Evidence map›Paper›PMID 39865377›Full record

ArticleDental traumatology : official publication of International Association for Dental Traumatology2025

Evaluation of Chatbots in the Emergency Management of Avulsion Injuries.

Şeyma Mustuloğlu, Büşra Pınar Deniz

Abstract read
In one paragraph

Article in Dental traumatology : official publication of International Association for Dental Traumatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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

  1. Are mobile health applications for traumatic dental injuries effective? A systematic review of their impact on diagnosis, prevention, management, and education.European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry · 2026
    Pooled it
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  4. Evaluating Guideline Adherence in Gemini-Powered Dental Trauma Workflows: Standalone Gemini Chat vs. Document-Grounded NotebookLM.Dental traumatology : official publication of International Association for Dental Traumatology · 2026
    Article
  5. New Frontiers in Dental Traumatology: Innovation, Prevention, and Clinical Practice.Dental traumatology : official publication of International Association for Dental Traumatology · 2026
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  8. Performance Comparison of a Domain-Specific Chatbot and General-Purpose Chatbots in Dental Traumatology.Dental traumatology : official publication of International Association for Dental Traumatology · 2026
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  20. Artificial intelligence model for application in dental traumatology.European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry · 2025
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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

2 authors.

Şeyma MustuloğluDepartment of Paediatric Dentistry, Faculty of Dentistry, Mersin University, Mersin, Turkey.ORCID 0000-0001-9796-4348
Büşra Pınar DenizDepartment of Paediatric Dentistry, Faculty of Dentistry, Mersin University, Mersin, Turkey.ORCID 0009-0008-5905-873X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study assessed the accuracy and consistency of responses provided by six Artificial Intelligence (AI) applications, ChatGPT version 3.5 (OpenAI), ChatGPT version 4 (OpenAI), ChatGPT version 4.0 (OpenAI), Perplexity (Perplexity.AI), Gemini (Google), and Copilot (Bing), to questions related to emergency management of avulsed teeth. MATERIALS AND

methodsTwo pediatric dentists developed 18 true or false questions regarding dental avulsion and asked public chatbots for 3 days. The responses were recorded and compared with the correct answers. The SPSS program was used to calculate the obtained accuracies and their consistency.

resultsChatGPT 4.0 achieved the highest accuracy rate of 95.6% over the entire time frame, while Perplexity (Perplexity.AI) had the lowest accuracy rate of 67.2%. ChatGPT version 4.0 (OpenAI) was the only AI that achieved perfect agreement with real answers, except at noon on day 1. ChatGPT version 3.5 (OpenAI) was the AI that showed the weakest agreement (6 times).

conclusionsWith the exception of ChatGPT's paid version, 4.0, AI chatbots do not seem ready for use as the main resource in managing avulsed teeth during emergencies. It might prove beneficial to incorporate the International Association of Dental Traumatology (IADT) guidelines in chatbot databases, enhancing their accuracy and consistency.

Indexed as

Artificial IntelligenceEmergency TreatmentTooth AvulsionChildGenerative Artificial IntelligenceHumansSurveys and Questionnairesartificial intelligencechatbotemergencylarge language modelstooth avulsion

Identifiers

PMID39865377
PMCPMC12260122

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.