Evidence map›Paper›PMID 41882222›Full record

ArticleAesthetic plastic surgery2026

Assessing ChatGPT and Gemini Responses to Common Patient Questions Regarding Augmentation Mammaplasty.

Pharel Njessi, Axel Maurice-Szamburski, Chris Amro, Carter J Boyd, Jérôme Laloze, Elise Lupon

Abstract readComparative Study
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In one paragraph

Article in Aesthetic plastic surgery, 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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0citing papers 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

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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

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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

6 authors.

Pharel NjessiLP2M, Université Côte d'Azur, CNRS, Nice, France.ORCID https://orcid.org/0009-0006-3557-9608
Axel Maurice-SzamburskiDepartment of Anesthesiology and Intensive Care Medicine, Hôpital universitaire Pasteur, Nice, Nice, France.ORCID https://orcid.org/0000-0003-4225-7392
Chris AmroHansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, NY, USA.
Carter J BoydHansjörg Wyss Department of Plastic Surgery, NYU Langone, New York, NY, USA.ORCID https://orcid.org/0000-0002-1421-6852
Jérôme LalozeDepartment of Maxillofacial, Plastic and Reconstructive Surgery Department, University Hospital Dupuytren, Limoges, France.
Elise LuponLP2M, Université Côte d'Azur, CNRS, Nice, France. lupon.e@chu-nice.fr.ORCID http://orcid.org/0000-0001-9414-0861

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLarge language models (LLMs) are becoming a common source of medical information for patients.

objectiveThis study aimed to evaluate and compare the quality and readability of ChatGPT and Google's Gemini in answering frequently asked questions (FAQs) about augmentation mammaplasty (AM).

methodsTen AM FAQs were submitted to ChatGPT (GPT-4.1 mini) and Gemini (2.5 Flash). Responses were de-identified and independently rated by two board-certified plastic surgeons and one senior resident using the Global Quality Score (GQS). Readability was assessed using the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL). Paired comparisons used the Wilcoxon signed-rank test for per-question median GQS, inter-rater agreement used Kendall's W, and readability used paired tests as appropriate.

resultsAcross 60 individual ratings (3 raters × 10 items × 2 models), per-question median GQS was 5 for 9/10 ChatGPT answers and 10/10 Gemini answers; the paired comparison showed no significant difference (Wilcoxon Z = -1.00; p = 0.317; effect size r = 0.32). Inter-rater agreement was W = 0.24 (ChatGPT, p = 0.091) and W = 0.60 (Gemini, p = 0.002). ChatGPT produced more readable outputs (FRE: 46.53 vs 43.70, p = 0.243; FKGL: 9.71 vs 11.43, p = 0.002), indicating approximately two US grade levels of easier reading.

conclusionChatGPT and Gemini both generated high-quality answers to common AM FAQs, with no difference in quality based on GQS. ChatGPT's responses were significantly easier to read according to FKGL. LLMs may support patient education when implemented with clinician oversight to mitigate limitations and prevent misinformation. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

MammaplastyPatient Education as TopicComprehensionFemaleGenerative Artificial IntelligenceHumansLarge Language ModelsSurveys and QuestionnairesArtificial intelligenceAugmentation mammaplastyChatGPTGeminiLarge language modelsPatient educationPlastic surgery

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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 Socratic graph.