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已发表论文
重症创伤性脑损伤术后 LEDVT 风险评估系统的开发与验证
Authors Mo M, Zhai D, Tao N, Zhang N, Zhang Y, Zeng G
Received 1 December 2025
Accepted for publication 30 March 2026
Published 21 April 2026 Volume 2026:19 585801
DOI https://doi.org/10.2147/RMHP.S585801
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Keon-Hyung Lee
Minling Mo,1,2 Dahong Zhai,2 Nina Tao,2 Na Zhang,1 Yajuan Zhang,1 Guqing Zeng2
1Department of Nursing, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, People’s Republic of China; 2School of Nursing, University of South China, Hengyang, Hunan Province, 421001, People’s Republic of China
Correspondence: Guqing Zeng, School of Nursing, University of South China, Hengyang, Hunan Province, 421001, People’s Republic of China, Tel +8615673427900, Email guqingzengzgq01@163.com Yajuan Zhang, Department of Nursing, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, People’s Republic of China, Tel +8618116230832, Email zhangyajuansh6@126.com
Objective: This study aimed to develop a structured risk assessment system for postoperative lower extremity deep vein thrombosis (LEDVT) in patients with severe traumatic brain injury (sTBI), and to validate its content and reliability through expert consensus.
Methods: The system was designed based on evidence from a comprehensive literature review and refined through a two-round Delphi expert consensus process involving 16 multidisciplinary experts. Indicator weights were assigned using an analytic hierarchy process combined with expert scoring.
Results: The finalized framework incorporated 6 primary domains—demographic characteristics, trauma-related indicators, coagulation parameters, comorbidities, iatrogenic factors, and venous thromboembolism prophylaxis—encompassing 19 secondary indicators. Response rates for two rounds of the expert questionnaire were 100%. The expert authority coefficient was 0.931. The coefficients of variation for the second-round indicators ranged from 0% to 7.01% and Kendall’s coefficient of concordance was 0.670 (p < 0.001), indicating a high degree of expert agreement.
Conclusion: A comprehensive risk prediction indicator system for LEDVT following sTBI surgery was established. The system is suitable for direct integration into hospital information systems, with weighted indicators reflecting clinical priorities and supporting the development of real-time monitoring modules.By enabling early identification of high-risk patients, this tool can facilitate timely prophylactic interventions, enhance clinical decision-making, and ultimately reduce the incidence of postoperative LEDVT, thereby improving patient safety and overall quality of care.
Keywords: assessment indicators, Delphi method, lower extremity deep venous thrombosis, nursing, risk factors, severe traumatic brain injury
1Department of Nursing, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, People’s Republic of China; 2School of Nursing, University of South China, Hengyang, Hunan Province, 421001, People’s Republic of China
Correspondence: Guqing Zeng, School of Nursing, University of South China, Hengyang, Hunan Province, 421001, People’s Republic of China, Tel +8615673427900, Email guqingzengzgq01@163.com Yajuan Zhang, Department of Nursing, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, People’s Republic of China, Tel +8618116230832, Email zhangyajuansh6@126.com
Objective: This study aimed to develop a structured risk assessment system for postoperative lower extremity deep vein thrombosis (LEDVT) in patients with severe traumatic brain injury (sTBI), and to validate its content and reliability through expert consensus.
Methods: The system was designed based on evidence from a comprehensive literature review and refined through a two-round Delphi expert consensus process involving 16 multidisciplinary experts. Indicator weights were assigned using an analytic hierarchy process combined with expert scoring.
Results: The finalized framework incorporated 6 primary domains—demographic characteristics, trauma-related indicators, coagulation parameters, comorbidities, iatrogenic factors, and venous thromboembolism prophylaxis—encompassing 19 secondary indicators. Response rates for two rounds of the expert questionnaire were 100%. The expert authority coefficient was 0.931. The coefficients of variation for the second-round indicators ranged from 0% to 7.01% and Kendall’s coefficient of concordance was 0.670 (p < 0.001), indicating a high degree of expert agreement.
Conclusion: A comprehensive risk prediction indicator system for LEDVT following sTBI surgery was established. The system is suitable for direct integration into hospital information systems, with weighted indicators reflecting clinical priorities and supporting the development of real-time monitoring modules.By enabling early identification of high-risk patients, this tool can facilitate timely prophylactic interventions, enhance clinical decision-making, and ultimately reduce the incidence of postoperative LEDVT, thereby improving patient safety and overall quality of care.
Keywords: assessment indicators, Delphi method, lower extremity deep venous thrombosis, nursing, risk factors, severe traumatic brain injury