1.Combination of CT/MRI LI-RADS With Second-Line Contrast-Enhanced Ultrasound Using Sulfur Hexafluoride or Perfluorobutane for Diagnosing Hepatocellular Carcinoma in High-Risk Patients
Yu LI ; Sheng LI ; Qing LI ; Kai LI ; Jing HAN ; Siyue MAO ; Xiaohong XU ; Zhongzhen SU ; Yanling ZUO ; Shousong XIE ; Hong WEN ; Xuebin ZOU ; Jingxian SHEN ; Lingling LI ; Jianhua ZHOU
Korean Journal of Radiology 2025;26(4):346-359
Objective:
The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB).
Materials and Methods:
This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB.
Results:
In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%).
Conclusion
The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.
2.Combination of CT/MRI LI-RADS With Second-Line Contrast-Enhanced Ultrasound Using Sulfur Hexafluoride or Perfluorobutane for Diagnosing Hepatocellular Carcinoma in High-Risk Patients
Yu LI ; Sheng LI ; Qing LI ; Kai LI ; Jing HAN ; Siyue MAO ; Xiaohong XU ; Zhongzhen SU ; Yanling ZUO ; Shousong XIE ; Hong WEN ; Xuebin ZOU ; Jingxian SHEN ; Lingling LI ; Jianhua ZHOU
Korean Journal of Radiology 2025;26(4):346-359
Objective:
The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB).
Materials and Methods:
This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB.
Results:
In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%).
Conclusion
The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.
3.Combination of CT/MRI LI-RADS With Second-Line Contrast-Enhanced Ultrasound Using Sulfur Hexafluoride or Perfluorobutane for Diagnosing Hepatocellular Carcinoma in High-Risk Patients
Yu LI ; Sheng LI ; Qing LI ; Kai LI ; Jing HAN ; Siyue MAO ; Xiaohong XU ; Zhongzhen SU ; Yanling ZUO ; Shousong XIE ; Hong WEN ; Xuebin ZOU ; Jingxian SHEN ; Lingling LI ; Jianhua ZHOU
Korean Journal of Radiology 2025;26(4):346-359
Objective:
The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB).
Materials and Methods:
This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB.
Results:
In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%).
Conclusion
The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.
4.Molecular epidemiological characterization of influenza A(H3N2) virus in Fengxian District, Shanghai, in the surveillance year of 2023
Hongwei ZHAO ; Lixin TAO ; Xiaohong XIE ; Yi HU ; Xue ZHAO ; Meihua LIU ; Qingyuan ZHANG ; Lijie LU ; Chen’an LIU ; Mei WU
Shanghai Journal of Preventive Medicine 2025;37(1):18-22
ObjectiveTo understand the epidemiological distribution and gene evolutionary variation of influenza A (H3N2) viruses in Fengxian District, Shanghai, in the surveillance year of 2023, and to provide a reference basis for influenza prevention and control. MethodsThe prevalence of influenza virus in Fengxian District in the 2023 influenza surveillance year (April 2023‒March 2024) was analyzed. The hemagglutinin (HA) gene, neuraminidase (NA) gene, and amino acid sequences of 75 strains of H3N2 influenza viruses were compared with the vaccine reference strain for similarity matching and phylogenetic evolutionary analysis, in addition to an analysis of gene characterization and variation. ResultsIn Fengxian District, there was a mixed epidemic of H3N2 and H1N1 in the spring of 2023, with H3N2 being the predominant subtype in the second half of the year, and Victoria B becoming the predominant subtype in the spring of 2024. A total of 75 influenza strains of H3N2 with HA and NA genes were distributed in the 3C.2a1b.2a.2a.2a.3a.1 and B.4 branches, with overall similarity to the reference strain of the 2024 vaccine higher than that of the reference strain of the 2022 and 2023 vaccine. Compared with the 2023 vaccine reference strain, three antigenic sites and one receptor binding site were changed in HA, with three glycosylation sites reduced and two glycosylation sites added; where as in NA seven antigenic sites and the 222nd resistance site changed with two glycosylation sites reduced. ConclusionThe risk of antigenic variation and drug resistance of H3N2 in this region is high, and it is necessary to strengthen the publicity and education on the 2024 influenza vaccine and long-term monitoring of influenza virus prevalence and variation levels.
5.Combination of CT/MRI LI-RADS With Second-Line Contrast-Enhanced Ultrasound Using Sulfur Hexafluoride or Perfluorobutane for Diagnosing Hepatocellular Carcinoma in High-Risk Patients
Yu LI ; Sheng LI ; Qing LI ; Kai LI ; Jing HAN ; Siyue MAO ; Xiaohong XU ; Zhongzhen SU ; Yanling ZUO ; Shousong XIE ; Hong WEN ; Xuebin ZOU ; Jingxian SHEN ; Lingling LI ; Jianhua ZHOU
Korean Journal of Radiology 2025;26(4):346-359
Objective:
The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB).
Materials and Methods:
This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB.
Results:
In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%).
Conclusion
The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.
6.Pathogen spectrum of diarrheal disease surveillance in Fengxian District, Shanghai, 2013‒2023
Meihua LIU ; Yuan ZHUANG ; Xiaohong XIE ; Hongwei ZHAO ; Yuan SHI ; Lijuan DING ; Yi HU ; Lixin TAO
Shanghai Journal of Preventive Medicine 2025;37(4):336-341
ObjectiveTo investigate the pathogenic spectrum and epidemiological characteristics of diarrheal disease in Fengxian District of Shanghai, and to provide scientific basis for the prevention and control of diarrheal diseases. MethodsBasic information of the initial adult cases visited diarrheal disease surveillance sentinel hospital in Fengxian District, Shanghai, was collected from August 2013 to 2023, and fecal samples were collected at 1∶5 sampling intervals to isolate and identify 5 kinds of diarrheagenic Escherichia coli (DEC), Salmonella (SAL), Vibrio parahaemolyticus, Campylobacter, Vibrio cholerae, Shigella and Yersinia enterocolitica (YE). Simultaneously, nucleic acid detection was performed for 3 kinds of rotavirus, 2 kinds of norovirus, intestinal adenovirus, astrovirus and sapovirus. ResultsA total of 1 861 cases of newly diagnosed diarrheal disease were reported, with the peak in July to August. Additionally, 704 surveillance samples were detected, with a total positive detection rate of 50.57%. The detection rates of bacterial, viral and mixed infection were 25.14%, 21.02% and 4.40%, respectively. Among the pathogens detected, DEC accounted for the highest (17.61%, 124/704), followed by norovirus (16.48%, 116/704), rotavirus (6.39%, 45/704), SAL (5.97%, 42/704) and Campylobacter (3.84%, 27/704). DEC detected were mainly enteroaggregative Escherichia coli and enterotoxigenic Escherichia coli, with no detection of Vibrio cholerae, Shigella and YE. The highest total pathogen detection rate was observed from June to September, and the detection peaks of norovirus were from March to June and from October to December, whereas that of DEC was from June to October. The detection rate of rotavirus peaked from January to February, but which was not detected between 2020‒2023. The SAL positive rate peak was in September, whereas that of Campylobacter was from July to September. ConclusionThe main pathogens detected in Fengxian District from 2013‒2019 are DEC, norovirus, rotavirus, SAL and Campylobacter. Different pathogens have different detection peaks, with bacteria predominating in summer and viruses in winter and spring. Prevention and control measures should be carried out according to the epidemiological characteristics of different seasons.
7.Combination of CT/MRI LI-RADS With Second-Line Contrast-Enhanced Ultrasound Using Sulfur Hexafluoride or Perfluorobutane for Diagnosing Hepatocellular Carcinoma in High-Risk Patients
Yu LI ; Sheng LI ; Qing LI ; Kai LI ; Jing HAN ; Siyue MAO ; Xiaohong XU ; Zhongzhen SU ; Yanling ZUO ; Shousong XIE ; Hong WEN ; Xuebin ZOU ; Jingxian SHEN ; Lingling LI ; Jianhua ZHOU
Korean Journal of Radiology 2025;26(4):346-359
Objective:
The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB).
Materials and Methods:
This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB.
Results:
In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%).
Conclusion
The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.
8.Bioinformatics combined with machine learning to identify early warning markers for severe dengue
Yizi XIE ; Shaofeng ZHAN ; Huiting HUANG ; Wujin WEN ; Xiaohong LIU ; Yong JIANG
Journal of China Medical University 2024;53(7):583-590
Objective The goals of this study were to identify early warning markers of severe dengue based on bioinformatics com-bined with machine learning,and explore the evaluation system of the risk of occurrence of severe dengue.Methods Based on the Gene Expression Omnibus database,the differentially expressed genes between dengue and severe dengue were analyzed,and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted.Early warning genes of severe dengue were screened using a random forest model,and the accuracy of the genes was verified using receiver operating characteristic(ROC)curves.Finally,nomograms were constructed to quantify the warning genes and predict the risk of progression from dengue to severe dengue based on the expression level of these genes.Results A total of 817 differentially expressed genes were identified,along with the associated biolo-gical processes that may be closely related to the occurrence and development of severe dengue,namely,antimicrobial humoral response,humoral immune response,serine hydrolase activity,and arachidonic acid metabolism.Based on this analysis,five early warning genes were isolated:AZU1,PDCD4,COL4A3BP,TRPM4,and ATP4A.Among these,ATP4A,COL4A3BP,and TRPM4 showed low expression levels,whereas AZU1and PDCD4were highly expressed.The ROC curves indicated that these genes were accurate pre-dictors of severe dengue.The nomograms indicated good predictive accuracy,clinical benefit rate,and clinical effectiveness of the model.Conclusion Measuring the expression levels of five warning genes(AZU1,PDCD4,COL4A3BP,TRPM4,and ATP4A)may help to evaluate the risk of severe dengue.
9.Multi-omics combined test performance effectiveness on opportunistic screening of high-risk liver cancer population
Chan XIE ; Bingliang LIN ; Hong DENG ; Xiaohong ZHANG ; Qiyi ZHAO ; Zhiliang GAO
Chinese Journal of Hepatology 2024;32(2):140-147
Objective:To validate the performance of a multi-omics combined test for early screening of high-risk liver cancer populations.Methods:173 high-risk patients with liver cancer were prospectively screened in a real-world setting, and 164 cases were finally enrolled. B-ultrasound, alpha-fetoprotein (AFP), and HCC screens were conducted in all patients. A multi-omics early screening test was performed for liver cancer in combination with multi-gene methylation, TP53/TERT/CTNNB1 mutations, AFP, and abnormal prothrombin (PIVKA-II). Differences in rates were compared using the chi-square test, adjusted chi-square test, or Fisher's exact probability method for count data. A non-parametric rank test (Mann-Whitney) was used to compare the differences between the two groups of data.Results:The HCCscreen detection had a sensitivity of 100% for liver cancer screening, 93.8% for liver cancer and precancerous diseases, 34.1% for positive predictive value, 99.2% for negative predictive value, and 0.89 for an area under the curve (AUC). Parallel detection of AFP, AFP+B-ultrasound, and methylation+mutation had a sensitivity/specificity and AUC of 31.3%/88.5% (AUC=0.78), 56.3%/88.2% (AUC=0.86), and 81.3%/82.4 % (AUC=0.84). At the same time, the disease severity range was significantly correlated with the methylation+mutation score, HCCscreen score, or positive detection rate (PDR). There was no significant correlation between AFP serum levels and methylation+mutation or HCCscreen scores, while there was a significant linear correlation between methylation+mutation scores and HCCscreen scores ( r ?=?0.73, P ?0.001). Conclusion:In real-world settings, HCCscreen shows high sensitivity for screening opportunistic, high-risk liver cancer populations. Furthermore, it may efficaciously detect liver cancer and precancerous diseases, with superior performance to AFP and AFP+ultrasound. Hence, HCCscreen has the potential to become an effective screening tool that is superior to existing screening methods for high-risk liver cancer populations.
10.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.

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