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.

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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
Controls
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article

Adherence to TRIPOD+AI guideline: an updated reporting assessment tool

Tom de Groot, Johannes B. Reitsma, Emilie de Kanter, Pauline Heus et al.
1 citations
Journal of Clinical Epidemiology
Artificial Intelligence in Healthcare and Education
0.65
article

Adherence to TRIPOD+AI guideline: an updated reporting assessment tool

Tom de Groot, Johannes B. Reitsma, Emilie de Kanter, Pauline Heus, Gary Collins, T. K. Kaul, Rene Harmen Kuijten, Johanna AA Damen, Karel G.M. Moons, Lotty Hooft
article en
1 citations

Abstract

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.

Journal of Clinical EpidemiologyVol. 191
University Medical Center Groningen (NL), Utrecht University (NL), University Medical Center Utrecht (NL), NIHR Birmingham Biomedical Research Centre (GB)
Openalex Percentile: Top 18%
Artificial Intelligence in Healthcare and Education
0.65
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Adherence to TRIPOD+AI guideline: an updated reporting assessment tool — Tom de Groot, Johannes B. Reitsma, et al. · Journal of Clinical Epidemiology (2025) | TGRS Research Map | TGRS