INTRODUCTION: Degenerative mitral stenosis (DMS) is frequently cited as increasing in prevalence in the developed world, although comparatively little is known about DMS in comparison to rheumatic mitral stenosis (RMS). METHOD: A retrospective observational study was conducted on 745 cases of native-valve mitral stenosis (MS) with median follow-up time of 7.25 years. Clinical and echocardiographic parameters were compared. Univariate and multivariate Cox regression analyses were performed for a composite of all-cause mortality and heart failure hospitalisation. RESULTS: Patients with DMS compared to RMS were older (age, mean ± standard deviation: 69.6 ± 12.3 versus [vs] 51.6 ± 14.3 years, respectively; P<0.001) and a greater proportion had medical comorbidities such as diabetes mellitus (78 [41.9%] vs 112 [20.0%], P<0.001). The proportion of cases of degenerative aetiology increased from 1.1% in 1991-1995 to 41.0% in 2016-2017. In multivariate analysis for the composite outcome, age (hazard ratio [HR] 95% confidence interval [CI] of 1.032 [1.020-1.044]; P<0.001), diabetes mellitus (HR 1.443, 95% CI 1.068-1.948; P=0.017), chronic kidney disease (HR 2.043, 95% CI 1.470-2.841; P<0.001) and pulmonary artery systolic pressure (HR 1.019, 95% CI 1.010- 1.027; P<0.001) demonstrated significant indepen-dent associations. The aetiology of MS was not independently associated with the composite outcome. CONCLUSION DMS is becoming an increasingly common cause of native-valve MS. Despite numerous clinical differences between RMS and DMS, the aetiology of MS did not independently influence a composite of mortality or heart failure hospitalisation.
Humans ; Mitral Valve Stenosis/etiology* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Rheumatic Heart Disease/mortality* ; Echocardiography ; Hospitalization/statistics & numerical data* ; Heart Failure/epidemiology* ; Singapore/epidemiology* ; Proportional Hazards Models ; Diabetes Mellitus/epidemiology*

INTRODUCTION: The primary objective of this guideline is to establish evidence-based recommendations for the clinical use of parenteral nutrition (PN) in adult patients within the acute hospital setting in Singapore. METHOD: An expert workgroup, consisting of healthcare practitioners actively involved in clinical nutrition support across all public health institutions, systematically evaluated existing evidence and addressed clinical questions relating to PN therapy. RESULTS: This clinical practice guideline developed 30 recommendations for PN therapy, which cover these key aspects related to PN use: indications, patient assess-ment, titration and formulation of PN bags, access routes and devices, and monitoring and management of PN-related complications. CONCLUSION This guideline provides recommendations to ensure appropriate and safe clinical practice of PN therapy in adult patients within the acute hospital setting.
Humans ; Singapore ; Parenteral Nutrition/adverse effects* ; Adult

INTRODUCTION: Paediatric sexual assault (SA) victims should be assessed for post-exposure prophylaxis (PEP) to mitigate the risk of sexually transmitted infections (STIs). We describe the clinical characteristics of children and young persons (CYPs) presenting with SA at KK Women's and Children's Hospital in Singapore, viral PEP (human immunodeficiency virus [HIV] and hepatitis B virus [HBV]) prescribing practices, and STI evaluation at follow-up. METHOD: Medical records of CYPs ≤16 years who presented with SA between January 2022 and August 2023 were reviewed, including assault and assailant characteristics, baseline and follow-up STI screening, PEP prescription, adherence and follow-up attendance. CYPs with SA in the preceding 72 hours by HIV-positive or HIV-status unknown assailants with high-risk characteris-tics were eligible for HIV PEP. RESULTS: We analysed 278 CYPs who made 292 SA visits. There were 40 (13.7%) CYPs eligible for HIV PEP, of whom 29 (82.9%) received it. Among those tested at baseline, 9% and 34.9% of CYPs tested positive for Chlamydia trachomatis and Gardnerella vaginalis, respectively. None tested positive for Neisseria gonorrhoeae, Trichomonas vaginalis, HIV, HBV or hepatitis C. Majority of CYPs tested were HBV non-immune (n=167, 67.6%); only 77 (46.1%) received the vaccine. Out of 27 CYPs eligible for HBV PEP with immunoglobulin, only 21 (77.7%) received immunoglobulin. A total of 37 CYPs received HIV PEP, including 8 who were retrospectively deemed ineligible. Only 10 (27%) completed the course. Overall, 153 (57.7%) CYPs attended follow-up, and none seroconverted for HIV or HBV. CONCLUSION We report suboptimal rates of HBV post-exposure vaccination, and low compliance to HIV PEP and follow-up among paediatric SA victims. Factors contri-buting to poor compliance should be examined to optimise care for this vulnerable population.
Humans ; Post-Exposure Prophylaxis/methods* ; Female ; Child ; Adolescent ; Singapore/epidemiology* ; HIV Infections/prevention & control* ; Male ; Sexually Transmitted Diseases/epidemiology* ; Retrospective Studies ; Hepatitis B/prevention & control* ; Follow-Up Studies ; Child, Preschool ; Sex Offenses/statistics & numerical data* ; Child Abuse, Sexual

OBJECTIVES: To investigate the chain mediating role of family care and emotional management in the relationship between social support and anxiety among rural primary school students. METHODS: A questionnaire survey was conducted among students in grades 4 to 6 from four counties in Hunan Province. Data were collected using the Social Support Rating Scale, Family Care Index Scale, Emotional Intelligence Scale, and Generalized Anxiety Disorder -7. Logistic regression analysis was used to explore the influencing factors of anxiety symptoms. Mediation analysis was conducted to assess the chain mediating effects of family care and emotional management between social support and anxiety. RESULTS: A total of 4 141 questionnaires were distributed, with 3 874 valid responses (effective response rate: 93.55%). The prevalence rate of anxiety symptoms among these students was 9.32% (95%CI: 8.40%-10.23%). Significant differences were observed in the prevalence rates of anxiety symptoms among groups with different levels of social support, family functioning, and emotional management ability (P<0.05). The total indirect effect of social support on anxiety symptoms via family care and emotional management was significant (β=-0.137, 95%CI: -0.167 to -0.109), and the direct effect of social support on anxiety symptoms remained significant (P<0.05). Family care and emotional management served as significant chain mediators in the relationship between social support and anxiety symptoms (β=-0.025,95%CI:-0.032 to -0.018), accounting for 14.5% of the total effect. CONCLUSIONS Social support can directly affect anxiety symptoms among rural primary school students and can also indirectly influence anxiety symptoms through the chain mediating effects of family care and emotional management. These findings provide scientific evidence for the prevention of anxiety in primary school students from multiple perspectives.
Humans ; Female ; Male ; Social Support ; Anxiety/etiology* ; Child ; Students/psychology* ; Emotions ; Logistic Models

Objective: To establish a machine learning-based precision blood donor recruitment model at the county level and assess its generalizability and applicability. Methods: A retrospective study was conducted using blood donation and SMS recruitment data from the Taicang Branch of the Suzhou Blood Center between 2019 and 2024. Multiple machine learning algorithms were employed, including extreme gradient boosting, support vector machine, k-nearest neighbor, logistic regression, decision tree, random forest, and multilayer perceptron. These were combined with techniques such as synthetic minority oversampling, undersampling, and cost-sensitive learning (using MFE and MSFE loss functions). Model parameters were optimized through grid search to identify the best-performing model. Results: In a prospective comparative study against conventional methods, the machine learning models increased the recruitment success rate among high-willingness donors by an average of 129.15%, and the recruitment efficiency per SMS improved by 125.02% compared with the traditional method. Under full-scale SMS sending, the recruitment rate per SMS increased by 42.61%, and SMS sending efficiency improved by 31.77%, significantly enhancing recruitment performance. Conclusion: This study represents the first application of a machine learning-based precision donor recruitment model at the county-level in China. The precise recruitment framework not only improves recruitment efficiency and reduces recruitment costs but also demonstrates strong scalability and generalizability. It provides a scientific and feasible intelligent pathway to ensure the safety and sustainability of the blood supply.

AIM To study the chemical constituents from Codonopsis pilosula(Franch.)Nannf in Shanxi and their anti-inflammatory activities.METHODS The 70％ ethanol extract from C.pilosula in Shanxi was isolated and purified by silica gel,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their in vitro anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as ethylsyringin(1),7-O-ethyltangshenoside Ⅱ(2),triandrin(3),trans-isoconiferin(4),methylsyringin(5),9-acetoxy syringin(6),cordifolioidyne B(7),codonopiloenynenoside A(8),codonopilodiynoside F(9),pratialin B(10),lobetyolinin(11),lariciresinol-4-O-β-D-glucoside(12),dihydrodehydrodiconiferyl alcohol 4′-O-β-D-glucoside(13),atractylenolid Ⅲ(14),baimantuoluoamide B(15),benzyl primeveroside(16).Compounds 1-2,5,7-11 and 13-15 had certain anti-inflammatory activities,among which compounds 11,14-15 had higher activities,whose IC50 values were(18.23±4.18),(17.73±3.12),(14.89±2.47)μmol/L,respectively.CONCLUSION Compounds 3,6,13,16 are first isolated from Campanulaceae,2,5,15 are first found from this plant.Compounds 11,14 and 15 have good anti-inflammatory activities.

Nonalcoholic fatty liver disease （NAFLD） is one of the most prevalent chronic liver diseases in the world， affecting about one quarter of the global population， and it is estimated that NAFLD will become the main indication for liver transplantation by 2030. NAFLD can lead to significant abnormalities in the levels of a variety of amino acids including branched-chain amino acids， thereby promoting the development and progression of NAFLD. These results suggest that in addition to glucose and lipid metabolism， amino acid metabolism also plays an important role in the progression of NAFLD. In order to systematically understand the role and mechanism of amino acid metabolism in NAFLD， this article reviews the research advances in amino acid metabolism in NAFLD. This article aims to explore the role and mechanism of amino acid metabolism in the progression of NAFLD， so as to provide ideas and a theoretical basis for clinical prevention and treatment.

Objective:To investigate the changes of the distribution and drug resistance profile of bacteria from ICU children with lower respiratory tract infection (LRTI) in Suzhou City, Jiangsu Province from 2017 to 2022.Methods:From January 2017 to December 2022, a cross-sectional observational study on the bacterial spectrum analysis among intensive care unit (ICU) children with LRTI was conducted in Children′s Hospital of Soochow University. The bacteria was cultivated by culture methods from sputum samples, and identified by MALDI-TOF mass spectrometry. Drug sensitivity tests were performed by the VITEK2 Compact fully automated analysis system and the paper slide method. The χ2 test or Fisher′s exact probability was used to analyze the changes of the distribution of sputum culture-positive bacteria and drug resistance in ICU children. Results:The overall detection rate of sputum culture was 42.06% (1 182/2 810). Staphylococcus aureus (25.63%,303/1 182), Acinetobacter baumannii (13.62%,161/1 182) and Haemaphilus influenzae (13.28%,157/1 182) were the top three. Proportions of Acinetobacter baumannii (17.90% vs. 11.02%, χ2=11.17, P=0.001), especially carbapenem-resistant Acinetobacter baumannii (43.70% vs. 23.50%, χ2=15.21, P<0.001) increased significantly from 2020 to 2022. However, the proportions of Haemophilus influenzae (8.50% vs. 16.19%, χ2=14.27, P<0.001), Streptococcus pneumoniae (8.50% vs. 15.92%, χ2=13.42, P<0.001) and extended-spectrum-lactamase producing Escherichia coli (8.89% vs. 18.00%, χ2=5.45, P=0.025) decreased. Drug resistant results showed that Acinetobacter baumannii was obviously more resistant to imipenem ( χ2=4.43, P=0.035) and levofloxacin ( χ2=12.53, P<0.001), while more sensitive to minocycline ( χ2=8.34, P=0.004). Escherichia coli showed a significant increase in resistance to piperacillin tazobactam ( χ2=8.29, P=0.008) and cefoperazone sulbactam ( χ2=5.07, P=0.024) from 2020 to 2022; Klebsiella pneumoniae consistently maintained a resistance rate of more than 60% to first and second-generation cephalosporins, and remain susceptible to quinolones and carbapenems. Staphylococcus aureus remained highly susceptible to levofloxacin (drug resistance rate: 2.31%,7/303) and sulfamethoxazole/trimethoprim (drug resistance rate: 4.95%,15/303) from 2020 to 2022. Conclusion:Higher detection and resistance rates of Acinetobacter baumannii from sputum culture in ICU children from 2020 to 2022 were explored. Resistance of Escherichia coli to β-lactamase inhibitor combinations was more serious. Regular monitoring the changes of the etiology of respiratory tract infections in ICU Children is particularly important for the prevention and treatment of multidrug-resistant bacterial infections.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.