Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
JAMA Netw Open. 2023 Jan 3;6(1):e2253840. doi: 10.1001/jamanetworkopen.2022.53840.
Time of day was associated with a decline in adenoma detection during colonoscopy. Artificial intelligence (AI) systems are effective in improving the adenoma detection rate (ADR), but the performance of AI during different times of the day remains unknown.
To validate whether the assistance of an AI system could overcome the time-related decline in ADR during colonoscopy.
DESIGN, SETTING, AND PARTICIPANTS: This cohort study is a secondary analysis of 2 prospective randomized controlled trials (RCT) from Renmin Hospital of Wuhan University. Consecutive patients undergoing colonoscopy were randomly assigned to either the AI-assisted group or unassisted group from June 18, 2019, to September 6, 2019, and July 1, 2020, to October 15, 2020. The ADR of early and late colonoscopy sessions per half day were compared before and after the intervention of the AI system. Data were analyzed from March to June 2022.
Conventional colonoscopy or AI-assisted colonoscopy.
Adenoma detection rate.
A total of 1780 patients (mean [SD] age, 48.61 [13.35] years, 837 [47.02%] women) were enrolled. A total of 1041 procedures (58.48%) were performed in early sessions, with 357 randomized into the unassisted group (34.29%) and 684 into the AI group (65.71%). A total of 739 procedures (41.52%) were performed in late sessions, with 263 randomized into the unassisted group (35.59%) and 476 into the AI group (64.41%). In the unassisted group, the ADR in early sessions was significantly higher compared with that of late sessions (13.73% vs 5.70%; P = .005; OR, 2.42; 95% CI, 1.31-4.47). After the intervention of the AI system, as expected, no statistically significant difference was found (22.95% vs 22.06%, P = .78; OR, 0.96; 95% CI; 0.71-1.29). Furthermore, the AI systems showed better assistance ability on ADR in late sessions compared with early sessions (odds ratio, 3.81; 95% CI, 2.10-6.91 vs 1.60; 95% CI, 1.10-2.34).
In this cohort study, AI systems showed higher assistance ability in late sessions per half day, which suggests the potential to maintain high quality and homogeneity of colonoscopies and further improve endoscopist performance in large screening programs and centers with high workloads.
一天中的时间与结肠镜检查中腺瘤检出率的下降有关。人工智能（AI）系统在提高腺瘤检出率（ADR）方面非常有效，但 AI 在一天中不同时间的性能仍不清楚。
验证 AI 系统的辅助是否可以克服结肠镜检查中与时间相关的 ADR 下降。
设计、设置和参与者：这是一项来自武汉大学人民医院的两项前瞻性随机对照试验（RCT）的二次分析队列研究。连续接受结肠镜检查的患者于 2019 年 6 月 18 日至 9 月 6 日和 2020 年 7 月 1 日至 10 月 15 日被随机分配至 AI 辅助组或未辅助组。比较了 AI 系统干预前后每半天结肠镜检查的早期和晚期 ADR。数据于 2022 年 3 月至 6 月进行分析。
常规结肠镜检查或 AI 辅助结肠镜检查。
腺瘤检出率。
共纳入 1780 例患者（平均[标准差]年龄 48.61[13.35]岁，837[47.02%]为女性）。共有 1041 例（58.48%）在早期进行，其中 357 例随机分为未辅助组（34.29%）和 AI 组（65.71%）。共有 739 例（41.52%）在晚期进行，其中 263 例随机分为未辅助组（35.59%）和 AI 组（64.41%）。在未辅助组中，早期 ADR 明显高于晚期（13.73%比 5.70%；P=0.005；OR，2.42；95%CI，1.31-4.47）。在 AI 系统干预后，预期不会发现统计学差异（22.95%比 22.06%，P=0.78；OR，0.96；95%CI，0.71-1.29）。此外，AI 系统在晚期的 ADR 辅助能力上表现优于早期（优势比，3.81；95%CI，2.10-6.91 比 1.60；95%CI，1.10-2.34）。
在这项队列研究中，AI 系统在每半天的晚期显示出更高的辅助能力，这表明有可能保持结肠镜检查的高质量和同质性，并进一步提高大筛查计划和高工作量中心的内镜医生的表现。
