BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

Multimodal image fusion technique is a key technology that combines a variety of medical imaging methods to obtain compre-hensive diagnostic information,which has been widely used in clinical disease research.Finite element analysis is essentially a numerical method for solving differential equations,which simulates various physiological and pathological scenarios through combining with multimodal image fusion technique.It has been applied to many medical fields such as the whole lumbar spine,and plays an important role in anatomical research,biomechanical research,and the occurrence and development of diseases.This combination of technologies can simulate pathological processes such as vertebral loading,intervertebral disc degeneration and ligament ossification in three-dimensional space,thereby offering precise support for the elucidation of mechanical mechanisms,assessment of risk and design of surgical plan.This paper systematically reviewed the advances of finite element analysis based on multimodal image fusion in different anatomical units of the whole lumbar spine through literature collection and collation,and analyzed its key problems in model construction,material property assignment,validation methods and clinical transformation.The synergy of finite element analysis and multimodal image fusion provides clinicians with more basis for the diagnosis and treatment of lumbar spine diseases,and has broad application prospects.

Objective To investigate the epidemiological characteristics of knee osteoarthritis(KOA)among military personnel in plateau regions and to explore its risk factors.Methods From July 2023 to July 2024,a multi-stage stratified cluster random sampling method was employed to survey the prevalence of KOA and related risk factors among military personnel in the northwest plateau regions of China,covering different altitudes(1500-4500 m)and geographical areas(Gansu,Qinghai,Tibet,and Xinjiang).All study subjects were divided into KOA and non-KOA groups based on the presence or absence of KOA.Variables including age,gender,body mass index(BMI),education level,smoking status,military rank,military branch,service duration,regional altitude,annual average temperature,training duration,perceived training intensity,and history of knee injury were selected for univariate analyses between groups.Variables with P<0.05 in the univariate analyses were included in the binary multifactor logistic regression to identify risk factors for KOA.Results A total of 3000 questionnaires were distributed,and 2854 valid questionnaires were collected,with a response rate of 95.13%.The sample included 2584 males and 270 females,with 510 cases of KOA,resulting in a prevalence rate of 17.9%.Univariate analysis showed that there were statistically significant differences between KOA and non-KOA groups in terms of age,BMI,smoking status,military rank,military branch,service duration,regional altitude,annual average temperature,training duration,perceived training intensity,and history of knee injury(P<0.05).However,no significant differences were found in gender and education level(P>0.05).Binary multivariate logistic regression analysis revealed that older age(OR=1.382,P=0.017),higher BMI(P<0.01),smoking(OR=1.929,P<0.01),higher military rank(OR=1.485,P=0.007),being a member of the Armed Police(P<0.01),longer service duration(P<0.01),higher regional altitude(OR=1.459,P<0.01),lower annual average temperature(OR=1.188,P=0.001),longer training duration(P<0.01),higher perceived training intensity(OR=2.450,P<0.01),and history of knee injury(OR=2.768,P=0.002)were independent risk factors for KOA.Conclusions Older age,overweight/obesity,smoking,higher military rank,being a member of the Armed Police,longer service duration,higher altitude,cold climate,longer training duration,higher training intensity,and history of knee injury are independent risk factors for KOA among military personnel in the northwest plateau regions of China.

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

Multimodal image fusion technique is a key technology that combines a variety of medical imaging methods to obtain compre-hensive diagnostic information,which has been widely used in clinical disease research.Finite element analysis is essentially a numerical method for solving differential equations,which simulates various physiological and pathological scenarios through combining with multimodal image fusion technique.It has been applied to many medical fields such as the whole lumbar spine,and plays an important role in anatomical research,biomechanical research,and the occurrence and development of diseases.This combination of technologies can simulate pathological processes such as vertebral loading,intervertebral disc degeneration and ligament ossification in three-dimensional space,thereby offering precise support for the elucidation of mechanical mechanisms,assessment of risk and design of surgical plan.This paper systematically reviewed the advances of finite element analysis based on multimodal image fusion in different anatomical units of the whole lumbar spine through literature collection and collation,and analyzed its key problems in model construction,material property assignment,validation methods and clinical transformation.The synergy of finite element analysis and multimodal image fusion provides clinicians with more basis for the diagnosis and treatment of lumbar spine diseases,and has broad application prospects.

Aim To explore the effects of Huannao Yicong decoction(HYD)on the learning and memory ability and brain iron metabolism in APP/PS1 mice and the correlation of HAMP knockout mice and APP/PS1 double transgenic model mice.Methods The ex-periment was divided into five groups,namely,HAMP-/-group(6-month HAMP gene knockout mice),APP/PS1 group(6-month APP/PS1-double-transgenic mice),HAMP-/-+HYD,APP/PS1+HYD,and negative control group(6-month C57BL/6J mice),with six mice in each group.The dose was ad-ministered(13.68 g·kg-1 weight),and the other groups received distilled water for gavage once a day for two months.After the administration of the drug,the mice in each group were tested for learning and memory in the Morris water maze;Biochemical detec-tion was performed to detect iron ion content in each mouse brain;Western blot and RT-qPCR were carried out to analyze hippocampal transferrin(TF),transfer-rin receptor1(TFR1),membrane iron transporter1(FPN1)divalent metal ion transporter 1(DMT1)and β-amyloid protein(Aβ)protein and mRNA expression levels in each group.Results Compared with the normal group,both HAMP-/-mice and APP/PS1 mice had reduced the learning and memory capacity,in-creased iron content in brain tissue,Aβ protein ex-pression increased in hippocampus of HAMP-/-group and APP/PS1 group mice(P＜0.01),the protein and mRNA expression of TF,TFR1 and DMT1 increased in hippocampal tissues of HAMP-/-and APP/PS1 groups(P＜0.01),and the FPN1 protein and mRNA expres-sion decreased(P＜0.01).Compared with the HAMP-and APP/PS1 groups,respectively,HAMP-/-+HYD group and APP/PS1+HYD group had improved learning and memory ability,decreased iron content,decreased Aβ protein expression(P＜0.01),decreased TF,TFR1,DMT1 protein and mR-NA expression(P＜0.01),and increased expression of FPN1 protein and mRNA(P＜0.01).Conclusions There is some association between HAMP-/-mice and APP/PS1 mice,HYD can improve the learning and memory ability of HAMP-/-and APP/PS1 mice and reduce the Aβ deposition.The mechanism may be related to the regulation of TF,TFR1,DMT1,FPN1 expression and improving brain iron overload.

Humans ; Stroke, Lacunar ; Mendelian Randomization Analysis ; Leukocytes ; Telomere/genetics* ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide

Objective: This cross-sectional investigation aimed to determine the incidence, clinical characteristics, prognosis, and related risk factors of olfactory and gustatory dysfunctions related to infection with the SARS-CoV-2 Omicron strain in mainland China. Methods: Data of patients with SARS-CoV-2 from December 28, 2022, to February 21, 2023, were collected through online and offline questionnaires from 45 tertiary hospitals and one center for disease control and prevention in mainland China. The questionnaire included demographic information, previous health history, smoking and alcohol drinking, SARS-CoV-2 vaccination, olfactory and gustatory function before and after infection, other symptoms after infection, as well as the duration and improvement of olfactory and gustatory dysfunction. The self-reported olfactory and gustatory functions of patients were evaluated using the Olfactory VAS scale and Gustatory VAS scale. Results: A total of 35 566 valid questionnaires were obtained, revealing a high incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain (67.75%). Females(χ2=367.013, P<0.001) and young people(χ2=120.210, P<0.001) were more likely to develop these dysfunctions. Gender(OR=1.564, 95%CI: 1.487-1.645), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), oral health status (OR=0.881, 95%CI: 0.839-0.926), smoking history (OR=1.152, 95%CI=1.080-1.229), and drinking history (OR=0.854, 95%CI: 0.785-0.928) were correlated with the occurrence of olfactory and taste dysfunctions related to SARS-CoV-2(above P<0.001). 44.62% (4 391/9 840) of the patients who had not recovered their sense of smell and taste also suffered from nasal congestion, runny nose, and 32.62% (3 210/9 840) suffered from dry mouth and sore throat. The improvement of olfactory and taste functions was correlated with the persistence of accompanying symptoms(χ2=10.873, P=0.001). The average score of olfactory and taste VAS scale was 8.41 and 8.51 respectively before SARS-CoV-2 infection, but decreased to3.69 and 4.29 respectively after SARS-CoV-2 infection, and recovered to 5.83and 6.55 respectively at the time of the survey. The median duration of olfactory and gustatory dysfunctions was 15 days and 12 days, respectively, with 0.5% (121/24 096) of patients experiencing these dysfunctions for more than 28 days. The overall self-reported improvement rate of smell and taste dysfunctions was 59.16% (14 256/24 096). Gender(OR=0.893, 95%CI: 0.839-0.951), SARS-CoV-2 vaccination status (OR=1.334, 95%CI: 1.164-1.530), history of head and facial trauma(OR=1.180, 95%CI: 1.036-1.344, P=0.013), nose (OR=1.104, 95%CI: 1.042-1.171, P=0.001) and oral (OR=1.162, 95%CI: 1.096-1.233) health status, smoking history(OR=0.765, 95%CI: 0.709-0.825), and the persistence of accompanying symptoms (OR=0.359, 95%CI: 0.332-0.388) were correlated with the recovery of olfactory and taste dysfunctions related to SARS-CoV-2 (above P<0.001 except for the indicated values). Conclusion: The incidence of olfactory and taste dysfunctions related to infection with the SARS-CoV-2 Omicron strain is high in mainland China, with females and young people more likely to develop these dysfunctions. Active and effective intervention measures may be required for cases that persist for a long time. The recovery of olfactory and taste functions is influenced by several factors, including gender, SARS-CoV-2 vaccination status, history of head and facial trauma, nasal and oral health status, smoking history, and persistence of accompanying symptoms.
Female ; Humans ; Adolescent ; SARS-CoV-2 ; Smell ; COVID-19/complications* ; Cross-Sectional Studies ; COVID-19 Vaccines ; Incidence ; Olfaction Disorders/etiology* ; Taste Disorders/etiology* ; Prognosis

Humans ; Consensus ; Hypersensitivity ; Desensitization, Immunologic/adverse effects* ; Immunotherapy/adverse effects* ; Injections, Subcutaneous ; Allergens

OBJECTIVE: To develop and validate a user-friendly risk score for older mitral regurgitation (MR) patients, referred to as the Elder-MR score. METHODS: The China Senile Valvular Heart Disease (China-DVD) Cohort Study functioned as the development cohort, while the China Valvular Heart Disease (China-VHD) Study was employed for external validation. We included patients aged 60 years and above receiving medical treatment for moderate or severe MR (2274 patients in the development cohort and 1929 patients in the validation cohort). Candidate predictors were chosen using Cox's proportional hazards model and stepwise selection with Akaike's information criterion. RESULTS: Eight predictors were identified: age ≥ 75 years, body mass index < 20 kg/m², NYHA class III/IV, secondary MR, anemia, estimated glomerular filtration rate < 60 mL/min per 1.73 m², albumin < 35 g/L, and left ventricular ejection fraction < 60%. The model displayed satisfactory performance in predicting one-year mortality in both the development cohort (C-statistic = 0.73, 95% CI: 0.69-0.77, Brier score = 0.06) and the validation cohort (C-statistic = 0.73, 95% CI: 0.68-0.78, Brier score = 0.06). The Elder-MR score ranges from 0 to 15 points. At a one-year follow-up, each point increase in the Elder-MR score represents a 1.27-fold risk of death (HR = 1.27, 95% CI: 1.21-1.34, P < 0.001) in the development cohort and a 1.24-fold risk of death (HR = 1.24, 95% CI: 1.17-1.30, P < 0.001) in the validation cohort. Compared to EuroSCORE II, the Elder-MR score demonstrated superior predictive accuracy for one-year mortality in the validation cohort (C-statistic = 0.71 vs. 0.70, net reclassification improvement = 0.320, P < 0.01; integrated discrimination improvement = 0.029, P < 0.01). CONCLUSIONS The Elder-MR score may serve as an effective risk stratification tool to assist clinical decision-making in older MR patients.