超速发展的安全性和有效性评估 (SEASE):市场上市后的国际多中心研究
Juan Vivanco-Suarez1, Mahmoud Dibas1, Demetrius Klee Lopes2
1Department of Neurology, Neurosurgery & Radiology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA.
Journal of neurointerventional surgery
|April 25, 2024
概括
超越进化 (SE) 流量转移器在治疗内动脉瘤 (IA) 中表现出高效,完全封闭率为73%. 这项研究证实了其在现实国际使用中有利的安全概况.
科学领域:
- 内血管神经外科手术 血管内血管神经外科
- 脑血管疾病管理的管理
- 医疗器械技术 医疗器械技术
背景情况:
- 内动脉瘤 (IA) 是发病率和死亡率的重要原因.
- 流量转移器代表了针对特定IA的第一线处理.
- 关于新一代Surpass Evolve (SE) 64线流量转移器的数据有限.
研究的目的:
- 为了评估Surpass Evolve (SE) 流量转移器的安全性和有效性.
- 报告与SE设备的第一个国际现实世界的经验.
- 评估iAs的SE植入后的完全封闭率和主要不良事件.
主要方法:
- 进行了一项多中心,回顾性,国际,营销后队列研究 (SEASE).
- 包括在2020-2022年间连续接受SE治疗的患者.
- 主要终点是动脉瘤完全堵塞 (雷蒙德-罗伊类1) 和重大安全事件 (缺血,出血,死亡率).
主要成果:
- 305名患有332个IA的患者接受了SE治疗.
- 随访时间中位数为10.2个月,完全闭塞率为73.0%.
- 大型中风发生在2%的病例中,与手术相关的死亡率在0.7%的病例中.
结论:
- 超越进化 (SE) 流量转移器在实现内动脉瘤的完全封闭方面表现出高效.
- 苏联表现出良好的安全性,主要缺血事件和死亡率较低.
- 这项研究支持在现实临床实践中使用SE作为内动脉瘤的可靠治疗选择.
更多相关视频
00:04A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
10.7K
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
8.3K
相关概念视频
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
125
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
125
01:15Assumptions of Survival Analysis
125
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
125