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人工智能对内镜医师疲劳状态下结直肠腺瘤检出率的影响

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目的 分析人工智能(AI)对内镜医师疲劳状态下结直肠腺瘤检出率(ADR)的影响。方法 选取在河北省衡水市人民医院内镜中心接受结肠镜检查的患者784例为研究对象。依据患者操作时间段分为A组(n=405,14:00-15:59)和B组(n=379,16:00-17:30)。A组、B组中使用AI辅助检查的纳入AI亚组,未使用AI辅助检查的患者纳入无AI亚组。收集患者年龄、性别、肠道准备质量情况[波士顿肠道准备量表(BBPS)评分]等基线资料。统计A组、B组的结直肠ADR和结直肠息肉检出率(PDR)。比较A组、B组在有无AI辅助情况下的ADR。结果 A组总ADR为32。10%,高于B组的26。91%,但差异无统计学意义(P>0。05)。未使用AI辅助时,A组的ADR为25。85%,高于B组的17。30%,差异有统计学意义(P<0。05)。B组使用AI辅助后,其ADR高于A组未使用AI辅助,差异有统计学意义(P<0。05);未使用AI辅助时,A组PDR为33。17%,高于B组的22。70%,差异有统计学意义(P<0。05)。使用AI辅助后,2组PDR比较,差异无统计学意义(P>0。05)。在A组中,AI亚组(n=200)的ADR为38。50%,无AI亚组(n=205)的ADR为25。80%,差异有统计学意义(P=0。006)。在B组中,AI亚组(n=194)的ADR为36。08%,无AI亚组(n=185)的ADR为17。30%,差异有统计学意义(P<0。001)。结论 AI辅助下的结肠镜检查可有效提高疲劳状态下内镜医师的结直肠ADR。
Impact of artificial intelligence on colorectal adenoma detection rate in fatigue state of endoscopists
Objective To analyze the impact of artificial intelligence(AI)on colorectal adenoma detection rate(ADR)in fatigue state of endoscopists.Methods A total of 784 patients undergoing colonoscopy at the Endoscopy Center of Hengshui People's Hospital in Hebei Province were enrolled.Patients were divided into group A(n=405,time from 14:00 to 15:59)and group B(n=379,time from 16:00 to 17:30)based on the operation time.Patients in both groups who underwent AI-assisted examination were included in AI subgroup,while those without AI assistance were included in non-AI subgroup.Baseline data,including age,gender and bowel preparation quality[assessed by the Boston Bowel Preparation Scale(BBPS)score]were collected.The ADR and polyp detection rate(PDR)for colorectal lesions were calculated for both groups,and the ADR was compared between groups with and without AI assistance.Results The overall ADR was 32.10%in the group A,which was higher than 26.91%in the group B,but the difference was not statistically significant(P>0.05).Without AI assistance,the ADR in the group A was 25.85%,which was significantly higher than 17.30%in the group B(P<0.05).In the group B with AI assistance,the ADR was significant-ly higher than that in the group A without AI assistance(P<0.05).Without AI assistance,the PDR in the group A was 33.17%,which was significantly higher than 22.70%in the group B(P<0.05).After using AI assistance,there was no significant difference in PDR between the two groups(P>0.05).In the group A,the ADR was 38.50%in the AI subgroup(n=200)and 25.80%in the non-AI subgroup(n=205),with a statistically significant difference(P=0.006).In the group B,the ADR was 36.08%in the AI subgroup(n=194)and 17.30%in the non-AI subgroup(n=185),with a statistically significant difference(P<0.001).Conclusion AI-assisted colonoscopy can effectively improve the ADR of endoscopists under fatigue conditions.

artificial intelligencefatigue statecolonoscopycolorectal adenomaadenoma detection rate

张丽贤、陈倩、刘颖、孙悦、卢冀超、董梁、尹平、王丽华

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河北省衡水市人民医院,河北衡水,053000

人工智能 疲劳状态 结肠镜 结直肠腺瘤 腺瘤检出率

2024

实用临床医药杂志
扬州大学,中国高校科技期刊研究会

实用临床医药杂志

CSTPCD
影响因子:1.543
ISSN:1672-2353
年,卷(期):2024.28(23)