使用IDEAL框架评估当前和新兴的内光机器人平台
Diya Shah1, Freweini Martha Tesfai2,3,4, Matthew Boal2,4,5
1University College London Medical School, London, UK.
概括
这次审查使用IDEAL框架评估了机器人辅助的内光系统. 大多数系统都处于早期开发阶段,这凸显了对这些外科创新的长期临床数据的关键需求.
科学领域:
- 最少侵入性的手术
- 手术机器人手术机器人手术机器人手术机器人
- 医疗器械评估 医疗器械评估
背景情况:
- 机器人辅助内光系统代表了微创手术领域快速发展的领域.
- IDEAL框架 (理念,开发,探索,评估和监测) 为评估新型外科技术提供了一个结构化的方法.
- 本综述通过IDEAL框架的透视来综合这些系统的现状.
研究的目的:
- 综合审查和分类现有和新兴的机器人辅助内光系统.
- 通过IDEAL框架评估这些系统的发展阶段.
- 发现这些创新的外科工具的评估和临床数据中的差距.
主要方法:
- 采用范围审查方法来确定相关系统.
- 数据收集包括虚拟采访,问卷,数据库搜索,公司网站和同行评审的文献.
- 根据收集的指标,系统被分配到特定的IDEAL框架阶段.
主要成果:
- 来自16家公司的17个不同的机器人辅助内光系统被确定.
- 九个系统已经获得了监管部门的批准.
- 大多数系统都处于IDEAL早期阶段 (第0,1和2阶段),只有两个系统达到第3阶段,没有一个系统进入第4阶段 (长期评估).
结论:
- 对于机器人辅助内膜系统的长期临床数据存在重大差距,IDEAL 4 阶段缺乏系统证明了这一点.
- 医疗界,监管机构和行业之间加强合作至关重要.
- 这种合作对于在手术机器人领域推进基于证据的医学和确保患者安全和疗效至关重要.
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