1.Diagnosis and treatment of colorectal liver metastases: Chinese expert consensus-based multidisciplinary team (2024 edition).
Wen ZHANG ; Xinyu BI ; Yongkun SUN ; Yuan TANG ; Haizhen LU ; Jun JIANG ; Haitao ZHOU ; Yue HAN ; Min YANG ; Xiao CHEN ; Zhen HUANG ; Weihua LI ; Zhiyu LI ; Yufei LU ; Kun WANG ; Xiaobo YANG ; Jianguo ZHOU ; Wenyu ZHANG ; Muxing LI ; Yefan ZHANG ; Jianjun ZHAO ; Aiping ZHOU ; Jianqiang CAI
Chinese Medical Journal 2025;138(15):1765-1768
2.Analysis of influencing factors of blood transfusion in children with traumatic brain injury and construc-tion of prediction model:A multi-center retrospective study
Wei LIU ; Jun HOU ; Longquan TANG ; Peng ZHOU ; Yan ZHONG ; Qinyan LUO ; Xiaoyu KUANG ; Hua LIU ; Ziqing XIONG ; Wei XIONG ; Chenggao WU ; Aiping LE
The Journal of Practical Medicine 2025;41(4):553-560
Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94~0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.
3.The impact of ultrasound-guided intercostal nerve block and thoracic paravertebral nerve block on anesthetic dosage and analgesic effect in video-assisted thoracoscopic lobectomy
Changwei YU ; Jianhua YE ; Gang WU ; Aiping TANG
Journal of Clinical Surgery 2025;33(3):275-279
Objective To explore the effects of ultrasound-guided intercostal nerve block(INB)and thoracic paravertebral nerve block(TPVB)on the dosage of anesthetics and the efficacy of analgesia in video-assisted thoracoscopic lobectomy.Methods From October 2019 to October 2023,90 patients undergoing video-assisted thoracoscopic lobectomy at the People's Hospital of Tongling City,Anhui,were selected.They were divided into the INB group(42 cases)and the TPVB group(48 cases).The INB group received ultrasound-guided intercostal nerve block,while the TPVB group was administered ultrasound-guided thoracic paravertebral nerve block.The two groups were compared before anesthesia induction(T0),15 minutes of anesthesia(T1),30 minutes of anesthesia(T2),45 minutes of anesthesia(T3),and after extubation(T4),vita4 signs,anesthetic dosage,analgesic effect,pain stress index and adverse reactions.Results In the TPVB group,systolic blood pressure(SBP)of T1,T2,T3 and T4 were(115.88±9.29)mmHg,(113.58±9.72)mmHg,(117.33±9.17)mmHg and(121.15±10.51)mmHg,respectively;diastolic blood pressure(DBP)were(86.74±7.35)mmHg,(90.83±8.82)mmHg,(90.83±8.82)mmHg and(91.05±8.73)mmHg,respectively;Heart rate(HR)were(79.94±7.46)times/min,(81.97±7.28)times/min,(82.36±7.41)times/min and(85.83±8.32)times/min,respectively.Which were all higher than the INB group[(103.53±8.28)mmHg,(105.40±8.66)mmHg,(109.03±8.13)mmHg,(114.64±9.65)mmHg.(77.68±6.57)mmHg,(79.27±6.69)mmHg,(83.21±7.37)mmHg,(85.83±8.21)mmHg,(71.17±6.21)times/min,(75.18±6.47)times/min,(74.82±6.12)times/min and(79.35±7.12)times/min,respectively],there were statistical significance between the two groups(P<0.05).Postoperatively,the TPVB group had lower 24-hour sufentanil consumption[(27.68±2.64)μg]and fewer presses of the analgesia pump[(5.16±0.38)times]compared to the INB group[(36.22±3.36)μg and(6.87±0.42)times,(P<0.05)].Visual analogue scale(VAS)scores for pain at rest and during coughing at 2,24,and 48 hours in group TPVB were 2.44±0.27,3.55±0.42,2.81±0.34 and 3.36±0.23,4.13±0.33,3.80±0.25,respectively,which were also lower than the INB group(2.83±0.44,3.98±0.55,3.33±0.46 and 3.87±0.30,4.59±0.47,4.17±0.29,respectively)(P<0.05).Levels of prostaglandin E2(PGE2)(1.53±0.28 μg/L),norepinephrine(NE)(362.25±33.85 ng/L),and cortisol(Cor)(278.72±25.13 ng/L)in the TPVB group were lower than those in the INB group(2.71±0.32 μg/L,425.67±38.37 ng/L,315.68±29.21 ng/L)(P<0.05).Adverse reactions such as nausea and vomiting,and dizziness were less frequent in the TPVB group[1(2.1%),1(2.1%)]compared to the INB group[6(12.5%),5(10.4%)](P<0.05).Conclusion Ultrasound-guided thoracic paravertebral nerve block is superior to intercostal nerve block in terms of anesthetic dosage and analgesic efficacy in video-assisted thoracoscopic lobectomy.
4.The impact of ultrasound-guided intercostal nerve block and thoracic paravertebral nerve block on anesthetic dosage and analgesic effect in video-assisted thoracoscopic lobectomy
Changwei YU ; Jianhua YE ; Gang WU ; Aiping TANG
Journal of Clinical Surgery 2025;33(3):275-279
Objective To explore the effects of ultrasound-guided intercostal nerve block(INB)and thoracic paravertebral nerve block(TPVB)on the dosage of anesthetics and the efficacy of analgesia in video-assisted thoracoscopic lobectomy.Methods From October 2019 to October 2023,90 patients undergoing video-assisted thoracoscopic lobectomy at the People's Hospital of Tongling City,Anhui,were selected.They were divided into the INB group(42 cases)and the TPVB group(48 cases).The INB group received ultrasound-guided intercostal nerve block,while the TPVB group was administered ultrasound-guided thoracic paravertebral nerve block.The two groups were compared before anesthesia induction(T0),15 minutes of anesthesia(T1),30 minutes of anesthesia(T2),45 minutes of anesthesia(T3),and after extubation(T4),vita4 signs,anesthetic dosage,analgesic effect,pain stress index and adverse reactions.Results In the TPVB group,systolic blood pressure(SBP)of T1,T2,T3 and T4 were(115.88±9.29)mmHg,(113.58±9.72)mmHg,(117.33±9.17)mmHg and(121.15±10.51)mmHg,respectively;diastolic blood pressure(DBP)were(86.74±7.35)mmHg,(90.83±8.82)mmHg,(90.83±8.82)mmHg and(91.05±8.73)mmHg,respectively;Heart rate(HR)were(79.94±7.46)times/min,(81.97±7.28)times/min,(82.36±7.41)times/min and(85.83±8.32)times/min,respectively.Which were all higher than the INB group[(103.53±8.28)mmHg,(105.40±8.66)mmHg,(109.03±8.13)mmHg,(114.64±9.65)mmHg.(77.68±6.57)mmHg,(79.27±6.69)mmHg,(83.21±7.37)mmHg,(85.83±8.21)mmHg,(71.17±6.21)times/min,(75.18±6.47)times/min,(74.82±6.12)times/min and(79.35±7.12)times/min,respectively],there were statistical significance between the two groups(P<0.05).Postoperatively,the TPVB group had lower 24-hour sufentanil consumption[(27.68±2.64)μg]and fewer presses of the analgesia pump[(5.16±0.38)times]compared to the INB group[(36.22±3.36)μg and(6.87±0.42)times,(P<0.05)].Visual analogue scale(VAS)scores for pain at rest and during coughing at 2,24,and 48 hours in group TPVB were 2.44±0.27,3.55±0.42,2.81±0.34 and 3.36±0.23,4.13±0.33,3.80±0.25,respectively,which were also lower than the INB group(2.83±0.44,3.98±0.55,3.33±0.46 and 3.87±0.30,4.59±0.47,4.17±0.29,respectively)(P<0.05).Levels of prostaglandin E2(PGE2)(1.53±0.28 μg/L),norepinephrine(NE)(362.25±33.85 ng/L),and cortisol(Cor)(278.72±25.13 ng/L)in the TPVB group were lower than those in the INB group(2.71±0.32 μg/L,425.67±38.37 ng/L,315.68±29.21 ng/L)(P<0.05).Adverse reactions such as nausea and vomiting,and dizziness were less frequent in the TPVB group[1(2.1%),1(2.1%)]compared to the INB group[6(12.5%),5(10.4%)](P<0.05).Conclusion Ultrasound-guided thoracic paravertebral nerve block is superior to intercostal nerve block in terms of anesthetic dosage and analgesic efficacy in video-assisted thoracoscopic lobectomy.
5.Analysis of influencing factors of blood transfusion in children with traumatic brain injury and construc-tion of prediction model:A multi-center retrospective study
Wei LIU ; Jun HOU ; Longquan TANG ; Peng ZHOU ; Yan ZHONG ; Qinyan LUO ; Xiaoyu KUANG ; Hua LIU ; Ziqing XIONG ; Wei XIONG ; Chenggao WU ; Aiping LE
The Journal of Practical Medicine 2025;41(4):553-560
Objective To develop a predictive model for guiding blood transfusion decisions in pediatric patients with traumatic brain injury(TBI)by identifying and analyzing key factors that influence blood transfusion requirements.Methods A retrospective analysis was conducted on the clinical data of 1,535 pediatric patients with TBI admitted to four medical institutions from January 1,2015,to December 31,2022.Patients were divided into two groups:those who received red blood cell transfusions during hospitalization and those who did not.Comparative analyses were performed on demographic,clinical,and laboratory data between these two groups.Logistic regression analysis was used to identify risk factors associated with in-hospital blood transfusion,and a predictive model was developed using a nomogram.The performance of this model was evaluated using a receiver operating characteristic(ROC)curve.Results Significant differences were observed between the blood transfusion and non-blood transfusion groups in terms of baseline demographics,clinical indicators,and laboratory test results(all P<0.05).Patients in the blood transfusion group exhibited significantly higher in-hospital mortality,compli-cation rates,use of mechanical ventilation,ICU admission rates,and length of stay compared to those in the non-blood transfusion group(all P<0.05).Multivariate logistic regression analysis identified heart rate,presence of other fractures,treatment methods,hemoglobin(Hb),platelet count(Plt),activated partial thromboplastin time(APTT),and D-dimer levels as independent risk factors for blood transfusion in TBI patients.The area under the ROC curve for the blood transfusion prediction model,based on these independent risk factors,was 0.95(95%CI:0.94~0.97),indicating excellent predictive accuracy.Calibration and decision curves further validated the robust-ness and reliability of the model's predictive capacity.Conclusions Heart rate,presence of other fractures,treatment methods,Hb,Plt count,APTT,and D-dimer levels serve as independent risk factors for blood transfusion in TBI patients.The prediction model developed based on these factors demonstrates excellent predictive performance,thereby guiding clinicians in making informed blood transfusion decisions and enhancing the success rate of patient outcomes.
6.Simultaneous determination of six components in Shangke Dieda Tablets by UPLC
Jinmiao TIAN ; Junshuai LI ; Xiaoyue WANG ; Xueting TANG ; Aiping HE ; Chunling ZHOU
Drug Standards of China 2024;25(4):366-371
Objective:To establish a UPLC method for the simultaneous determination of paeoniflorin,naringin,hesperidin,neohesperidin,costunolide and dehydrocostuslactone to improve the quality standard of Shangke Dieda Tablets.Methods:An Agilent Poroshell 120 C18 column(100 mm × 4.6 mm;2.7 μm)was used with a mobile phase of acetonitrile and 0.1%phosphate solution with binary gradient system at a flow rate of 1.0 mL·min-1.The detection wavelength was 230 nm and the column temperature was 30 ℃.Results:Paeoniflorin,naringin,hesperidin,neohesperidin,cosinolide and dehydrocosinolide showed a good linear relationship between injection concentration and peak area(r>0.999).The linear ranges of six components were 0.854 2-256.272 μg·mL-1(r=0.999 9),1.057 5-317.247 μg·mL-1(r=0.999 9),and 0.989 5-269.850 μg·mL-1(r=0.999 9),1.055 6-316.689 μg·mL-1(r=0.999 9),0.905 1-271.527 μg·mL-1(r=0.999 8),and 1.064 7-319.395 μg·mL-1(r=0.999 9),respectively.The average recoveries of six components were 99.4%(RSD=1.2%),104.0%(RSD=1.2%),101.6%(RSD=1.0%),102.9%(RSD=0.4%),97.0%(RSD=1.9%),and 104.2%(RSD=1.0%),respectively.A total of 74 batches of samples were collected from 10 manufacturers.The contents of paeoniflorin,naringin,hesperidin,neohesperidin,coxinolactone,and dehydro-cosinolactone were 0.250 8-0.653 2,0.042 2-0.930 9,0.590 9-3.978 0,0.021 2-0.592 6,0.002 4-0.156 7,0.009 2-0.231 3 mg per tablet,respectively.Conclusion:The validated results showed that the method can be used to control the quality of Shangke Dieda Tablets.
7.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
8.Development of postoperative exercise rehabilitation review indicators for patients with vertebral fractures and obstacles
Chi TANG ; Dan ZHOU ; Aiping ZHAO ; Qian ZHANG ; Kai ZHU
Chinese Journal of Modern Nursing 2024;30(11):1464-1470
Objective:To carry out evidence-based nursing for postoperative exercise rehabilitation of patients with vertebral fractures, develop review indicators, analyze obstacles and facilitators in evidence-based nursing practice, and formulate reform strategies.Methods:Guided by the evidence-based nursing practice model of the Joanna Briggs Institute, this study incorporated evidence of postoperative exercise rehabilitation in patients with vertebral fractures and developed review items. Based on baseline review, the obstacles and facilitators in evidence-based nursing practice were analyzed, and reform strategies were formulated.Results:A total of 29 evidence items were included, and 16 review indicators were formulated. Only seven indicators had a compliance rate of 100%, two indicators had a compliance rate of 0, and the compliance rate of the remaining indicators was between 11% and 95%. The obstacles in evidence-based nursing practice came from three levels: system, practitioner, and patient. The facilitators included strong leadership and organizational abilities, close cooperation between medical and nursing teams, and so on. Corresponding change strategies were developed based on obstacles and facilitators.Conclusions:There is a certain gap between the evidence of exercise rehabilitation and evidence-based nursing practice in postoperative patients with vertebral fractures. We should make full use of facilitators to overcome obstacles and implement reform strategies.
9.Advances in genomics of multi-drug resistant Stenotrophomonas.
Yuhang TANG ; Shiqi FANG ; Linlin XIE ; Chao SUN ; Shanshan LI ; Aiping ZHOU ; Guangxiang CAO ; Jun LI
Chinese Journal of Biotechnology 2023;39(4):1314-1331
Stenotrophomonas species are non-fermentative Gram-negative bacteria that are widely distributed in environment and are highly resistant to numerous antibiotics. Thus, Stenotrophomonas serves as a reservoir of genes encoding antimicrobial resistance (AMR). The detection rate of Stenotrophomonas is rapidly increasing alongside their strengthening intrinsic ability to tolerate a variety of clinical antibiotics. This review illustrated the current genomics advances of antibiotic resistant Stenotrophomonas, highlighting the importance of precise identification and sequence editing. In addition, AMR diversity and transferability have been assessed by the developed bioinformatics tools. However, the working models of AMR in Stenotrophomonas are cryptic and urgently required to be determined. Comparative genomics is envisioned to facilitate the prevention and control of AMR, as well as to gain insights into bacterial adaptability and drug development.
Stenotrophomonas/genetics*
;
Drug Resistance, Bacterial/genetics*
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Anti-Bacterial Agents/pharmacology*
;
Gram-Negative Bacteria
;
Genomics
;
Microbial Sensitivity Tests

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