脑膜瘤手术的综合性DVT风险评估模型:开发,验证和临床实施
Dragan Nikolić1,2,3, Djula Djilvesi4,5, Vladimir Manojlović4,6
1Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia. dragan.nikolic@mf.uns.ac.rs.
Neurosurgical review
|April 24, 2025
概括
一个新的风险评估模型准确地预测了脑膜瘤手术后的深静脉血栓 (DVT). 这种工具改善了患者分层,减少了不必要的治疗,从而大大节省了成本.
科学领域:
- 神经外科 神经外科
- 血管外科 血管外科
- 在瘤学瘤学.
背景情况:
- 深静脉血栓 (DVT) 是经过脑膜瘤手术后的常见并发症,发生率在10-30%之间.
- 现有的预测模型对于这种患者群体缺乏足够的准确性.
- 需要改进风险分层工具,以指导预防措施.
研究的目的:
- 开发和验证一个精确的预测模型后手术DVT在脑膜瘤患者.
- 在这个队列中确定DVT的独立预测因子.
- 评估开发模型的临床实用性和成本效益.
主要方法:
- 一个单一中心对126名脑膜瘤手术患者 (2019-2024) 的回顾性队列研究.
- 采用多重回归分析,使用临床,实验室和手术参数构建预测模型.
- 模型验证使用引导重抽样 (1000次代) 进行.
主要成果:
- 开发的模型显示出优异的预测准确性 (AUC在导出中为0.83,在验证队列中为0.81).
- 独立预测因素包括手术前血小板数量升高,高D-二次数水平,长时间不运动,瘤大小增加和手术持续时间延长.
- 模型的实施导致查减少了28%,预防性抗凝药减少了35%,每名患者的成本节省了42%.
结论:
- 一种新的,经过验证的风险评估模型可在脑膜瘤患者中提供强有力的术后DVT预测.
- 该模型增强了风险分层,并优化了资源利用.
- 该模型的临床实施得到了其准确性,效率和成本效益的支持.
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