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一种预测短期可回收下腔静脉滤器无法取出的列线图模型。

A nomogram model to predict non-retrieval of short-term retrievable inferior vena cava filters.

作者信息

Qin Lihao, Gu Xiaocheng, Ni Caifang, Wang Kai, Xue Tongqing, Jia Zhongzhi, Wang Yun

机构信息

Department of Interventional and Vascular Surgery, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, China.

Department of Interventional Radiology, First Affiliated Hospital of Soochow University, Suzhou, China.

出版信息

Front Cardiovasc Med. 2024 Dec 6;11:1393410. doi: 10.3389/fcvm.2024.1393410. eCollection 2024.

Abstract

OBJECTIVE

To develop and validate a nomogram for predicting non-retrieval of the short-term retrievable inferior vena cava (IVC) filters.

METHODS

In this study, univariate and multivariate logistic regression analyses were performed to identify predictive factors of short-term retrievable filter (Aegisy or OptEase) non-retrieval, and a nomogram was then established based on these factors. The nomogram was created based on data from a training cohort and validated based on data from a validation cohort. The predictive value of the nomogram was estimated using area under the curve (AUC) and calibration curve analysis (Hosmer-Lemeshow test).

RESULTS

A total of 1,321 patients who had undergone placement of short-term retrievable filters (Aegisy or OptEase) were included in the analysis. The overall retrieval rate was 68.7%. Age, proximal and distal deep vein thrombosis (DVT) vs. distal DVT, active cancer, history of long-term immobilization, VTE was detected in the intensive care unit, active/recurrent bleeding, IVC thrombosis, and history of venous thromboembolism were independent predictive risk factors for non-retrieval of filters. Interventional therapy for DVT, acute fracture, and interval of ≥14 days between filter placement and patient discharge were independent protective factors for non-retrieval of filters. The nomogram based on these factors demonstrated good ability to predict the non-retrieval of filters (training cohort AUC = 0.870; validation cohort AUC = 0.813.

CONCLUSION

This nomogram demonstrated strong predictive accuracy and discrimination capability. This model may help clinicians identify patients who are not candidates for short-term retrievable filter placement and help clinicians make timely, individualized decisions in filter choice strategies.

摘要

目的

开发并验证一种用于预测短期可回收下腔静脉(IVC)滤器无法回收的列线图。

方法

在本研究中,进行单因素和多因素逻辑回归分析以确定短期可回收滤器(Aegisy或OptEase)无法回收的预测因素,然后基于这些因素建立列线图。该列线图基于训练队列的数据创建,并基于验证队列的数据进行验证。使用曲线下面积(AUC)和校准曲线分析(Hosmer-Lemeshow检验)评估列线图的预测价值。

结果

共有1321例接受短期可回收滤器(Aegisy或OptEase)置入的患者纳入分析。总体回收成功率为68.7%。年龄、近端和远端深静脉血栓形成(DVT)与单纯远端DVT、活动性癌症、长期制动史、在重症监护病房检测到静脉血栓栓塞(VTE)、活动性/复发性出血、IVC血栓形成以及静脉血栓栓塞病史是滤器无法回收的独立预测危险因素。DVT的介入治疗、急性骨折以及滤器置入与患者出院之间间隔≥14天是滤器无法回收的独立保护因素。基于这些因素的列线图显示出良好的预测滤器无法回收的能力(训练队列AUC = 0.870;验证队列AUC = 0.813)。

结论

该列线图显示出强大的预测准确性和辨别能力。该模型可帮助临床医生识别不适合短期可回收滤器置入的患者,并帮助临床医生在滤器选择策略中做出及时、个性化的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91e0/11659264/747803f3cadf/fcvm-11-1393410-g001.jpg

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