Volume 23 Issue 4
Apr.  2025
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LI Lin, WANG Enzhao, LI Laichun, ZHOU Jiehao, SONG Kun. Application of '5G' emergency management model in trauma emergency treatment[J]. Chinese Journal of General Practice, 2025, 23(4): 604-607. doi: 10.16766/j.cnki.issn.1674-4152.003961
Citation: LI Lin, WANG Enzhao, LI Laichun, ZHOU Jiehao, SONG Kun. Application of "5G" emergency management model in trauma emergency treatment[J]. Chinese Journal of General Practice, 2025, 23(4): 604-607. doi: 10.16766/j.cnki.issn.1674-4152.003961
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Application of "5G" emergency management model in trauma emergency treatment

doi: 10.16766/j.cnki.issn.1674-4152.003961
  • 1.

    Department of Emergency Surgery, Fuyang People' s Hospital, Fuyang, Anhui 236000, China

Funds:

 FY2021-141

 工信厅联通信函〔2020〕270号

  • Received Date: 2024-08-13
    Available Online: 2025-06-30
    Abstract
  •   Objective  To explore the effect of the "5G" emergency management model in trauma treatment, and analyze the factors influencing the success rate of resuscitation.  Methods  A total of 198 trauma patients treated in Fuyang People' s Hospital from January 2021 to August 2023 were retrospectively analyzed. According to the different rescue models, they were divided into observation group (90 cases, treated using 5G emergency management model) and control group (108 cases, treated using routine trauma center rescue process). The rescue effect of the two groups were compared. According to whether the rescue was successful, the patients were divided into an effective group and an ineffective group. Univariate and Multivariate logistic regression analysis were performed to identify the risk factors affecting the success of the rescue, and based on this, a corresponding early warning model was established.  Results  Compared with the control group, the observation group had shorter examination completion time, consultation completion time, first diagnosis confirmation time, blood transfusion waiting time, and surgery waiting time (P < 0.05), the ICU admission rate and mortality rate were low (P < 0.05). Compared with the effective group, the time from injury to admission in the ineffective group was significantly longer, the injure severity score (ISS) score before treatment was higher, and the proportion of patients with abbreviated injury scale (AIS) head and AIS chest scores ≥3 was larger (P < 0.05). Logistic regression analysis showed that high ISS score before treatment, AIS≥3 score and long time from injury to hospital admission were risk factors affecting the treatment effect of trauma patients (OR > 1, P < 0.05), while adopting the "5G" emergency management model was a protective factor to improve the rescue effect of trauma patients (OR < 1, P < 0.05). Early warning model constructed by four factors, including ISS score, ASI score, time from injury to admission, and rescue management model, had high early prediction power on the rescue effect of trauma patients, with ROC-AUC of 0.861.  Conclusion  ISS score, ASI score, and time from injury to admission are factors that affect the treatment effect of trauma patients. Adopting the "5G" emergency management model can improve the rescue efficiency and success rate. The early warning model built based on the influencing factors has good predictive effectiveness for the treatment effect of trauma patients.

     

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