Evidence map›Paper›PMID 41637205›Full record

ArticleSaudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association2026

Effectiveness of AI-enhanced colonoscopy: A case-control study using real world evidence in a young screening age population.

Maryam A Alahmad, Youstina A Ghoris, Colleen S Thomas, Mutaz I Atieh, Heba A Abulkas, Ishtiaq Ahmed, Enas F Ahmed, Ameirah B Al Ali, Darshan Nagaraju, Mohammed A Karajeh and 1 more

Abstract read
In one paragraph

Article in Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Maryam A AlahmadDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Youstina A GhorisDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Colleen S ThomasMayo Clinic, Jacksonville, FL, United States.
Mutaz I AtiehDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Heba A AbulkasDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Ishtiaq AhmedDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Enas F AhmedDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Ameirah B Al AliDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Darshan NagarajuDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Mohammed A KarajehDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.
Michael B WallaceDivision of Gastroenterology and Hepatology, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Computer aided detection (CADe) colonoscopy has been shown in randomized controlled trials to improve detection of adenomatous colorectal polyps. However, in real-world settings the benefits are less clear. Our objective was to assess CADe colonoscopy compared to routine colonoscopy in a clinical practice setting in the Arab region with a low screening age (40 years old). Methods: After the implementation of the CADe system (GI Genius, Medtronic) in our hospital in September 2021 until July 2023, all CADe cases were registered and matched to routine colonoscopy cases with (1:4) ratio. Assignment of patients to the CADe system versus the routine colonoscopy was pragmatic design based on scheduling and availability factors. Primary endpoints were adenoma per colonoscopy (APC), and adenoma detection rate (ADR). Results: A total of 840 patients were included, out of that 72 patients were excluded due to Boston Bowel Prep <6. The final analysis included 768 patients (161 with CADe, 607 without). The CADe system was found to significantly increase the mean APC (0.602 vs. 0.293; rate ratio 1.80 [1.40–2.32]; P < 0.001) and ADR, 30.4% with CADe versus 16.8% without CADe (adjusted RR 1.68 [1.27–2.22], P < 0.001). There was no significant difference in withdrawal time with CADe. Conclusion: In our study, CADe significantly increased the detection of adenomatous polyps in a young screening age population in a clinical practice setting. These findings support recent randomized controlled trials and contrast the findings of recent studies showing lack of benefit in real world practice.

Indexed as

Adenomas detectionadvanced and non-advanced adenomasartificial intelligencecolonoscopycolorectal cancercolorectal neoplasiadeep learningrandomized controlled trialsreal-time CADe

Identifiers

PMID41637205
PMCPMC13016595

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

None linked

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.