Evidence map›Paper›PMID 39238788›Full record

ArticleAnnals of gastroenterology

Assessing ChatGPT4 with and without retrieval-augmented generation in anticoagulation management for gastrointestinal procedures.

Sheza Malik, Himal Kharel, Dushyant S Dahiya, Hassam Ali, Hanna Blaney, Achintya Singh, Jahnvi Dhar, Abhilash Perisetti, Antonio Facciorusso, Saurabh Chandan and 1 more

Abstract read
In one paragraph

Article in Annals of gastroenterology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

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

Sheza MalikInternal Medicine, Rochester General Hospital, NY, USA (Sheza Malik, Himal Kharel).
Himal KharelInternal Medicine, Rochester General Hospital, NY, USA (Sheza Malik, Himal Kharel).
Dushyant S DahiyaGastroenterology, Hepatology, University of Kansas School of Medicine, Kansas, USA (Dushyant S. Dahiya).
Hassam AliGastroenterology, Hepatology, East Carolina University, NC, USA (Hassam Ali).
Hanna BlaneyGastroenterology, Hepatology, New York University Grossman School of Medicine, NC, USA (Hanna Blaney).
Achintya SinghGastroenterology, Hepatology, Metro Health, OH, USA (Achintya Singh).
Jahnvi DharGastroenterology, Hepatology, Postgraduate Institute of Medical Education and Research, Chandigarh, India (Jahnvi Dhar).
Abhilash PerisettiGastroenterology, Hepatology, Kansas City VA, USA (Abhilash Perisetti).
Antonio FacciorussoGastroenterology, Hepatology, University of Foggia, Italy (Antonio Facciorusso).
Saurabh ChandanGastroenterology, Hepatology, Creighton University Medical Center, USA (Saurabh Chandan).
Babu P MohanGastroenterology, Hepatology, Orlando Gastroenterology, FL, USA (Babu P. Mohan).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In view of the growing complexity of managing anticoagulation for patients undergoing gastrointestinal (GI) procedures, this study evaluated ChatGPT-4's ability to provide accurate medical guidance, comparing it with its prior artificial intelligence (AI) models (ChatGPT-3.5) and the retrieval-augmented generation (RAG)-supported model (ChatGPT4-RAG). Methods: Thirty-six anticoagulation-related questions, based on professional guidelines, were answered by ChatGPT-4. Nine gastroenterologists assessed these responses for accuracy and relevance. ChatGPT-4's performance was also compared to that of ChatGPT-3.5 and ChatGPT4-RAG. Additionally, a survey was conducted to understand gastroenterologists' perceptions of ChatGPT-4. Results: ChatGPT-4's responses showed significantly better accuracy and coherence compared to ChatGPT-3.5, with 30.5% of responses fully accurate and 47.2% generally accurate. ChatGPT4-RAG demonstrated a higher ability to integrate current information, achieving 75% full accuracy. Notably, for diagnostic and therapeutic esophagogastroduodenoscopy, 51.8% of responses were fully accurate; for endoscopic retrograde cholangiopancreatography with and without stent placement, 42.8% were fully accurate; and for diagnostic and therapeutic colonoscopy, 50% were fully accurate. Conclusions: ChatGPT4-RAG significantly advances anticoagulation management in endoscopic procedures, offering reliable and precise medical guidance. However, medicolegal considerations mean that a 75% full accuracy rate remains inadequate for independent clinical decision-making. AI may be more appropriately utilized to support and confirm clinicians' decisions, rather than replace them. Further evaluation is essential to maintain patient confidentiality and the integrity of the physician-patient relationship.

Indexed as

accuracyAnticoagulation managementChatGPT4-RAGendoscopic proceduresgastrointestinal procedures

Identifiers

PMID39238788
PMCPMC11372545

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.