Nomogram to Assess the Risk of Deep Venous Thrombosis After Posterior Lumbar Fusion: A Retrospective Study.

IF 3 3区 医学 Q2 CLINICAL NEUROLOGY Global Spine Journal Pub Date : 2025-05-01 Epub Date: 2024-10-11 DOI:10.1177/21925682241289119
Xiang Li, Jinlong Ma, Lu Xue, Limin Wang, Guangjun Jiao, Yunzhen Chen
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Abstract

Study DesignRetrospective cohort study.ObjectivesDeep venous thrombosis (DVT) is a common complication following lumbar spine surgery, which can lead to adverse consequences such as venous thromboembolism and pulmonary embolism. This study aimed to investigate whether predictors of DVT can improve clinical interventions.MethodsThe study included patients who underwent posterior lumbar fusion between 2012 and 2022. In the training cohort, stepwise logistic regression, based on the Akaike information criterion minimum, was used to identify variables for constructing the nomogram. The nomogram was evaluated and validated using calibration curves, Brier scores, receiver operating characteristic (ROC) curves, C-index, decision curve analyses (DCAs), clinical impact curves (CICs), and risk stratification analyses.ResultsA total of 9216 patients were enrolled after screening. The nomogram included seven variables: cerebrovascular disease, diabetes, body mass index, age, pedicular screw quantity, D-dimer, and hypertension. Calibration plots demonstrated favorable agreement between predicted and observed probabilities. The C-index indicated satisfactory discriminatory ability of the nomogram (0.772 for the training cohort and 0.792 for the validation cohort). Additionally, the DCA and CIC revealed that the nomogram could provide clinical benefits for patients.ConclusionsThis study successfully developed and validated a nomogram that can assess the risk of DVT following posterior lumbar fusion. The nomogram will assist surgeons in making informed clinical decisions.

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评估后路腰椎融合术后深静脉血栓风险的提名图:回顾性研究
研究设计研究目的:回顾性队列研究:深静脉血栓(DVT)是腰椎手术后常见的并发症,可导致静脉血栓栓塞和肺栓塞等不良后果。本研究旨在探讨深静脉血栓形成的预测因素能否改善临床干预措施:研究纳入了2012年至2022年期间接受后路腰椎融合术的患者。在训练队列中,使用基于 Akaike 信息标准最小值的逐步逻辑回归来确定构建提名图的变量。使用校准曲线、布赖尔评分、接收者操作特征曲线(ROC)、C指数、决策曲线分析(DCA)、临床影响曲线(CIC)和风险分层分析对提名图进行了评估和验证:经过筛选,共有 9216 名患者入选。提名图包括七个变量:脑血管疾病、糖尿病、体重指数、年龄、足螺钉数量、D-二聚体和高血压。校准图显示,预测概率与观察概率之间存在良好的一致性。C 指数显示提名图的判别能力令人满意(训练队列为 0.772,验证队列为 0.792)。此外,DCA 和 CIC 显示,提名图可为患者带来临床益处:本研究成功开发并验证了一种可评估腰椎后路融合术后深静脉血栓风险的提名图。该提名图将有助于外科医生做出明智的临床决策。
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来源期刊
Global Spine Journal
Global Spine Journal Medicine-Surgery
CiteScore
6.20
自引率
8.30%
发文量
278
审稿时长
8 weeks
期刊介绍: Global Spine Journal (GSJ) is the official scientific publication of AOSpine. A peer-reviewed, open access journal, devoted to the study and treatment of spinal disorders, including diagnosis, operative and non-operative treatment options, surgical techniques, and emerging research and clinical developments.GSJ is indexed in PubMedCentral, SCOPUS, and Emerging Sources Citation Index (ESCI).
期刊最新文献
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