描述ION机器人支气管检查的学习曲线:基于CUSUM的诊断产量的分析
Juliana Guarize1, Luca Bertolaccini2, Claudia Bardoni2
1Division of Interventional Pulmonology.
Journal of bronchology & interventional pulmonology
|November 11, 2025
概括
形状感应ION机器人辅助支气管镜 (ION) 系统显示了学习曲线,在大约40个病例后,诊断产量和手术时间显著改善. 结构化的培训是初步采用成功的关键.
科学领域:
- 肺部病理学 肺部病理学
- 医疗机器人 医疗机器人
- 诊断程序 诊断程序 诊断程序
背景情况:
- 描述形状感应ION机器人辅助支气管检查 (ION) 的程序学习曲线对于优化其实施至关重要.
- 评估诊断性能和手术时间是评估学习曲线的关键指标.
研究的目的:
- 定义和分析ION机器人辅助支气管镜系统的学习曲线.
- 评估经验对诊断产量和程序效率的影响.
主要方法:
- 在129个手术中使用离子系统采样的147个肺结节的回顾性分析.
- 用于诊断产量和程序学习时间曲线分析的累积和 (CUSUM) 控制图.
- 一般化的线性混合效应模型 (GLMMs) 用于识别诊断成功的预测因素.
主要成果:
- 高诊断产率达到了87.8% (129/147个结节),有108个恶性和21个非恶性诊断.
- 诊断产量的性能高原观察到大约45个案例;手术时间稳定了40个案例,从60分钟的中位数减少到35分钟.
- 较短的手术持续时间与更高的诊断成功显著相关 (OR:0.997;P=0.005);结节大小<15毫米没有显著影响产量.
结论:
- 在约40个病例后,ION系统表现出可测量的学习曲线,诊断产量和效率显著提高.
- 结构化的培训和持续的绩效监测对于成功采用机器人辅助支气管镜术至关重要.
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