Evidence map›Paper›PMID 40786526›Full record

ArticleTechniques and innovations in gastrointestinal endoscopy2024

Development and Validation of an Automated, Real-time Adenoma Detection Rate and Colonoscopy Quality Metrics Calculator.

Todd A Brenner, Branislav Bujnak, Matthew Alverson, Alexandra T Strauss, Anmol Singh, Saowanee Ngamruengphong, Mouen Khashab, Vikesh Singh, Eun Ji Shin, Venkata S Akshintala

Abstract read
In one paragraph

Article in Techniques and innovations in gastrointestinal endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Todd A BrennerDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Branislav BujnakPentax Medical, Montvale, New Jersey.
Matthew AlversonProvation Medical, Minneapolis, Minnesota.
Alexandra T StraussDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Anmol SinghDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Saowanee NgamruengphongDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Mouen KhashabDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Vikesh SinghDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Eun Ji ShinDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.
Venkata S AkshintalaDivision of Gastroenterology, Johns Hopkins Hospital, Baltimore, Maryland.

Funding

Improving the liver transplant evaluation process: a data science-focused and team-based approachK08DK133638 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI Alexandra Teresa Strauss · 2022 to 2026
$864k
NIDDK NIH HHS K08 DK133638
6 · The paper itself

Abstract

BACKGROUND AND

aimsHigh-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.

methodsEndoscopy 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.

resultsThe 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.

conclusionWe 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.

Indexed as

Adenoma detection rateCecal intubation rateColonoscopy quality indicators

Identifiers

PMID40786526
PMCPMC12333395

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.