Journal of Peking University (Health Sciences) ›› 2020, Vol. 52 ›› Issue (2): 298-301. doi: 10.19723/j.issn.1671-167X.2020.02.017

Previous Articles     Next Articles

Application of multidisciplinary team (MDT) in the treatment of severe trauma

Zhe DU,Wei HUANG,Zhi-wei WANG,Jing ZHOU,Jian XIONG,Ming LI,Peng ZHANG,Zhong-di LIU,Feng-xue ZHU,Chuan-lin WANG,Bao-guo JIANG,Tian-bing WANG()   

  1. Trauma Center, Peking University People's Hospital, National Center for Trauma Medicine, Beijing 100044, China
  • Received:2019-08-14 Online:2020-04-18 Published:2020-04-18
  • Contact: Tian-bing WANG E-mail:wangtianbing@pkuph.edu.cn
  • Supported by:
    Supported by Subproject of 2022 Science and Technology Winter Olympic Project(2018YFF0301103);Peking University People’s Hospital Scientific Research Development Funds(RD2019-02)

Abstract:

Objective: To explore the effect of multi-disciplinary team (MDT) in general hospitals on severe trauma patients.Methods: This study reviewed the treatment of patients with severe trauma in trauma center of Peking University People's Hospital from March 2017 to April 2019. The baseline information: the patients' gender, age, injury mechanism, etc.; the start indicators: the Glasgow coma scale (GCS), trauma index (TI), injury severity score (ISS); the start related indicators: time for activation, time for MDT to arrive, time for CT scan, time for damage control surgery; patient treatment and prognosis: ICU (intensive care unit) length of stay, number of cured and discharged patients, number of dead cases, number of patients transferred to rehabilitation hospital, were all analyzed. It discussed the composition of MDT, the initiation scheme, the indicators of initiation of MDT for severe trauma, and analyzed the correlation between the application of MDT and the prognosis of patients.Results: From March 2017 to April 2019, 112 trauma patients were treated by MDT in Peking University People's Hospital. There were 69 males and 43 females. The minimum age was 15 years, the maximum age was 89 years, most of them were 36-55 years old. The main injury mechanism was traffic accident injury. The GCS, TI, ISS were 13.0±2.9, 13.0±2.8, and 21.5±11.9, respectively. It took 3.7±0.8 minutes to start the call, 6.1±0.9 minutes for MDT personnel to arrive at the emergency rescue area, 23.8±3.0 minutes for fast CT and 92.6±15.4 minutes for injury control operation. All the hospitalized patients were treated effectively. ICU (Intensive care unit) hospitalization time was 12.6±6.7 days. 55 discharged patients were cured, 5 died (1 died of hemorrhagic shock, 4 died of severe brain injury) and 52 transferred to rehabilitation hospital.Conclusion: The treatment of severe trauma patients by MDT in trauma center of general hospitals can greatly improve the ability and level of treatment of severe trauma patients, make up for the lack of treatment of severe trauma especially multiple trauma patients in large general hospitals, and improve the treatment effect of severe trauma patients. It provides a reference model for large general hospitals to treat patients with severe trauma and multiple trauma and for the construction of trauma centers.

Key words: Trauma center, Multidisciplinary team (MDT), Model, Severe trauma, Application

CLC Number: 

  • R649.9

Table 1

The baseline characteristics of severe trauma patients"

Items Number
Gender
Male 69
Female 43
Age
15-35 12
36-55 48
56-75 39
>75 13
Mechanics of injury
Traffic accidents 52
Fall 29
Explosion, crush injury 19
Others 12

Table 2

Evaluation of related indicators after start-up of MDT"

Indicators Data
Activation indicators
GCS 13.0±2.9
TI 13.0±3.8
ISS 21.5±11.9
Activation related indicators/min
Time for activation 3.7±0.8
Time for MDT to arrive 6.1±0.9
Time for CT scan 23.8±3.0
Time for damage control surgery 92.6±15.4
[1] 王天兵, 李明, 杜哲 , 等. 创伤救治中心建设中的医疗质量控制[J]. 中华创伤杂志, 2019,35(3):212-215.
[2] Mercer SJ, Kingston EV, Jones CPL . The trauma call[J]. BMJ, 2018,361:k2272.
[3] 唐华民 . 创伤救治"黄金 1h": 美国创伤系统介绍[J]. 创伤外科杂志, 2017,19(8):638-640.
[4] 胡培阳, 张连阳 . 综合性医院创伤救治多学科团队的建设和维护[J]. 创伤外科杂志, 2018,20(9):719-720.
[5] 都定元, 王建柏 . 中国创伤外科发展现状与展望[J]. 创伤外科杂志, 2018,20(3):161-165.
[6] 邓进, 张连阳 . 我国创伤救治中心建设的困境与对策[J]. 中华灾害救援医学, 2017,5(8):464-466.
[7] 邓鹏, 陈建红, 周祥军 , 等. 县市级创伤救治中心 MDT 模式对提高重症创伤患者生存率的研究[J]. 现代医学与健康研究, 2018,2(16):163-165.
[8] Long AM, Lefebvre CM, Masneri DA , et al. The golden opportunity: multidisciplinary simulation training improves trauma team efficiency[J]. J Surg Educ, 2019,76(4):1116-1121.
[9] 寇玉辉, 殷晓峰, 王天兵 , 等. 严重创伤救治规范的研究与推广[J]. 北京大学学报(医学版), 2015,47(2):207-210.
[1] LIU Si-min,ZHAO Yi-jiao,WANG Xiao-yan,WANG Zu-hua. In vitro evaluation of positioning accuracy of trephine bur at different depths by dynamic navigation [J]. Journal of Peking University (Health Sciences), 2022, 54(1): 146-152.
[2] Rui-xuan JIA,Shang-wei JIANG,Lin ZHAO,Li-ping YANG. Generation and characterization of Cyp4v3 gene knockout mice [J]. Journal of Peking University (Health Sciences), 2021, 53(6): 1099-1106.
[3] WANG Gui-hong,ZUO Ting,LI Ran,ZUO Zheng-cai. Effect of rebamipide on the acute gouty arthritis in rats induced by monosodium urate crystals [J]. Journal of Peking University (Health Sciences), 2021, 53(4): 716-720.
[4] LIU Qiu-ping,CHEN Xi-jin,WANG Jia-min,LIU Xiao-fei,SI Ya-qin,LIANG Jing-yuan,SHEN Peng,LIN Hong-bo,TANG Xun,GAO Pei. Effectiveness of different screening strategies for cardiovascular diseases prevention in a community-based Chinese population: A decision-analytic Markov model [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 460-466.
[5] WANG Xiao-qi,CHEN Mei-jun,YUN Qing-ping,SUN Si-wei,WANG Xi-kai,SHI Yu-hui,JI Ying,GUAN Zhong-jun,CHANG Chun. Impact of health literacy on patient experience of outpatients in China and its mechanism [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 560-565.
[6] ZHANG Jia-wei, HAN Pei-en, YANG Li. Spatial accessibility of fever clinics for multi-tiered prevention and control on COVID-19 in Beijing [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 543-548.
[7] CHEN Huai-an,LIU Shuo,LI Xiu-jun,WANG Zhe,ZHANG Chao,LI Feng-qi,MIAO Wen-long. Clinical value of inflammatory biomarkers in predicting prognosis of patients with ureteral urothelial carcinoma [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 302-307.
[8] WANG Zhi-cheng,GUO Yan. Association between community socioeconomic status and adults’ self-rated health in China [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 314-319.
[9] CHEN Di,XU Xiang-yu,WANG Ming-rui,LI Rui,ZANG Gen-ao,ZHANG Yue,QIAN Hao-nan,YAN Guang-rong,FAN Tian-yuan. Preparation and in vitro evaluation of fused deposition modeling 3D printed verapa-mil hydrochloride gastric floating formulations [J]. Journal of Peking University (Health Sciences), 2021, 53(2): 348-354.
[10] GAO Yang-xu,SUN Qing,LI Hui,XIE Yao,YAO Hong-xin,ZHAO Wei-hong. Therapeutic effect and clinical cost of multi-disciplinary team model of hepatoblastoma in children [J]. Journal of Peking University (Health Sciences), 2021, 53(1): 200-203.
[11] Ze-ming LI,Min GAO,Xue-ying CHEN,Xin-ying SUN. Relationship between the five-factor model of personality traits and self-management attitude of patients with type 2 diabetes [J]. Journal of Peking University (Health Sciences), 2020, 52(3): 506-513.
[12] Xiao-yuan ZHANG,Cheng-cheng GUO,Ying-xiang YU,Lan XIE,Cui-qing CHANG. Establishment of high-fat diet-induced obesity and insulin resistance model in rats [J]. Journal of Peking University (Health Sciences), 2020, 52(3): 557-563.
[13] Ning XIAO,Yu-chun SUN,Yi-jiao ZHAO,Yong WANG. Preliminary study on three digital analysis methods for analyzing the distribution and area of occlusal contacts [J]. Journal of Peking University(Health Sciences), 2020, 52(1): 144-151.
[14] Shan-shan BAI,Si-yi MO,Xiao-xiang XU,Yun LIU,Qiu-fei XIE,Ye CAO. Characteristics of orofacial operant test for orofacial pain sensitivity caused by occlusal interference in rats [J]. Journal of Peking University(Health Sciences), 2020, 52(1): 51-57.
[15] Fei-long YANG,Kai HONG,Guo-jiang ZHAO,Cheng LIU,Yi-meng SONG,Lu-lin MA. Construction of prognostic model and identification of prognostic biomarkers based on the expression of long non-coding RNA in bladder cancer via bioinformatics [J]. Journal of Peking University(Health Sciences), 2019, 51(4): 615-622.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] . [J]. Journal of Peking University(Health Sciences), 2009, 41(4): 456 -458 .
[2] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 125 -128 .
[3] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 135 -140 .
[4] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 158 -161 .
[5] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 217 -220 .
[6] . [J]. Journal of Peking University(Health Sciences), 2009, 41(1): 52 -55 .
[7] . [J]. Journal of Peking University(Health Sciences), 2009, 41(1): 109 -111 .
[8] . [J]. Journal of Peking University(Health Sciences), 2009, 41(3): 297 -301 .
[9] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 505 -515 .
[10] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 599 -601 .