腺瘤自动实时检测率和结肠镜检查质量指标计算器的开发与验证

IF 1.2 Q4 GASTROENTEROLOGY & HEPATOLOGY
Todd A. Brenner , Branislav Bujnak , Matthew Alverson , Alexandra T. Strauss , Anmol Singh , Saowanee Ngamruengphong , Mouen Khashab , Vikesh Singh , Eun Ji Shin , Venkata S. Akshintala
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引用次数: 0

摘要

背景和目的高质量的结肠镜检查可降低结肠直肠癌的死亡风险。腺瘤检出率(ADR)是衡量结肠镜检查质量的主要指标,但计算繁琐。我们报告了一个全自动平台的开发情况,该平台用于计算 ADR 和其他关键结肠镜检查质量指标,无需手动输入数据。开发了基于文本的分类参数,用于识别平均风险筛查结肠镜检查、腺瘤病理、盲肠插管和退出时间。基于这些分类的自动质量指标计算器被内置到一个基于网络的报告平台中,由此产生的质量指标与通过人工记录审查产生的质量指标进行比较。结果该研究包括 3809 例结肠镜检查(平均年龄 56.1 ± 6.40 岁,53.7% 为女性,38 名内镜医师)。自动计算器得出的 ADR 为 45.1%,而人工审核的 ADR 为 44.3%。对符合 ADR 筛选结肠镜检查的正确分类具有很高的预测价值,灵敏度为 0.918,特异性为 1.0。结论我们证明了结肠镜检查质量报告平台的可行性和性能,该平台能够利用新颖的全自动病理报告集成和基于文本查询的分类方法计算 ADR 和其他关键指标,适用于各种实践环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and Validation of an Automated, Real-time Adenoma Detection Rate and Colonoscopy Quality Metrics Calculator

Background and Aims

High-quality colonoscopy reduces the risk of death from colorectal cancer. The adenoma detection rate (ADR) is the principal measure of colonoscopy quality but is onerous to calculate. We report the development of a fully automated platform for calculation of the ADR and other key colonoscopy quality indicators without the need for manual data entry.

Methods

Endoscopy and pathology reports from 6 centers were collected over a 3-month period and collated using a novel data transfer interface. Text-based classification parameters were developed to identify average-risk screening colonoscopies, adenomatous pathology, cecal intubation, and withdrawal time. Automated quality metrics calculators based on these classifications were built into a web-based reporting platform, and the resulting quality metrics were benchmarked against those produced through a manual record review. Confirmation of the calculator's performance was performed in a validation cohort with data collected over a 1-month period, 6 months after the initial study.

Results

The study included 3809 colonoscopies (mean age 56.1 ± 6.40 years, 53.7% female, 38 endoscopists). The automated calculator yielded an ADR of 45.1% compared with 44.3% on manual review. Correct classification of ADR-qualifying screening colonoscopies was achieved with high predictive value, with a sensitivity of 0.918 and specificity of 1.0. The cecal intubation rate was 95.8%, and the average withdrawal time was 10:05 minutes.

Conclusion

We demonstrate the feasibility and performance of a colonoscopy quality reporting platform capable of calculating the ADR and other key metrics using novel, fully automated pathology report integration and a text query-based classification accessible in a wide range of practice settings.

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来源期刊
CiteScore
2.10
自引率
50.00%
发文量
60
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