Revised Preferred Reporting of Case Series in Surgery (PROCESS) Guideline: An Update for the Age of Artificial Intelligence

INTRODUCTION Artificial intelligence (AI) is rapidly transforming healthcare and scientific publishing. Reporting guidelines need to be updated to take this advancement into account. The PROCESS Guideline 2025 update adds a new AI-focused domain to promote transparency, reproducibility, and ethical integrity in surgical case series involving AI. METHODS A Delphi consensus exercise was conducted to update the PROCESS guidelines. The panel comprised 49 surgical and scientific experts, who were invited to rate proposed new items. In Round 1, participants scored each item on a nine-point Likert scale and provided feedback. Items not meeting consensus were revised or discarded. RESULTS A 92% response rate occurred amongst participants (45/49) in the first round. Ratings were analyzed for agreement levels, and consensus was reached on all six proposed AI-related items. A revised PROCESS 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 PROCESS 2025 guideline provides an up-to-date framework for surgical case series in the era of AI. Through a robust consensus process, we have added specific reporting criteria for AI to ensure that any use of AI in a case series is clearly documented, explained, and discussed, including considerations of bias and ethics. This update will help maintain the quality, transparency, and clinical relevance of the case series, ultimately improving their educational value and trustworthiness for the surgical community.

Authors

Institutions

Publication Details

Journal
Premier journal of science.
Published
2025-05-22
DOI
https://doi.org/10.70389/pjs.100080
Citations
40
Primary Topic
Clinical practice guidelines implementation
Type
article
Field-Weighted Citation Impact
75.14
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revised Preferred Reporting of Case Series in Surgery (PROCESS) Guideline: An Update for the Age of Artificial Intelligence

Maliha Agha, Thomas Franchi, Ahmed Kerwan, Ahmed Al‐Jabir et al.
40 citations
Premier journal of science.
Clinical practice guidelines implementation
75.14
article

Revised Preferred Reporting of Case Series in Surgery (PROCESS) Guideline: An Update for the Age of Artificial Intelligence

Maliha Agha, Thomas Franchi, Ahmed Kerwan, Ahmed Al‐Jabir, Maria Nicola, Catrin Sohrabi, Ginimol Mathew, Riaz Agha, Rasha Rashid
article en
40 citations

Abstract

INTRODUCTION Artificial intelligence (AI) is rapidly transforming healthcare and scientific publishing. Reporting guidelines need to be updated to take this advancement into account. The PROCESS Guideline 2025 update adds a new AI-focused domain to promote transparency, reproducibility, and ethical integrity in surgical case series involving AI. METHODS A Delphi consensus exercise was conducted to update the PROCESS guidelines. The panel comprised 49 surgical and scientific experts, who were invited to rate proposed new items. In Round 1, participants scored each item on a nine-point Likert scale and provided feedback. Items not meeting consensus were revised or discarded. RESULTS A 92% response rate occurred amongst participants (45/49) in the first round. Ratings were analyzed for agreement levels, and consensus was reached on all six proposed AI-related items. A revised PROCESS 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 PROCESS 2025 guideline provides an up-to-date framework for surgical case series in the era of AI. Through a robust consensus process, we have added specific reporting criteria for AI to ensure that any use of AI in a case series is clearly documented, explained, and discussed, including considerations of bias and ethics. This update will help maintain the quality, transparency, and clinical relevance of the case series, ultimately improving their educational value and trustworthiness for the surgical community.

Premier journal of science.
University College Hospital (GB), Harvard University (US), Royal Free London NHS Foundation Trust (GB), Imperial Valley College (US), Hutt Hospital (NZ), Premier Research Group (US), University College London (GB), Imperial College London (GB)
Openalex Percentile: Top 0%
Clinical practice guidelines implementation
75.14
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.