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已发表论文
创伤后脓毒症的流行病学、危险因素及预测模型：一项回顾性队列研究
Authors Fu X, Wang ZY, Qin YJ, Cao XX, Deng WS, Dai C, Hu DZ, Dong SM
Received 22 May 2025
Accepted for publication 27 September 2025
Published 23 October 2025 Volume 2025:18 Pages 3449—3464
DOI https://doi.org/10.2147/RMHP.S542208
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Gulsum Kaya
Xue Fu,1,* Zhen-Yi Wang,2,* Yan-Jun Qin,1 Xue-Xia Cao,1 Wang-Sheng Deng,2 Chen Dai,1 De-Zheng Hu,1 Shi-Min Dong1
1Department of Emergency Medicine, Hebei Medical University Third Hospital, Shijiazhuang, Hebei, 050011, People’s Republic of China; 2Department of Emergency Medicine, Shenzhen Longhua District People’s Hospital, Shenzhen, Guangdong, 518000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shi-Min Dong, Department of Emergency Medicine, Hebei Medical University Third Hospital, 139 Ziqiang Road, Shijiazhuang, Hebei, 050011, People’s Republic of China, Tel +86031188602330, Email dongsm@hebmu.edu.cn
Objective: This study aimed to evaluate the distribution spectrum and epidemiological characteristics associated with post-traumatic sepsis and to identify associated risk factors.
Methods: This retrospective study analyzed data from 722 patients with traumatic injuries admitted to the Emergency Department of the Hebei Medical University Third Hospital between January 1, 2021, and November 30, 2023. Participants were categorized into two groups: those who developed sepsis and those who did not. Patients diagnosed with sepsis were further categorized into survival and non-survival subgroups. Patient demographics, injury characteristics, and clinical variables were collected. Sepsis occurrence was assessed within the first week post-injury. Multivariate logistic regression analysis was performed to identify independent risk factors for post-traumatic sepsis.
Results: Among 722 trauma patients, 189 developed sepsis. In the sepsis cohort, injuries were mainly from traffic accidents (54.5%), falls from heights (17.46%), crush injuries (13.76%), and falls/collisions (11.64%). In contrast, non-sepsis cases (n=533) were predominantly due to falls/collisions (43.15%) and traffic accidents (36.02%). Pulmonary infection was the leading site in both survivors (95.62%) and non-survivors (100%), with some patients presenting multiple infection sites. A predictive model for post-traumatic sepsis, incorporating 10 variables such as hospitalization length and injury site number, achieved excellent performance (AUROC 0.998). A sepsis mortality model, based on five variables including age and injury sites, also showed high accuracy (AUROC 0.969).
Conclusion: Traffic accidents were the primary cause of post-traumatic sepsis. Key risk factors included injury severity, CRP level, and hospitalization duration. Independent predictors of 28-day mortality included age, organ failure score, and vasoactive drug use.
Keywords: epidemiological characteristics, ISS, post-traumatic sepsis, predictive modelling, risk factor, receiver operating characteristic curve, ROC curve, SOFA score
1Department of Emergency Medicine, Hebei Medical University Third Hospital, Shijiazhuang, Hebei, 050011, People’s Republic of China; 2Department of Emergency Medicine, Shenzhen Longhua District People’s Hospital, Shenzhen, Guangdong, 518000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Shi-Min Dong, Department of Emergency Medicine, Hebei Medical University Third Hospital, 139 Ziqiang Road, Shijiazhuang, Hebei, 050011, People’s Republic of China, Tel +86031188602330, Email dongsm@hebmu.edu.cn
Objective: This study aimed to evaluate the distribution spectrum and epidemiological characteristics associated with post-traumatic sepsis and to identify associated risk factors.
Methods: This retrospective study analyzed data from 722 patients with traumatic injuries admitted to the Emergency Department of the Hebei Medical University Third Hospital between January 1, 2021, and November 30, 2023. Participants were categorized into two groups: those who developed sepsis and those who did not. Patients diagnosed with sepsis were further categorized into survival and non-survival subgroups. Patient demographics, injury characteristics, and clinical variables were collected. Sepsis occurrence was assessed within the first week post-injury. Multivariate logistic regression analysis was performed to identify independent risk factors for post-traumatic sepsis.
Results: Among 722 trauma patients, 189 developed sepsis. In the sepsis cohort, injuries were mainly from traffic accidents (54.5%), falls from heights (17.46%), crush injuries (13.76%), and falls/collisions (11.64%). In contrast, non-sepsis cases (n=533) were predominantly due to falls/collisions (43.15%) and traffic accidents (36.02%). Pulmonary infection was the leading site in both survivors (95.62%) and non-survivors (100%), with some patients presenting multiple infection sites. A predictive model for post-traumatic sepsis, incorporating 10 variables such as hospitalization length and injury site number, achieved excellent performance (AUROC 0.998). A sepsis mortality model, based on five variables including age and injury sites, also showed high accuracy (AUROC 0.969).
Conclusion: Traffic accidents were the primary cause of post-traumatic sepsis. Key risk factors included injury severity, CRP level, and hospitalization duration. Independent predictors of 28-day mortality included age, organ failure score, and vasoactive drug use.
Keywords: epidemiological characteristics, ISS, post-traumatic sepsis, predictive modelling, risk factor, receiver operating characteristic curve, ROC curve, SOFA score