医学检查与临床诊断

传统开放腰椎椎体间融合术后切口并发症列线图预测模型的建立

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  • 江苏大学附属医院(江苏镇江 212000)

网络出版日期: 2021-02-25

Establishment of a line chart prediction model for incisional complications after traditional open lumbar interbody fusion

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  • The Affiliated Hospital of Jiangsu University,Zhen⁃ jiang 212000,China

Online published: 2021-02-25

摘要

目的 建立传统开放腰椎椎体间融合术(lumbar interbody fusion,LIF)后发生切口并发症的 列线图预测模型,以期为临床围术期管理提供参考。方法 回顾性分析 2015 9 月至 2020 8 月于我院 住院并接受传统开放 LIF 患者的临床资料,分析相关危险因素,通过单因素、多因素 logistic 回归分析结果 建立列线图预测模型。对预测模型的预测效能、特异度、灵敏度进行评价。结果 本研究 426 例患者共出 现术后切口并发症65例,发生率为15.26%。单因素分析及多因素非条件logistic 回归分析结果显示,年龄、 BMI、术前白蛋白、手术时间、手术节段数是传统开放 LIF 术后切口并发症的独立危险因素(OR = 2.290 2.679、3.524、2.740、3.330,P<0.05)。建立列线图预测模型,计算 ROC 曲线下面积 0.809(95%CI:0.768 0.845,P<0.001),约登指数为 0.549,特异度为 0.795,灵敏度为 0.754。结论 本研究建立的列线图模型预 测效能较好,为临床早期识别高危人群、进行早期干预提供有效参考。

本文引用格式

于洪威, 周雪莲, 崔学文 .

传统开放腰椎椎体间融合术后切口并发症列线图预测模型的建立
[J]. 实用医学杂志, 2021 , 37(4) : 513 -517 . DOI: 10.3969/j.issn.1006⁃5725.2021.04.019

Abstract

Objective To establish a line chart prediction model of incision complications after traditional open lumbar interbody fusion(lumbar interbody fusion,LIF),in order to provide reference for clinical periopera⁃ tive management. Methods The clinical data of patients with traditional open LIF hospitalized in our hospital from September 2015 to August 2020 were analyzed retrospectively,and the related risk factors were analyzed. The line chart prediction model was established by the results of univariate and multivariate logistic regression analysis. the prediction efficiency,specificity and sensitivity of the prediction model are evaluated. Results In this study 65 cases of postoperative incision complications occurred in 426 patients,with an incidence of 15.26%. The results of univariate analysis and multivariate unconditional Logistic regression analysis showed that age,BMI,preoperative albumin,operation time and the number of operative segments were independent risk factors for incisional compli⁃ cations after traditional open LIF,and their odds ratios were 2.290,2.679,3.524,2.740 and 3.330,respectively (P<0.05). The prediction model of line chart was established,and the area under ROC curve was calculated (AUC=0.809,95% CI:0.768 ~ 0.845,P<0.001). The Jordan index,specificity and sensitivity were 0.549 0.795 and 0.754 respectively. Conclusions The prediction efficiency of the line chart model established in this study is good,which provides an effective reference for early clinical identification of high⁃risk groups and early intervention.

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