Evidence map›Paper›PMID 40698206›Full record

ArticleCureus2025

Evaluating the Reliability of OpenAI's ChatGPT-4 in Providing Pre-colonoscopy Patient Guidance.

Akash Patel, Adewale Ajumobi

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. ChatGPT and Gemini in warfarin counseling.Croatian medical journal · 2026
    Article
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

2 authors.

Akash PatelInternal Medicine, Eisenhower Health, Rancho Mirage, USA.
Adewale AjumobiGraduate Medical Education, Eisenhower Health, Rancho Mirage, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe integration of artificial intelligence (AI) in healthcare is a growing area of interest. This study aims to evaluate the reliability of OpenAI's ChatGPT-4.0 in providing pre-colonoscopy patient guidance, a critical aspect of gastrointestinal care where patient misconceptions and non-compliance are common challenges.

methodsThe study employed a qualitative design to assess ChatGPT-4.0 against established clinical guidelines from various medical societies. Twenty-five patient-like queries encompassing dietary recommendations, bowel preparation, cardiovascular medications, antibiotic prophylaxis, and diabetes medications management were presented to ChatGPT-4.0. The AI's responses were independently evaluated and classified in terms of their alignment with the guidelines.

resultsChatGPT-4 demonstrated high accuracy, with all 25 sample queries' responses aligning with the established clinical guidelines. It provided precise guidance on dietary restrictions, medication management, and bowel preparation in accordance with the European Society of Gastrointestinal Endoscopy (ESGE), the U.S. Multi-Society Task Force on Colorectal Cancer (USMSTF), the American College of Gastroenterology-Canadian Association of Gastroenterology (ACG-CAG), the American College of Cardiology-American Heart Association (ACC-AHA), the American Society for Gastrointestinal Endoscopy (ASGE), and the Australian Diabetes Society (ADS).

conclusionThe high degree of guideline adherence by ChatGPT-4.0 underscores its viability as a dependable resource for patient education. Despite its promising results, the study acknowledges limitations such as the structured nature of patient queries and the lack of real patient interactions. The findings suggest a potential role for AI in augmenting patient education and standardizing information dissemination in healthcare.

Indexed as

artificial intelligence in medicinechatgptchatgpt-3.5chatgpt-4colon cancer awarenesscolon cancer preventioncolon cancer screeninglarge language modelllmpatient education

Identifiers

PMID40698206
PMCPMC12280836

What OpenQuestion holds

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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.