Revised Strengthening the reporting of cohort, cross-sectional and case-control studies in surgery (STROCSS) Guideline: An update for the age of Artificial Intelligence
Abstract
Introduction: Artificial intelligence (AI) is rapidly transforming healthcare and scientific publishing. Reporting guidelines need to be updated to take into account this advance. The STROCSS Guideline 2025 update adds a new AI-focused domain to promote transparency, reproducibility, and ethical integrity in surgical observational studies involving AI.
Methods: A Delphi consensus exercise was conducted to update the STROCSS guidelines. A panel of 49 surgical and scientific experts were invited to rate proposed new items. In round 1, participants scored each item on a 9-point Likert scale and provided feedback. Items not meeting consensus were revised or discarded.
Results: A 94% response rate occurred amongst participants (46/49) in the first round. Ratings were analysed for agreement levels, and consensus was reached on all six proposed AI-related items. A revised STROCSS checklist is presented which incorporates these new AI related items. Authors are now expected to disclose AI involvement not only in patient care but also in manuscript preparation, as exemplified by this paper.
Conclusion: The STROCSS 2025 guideline provides an up-to-date framework for surgical observational studies in the era of AI. Through a robust consensus STROCSS, we have added specific reporting criteria for AI to ensure that any use of artificial intelligence in a surgical observational study is clearly documented, explained and discussed including with respect to bias and ethics. This update will…
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Evidence Hub reads this as a case-control, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.
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