A clinical risk prediction model for perioperative lower extremity DVT in patients undergoing spinal fracture surgery.

IF 1.6 4区 医学 Q2 SURGERY
Frontiers in Surgery Pub Date : 2025-09-18 eCollection Date: 2025-01-01 DOI:10.3389/fsurg.2025.1597101
ShuYuan Zhuang, Jing Wang, Peng Du, SiHong Dong, Jiao Wu, DeLong Li, YuanTong Zang, Li Li
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引用次数: 0

Abstract

Objective: To develop a perioperative lower-extremity deep vein thrombosis (DVT) risk prediction model for spinal fracture surgery patients using logistic regression, supporting clinical prevention strategies.

Methods: Clinical data from 249 patients undergoing spinal fracture surgery (July 2019-October 2024) were retrospectively analyzed. Participants were divided into a model group (n = 166) and a validation group (n = 83) in a 2:1 ratio. Univariate and multivariate logistic regression identified independent risk factors for perioperative DVT, and a predictive model was established. Model fit was evaluated using the Hosmer-Lemeshow test, and predictive performance was assessed via receiver operating characteristic (ROC) curve analysis.

Results: Independent risk factors included perioperative blood transfusion, elevated C-reactive protein, D-dimer >500 μg/L, hypertension, age ≥60 years, and prolonged bed rest. The model [P = 1/(1 + e^-Z)] demonstrated a good fit (Hosmer-Lemeshow χ 2 = 12.139, P = 0.807). ROC analysis showed AUC values of 0.75 (95% CI: 0.80-0.92) for the model group and 0.81 (95% CI: 0.64-0.98) for the validation group, indicating robust predictive performance.

Conclusion: The identified risk factors are critical predictors of perioperative DVT in spinal fracture patients. The proposed model exhibits strong clinical utility for early risk stratification and intervention guidance.

Abstract Image

Abstract Image

脊柱骨折手术患者下肢深静脉血栓围手术期临床风险预测模型。
目的:应用logistic回归方法建立脊柱骨折手术患者围手术期下肢深静脉血栓形成(DVT)风险预测模型,为临床预防策略提供支持。方法:回顾性分析2019年7月- 2024年10月249例脊柱骨折手术患者的临床资料。将参与者按2:1的比例分为模型组(n = 166)和验证组(n = 83)。单因素和多因素logistic回归分析确定围手术期DVT的独立危险因素,并建立预测模型。采用Hosmer-Lemeshow检验评估模型拟合,通过受试者工作特征(ROC)曲线分析评估预测效果。结果:围手术期输血、c反应蛋白升高、d -二聚体>500 μg/L、高血压、年龄≥60岁、卧床时间过长是独立危险因素。模型[P = 1/(1 + e^-Z)]拟合良好(Hosmer-Lemeshow χ 2 = 12.139, P = 0.807)。ROC分析显示,模型组的AUC值为0.75 (95% CI: 0.80-0.92),验证组的AUC值为0.81 (95% CI: 0.64-0.98),表明预测性能稳健。结论:确定的危险因素是预测脊柱骨折患者围手术期DVT发生的重要因素。该模型在早期风险分层和干预指导方面具有很强的临床实用性。
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来源期刊
Frontiers in Surgery
Frontiers in Surgery Medicine-Surgery
CiteScore
1.90
自引率
11.10%
发文量
1872
审稿时长
12 weeks
期刊介绍: Evidence of surgical interventions go back to prehistoric times. Since then, the field of surgery has developed into a complex array of specialties and procedures, particularly with the advent of microsurgery, lasers and minimally invasive techniques. The advanced skills now required from surgeons has led to ever increasing specialization, though these still share important fundamental principles. Frontiers in Surgery is the umbrella journal representing the publication interests of all surgical specialties. It is divided into several “Specialty Sections” listed below. All these sections have their own Specialty Chief Editor, Editorial Board and homepage, but all articles carry the citation Frontiers in Surgery. Frontiers in Surgery calls upon medical professionals and scientists from all surgical specialties to publish their experimental and clinical studies in this journal. By assembling all surgical specialties, which nonetheless retain their independence, under the common umbrella of Frontiers in Surgery, a powerful publication venue is created. Since there is often overlap and common ground between the different surgical specialties, assembly of all surgical disciplines into a single journal will foster a collaborative dialogue amongst the surgical community. This means that publications, which are also of interest to other surgical specialties, will reach a wider audience and have greater impact. The aim of this multidisciplinary journal is to create a discussion and knowledge platform of advances and research findings in surgical practice today to continuously improve clinical management of patients and foster innovation in this field.
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