1.Effects of Contralateral Limb Cross-Balance Training on Rehabilitation Outcomes after Anterior Cruciate Ligament Reconstruction
Chao LIU ; Jianping LI ; Shijia LI ; Shaopeng ZOU ; Jianwei XIA ; Honghao ZHANG ; Guqiang LI ; Xiangzhan JIANG
Journal of Medical Biomechanics 2025;40(2):337-343
Objective To evaluates the effects of cross-balance training on knee function,dynamic balance,and rectus femoris(RF)activation in patients after anterior cruciate ligament reconstruction(ACLR).Methods Forty ACLR patients at 5th-6th week after operation were randomly divided into experimental group and control group.The experimental group received the cross-balance training on the basis of standard rehabilitation,while the control group received only standard rehabilitation.Knee function was assessed with the Lysholm score,dynamic balance,and root mean square(RMS)of RF surface electromyography.The correlation between RMS and dynamic balance was also examined.Results After intervention,the Lysholm score of the experimental group was significantly higher than that of the control group(P<0.01).Regarding balance function,both the gait line length and single support line length of the experimental group were significantly greater than those of the control group(P<0.01).Conversely,the mediolateral displacement of the experimental group was significantly lower than that of the control group(P<0.01).Furthermore,the RF RMS of the experimental group was significantly larger than that of the control group(P<0.01).The RF RMS was positively correlated with the gait line length and single support line length,whereas it was negatively correlated with the mediolateral displacement(P<0.05).Conclusions Cross-balance training significantly enhances knee function,dynamic balance,and RF activation in post-ACLR patients,supports the theory of cross-education.Cross-balance training has certain application values in ACL postoperative rehabilitation.
2.Associations of Life's Crucial 9 and the risk of thyroid dysfunction: a cohort study
Juanjuan ZHANG ; Yuerong HE ; Zhiyuan TANG ; Xiangdong SUN ; Jiale SHEN ; Jianping GONG ; Chao LIU ; Yang XIA
Chinese Journal of Epidemiology 2025;46(8):1400-1408
Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.
3.Effects of Contralateral Limb Cross-Balance Training on Rehabilitation Outcomes after Anterior Cruciate Ligament Reconstruction
Chao LIU ; Jianping LI ; Shijia LI ; Shaopeng ZOU ; Jianwei XIA ; Honghao ZHANG ; Guqiang LI ; Xiangzhan JIANG
Journal of Medical Biomechanics 2025;40(2):337-343
Objective To evaluates the effects of cross-balance training on knee function,dynamic balance,and rectus femoris(RF)activation in patients after anterior cruciate ligament reconstruction(ACLR).Methods Forty ACLR patients at 5th-6th week after operation were randomly divided into experimental group and control group.The experimental group received the cross-balance training on the basis of standard rehabilitation,while the control group received only standard rehabilitation.Knee function was assessed with the Lysholm score,dynamic balance,and root mean square(RMS)of RF surface electromyography.The correlation between RMS and dynamic balance was also examined.Results After intervention,the Lysholm score of the experimental group was significantly higher than that of the control group(P<0.01).Regarding balance function,both the gait line length and single support line length of the experimental group were significantly greater than those of the control group(P<0.01).Conversely,the mediolateral displacement of the experimental group was significantly lower than that of the control group(P<0.01).Furthermore,the RF RMS of the experimental group was significantly larger than that of the control group(P<0.01).The RF RMS was positively correlated with the gait line length and single support line length,whereas it was negatively correlated with the mediolateral displacement(P<0.05).Conclusions Cross-balance training significantly enhances knee function,dynamic balance,and RF activation in post-ACLR patients,supports the theory of cross-education.Cross-balance training has certain application values in ACL postoperative rehabilitation.
4.Stroke etiology and infarction characteristics in patients with acute ischemic stroke
Yuxi HOU ; Shiyue CHEN ; Xia TIAN ; Hongjian SHEN ; Chengwei SHAO ; Jianping LU ; Bing TIAN
Academic Journal of Naval Medical University 2025;46(9):1108-1115
Objective To explore the correlation between stroke etiology and clinical and imaging features in patients with acute ischemic stroke(AIS)due to large vessel occlusion treated by intravascular thrombectomy.Methods A total of 213 patients with AIS and endovascular embolectomy in our hospital from Oct.2016 to Jun.2018 were enrolled retrospectively.According to the etiological classification criteria of Trial of Org 10172 in Acute Stroke Treatment(TOAST),there were 116 cases of cardioembolism and 97 cases of non-cardioembolism.Multivariate logistic regression analysis was used to screen the clinical and imaging characteristics for identifying cardioembolism and non-cardioembolism.Results Compared with non-cardioembolism AIS,cardioembolism AIS was associated with higher NIHSS scores(adjusted odds ratio[OR]=1.09,95%confidence interval[95%CI]1.01-1.18,P=0.02),atrial fibrillation(adjusted OR=76.46,95%CI 26.75-218.51,P<0.01),absence of hypertension(adjusted OR=0.32,95%CI 0.12-0.84,P=0.02),antiplatelet drug use(adjusted OR=5.03,95%CI 1.22-20.63,P=0.03),shorter onset-to-puncture time(adjusted OR=0.998,95%CI 0.996-1.000,P=0.04),and presence of hyperdense artery sign(HAS)(adjusted OR=4.45,95%CI 1.47-13.49,P=0.01).Conclusion There are some differences in clinical and imaging characteristics between patients with cardioembolism and non-cardioembolism AIS.The occurrence of HAS suggests a higher probability of cardioembolism in AIS patients.
5.Associations of Life's Crucial 9 and the risk of thyroid dysfunction: a cohort study
Juanjuan ZHANG ; Yuerong HE ; Zhiyuan TANG ; Xiangdong SUN ; Jiale SHEN ; Jianping GONG ; Chao LIU ; Yang XIA
Chinese Journal of Epidemiology 2025;46(8):1400-1408
Objective:Exploring the association between Life's Crucial 9 (LC9) and the risk of thyroid dysfunction (TD), as well as its potential predictive capacity.Methods:A total of 247 600 TD-free participants from the UK Biobank were enrolled in the study. The LC9 score was divided into three CVH groups: low (0-), medium (50-), and high (80-100). Cox proportional hazards regression models were used to calculate the HRs and 95% CIs of the risk of TD with LC9 CVH status. Calculate Harrell's concordance index ( C-index), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) to evaluate the predictive ability of the LC9 score and Life's Essential 8 (LE8) score. Results:During a median follow-up of 12.3 years, 5 515, 911, and 4 869 new cases of TD, hyperthyroidism, and hypothyroidism were documented, respectively. Participants with a high LE8 CVH group had 57.00% ( HR=0.43, 95% CI: 0.38-0.49), 55.00% ( HR=0.45, 95% CI: 0.34-0.60), and 58.00% ( HR=0.42, 95% CI: 0.37-0.47) lower risk of TD, hyperthyroidism, and hypothyroidism, respectively, than those with low CVH group. Compared with the LE8 score, the improvement in C-index for the LC9 score predicted TD risk was 0.004 (95% CI: 0.001-0.007), the NRI was 0.101 (95% CI: 0.021-0.103), and the IDI was 0.001 (95% CI: 0.000-0.001). Conclusions:The better CVH status, defined by LC9, was associated with a lower risk of TD. Compared to the LE8 score, the LC9 score demonstrated a significant enhancement in both risk discrimination and reclassification capability for TD risk.
6.Multidimensional CT radiomics for preoperative prediction of TFE3-rearranged renal cell carcinoma
Bin XIA ; Chengwei CHEN ; Na LI ; Yun BIAN ; Chengwei SHAO ; Jianping LU ; Qinqin KANG
Chinese Journal of Urology 2025;46(5):343-348
Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma(TFE3-rRCC).Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma(RCC)patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023,including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC(comprising clear cell RCC,papillary RCC,and chromophobe RCC). Among them,627 were male and 238 were female,with a mean age of(54.1 ± 12.7)years(range:14?82 years). The median maximum tumor diameter was 4.0(2.6,6.0)cm. Based on the chronological order of CT examinations,the patients were divided into training( n=478),validation( n=206),and test( n=181)sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images,we extracted peritumoral imaging features,habitat features,3D radiomic features,and 2.5D deep learning radiomic features. A deep learning radiomics score(DLR-SCORE)prediction model was constructed using least absolute shrinkage and selection operator(LASSO)regression. The diagnostic performance of the model was evaluated by receiver operating characteristic(ROC)curve analysis,with the area under the curve(AUC)as the primary metric. Additionally,sensitivity,specificity,and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images,from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%(471/478)in the training set,81.6%(168/206)in the validation set,and 86.2%(156/181)in the test set. The AUC of ROC curve was 0.98(95% CI 0.96?1.00)in the training set,0.83(95% CI 0.71?0.94)in the validation set,and 0.88(95% CI 0.76?1.00)in the test set. In the test set,the DLR-SCORE model achieved a sensitivity of 88.9%(16/18)and a specificity of 85.9%(140/163)for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC,offering a promising noninvasive tool to assist preoperative diagnosis.
9.Multidimensional CT radiomics for preoperative prediction of TFE3-rearranged renal cell carcinoma
Bin XIA ; Chengwei CHEN ; Na LI ; Yun BIAN ; Chengwei SHAO ; Jianping LU ; Qinqin KANG
Chinese Journal of Urology 2025;46(5):343-348
Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma(TFE3-rRCC).Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma(RCC)patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023,including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC(comprising clear cell RCC,papillary RCC,and chromophobe RCC). Among them,627 were male and 238 were female,with a mean age of(54.1 ± 12.7)years(range:14?82 years). The median maximum tumor diameter was 4.0(2.6,6.0)cm. Based on the chronological order of CT examinations,the patients were divided into training( n=478),validation( n=206),and test( n=181)sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images,we extracted peritumoral imaging features,habitat features,3D radiomic features,and 2.5D deep learning radiomic features. A deep learning radiomics score(DLR-SCORE)prediction model was constructed using least absolute shrinkage and selection operator(LASSO)regression. The diagnostic performance of the model was evaluated by receiver operating characteristic(ROC)curve analysis,with the area under the curve(AUC)as the primary metric. Additionally,sensitivity,specificity,and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images,from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%(471/478)in the training set,81.6%(168/206)in the validation set,and 86.2%(156/181)in the test set. The AUC of ROC curve was 0.98(95% CI 0.96?1.00)in the training set,0.83(95% CI 0.71?0.94)in the validation set,and 0.88(95% CI 0.76?1.00)in the test set. In the test set,the DLR-SCORE model achieved a sensitivity of 88.9%(16/18)and a specificity of 85.9%(140/163)for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC,offering a promising noninvasive tool to assist preoperative diagnosis.
10.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.

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