Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Artificial Intelligence Extension

Study Overview
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Brief Summary
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The investigators aim to develop the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Artificial Intelligence Extension (PRISMA-AI) guideline as a stand-alone extension of the PRISMA statement, modified to reflect the particular requirements for the reporting of AI and its related topics (namely machine learning, deep learning, neuronal networking) in systematic reviews.

Detailed Description
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With advances in artificial intelligence (AI) over the last two decades, enthusiasm and adoption of this technology in medicine have steadily increased. Yet despite the greater adoption of AI in medicine, the way such methodologies and results are reported varies widely and the readability of clinical studies utilizing AI can be challenging to the general clinician. Systematic reviews of AI applications are an important area for which specific guidance is needed. An ongoing systematic review led by our team has shown that the number of systematic reviews on AI applications (with or without meta-analysis) is increasing dramatically over the time, yet the quality of reporting is still poor and heterogeneous, leading to inconsistencies in the reporting of informational details among individual studies. Consequently, the lack of these informational details may front problems for primary research and synthesis and potentially limits their usefulness for stakeholders interested in implementing AI or using the information in systematic reviews. The criteria will derive from the consensus among multi-specialty experts (in each medical specialty) who have already published about AI applications in leading medical journals and the lead authors of PRISMA, STARD-AI, CONSORT-AI, SPIRIT-AI, TRIPOD-AI, PROBAST-AI, CLAIM-AI and DECIDE-AI to ensure that the criteria have global applicability in all the disciplines and for each type of study which involves the AI. The proposed PRISMA-AI extension criteria focus on standardizing the reporting of methods and results for clinical studies utilizing AI. These criteria will reflect the most relevant technical details a data scientist requires for future reproducibility, yet they focus on the ability for the clinician reader to critically follow and ascertain the relevant outcomes of such studies. The resultant PRISMA-AI extension will help stakeholders interested in implementing AI or using AI-related information in systematic reviews create a framework for reviewers that assess publications, provide a tool for training researchers on Artificial Intelligence SR methodology help end-users of the SR such as physicians and policymakers to better evaluate SR's validity and applicability in their decision-making process. The success of the criteria will be seen in how manuscripts are written, how peer reviewers assess them, and finally, how the general readership is able to read and digest the published studies

Official Title
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Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Artificial. Delphi Consensus

Conditions
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Consensus Development

Intervention / Treatment
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* Other: Delphi Questionnaire


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: experts in the use AI technology in medicine experts in PRISMA leading authors of STARD-AI, CONSORT-AI, SPIRIT-AI, TRIPOD-AI, PROBAST-AI, CLAIM-AI and DECIDE-AI Exclusion Criteria: Panelists who were not able to commit to all rounds of the modified Delphi process will be excluded

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Delphi Panel<br>A team of experts in the use AI technology in medicine together with experts in PRISMA, STARD-AI, CONSORT-AI, SPIRIT-AI, TRIPOD-AI, PROBAST-AI, CLAIM-AI and DECIDE-AI will evaluate the PRISMA-AI extension reporting guidelines | Other: Delphi Questionnaire<br>* An invitation email, including a link to the survey, will be sent to the panel of experts in Ai in healthcare. The Delphi questionnaire will be administered via Welphi.com. In the first survey, panel members will outline the AI reporting standards in systematic reviews and objectively identify critical aspects of reporting methodology and results. In subsequent surveys, the expert panel will evaluate the modified criteria using a 1 to 5-point Likert scale with space provided for suggested edits and comments. Multiple rounds will be conducted until consensus is reached. After each round of Likert responses, the study team will calculate the agreement and distribution of responses. Likert responses will be dichotomized with positive values indicating agreement and neutral or negative values indicating disagreement. For the questions that do not reach a consensus of more than 80% in the first round or need further explanation, additional rounds of the survey may be performed.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Degree of consensus | The level of agreement for all statements achieving consensus from the expert panel; consensus is predefined as ≥ 80% of the panel rating a given statement | 3 months |