Title Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120389 Type 2 Diabetics over 11 Years Follow-Up.

Pedro ROMERO-AROCA; Raquel Verges; Jordi Pascual-Fontanilles; Aida Valls; Josep Franch-Nadal; Xavier Mundet; Antonio Moreno; Josep Basora; Eugeni Garcia-Curto; Marc Baget-Bernaldiz

doi:10.20944/preprints202403.0050.v1

A peer-reviewed article of this Preprint also exists.

Romero-Aroca, P.; Verges, R.; Pascual-Fontanilles, J.; Valls, A.; Franch-Nadal, J.; Mundet, X.; Moreno, A.; Basora, J.; Garcia-Curto, E.; Baget-Bernaldiz, M. Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120,389 Type 2 Diabetics over 11 Years Follow-Up. Diagnostics 2024, 14, 833. Romero-Aroca, P.; Verges, R.; Pascual-Fontanilles, J.; Valls, A.; Franch-Nadal, J.; Mundet, X.; Moreno, A.; Basora, J.; Garcia-Curto, E.; Baget-Bernaldiz, M. Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120,389 Type 2 Diabetics over 11 Years Follow-Up. Diagnostics 2024, 14, 833.

Abstract

(1) Background Diabetic Retinopathy (DR) is the primary cause of poor vision in young adults. Screening for DR is important but many patients do not attend; (2) Methods: We validated an algorithm for predicting DR and its progression by conducting a retrospective study of 11 children in a population of 120,389 T2DM (3) Results: By applying the algorithm to the population showed an AUC of 0.93 (95% CI, 0.92–0.94) for any-DR and 0.90 (95% CI, 0.89–0.91) for referable-DR(4) Conclusions: The algorithm is useful for predicting patients who could develop referable forms of DR and also for any-DR. This would allow a personalized screening plan to be drawn up for each patient.

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Title Referable Diabetic Retinopathy Prediction Algorithm Applied to a Population of 120389 Type 2 Diabetics over 11 Years Follow-Up.

Abstract

Keywords

Subject

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