Lemeshow test, χ²=3.245, P> 0.05). Conclusion Factors such as boarding school attendance, smoking history, alcohol consumption, less than 1 hour of daily outdoor activity, internet addiction, and school bullying are significantly associated with the comorbidity of screening myopia and depressive symptoms among middle school students in Yichang City. The nomogram model effectively predicts the comorbidity risk in this population, facilitating timely intervention for high-risk individuals.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

Objective:To explore the relationship between international collaboration papers and academic impact in global health,using the member universities of the Chinese Consortium of Universities for Global Health(CCUGH)as a case study.Methods:The study focuses on journal articles in global health field published by 31 CCUGH member universities between 2014 and 2024.Descriptive statistical analysis of international and non-international collaboration publication volumes was conducted using Excel.Regression analysis and chi-square tests were performed using R to examine the relationship between international collaboration papers and academic impact,and the correlation between the breadth of collaboration and the academic impact of the papers.Results:From 2014 to 2023,the total number of publications,the number of non-international collaborationpublications,and the number of internationally collaborated publications all showed a consistent annual increase,with average annual growth rates of 56.7%,68.3%,and 41.4%,respectively.By the first half of 2024,the total number of publications had increased to 1.5 times that of the corresponding period in 2023.International collaboration positively influenced academic impact,with broader collaborative networks correlating with higher academic influence.Conclusion:The global health publication output of CCUGH member universities has steadily increased,but the volume of international collaboration papers and their proportion remain relatively low.Therefore,it is necessary for CCUGH member universities to strengthen international collaboration papers in global health.

RNA-binding protein human antigen R(HuR)is a protein product of the embryonic lethal abnormal vision gene(ELAVL).It is widely expressed in human cells and primarily regulates mRNA stability through post-transcriptional mecha-nisms,particularly by binding to AU-enriched elements(AR-Es).Recent studies have indicated that HuR interacts with non-coding RNAs to participate in the regulation of gene expression,including long non-coding RNAs,circular RNAs,microRNAs,and vault RNAs.The interactions between HuR and these ncR-NAs play a crucial role in the occurrence and development of va-rious diseases,including tumors.Since there are already reviews summarizing the research on tumors,this review mainly focuses on summarizing the role of HuR-ncRNA interactions in diseases other than tumors.

The literature related to luminal instruments published in CNKI,Wanfang and VIP databases from the establish-ment of the databases to September 27th,2024,was analyzed statistically and visually by applying CiteSpace in terms of the number of publications,authors,institutions and keywords.It's pointed out that the number of publications on luminal instru-ments in China was on a rising trend in general,and that the operating room,cleaning,disinfection,sterilization and manage-ment were the current hot spots in the research.A new thought was provided on the management and scientific research of luminal instruments in China.[Chinese Medical Equipment Journal,2025,46(3):69-74]

Bovine rotavirus(BRV)is an important pathogen causing diarrhea in calves.To understand the genomic charac-teristics and genetic variations in bovine rotavirus,and to further enrich data on the biological characteristics of rotavirus,we aimed to amplify 11 gene segments of the isolated and cultured G6P[1]bovine rotavirus BLL strain,perform whole genome se-quencing,and analyze the molecular characteristics.MEGA7.0 and DNAMAN software were used for homology and typing a-nalysis,and the whole genome phylogenetic tree was constructed to analyze genetic evolution relationships.The complete geno-type of the BLL strain was G6-P[1]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis of the VP7 and VP4 genes of the BLL strain showed that the VP7 gene had the highest homology with RVA/Cow-wt/HB01/China/2021,and the VP4 gene of the BLL strain was in the same branch as RVA/Human-tc/ISR/Ro8059/1995.From the sequence alignment of VP8*amino acids,the sialic acid domain of the BLL strain was found to be similar to that in other P[1]strains,but different from those in other types of strains,except for residue 189,which was the same as that in Ro8059 but different from that in other strains.The results suggested that the BLL strain might potentially infect humans.Therefore,continued monitoring and study of the biological characteristics of this strain are necessary to provide more information and evidence supporting further research on the cross-species transmission of group A rotavirus in China.

OBJECTIVE: To investigate the feasibility and prognostic implications of assessing volume status during early fluid resuscitation in septic patients based on estimated plasma volume status (ePVS). METHODS: A prospective study was conducted. Patients with sepsis admitted to intensive care unit (ICU) of the First Affiliated Hospital of Kunming Medical University from March to December in 2023 were enrolled. The general information and laboratory indicators at ICU admission were recorded, and ePVS, sequential organ failure assessment (SOFA) score, acute physiology and chronic health status evaluation II (APACHE II) score were calculated. The vital signs, arterial blood gas analysis and volume status related indicators before liquid resuscitation (T0h) and 3 hours (T3h) and 6 hours (T6h) of fluid resuscitation were recorded. The diameter and variability of the inferior vena cava (IVC) were measured by ultrasound, and ePVS, percentage change value of estimated plasma volume status (ΔePVS%), difference in central venous-to-arterial partial pressure of carbon dioxide (Pcv-aCO₂), and lactate clearance rate (LCR) were calculated. Patients were divided into sepsis group and septic shock group based on the diagnosis at ICU admission, and septic patients were subdivided into survival group and death group based on their 28-day survival status. The differences in clinical data between the groups were compared. The correlation between ePVS or ΔePVS% and volume status related indicators during early liquid resuscitation was analyzed by Spearman rank sum correlation test. The predictive value of each variable for 28-day survival in patients with sepsis was analyzed by receiver operator characteristic curve (ROC curve), and 28-day death risk factors were analyzed by Logistic regression method. RESULTS: Fifty-four septic patients were enrolled in the final analysis, including 17 with sepsis and 37 with septic shock; 34 survived at 28 days and 20 died, with a 28-day survival rate of 63.0%. Compared with the sepsis group, the septic shock group had a lower venous ePVS at ICU admission [dL/g: 4.96 (3.67, 7.15) vs. 7.55 (4.36, 10.07), P < 0.05]. Compared with the death group, the survival group had higher T6h arterial and venous ΔePVS%, and albumin [Alb; T6h arterial ΔePVS% (%): 11.57% (-1.82%, 31.35%) vs. 0.48% (-5.67%, 6.02%), T6h venous ΔePVS%: 9.62% (3.59%, 25.75%) vs. 1.52% (-9.65%, 7.72%), Alb (g/L): 27.57±4.15 vs. 23.77±6.97, all P < 0.05], lower SOFA score, APACHE II score, AST, T0h Lac, and T3h and T6h norepinephrine dosage [SOFA score: 9.00 (8.00, 10.00) vs. 11.50 (9.25, 14.50), APACHE II score: 18.00 (14.75, 21.25) vs. 25.50 (21.00, 30.00), AST (U/L): 34.09 (23.20, 56.64) vs. 79.24 (25.34, 196.59), T0h Lac (mmol/L): 1.75 (1.40, 2.93) vs. 3.25 (2.33, 5.30), norepinephrine dosage (mg): 0.98 (< 0.01, 3.10) vs. 4.60 (1.05, 8.55) at T3h, 1.82 (0.38, 5.30) vs. 8.20 (2.80, 17.73) at T6h, all P < 0.05]. While there were no significantly differences in other basic data and ePVS at all of the time points before and after resuscitation between the two groups. Correlation analysis showed that T6h venous ePVS was significantly positively correlated with T6h IVC variability in septic patients (r = 0.360, P < 0.05), T0h arterial ePVS was significantly negatively correlated with T3h and T6h liquid intake volume (r₁ = -0.367, r₂ = -0.280, both P < 0.05), and venous ePVS at ICU admission was significantly positively correlated with NT-proBNP at ICU admission (r = 0.409, P < 0.05). T6h venous ΔePVS% was significantly positively correlated with T3h liquid intake volume and T6h LCR (r₁ = 0.286, r₂ = 0.286, both P < 0.05), and significantly negatively correlated with T6h urine volume and T6h change value of Pcv-aCO₂ (ΔPcv-aCO₂; r₁ = -0.321, r₂ = -0.371, both P < 0.05). ROC curve analysis showed that the area under the ROC curve (AUC) of T6h venous ΔePVS% for predicting 28-day survival in septic patients was 0.726 [95% confidence interval (95%CI) was 0.578-0.875, P = 0.006], with a sensitivity of 82.4%, a specificity of 60.0%, and an optimal cut-off value of 3.09%. Binary multifactorial Logistic regression analysis showed that an increase in T6h venous ΔePVS% was a protective factor for 28-day death in patients with sepsis on early fluid resuscitation [odds ratio (OR) = 0.900, 95%CI was 0.834-0.972, P = 0.007]. CONCLUSIONS ePVS may have potential for assessing the volume status of septic patients during early fluid resuscitation. The ΔePVS% during early fluid resuscitation may help to identify septic patients with a poor prognosis.
Humans ; Prognosis ; Fluid Therapy ; Sepsis/physiopathology* ; Prospective Studies ; Plasma Volume ; Intensive Care Units ; Resuscitation ; Male ; Female ; Middle Aged ; Shock, Septic/therapy*

The literature related to luminal instruments published in CNKI,Wanfang and VIP databases from the establish-ment of the databases to September 27th,2024,was analyzed statistically and visually by applying CiteSpace in terms of the number of publications,authors,institutions and keywords.It's pointed out that the number of publications on luminal instru-ments in China was on a rising trend in general,and that the operating room,cleaning,disinfection,sterilization and manage-ment were the current hot spots in the research.A new thought was provided on the management and scientific research of luminal instruments in China.[Chinese Medical Equipment Journal,2025,46(3):69-74]

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.