1.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
		                        		
		                        			 Background:
		                        			and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. 
		                        		
		                        			Methods:
		                        			This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. 
		                        		
		                        			Results:
		                        			Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. 
		                        		
		                        			Conclusions
		                        			The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy. 
		                        		
		                        		
		                        		
		                        	
2.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
		                        		
		                        			 Background:
		                        			and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. 
		                        		
		                        			Methods:
		                        			This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. 
		                        		
		                        			Results:
		                        			Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. 
		                        		
		                        			Conclusions
		                        			The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy. 
		                        		
		                        		
		                        		
		                        	
3.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
		                        		
		                        			 Background:
		                        			and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. 
		                        		
		                        			Methods:
		                        			This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. 
		                        		
		                        			Results:
		                        			Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. 
		                        		
		                        			Conclusions
		                        			The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy. 
		                        		
		                        		
		                        		
		                        	
4. Mechanism of EGFR inhibitor AG1478 combined with oxaliplatin in inhibiting PI3K/AKT pathway and promoting autophagy in HI 975 cells
Jin-Qing HUANG ; Yang LI ; Dong-Xue WEI ; Shan JIANG ; Shao-Feng JIANG
Chinese Pharmacological Bulletin 2024;40(2):242-278
		                        		
		                        			
		                        			 Aim To explore the effect of oxaliplatin combined with epidermal growth factor receptor tyrosine kinase inhibitor AG1478 on autophagy in non-small cell lung cancer H1975 cells. Methods H1975 cells were cultured in vitro using gradient concentrations of AG1478 (0, 5, 10, 15, 20, 25, 30, 35, 40 jjimol • IT 
		                        		
		                        		
		                        		
		                        	
5.Clinical application and complication analysis of umbilical arterial catheterization in premature infants
Xifang RU ; Qi FENG ; Ying WANG ; Huixuan YUE ; Tian SANG ; Xiaofang HUANG ; Shan LI ; Xueyan DU
Chinese Journal of Neonatology 2024;39(2):84-89
		                        		
		                        			
		                        			Objective:To study the clinical application and complications of umbilical arterial catheterization (UAC) in premature infants.Methods:From January 2021 to December 2022, premature infants with UAC successfully inserted in NICU of our hospital were enrolled. According to birth weight (BW), the infants were assigned into three groups: <1 000 g, 1 000~1 499 g and ≥1 500 g. The perinatal data, UAC usage, UAC-related complications and risk factors of UAC-related complications were retrospectively analyzed.Results:A total of 39 premature infants received UAC, with gestational age 29.3(27.3, 30.4) weeks and BW 1 100 (900, 1 310) g. The insertion length (IL) of UAC was calculated using the average value of two formulas: a, IL (cm) =4×BW (kg) +7; and b, IL(cm) =3×BW (kg)+9. The accuracy of tube end position was determined using chest/abdomen radiography. 30(76.9%) cases had accurate position, 6(15.4%) had higher position and 3(7.7%) had lower position. The proportion of appropriately positioned tube end in <1 000 g, 1 000~1 499 g and ≥1 500 g groups were 80.0%, 76.5% and 71.4%, respectively, without statistically significant differences ( P>0.05) .No significant differences existed among the three groups in UAC duration and UAC routinely removal rate ( P>0.05). 9 cases (23.1%) of UAC were removed for specific reasons, including 4 cases of arterial spasm, 2 cases of withdrawal of treatment, 1 case of tube end displacement, 1 case of abdominal distension and 1 case of death. 21 cases received 1 U/ml heparin (0.9%NaCl solution) 0.5~1 ml/h arterial infusion. 23.8% (5/21) had hypernatremia and the level of sodium became normal after reducing the concentration of NaCl solution. Arterial vasospasm occurred in 4 patients with skin color changes of one side of the lower extremities. After UAC removal, the skin color returned to normal. Conclusions:UAC is helpful and safe for preterm infants, however, its complications should be alerted to.
		                        		
		                        		
		                        		
		                        	
6.Correlation between clinical staging of human immunodeficiency virus infection and specific antibody immunoblot bands
Xiaoyu SONG ; Zhengling SHANG ; Qinying FENG ; Shan HUANG ; Xinzhong ZHOU ; Zhangwen GE
Journal of Clinical Medicine in Practice 2024;28(16):40-43
		                        		
		                        			
		                        			Objective To analyze the differences in the expression of specific antibodies targeting different human immunodeficiency virus (HIV) antigens among patients at different clinical stages in Qiandongnan Prefecture of Guizhou Province, and to explore their association with the clinical staging of acquired immunodeficiency syndrome. Methods A total of 307 HIV-positive blood samples from Qiandongnan of Guizhou Province were selected for specific HIV antibody immunoblotting assays. CD3+CD4+T cell counts andHIV viral load nucleic acid testing were performed on the blood samples. Multivariate regression analysis was conducted on relevant indicators during HIV infection and AIDS stages. Results Among the 307 HIV-infected individuals, 218 were male and 89 were female, with a mean age of (48.53±16.03) years. The composition ratios of specific antibodies gp160, gp120, gp41, p66, p51, p31, p55, p24 and p17 were 98.7%, 90.9%, 92.2%, 74.3%, 66.4%, 86.6%, 3.9%, 97.4% and 73.9%, respectively. Multivariate binary Logistic regression model analysis showed that expression of p24-specific antibodies were more likely to be judged as influencing factors in the infection stage (OR=0.158, 95%CI, 0.032 to 0.768, 
		                        		
		                        	
		                				7.Identification and anti-inflammatory activity of chemical constituents and a pair of new monoterpenoid enantiomers from the fruits of Litsea cubeba 
		                			
		                			Mei-lin LU ; Wan-feng HUANG ; Yu-ming HE ; Bao-lin WANG ; Fu-hong YUAN ; Ting ZHANG ; Qi-ming PAN ; Xin-ya XU ; Jia HE ; Shan HAN ; Qin-qin WANG ; Shi-lin YANG ; Hong-wei GAO
Acta Pharmaceutica Sinica 2024;59(5):1348-1356
		                        		
		                        			
		                        			 Eighteen compounds were isolated from the methanol extract of the fruits of 
		                        		
		                        	
8.Analysis of FU Wen-Bin's Experience in the Treatment of Radiation Encephalopathy
Jin-Feng GAO ; Shan-Ze WANG ; Ying DENG ; Xi-Chang HUANG ; Si-Bo WEI ; Wen-Bin FU
Journal of Guangzhou University of Traditional Chinese Medicine 2024;41(6):1493-1498
		                        		
		                        			
		                        			Based on the principle of'treating disease and seeking the root cause',Professor FU Wen-Bin proposed'treating radiation encephalopathy(REP)from yang',pointing out that the main pathogenesis of REP is yang qi deficiency,brain spirit dystrophy,phlegm and blood stasis blocking orifices.Using'supplementing yang and unblocking yang simultaneously','treating spirit from heart and gallbladder',combined with the method of regulating spirit and unblocking orifices at acupoints of governor vessol and conception vessel,and using the integrated acupuncture mode of'firstly applying needling,secondly using moxibustion,thirdly focusing on consolidation'to play the role of supporting yang and treating spirit can effectively relieve symptoms and delay the development of the disease.
		                        		
		                        		
		                        		
		                        	
9.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; 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 ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
		                        		
		                        			
		                        			Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
		                        		
		                        		
		                        		
		                        	
10.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; 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 ; Chao YAN ; 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 ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
		                        		
		                        			
		                        			Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
		                        		
		                        		
		                        		
		                        	
            

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