Evidence map›Paper›PMID 41543410›Full record

ArticleAnnals of cardiac anaesthesia2026

Comparative Evaluation of Popular Gen-AI Chatbots in Generating Patient Education Material on Pulmonary Artery Catheter Insertion.

Omshubham Gangadhar Asai, Nayana Sabu, Prakash Gondode, Soumya Das, Gajanan Chauhan

Abstract readComparative Study
In one paragraph

Article in Annals of cardiac anaesthesia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

5 authors.

Omshubham Gangadhar AsaiDepartment of Anesthesiology, All India Institute of Medical Sciences (AIIMS), Nagpur, Maharashtra, India.
Nayana SabuDepartment of Anesthesiology, All India Institute of Medical Sciences (AIIMS), Nagpur, Maharashtra, India.
Prakash GondodeDepartment of Anesthesiology, Pain Medicine and Critical Care, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Soumya DasDepartment of Transfusion Medicine, All India Institute of Medical Sciences (AIIMS), Nagpur, Maharashtra, India.
Gajanan ChauhanDepartment of Anesthesiology, All India Institute of Medical Sciences (AIIMS), Nagpur, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPatient education significantly improves outcomes, especially in high-risk procedures. However, traditional educational resources often fail to address patient literacy and emotional needs adequately. Large language models like ChatGPT (OpenAI) and Gemini (Google) offer promising alternatives, potentially enhancing both accessibility and comprehensibility of procedural information. This study evaluates and compares the effectiveness of ChatGPT and Gemini in generating accurate, readable, and clinically relevant patient education materials (PEMs) for pulmonary artery catheter insertion. METHODOLOGY: A comparative, single-blinded study was conducted using structured validation methods using a common prompt for both gen artificial intelligence (AI) chatbots. AI-generated PEMs were assessed by board-certified anesthesiologists and intensivists. Face validity was determined using a 5-point Likert scale evaluating appropriateness, clarity, relevance, and trustworthiness. Content validity was measured by calculating content validity index. Accuracy and completeness were evaluated by a separate expert panel using a 10-point Likert scale. Readability and sentiment analysis were assessed via automated online tools.

resultsBoth chatbots achieved robust face and content validity (S-CVI = 0.91). ChatGPT scored significantly higher on accuracy [9.00 vs. 8.00; P = 0.021] and perceived trustworthiness, while Gemini outperformed in readability (Flesch Reading Ease score: 65 vs. 54; Flesch-Kincaid Grade Level: 7.58 vs. 8.64) and clarity. Both outputs maintained a neutral emotional tone.

conclusionAI chatbots show promise as innovative tools for patient education. By leveraging the strengths of both AI-driven technologies and human expertise, healthcare providers can enhance patient education and empower individuals to make informed decisions about their health and medical care involving complex clinical procedures.

Indexed as

Patient Education as TopicPulmonary ArteryComprehensionFemaleGenerative Artificial IntelligenceHumansLarge Language ModelsMaleSingle-Blind MethodFace validitygenerative artificial intelligencepatient educationpulmonary arteriesreadabilitysentiment analysis

Identifiers

PMID41543410
PMCPMC12935120

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.