Suppr超能文献

预测隆鼻手术患者术后静脉血栓栓塞的风险:一项队列研究。

Predicting the risk of postoperative venous thromboembolism in rhinoplasty patients: a cohort study.

作者信息

Chen Jie, Zhang Jianfei, Xiao Xia, Tang Yujun, Huang Hejin, Xi Wenwen, Liu Lina, Shen Zhengzhou, Tan Jianhua, Yang Feng

机构信息

Department of Burns and Plastic Surgery, Hengyang Medical School, The Second Affiliated Hospital, University of South China, No. 35 Jiefang Avenue, Zhengxiang District, Hengyang, 421001, China.

Beauty Surgery, Nantong Shenmei Medical Beauty Clinic, Nantong, 226001, China.

出版信息

Thromb J. 2025 Apr 11;23(1):33. doi: 10.1186/s12959-025-00712-0.

Abstract

BACKGROUND

Venous thromboembolism (VTE) is a rare complication following rhinoplasty surgery, with an occurrence rate generally estimated to be between 0.5% and 1%. In contrast, the occurrence rate of VTE in orthopedic surgeries, particularly in lower limb fracture surgeries, can reach as high as 10% or more. This significant difference highlights the varying risks associated with different surgical procedures and underscores the importance of identifying risk factors specific to rhinoplasty. Despite its relatively low incidence, the potential for VTE in rhinoplasty patients necessitates a thorough analysis of risk factors to enhance patient safety and guide clinical practice. This study aims to analyze the risk factors for postoperative VTE in rhinoplasty patients and develop a predictive model to assist clinicians in identifying at-risk individuals.

METHODS

A retrospective analysis was conducted on the clinical data of 1100 rhinoplasty patients admitted to a cosmetic hospital from January 2016 to January 2022. Patients were divided into Non-VTE group (1012 cases) and VTE group (88 cases) based on the occurrence of VTE within one month postoperatively. General patient information was collected and subjected to univariate analysis. Multivariate logistic regression analysis was used to identify risk factors for postoperative VTE in rhinoplasty patients and establish a predictive model. Internal validation was performed using bootstrapping technique to assess the accuracy and predictive performance of the model.

RESULTS

Univariate analysis showed that the proportions of IBD, Myocardial infarction, Previous VTE, PICC/central line, Rib graft, and History of nasal surgery were significantly higher in the VTE group compared to the Non-VTE group (all P < 0.05). Multivariate logistic regression analysis identified IBD, Myocardial infarction, Previous VTE, Rib graft, and History of nasal surgery as independent risk factors for VTE (P < 0.05). The constructed predictive nomogram model demonstrated good calibration and predictive accuracy, with an area under the ROC curve of 0.845, indicating excellent discrimination and clinical predictive performance.

CONCLUSION

IBD, Myocardial infarction, Previous VTE, Rib graft, and History of nasal surgery are independent risk factors for postoperative VTE in rhinoplasty patients. The predictive model effectively assesses the risk of VTE in patients, providing important guidance for clinical decision-making.

摘要

背景

静脉血栓栓塞症(VTE)是隆鼻手术后一种罕见的并发症,发生率一般估计在0.5%至1%之间。相比之下,整形外科手术中VTE的发生率,尤其是下肢骨折手术中,可高达10%或更高。这一显著差异凸显了不同手术程序所涉及的不同风险,并强调了识别隆鼻手术特有风险因素的重要性。尽管其发病率相对较低,但隆鼻患者发生VTE的可能性使得有必要对风险因素进行全面分析,以提高患者安全性并指导临床实践。本研究旨在分析隆鼻患者术后VTE的风险因素,并建立一个预测模型,以协助临床医生识别高危个体。

方法

对2016年1月至2022年1月期间一家美容医院收治的1100例隆鼻患者的临床资料进行回顾性分析。根据术后1个月内是否发生VTE将患者分为非VTE组(1012例)和VTE组(88例)。收集患者的一般信息并进行单因素分析。采用多因素logistic回归分析来识别隆鼻患者术后VTE的风险因素并建立预测模型。使用自抽样技术进行内部验证,以评估模型的准确性和预测性能。

结果

单因素分析显示,VTE组中炎症性肠病(IBD)、心肌梗死、既往VTE、经外周静脉中心静脉置管(PICC)/中心静脉导管、肋软骨移植以及鼻部手术史的比例均显著高于非VTE组(所有P<0.05)。多因素logistic回归分析确定IBD、心肌梗死、既往VTE、肋软骨移植以及鼻部手术史为VTE的独立风险因素(P<0.05)。构建的预测列线图模型显示出良好的校准度和预测准确性,ROC曲线下面积为0.845,表明具有出色的区分度和临床预测性能。

结论

IBD、心肌梗死、既往VTE、肋软骨移植以及鼻部手术史是隆鼻患者术后VTE的独立风险因素。该预测模型有效地评估了患者发生VTE的风险,为临床决策提供了重要指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c388/11992759/8fb3f407b189/12959_2025_712_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验