2.Impact of posterior cruciate ligament resection on the elasticity of the periarticular soft tissue sleeve in the knee joint.
Yun-Feng ZHANG ; De-Jin YANG ; Zhao-Lun WANG ; Yi-Xin ZHOU ; Hao TANG ; Xiang-Dong WU ; Han-Long ZHENG
China Journal of Orthopaedics and Traumatology 2025;38(10):1055-1060
OBJECTIVE:
To evaluate the effects of posterior cruciate ligament(PCL) resection on soft tissue elasticity and knee stability in total knee arthroplasty(TKA).
METHODS:
Six adult cadaveric knee specimens (involving 10 knees) were included in the study. With the assistance of the robotic system(TiRobot Recon, TINAVI, Beijing), total knee arthroplasty (TKA) was performed sequentially using cruciate retaining (CR) prostheses and posterior stabilizing (PS) prostheses. Between the two surgical procedures, the femoral and tibial osteotomy surfaces were not altered;only the posterior cruciate ligament (PCL) was resected and the intercondylar fossa was treated. After installing the femoral trial component, a soft tissue balance solver was used to apply tension ranging from 30 N to 90 N in 5 N increments at 0°, 10°, and 90° of knee flexion. Meanwhile, the medial and lateral joint gaps were measured synchronously. Based on the tension-gap coupling data, the equivalent elastic coefficients of the medial and lateral soft tissue sleeves at different knee flexion angles, as well as the range of the joint line convergence angle (JLCA) under fixed varus-valgus stress, were calculated. Additionally, the gap balance status under 80 N of tension was analyzed. Self-control comparisons of each indicator were conducted before and after PCL resection to analyze the change patterns.
RESULTS:
After PCL resection, in the fully extended position (knee flexion 0°). The medial equivalent elastic coefficient was 32.2 (25.7, 63.3) N·mm-1 for the CR prosthesis and 27.7 (22.0, 51.9) N·mm-1 for the PS prosthesis, and the statistically significant difference (P=0.013). The range of JLCA was 0.41°(0.26, 0.55)° for the CR prosthesis, which was smaller than 0.75° (0.40, 0.98)° for the PS prosthesis, and the difference was statistically significant(P=0.041). At 90° of knee flexion, the medial joint gap was 10.7(10.1, 11.7) mm for the CR prosthesis, which was smaller than 12.1(10.9, 15.1) mm for the PS prosthesis, with a statistically significant difference(P=0.011). No statistically significant differences were observed in other joint gaps.
CONCLUSION
PCL resection reduces the rigidity of the medial soft tissues in the fully extended knee and increases the medial joint gap in the flexed position, thereby affecting knee stability and balance. This finding suggests that PS and CR prostheses may require different morphological designs, and there should be differences in indications and osteotomy strategies between CR-TKA and PS-TKA. CR-TKA is more suitable for patients with preoperative medial soft tissue laxity.
Humans
;
Posterior Cruciate Ligament/physiopathology*
;
Knee Joint/physiopathology*
;
Arthroplasty, Replacement, Knee
;
Elasticity
;
Male
;
Female
;
Middle Aged
;
Aged
;
Biomechanical Phenomena
;
Adult
3.Exploring urban versus rural disparities in atrial fibrillation: prevalence and management trends among elderly Chinese in a screening study.
Wei ZHANG ; Yi CHEN ; Lei-Xiao HU ; Jia-Hui XIA ; Xiao-Fei YE ; Wen-Yuan-Yue WANG ; Xin-Yu WANG ; Quan-Yong XIANG ; Qin TAN ; Xiao-Long WANG ; Xiao-Min YANG ; De-Chao ZHAO ; Xin CHEN ; Yan LI ; Ji-Guang WANG ; FOR THE IMPRESSION INVESTIGATORS AND COORDINATORS
Journal of Geriatric Cardiology 2025;22(2):246-254
BACKGROUND:
Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese.
METHODS:
Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics.
RESULTS:
The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05).
CONCLUSIONS
In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.
4.The Valvular Heart Disease-specific Age-adjusted Comorbidity Index (VHD-ACI) score in patients with moderate or severe valvular heart disease.
Mu-Rong XIE ; Bin ZHANG ; Yun-Qing YE ; Zhe LI ; Qing-Rong LIU ; Zhen-Yan ZHAO ; Jun-Xing LV ; De-Jing FENG ; Qing-Hao ZHAO ; Hai-Tong ZHANG ; Zhen-Ya DUAN ; Bin-Cheng WANG ; Shuai GUO ; Yan-Yan ZHAO ; Run-Lin GAO ; Hai-Yan XU ; Yong-Jian WU
Journal of Geriatric Cardiology 2025;22(9):759-774
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.
5.Performance assessment of computed tomographic angiography fractional flow reserve using deep learning: SMART trial summary.
Wei ZHANG ; You-Bing YIN ; Zhi-Qiang WANG ; Ying-Xin ZHAO ; Dong-Mei SHI ; Yong-He GUO ; Zhi-Ming ZHOU ; Zhi-Jian WANG ; Shi-Wei YANG ; De-An JIA ; Li-Xia YANG ; Yu-Jie ZHOU
Journal of Geriatric Cardiology 2025;22(9):793-801
BACKGROUND:
Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR).
METHODS:
This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries.
RESULTS:
Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s.
CONCLUSIONS
The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.
6.Expert consensus on the application of nasal cavity filling substances in nasal surgery patients(2025, Shanghai).
Keqing ZHAO ; Shaoqing YU ; Hongquan WEI ; Chenjie YU ; Guangke WANG ; Shijie QIU ; Yanjun WANG ; Hongtao ZHEN ; Yucheng YANG ; Yurong GU ; Tao GUO ; Feng LIU ; Meiping LU ; Bin SUN ; Yanli YANG ; Yuzhu WAN ; Cuida MENG ; Yanan SUN ; Yi ZHAO ; Qun LI ; An LI ; Luo BA ; Linli TIAN ; Guodong YU ; Xin FENG ; Wen LIU ; Yongtuan LI ; Jian WU ; De HUAI ; Dongsheng GU ; Hanqiang LU ; Xinyi SHI ; Huiping YE ; Yan JIANG ; Weitian ZHANG ; Yu XU ; Zhenxiao HUANG ; Huabin LI
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(4):285-291
This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans
;
Nasal Cavity/surgery*
;
Nasal Surgical Procedures
;
China
;
Consensus
;
Sinusitis/surgery*
;
Dermal Fillers
7.The Impacts of Climate Change on the Environment and Human Health in China: A Call for more Ambitious Action.
Shi Lu TONG ; Yu WANG ; Yong Long LU ; Cun de XIAO ; Qi Yong LIU ; Qi ZHAO ; Cun Rui HUANG ; Jia Yu XU ; Ning KANG ; Tong ZHU ; Dahe QIN ; Ying XU ; Buda SU ; Xiao Ming SHI
Biomedical and Environmental Sciences 2025;38(2):127-143
As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O 3 air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change
;
China
;
Humans
;
Greenhouse Gases
;
Air Pollution
;
Sustainable Development
;
Environment
8.Molecular Characterization of New Recombinant Human Adenoviruses Detected in Children with Acute Respiratory Tract Infections in Beijing, China, 2022-2023.
Yi Nan GUO ; Ri DE ; Fang Ming WANG ; Zhen Zhi HAN ; Li Ying LIU ; Yu SUN ; Yao YAO ; Xiao Lin MA ; Shuang LIU ; Chunmei ZHU ; Dong QU ; Lin Qing ZHAO
Biomedical and Environmental Sciences 2025;38(9):1071-1081
OBJECTIVE:
Recombination events are common and serve as the primary driving force of diverse human adenovirus (HAdV), particularly in children with acute respiratory tract infections (ARIs). Therefore, continual monitoring of these events is essential for effective viral surveillance and control.
METHODS:
Respiratory specimens were collected from children with ARIs between January 2022 and December 2023. The penton base, hexon, and fiber genes were amplified from HAdV-positive specimens and sequenced to determine the virus type. In cases with inconsistent typing results, genes were cloned into the pGEM-T vector to detect recombination events. Metagenomic next-generation sequencing (mNGS) was performed to characterize the recombinant HAdV genomes.
RESULTS:
Among 6,771 specimens, 277 (4.09%, 277/6,771) were positvie for HAdV, of which 157 (56.68%, 157/277) were successfully typed, with HAdV-B3 being the dominant type (91.08%, 143/157), and 14 (5.05%, 14/277) exhibited inconsistent typing results, six of which belonged to species B. The penton base genes of these six specimens were classified as HAdV-B7, whereas their hexon and fiber genes were classified as HAdV-B3, resulting in a recombinant genotype designated P7H3F3, which closely resembled HAdV-B114. Additionally, a partial gene encoding L1 52/55 kD was identified, which originated from HAdV-B16.
CONCLUSION
A novel recombinant, P7H3F3, was identified, containing sequences derived from HAdV-B3 and HAdV-B7, which is similar to HAdV-B114, along with additional sequences from HAdV-B16.
Humans
;
Adenoviruses, Human/isolation & purification*
;
Respiratory Tract Infections/epidemiology*
;
Child, Preschool
;
Child
;
Recombination, Genetic
;
Male
;
Beijing/epidemiology*
;
Infant
;
Female
;
Phylogeny
;
Adenovirus Infections, Human/epidemiology*
;
Acute Disease
;
Genome, Viral
9.Progress on Wastewater-based Epidemiology in China: Implementation Challenges and Opportunities in Public Health.
Qiu da ZHENG ; Xia Lu LIN ; Ying Sheng HE ; Zhe WANG ; Peng DU ; Xi Qing LI ; Yuan REN ; De Gao WANG ; Lu Hong WEN ; Ze Yang ZHAO ; Jianfa GAO ; Phong K THAI
Biomedical and Environmental Sciences 2025;38(11):1354-1358
Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology*
;
Humans
;
Wastewater/analysis*
;
COVID-19/epidemiology*
;
Public Health
;
Wastewater-Based Epidemiological Monitoring
;
SARS-CoV-2
10.Clinical characterization and prediction modeling of lung cancer patients with high energy metabolism
Jiang-Shan REN ; Jun-Mei JIA ; Ping SUN ; Mei PING ; Qiong-Qiong ZHANG ; Yan-Yan LIU ; He-Ping ZHAO ; Yan CHEN ; Dong-Wen RONG ; Kang WANG ; Hai-Le QIU ; Chen-An LIU ; Yu-Yu FAN ; De-Gang YU
Medical Journal of Chinese People's Liberation Army 2024;49(9):1004-1010
Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

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