Adherence to TRIPOD+AI guideline: an updated reporting assessment tool
Accurate and complete reporting is crucial in biomedical research to ensure findings can be effectively used. To support researchers in reporting their findings well, reporting guidelines have been developed for different study types. One such guideline is TRIPOD, which focuses on research studies about medical prediction tools. In 2024, TRIPOD was updated to TRIPOD + AI to address the increasing use of AI and ML in prediction model studies. In 2019, we developed a scoring system to evaluate how well research papers on prediction tools adhered to the TRIPOD guideline, resulting in a reporting completeness score. This score allows for easier comparison of reporting completeness across various medical fields, and to monitor improvement in reporting over time. With the introduction of TRIPOD + AI, an update of the scoring system was required to align with the new reporting recommendations. We achieved this by reviewing our previous scoring system and incorporating the new items from TRIPOD + AI to better suit studies involving AI. We believe that this system will facilitate comparisons of prediction model reporting completeness across different fields and encourage improved reporting practices.
Authors
- Tom de Groot
- Johannes B. Reitsma (ORCID: https://orcid.org/0000-0003-4026-4345)
- Emilie de Kanter (ORCID: https://orcid.org/0000-0002-7756-6067)
- Pauline Heus (ORCID: https://orcid.org/0000-0002-6886-4652)
- Gary Collins
- T. K. Kaul (ORCID: https://orcid.org/0000-0002-4402-5379)
- Rene Harmen Kuijten
- Johanna AA Damen
- Karel G.M. Moons
- Lotty Hooft
Institutions
- University Medical Center Groningen (NL)
- Utrecht University (NL)
- University Medical Center Utrecht (NL)
- NIHR Birmingham Biomedical Research Centre (GB)
Publication Details
- Journal
- Journal of Clinical Epidemiology
- Published
- 2025-12-23
- DOI
- https://doi.org/10.1016/j.jclinepi.2025.112118
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65