Evidence map›Paper›PMID 38361499›Full record

ArticleRevista panamericana de salud publica = Pan American journal of public health2023

[Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extensionDiretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI].

Samantha Cruz Rivera, Xiaoxuan Liu, An-Wen Chan, Alastair K Denniston, Melanie J Calvert, Grupo de Trabajo SPIRIT-AI y CONSORT-AI, Grupo Directivo SPIRIT-AI y CONSORT-AI, Grupo de Consenso SPIRIT-AI y CONSORT-AI

Abstract readCase ReportsEnglish Abstract
In one paragraph

Article in Revista panamericana de salud publica = Pan American journal of public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Samantha Cruz RiveraCentre for Patient Reported Outcomes Research Institute of Applied Health Research University of Birmingham Birmingham Reino Unido Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, Reino Unido.
Xiaoxuan LiuBirmingham Health Partners Centre for Regulatory Science and Innovation University of Birmingham Birmingham Reino Unido Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, Reino Unido.
An-Wen ChanDepartment of Medicine, Women's College Research Institute Women's College Hospital University of Toronto Ontario Canadá Department of Medicine, Women's College Research Institute, Women's College Hospital, University of Toronto, Ontario, Canadá.
Alastair K DennistonCentre for Patient Reported Outcomes Research Institute of Applied Health Research University of Birmingham Birmingham Reino Unido Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, Reino Unido.
Melanie J CalvertCentre for Patient Reported Outcomes Research Institute of Applied Health Research University of Birmingham Birmingham Reino Unido Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, Reino Unido.
Grupo de Trabajo SPIRIT-AI y CONSORT-AI
Grupo Directivo SPIRIT-AI y CONSORT-AI
Grupo de Consenso SPIRIT-AI y CONSORT-AI

Funding

Wellcome Trust
6 · The paper itself

Abstract

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

Identifiers

PMID38361499
PMCPMC10868409

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.