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Autonomous artificial intelligence increases screening and follow-up for diabetic retinopathy in youth: the ACCESS randomized control trial.
Wolf, Risa M; Channa, Roomasa; Liu, T Y Alvin; Zehra, Anum; Bromberger, Lee; Patel, Dhruva; Ananthakrishnan, Ajaykarthik; Brown, Elizabeth A; Prichett, Laura; Lehmann, Harold P; Abramoff, Michael D.
Afiliação
  • Wolf RM; Department of Pediatrics, Division of Endocrinology, Johns Hopkins School of Medicine, Baltimore, MD, USA. RWolf@jhu.edu.
  • Channa R; Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison, WI, USA.
  • Liu TYA; Wilmer Eye Institute at the Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Zehra A; Department of Pediatrics, Division of Endocrinology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Bromberger L; Department of Pediatrics, Division of Endocrinology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Patel D; Department of Pediatrics, Division of Endocrinology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Ananthakrishnan A; Department of Pediatrics, Division of Endocrinology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Brown EA; Department of Pediatrics, Division of Endocrinology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  • Prichett L; Johns Hopkins School of Medicine Biostatistics, Epidemiology and Data Management (BEAD) Core, Baltimore, MD, USA.
  • Lehmann HP; Section on Biomedical Informatics and Data Science, Johns Hopkins University, Baltimore, MD, USA.
  • Abramoff MD; Department of Ophthalmology and Visual Sciences, The University of Iowa, Iowa City, IA, USA.
Nat Commun ; 15(1): 421, 2024 Jan 11.
Article em En | MEDLINE | ID: mdl-38212308
ABSTRACT
Diabetic retinopathy can be prevented with screening and early detection. We hypothesized that autonomous artificial intelligence (AI) diabetic eye exams at the point-of-care would increase diabetic eye exam completion rates in a racially and ethnically diverse youth population. AI for Children's diabetiC Eye ExamS (NCT05131451) is a parallel randomized controlled trial that randomized youth (ages 8-21 years) with type 1 and type 2 diabetes to intervention (autonomous artificial intelligence diabetic eye exam at the point of care), or control (scripted eye care provider referral and education) in an academic pediatric diabetes center. The primary outcome was diabetic eye exam completion rate within 6 months. The secondary outcome was the proportion of participants who completed follow-through with an eye care provider if deemed appropriate. Diabetic eye exam completion rate was significantly higher (100%, 95%CI 95.5%, 100%) in the intervention group (n = 81) than the control group (n = 83) (22%, 95%CI 14.2%, 32.4%)(p < 0.001). In the intervention arm, 25/81 participants had an abnormal result, of whom 64% (16/25) completed follow-through with an eye care provider, compared to 22% in the control arm (p < 0.001). Autonomous AI increases diabetic eye exam completion rates in youth with diabetes.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Retinopatia Diabética Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Screening_studies Limite: Adolescent / Child / Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Mellitus Tipo 2 / Retinopatia Diabética Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Screening_studies Limite: Adolescent / Child / Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article