人工智能对内镜的分析优于传统的内镜评分,在第3阶段性结肠炎试验中与症状和生活质量一致
Ryan W Stidham1,2,3, Lingrui Cai1, Emily Wittrup1
1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
人工智能 (AI) 内镜评分显示,与梅奥内镜评分 (MES) 相比,与性结肠炎 (UC) 症状缓解和生活质量更好地一致. 这种人工智能工具可能会重新定义UC患者内镜治疗评估.
科学领域:
- 胃肠病学 胃肠病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 性结肠炎 (UC) 的评估依赖于粘膜的愈合和症状,这些症状可能是不一致的.
- 目前的内镜评分系统可能无法完全捕捉疾病活动或对生活质量的影响.
研究的目的:
- 将AI衍生的累积疾病得分 (CDS) 与梅奥内镜得分 (MES) 进行比较,以了解UC患者与症状和与健康相关的生活质量 (HR-QoL) 的一致性.
- 评估AI在重新定义内镜治疗标准方面的潜力.
主要方法:
- 来自第三阶段试验 (TrueNorth) 的内镜视频分析,涉及用ozanimod (OZA) 或安慰剂 (PBO) 治疗的UC患者.
- AI CDS和MES与部分梅奥缓解 (PMS) 和EQ-5D HR-QoL措施的比较.
- 使用曼-惠特尼U和克鲁斯卡尔-瓦利斯测试进行统计分析,并使用科恩的卡帕进行一致性评估.
主要成果:
- 与MES相比,AI CDS与症状缓解 (PMS) 和HR-QoL (EQ-5D) 的一致性更好 (kappa=0.53与0.44).
- 较低的CDS截止值 (<40) 显示了与PMS缓解的改善一致性 (kappa=0.57与MES的0.72相比).
- 人工智能评分在MES 2,3受试者中发现了QOL差异,并增加了OZA和PBO之间观察到的治疗差异.
结论:
- 与MES相比,人工智能支持的内镜评分提供了与UC中的症状缓解和HR-QoL的优越协议.
- 人工智能CDS提供了一种定量度量,可以重新定义UC的足够的粘膜愈合标准.
- 这项技术有可能改善性结肠炎的疾病评估和治疗评估.
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