1.Genetic Correlation and Mendelian Randomization Analysis Revealed an Unidirectional Causal Relationship Between Left Caudal Middle Frontal Surface Area and Cigarette Consumption
Hongcheng XIE ; Anlin WANG ; Minglan YU ; Tingting WANG ; Xuemei LIANG ; Rongfang HE ; Chaohua HUANG ; Wei LEI ; Jing CHEN ; Youguo TAN ; Kezhi LIU ; Bo XIANG
Psychiatry Investigation 2025;22(3):279-286
Objective:
Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them.
Methods:
To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted.
Results:
The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4).
Conclusion
Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.
2.Genetic Correlation and Mendelian Randomization Analysis Revealed an Unidirectional Causal Relationship Between Left Caudal Middle Frontal Surface Area and Cigarette Consumption
Hongcheng XIE ; Anlin WANG ; Minglan YU ; Tingting WANG ; Xuemei LIANG ; Rongfang HE ; Chaohua HUANG ; Wei LEI ; Jing CHEN ; Youguo TAN ; Kezhi LIU ; Bo XIANG
Psychiatry Investigation 2025;22(3):279-286
Objective:
Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them.
Methods:
To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted.
Results:
The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4).
Conclusion
Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.
3.Genetic Correlation and Mendelian Randomization Analysis Revealed an Unidirectional Causal Relationship Between Left Caudal Middle Frontal Surface Area and Cigarette Consumption
Hongcheng XIE ; Anlin WANG ; Minglan YU ; Tingting WANG ; Xuemei LIANG ; Rongfang HE ; Chaohua HUANG ; Wei LEI ; Jing CHEN ; Youguo TAN ; Kezhi LIU ; Bo XIANG
Psychiatry Investigation 2025;22(3):279-286
Objective:
Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them.
Methods:
To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted.
Results:
The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4).
Conclusion
Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.
4.Genetic Correlation and Mendelian Randomization Analysis Revealed an Unidirectional Causal Relationship Between Left Caudal Middle Frontal Surface Area and Cigarette Consumption
Hongcheng XIE ; Anlin WANG ; Minglan YU ; Tingting WANG ; Xuemei LIANG ; Rongfang HE ; Chaohua HUANG ; Wei LEI ; Jing CHEN ; Youguo TAN ; Kezhi LIU ; Bo XIANG
Psychiatry Investigation 2025;22(3):279-286
Objective:
Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them.
Methods:
To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted.
Results:
The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4).
Conclusion
Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.
5.Genetic Correlation and Mendelian Randomization Analysis Revealed an Unidirectional Causal Relationship Between Left Caudal Middle Frontal Surface Area and Cigarette Consumption
Hongcheng XIE ; Anlin WANG ; Minglan YU ; Tingting WANG ; Xuemei LIANG ; Rongfang HE ; Chaohua HUANG ; Wei LEI ; Jing CHEN ; Youguo TAN ; Kezhi LIU ; Bo XIANG
Psychiatry Investigation 2025;22(3):279-286
Objective:
Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them.
Methods:
To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted.
Results:
The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4).
Conclusion
Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.
6.Research progress on the chemical constituents,pharmacological mechanisms and clinical application of Jiegeng decoction
Yun HUANG ; Shunwang HUANG ; Jinwei QIAO ; Qian XU ; Xiaoming GAO ; Xuemei BAO ; Manqin YANG ; Ruonan XIE ; Ming CAI
China Pharmacy 2025;36(18):2348-2352
Jiegeng decoction is a classic prescription composed of two Chinese medicinal herbs: Platycodon grandiflorum and Glycyrrhiza uralensis. It has the efficacy of diffusing lung qi, resolving phlegm, relieving sore throat and discharging pus, and is commonly used in the treatment of respiratory diseases such as cough and pharyngodynia. This article reviews the chemical components, pharmacological mechanisms and clinical applications of Jiegeng decoction. It was found that Jiegeng decoction contains triterpenoid saponins, flavonoids, glycosides, acids, and other components, with platycodin D, platycodin D2, glycyrrhizic acid, glycyrrhetinic acid, liquiritin, etc., serving as the main active pharmaceutical ingredients. Jiegeng decoction and its chemical constituents exert anti-inflammatory effects by inhibiting signaling pathways such as nuclear factor-κB and mitogen- activated protein kinases, and demonstrate anti-tumor activities through mechanisms like modulating the tumor immune microenvironment and promoting cancer cell apoptosis. Additionally, it exhibits various pharmacological actions including antibacterial, antiviral, and antioxidant effects. Clinically, Jiegeng decoction, its modified prescription and compound combinations are widely used in the treatment of respiratory diseases such as cough, pneumonia, and pharyngitis, as well as digestive system disorders like constipation.
7.Clinical features of recompensation in autoimmune hepatitis-related decompensated cirrhosis and related predictive factors
Xiaolong LU ; Lin HAN ; Huan XIE ; Lilong YAN ; Xuemei MA ; Dongyan LIU ; Xun LI ; Qingsheng LIANG ; Zhengsheng ZOU ; Caizhe GU ; Ying SUN
Journal of Clinical Hepatology 2025;41(9):1808-1817
ObjectiveTo investigate the clinical features and outcomes of recompensation in patients with autoimmune hepatitis (AIH)-related decompensated cirrhosis, to identify independent predictive factors, and to construct a nomogram prediction model for the probability of recompensation. MethodsA retrospective cohort study was conducted among the adult patients with AIH-related decompensated cirrhosis who were admitted to The Fifth Medical Center of PLA General Hospital from January 2015 to August 2023 (n=211). The primary endpoint was achievement of recompensation, and the secondary endpoint was liver-related death or liver transplantation. According to the outcome of the patients at the end of the follow-up, the patients were divided into the recompensation group (n=16) and the persistent decompensation group(n=150).The independent-samples t test was used for comparison of normally distributed continuous data with homogeneity of variance, and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data with heterogeneity of variance; the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups; the Kaplan-Meier method was used for survival analysis; the Cox proportional-hazards regression model was used to identify independent predictive factors, and a nomogram model was constructed and validated. ResultsA total of 211 patients were enrolled, with a median age of 55.0 years and a median follow-up time of 44.0 months, and female patients accounted for 87.2%. Among the 211 patients, 61 (with a cumulative proportion of 35.5%) achieved recompensation. Compared with the persistent decompensation group, the recompensation group had significantly higher white blood cell count, platelet count (PLT), total bilirubin (TBil), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bile acid, prothrombin time, international normalized ratio (INR), SMA positive rate, Model for End-Stage Liver Disease (MELD) score, Child-Pugh score, and rate of use of glucocorticoids (all P0.05), as well as significantly lower age at baseline, number of complications, and death/liver transplantation rate (all P0.05). At 3 and 12 months after treatment, the recompensation group had continuous improvements in AST, TBil, INR, IgG, MELD score, and Child-Pugh score, which were significantly lower than the values in the persistent decompensation group (all P0.05), alongside with continuous increases in PLT and albumin, which were significantly higher than the values in the persistent decompensation group (P0.05). The multivariate Cox regression analysis showed that baseline ALT (hazard ratio [HR]=1.067, 95% confidence interval [CI]: 1.010 — 1.127, P=0.021), IgG (HR=0.463,95%CI:0.258 — 0.833, P=0.010), SMA positivity (HR=3.122,95%CI:1.768 — 5.515, P0.001), and glucocorticoid therapy (HR=20.651,95%CI:8.744 — 48.770, P0.001) were independent predictive factors for recompensation, and the nomogram model based on these predictive factors showed excellent predictive performance (C-index=0.87,95%CI:0.84 — 0.90). ConclusionAchieving recompensation significantly improves clinical outcomes in patients with AIH-related decompensated cirrhosis. Baseline SMA positivity, a high level of ALT, a low level of IgG, and corticosteroid therapy are independent predictive factors for recompensation. The predictive model constructed based on these factors can provide a basis for decision-making in individualized clinical management.
8.Prediction and evaluation of nomogram model on risk of hyperuricemia in overweight and obese children and adolescents
Jianying JING ; Ningting XIAO ; Xuemei GUO ; Xueming JING ; Rong XIE ; Yonglong HE
Chongqing Medicine 2024;53(2):220-225
Objective To establish a nomogram prediction model of hyperuricemia(HUA)onset risk in overweight and obese children and adolescents in order to provide reference for the prevention and treatment of HUA in this population.Methods The clinical data of 1 410 overweight and obese children and adolescents aged 6-17 years old visiting in this hospital from September 2021 to August 2022 were retrospectively analyzed.A total of 987 overweight and obese children and adolescents were randomly extracted according to a ratio of 7:3 to establish the model,and the remaining 423 cases were validated internally.Referring to the definition of high uric acid in"Zhu-futang Practical Pediatrics",the subjects were divided into high uric acid group and non-high uric acid group.The logis-tic regression analysis was used to analyze the influencing factors of HUA in overweight and obese children and adoles-cents.The nomogram model was constructed by using the R language.The area under the receiver operating character-istic(ROC)curve(AUC),decision analysis curve(DIC),clinical impact curve(CIC)and C-index were used to evalu-ate the predictive ability of the model,and the Bootstrap repeated sampling method(taking samples for 1000 times)was used for internal validation of the model.Results The results of multivariate analysis showed that the age(OR=2.324,95%CI:1.155-4.672,P=0.018),gender(OR=0.456,95%CI:0.256-0.810,P=0.007),triglycerides(OR=3.775,95%CI:2.321-6.138,P<0.001),blood calcium(OR=26.986,95%CI:3.186-228.589,P=0.003)and blood creatinine(OR=1.047,95%CI:1.026-1.070,P<0.001)were the influen-cing factors of HUA in overweight and obese children and adolescents.AUC of the ROC curve of the model was 0.840,the sensitivity was 0.786,the specificity was 0.762,the Youden index was 0.548,and the C-index was 0.840.The risk probability of DC A was 0.1-0.8,the net benefit rate of both models was>0,AUC of ROC curve in the internal verification was 0.871.Conclusion The constructed nomogram in this study has a good predictive efficiency for the onset risk of HUA in overweight and obese children and adolescents,and may provide reference for the early diagnosis and treatment of this population.
9.Efficacy and safety analysis of upadacitinib in the treatment of moderate to severe inflammatory bowel disease
Xiuli ZHU ; Jiaqin XU ; Qiaomin WANG ; Li XIE ; Xuemei XU
Modern Interventional Diagnosis and Treatment in Gastroenterology 2024;29(8):917-922
Objective This study summarized the clinical data of IBD patients receiving upadacitinib treatment in our hospital,and provided more Chinese data to better guide the treatment of upadacitinib in Chinese IBD population.Methods Clinical data of 11 patients with IBD who received upadacitinib treatment at Anhui Provincial Hospital from March 1,2023 to September 8,2024 were retrospectively analyzed.Platelet count,ESR,CRP,disease severity score,endoscopic score,and adverse reactions were compared before treatment,at the 4th and 8th week of treatment,and clinical response rate,clinical response rate,endoscopic response rate,and endoscopic response rate were calculated.SPSS 25.0 software was used for statistical analysis.Results The platelets,ESR and CRP of patients at the 4th and 8th week after upadacitinib treatment were decreased compared with those before treatment,with statistical significance.At the 4th week,the clinical response rate was 72.72%(8/11),the clinical remission rate was 0,the clinical response rate of UC patients was 83.33%(5/6),and the clinical response rate of CD patients was 60%(3/5).At the 8th week of treatment,the clinical response rate was 100%(10/10),the clinical remission rate was 80.00%(8/10),the clinical response rate of UC patients was 100%(6/6),the clinical remission rate of UC patients was 83.33%(5/6),the clinical response rate of CD patients was 100%(4/4),and the clinical remission rate of CD was 75%(3/4).There were no adverse reactions during treatment.Three patients were re-examined by colonoscopy,all of whom were severe UC patients and achieved mucosal healing.Conclusion Upadacitinib can rapidly,effectively and sustainably control the disease in patients with moderate and severe IBD,with high safety.
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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