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Background: Retinopathy of prematurity (ROP) is a vasoproliferative disease responsible for more than 30 000 blind children worldwide. Its diagnosis and treatment are challenging due to the lack of specialists, divergent diagnostic concordance and variation in classification standards. While artificial intelligence (AI) can address the shortage of professionals and provide more cost-effective management, its development needs fairness, generalisability and bias controls prior to deployment to avoid producing harmful unpredictable results. This review aims to compare AI and ROP study's characteristics, fairness and generalisability efforts., Methods: Our review yielded 220 articles, of which 18 were included after full-text assessment. The articles were classified into ROP severity grading, plus detection, detecting treatment requiring, ROP prediction and detection of retinal zones., Results: All the article's authors and included patients are from middle-income and high-income countries, with no low-income countries, South America, Australia and Africa Continents representation.Code is available in two articles and in one on request, while data are not available in any article. 88.9% of the studies use the same retinal camera. In two articles, patients' sex was described, but none applied a bias control in their models., Conclusion: The reviewed articles included 180 228 images and reported good metrics, but fairness, generalisability and bias control remained limited. Reproducibility is also a critical limitation, with few articles sharing codes and none sharing data. Fair and generalisable ROP and AI studies are needed that include diverse datasets, data and code sharing, collaborative research, and bias control to avoid unpredictable and harmful deployments., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: In ophthalmology, clinical trials (CTs) guide the treatment of diseases such as diabetic retinopathy, myopia, age-related macular degeneration, glaucoma and keratoconus with distinct presentations, pathological characteristics and responses to treatment in minority populations.Reporting gender and race and ethnicity in healthcare studies is currently recommended by National Institutes of Health (NIH) and Food and Drug Administration (FDA) guidelines to ensure representativeness and generalisability; however, CT results that include this information have been limited in the past 30 years.The objective of this review is to analyse the sociodemographic disparities in ophthalmological phases III and IV CT based on publicly available data., Methods: This study included phases III and IV complete ophthalmological CT available from clinicaltrials.org, and describes the country distribution, race and ethnicity description and gender, and funding characteristics., Results: After a screening process, we included 654 CTs, with findings that corroborate the previous CT reviews' findings that most ophthalmological participants are white and from high-income countries. A description of race and ethnicity is reported in 37.1% of studies but less frequently included within the most studied ophthalmological specialty area (cornea, retina, glaucoma and cataracts). The incidence of race and ethnicity reporting has improved during the past 7 years., Discussion: Although NIH and FDA promote guidelines to improve generalisability in healthcare studies, the inclusion of race and ethnicity in publications and diverse participants in ophthalmological CT is still limited. Actions from the research community and related stakeholders are necessary to increase representativeness and guarantee generalisability in ophthalmological research results to optimise care and reduce related healthcare disparities., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)