Evidence map›Paper›PMID 38929784›Full record

ArticleJournal of personalized medicine2024

ChatGPT as a New Tool to Select a Biological for Chronic Rhino Sinusitis with Polyps, "Caution Advised" or "Distant Reality"?

Federico Sireci, Francesco Lorusso, Angelo Immordino, Manuela Centineo, Ignazio Gerardi, Gaetano Patti, Simona Rusignuolo, Riccardo Manzella, Salvatore Gallina, Francesco Dispenza

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Comparative evaluation of four large language models (ChatGPT-5, Gemini 2.5 Pro, Claude Sonnet-4, and DeepSeek-R1) for diagnostic and therapeutic decision-making in real-world otolaryngology scenarios.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Review
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

10 authors.

Federico SireciOtorhinolaryngology Section, Department of Precision Medicine in Medical, Surgical and Critical Care (Me.Pre.C.C), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Francesco LorussoOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Angelo ImmordinoOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Manuela CentineoDigital Consultant Freelance, 90100 Palermo, Italy.
Ignazio GerardiOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Gaetano PattiOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.ORCID 0000-0001-8404-0314
Simona RusignuoloOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Riccardo ManzellaOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Salvatore GallinaOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.
Francesco DispenzaOtorhinolaryngology Section, Biomedicine, Neuroscience and Advanced Diagnosics Department (BiND), University of Palermo, Via del Vespro 129, 133, 90127 Palermo, Italy.ORCID 0000-0002-5844-9762

Funding

European Union - NextGenerationEU MUR funds D.M. 737/2021 - research project "Age-related hearing loss (ARHL) and neuro-cognitive decline: from early diagnosis to tele-rehabilitation"
6 · The paper itself

Abstract

ChatGPT is an advanced language model developed by OpenAI, designed for natural language understanding and generation. It employs deep learning technology to comprehend and generate human-like text, making it versatile for various applications. The aim of this study is to assess the alignment between the Rhinology Board's indications and ChatGPT's recommendations for treating patients with chronic rhinosinusitis with nasal polyps (CRSwNP) using biologic therapy. An observational cohort study involving 72 patients was conducted to evaluate various parameters of type 2 inflammation and assess the concordance in therapy choices between ChatGPT and the Rhinology Board. The observed results highlight the potential of Chat-GPT in guiding optimal biological therapy selection, with a concordance percentage = 68% and a Kappa coefficient = 0.69 (CI95% [0.50; 0.75]). In particular, the concordance was, respectively, 79.6% for dupilumab, 20% for mepolizumab, and 0% for omalizumab. This research represents a significant advancement in managing CRSwNP, addressing a condition lacking robust biomarkers. It provides valuable insights into the potential of AI, specifically ChatGPT, to assist otolaryngologists in determining the optimal biological therapy for personalized patient care. Our results demonstrate the need to implement the use of this tool to effectively aid clinicians.

Indexed as

artificial intelligencebiological therapyChatGPTchronic rhinosinusitismonoclonal antibodiesnasal polyps

Identifiers

PMID38929784
PMCPMC11204527

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.