AI-driven abstract generating: evaluating LLMs with a tailored prompt under the PRISMA-A framework


Demi̇r G. B., GÖKMEN Ş., Süküt Y., TOPSAKAL K. G., GÖRGÜLÜ S.

BMC Oral Health, cilt.25, sa.1, 2025 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 1
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1186/s12903-025-06982-4
  • Dergi Adı: BMC Oral Health
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, MEDLINE, Directory of Open Access Journals
  • Anahtar Kelimeler: PRISMA-A, Systematic review, Meta-analyses, Large language models, Prompt engineering, ChatGPT, Gemini
  • Sağlık Bilimleri Üniversitesi Adresli: Evet

Özet

Background: This study aimed to assess and compare ChatGPT-4o and Gemini Pro’s ability to generate structured abstracts from full-text systematic reviews and meta-analyses in orthodontics, based on adherence to the PRISMA Abstract (PRISMA-A) Checklist, using a customised prompt developed for this purpose. Materials and methods: A total of 162 full-text systematic reviews and meta-analyses published in Q1-ranked orthodontic journals since January 2019 were included. Each full-text article was processed by ChatGPT-4o and Gemini Pro, using a PRISMA-A Checklist-aligned structured prompt. Outputs were scored using a tailored Overall quality Score OQS derived from 11 PRISMA-A checklist. Inter-rater and time-dependent reliability were assessed with Intraclass Correlation Coefficients (ICCs), and model outputs were compared using Mann–Whitney U tests. Results: Both models yielded satisfactory OQS in generating PRISMA-A checklist compliant abstracts; however, ChatGPT-4o consistently achieved higher scores than Gemini Pro. The most notable differences were observed in the “Included Studies” and “Synthesis of Results” sections, where ChatGPT-4o produced more complete and structurally coherent outputs. ChatGPT-4o achieved a mean OQS of 21.67 (SD 0.58) versus 21.00 (SD 0.71) for Gemini Pro, a difference that was highly significant (p < 0.001). Conclusions: Both LLMs demonstrated the ability to generate PRISMA-A-compliant abstracts from systematic reviews, with ChatGPT-4o consistently achieving higher quality scores than Gemini Pro. While tested in orthodontics, the approach holds potential for broader applications across evidence-based dental and medical research. Systematic reviews and meta-analyses are essential to evidence-based dentistry but can be challenging and time-consuming to report in accordance with established standards. The structured prompt developed in this study may assist researchers in generating PRISMA-A-compliant outputs more efficiently, helping to accelerate the completion and standardisation of high-level clinical evidence reporting.