New artificial intelligence index based on Scheimpflug corneal tomography to distinguish subclinical keratoconus from healthy corneas

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorFaculty of Medicine of São José do Rio Preto-
Autor(es): dc.contributorBase Hospital of São José do Rio Preto-
Autor(es): dc.contributorVisum Eye Center-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorRio Claro Eye Institute-
Autor(es): dc.contributorUniversity of Liverpool-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorFederal University of Alagoas-
Autor(es): dc.contributorFederal University the State of Rio de Janeiro-
Autor(es): dc.creatorAlmeida, Gildásio Castello-
Autor(es): dc.creatorGuido, Rodrigo Capobianco-
Autor(es): dc.creatorBalarin Silva, Henrique Monteiro-
Autor(es): dc.creatorBrandão, Cinara Cássia-
Autor(es): dc.creatorDe Mattos, Luiz Carlos-
Autor(es): dc.creatorLopes, Bernardo T.-
Autor(es): dc.creatorMachado, Aydano Pamponet-
Autor(es): dc.creatorAmbrósio, Renato-
Data de aceite: dc.date.accessioned2025-08-21T18:33:33Z-
Data de disponibilização: dc.date.available2025-08-21T18:33:33Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2022-10-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1097/j.jcrs.0000000000000946-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/247723-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/247723-
Descrição: dc.descriptionPurpose: To assess the efficiency of an index derived from multiple logistic regression analysis (MLRA) to measure differences in corneal tomography findings between subclinical keratoconus (KC) in 1 eye, corneal ectasia, and healthy corneas. Setting: 2 private Brazilian ophthalmological centers. Design: Multicenter case-control study. Methods: This study included 187 eyes with very asymmetric ectasia and with normal corneal topography and tomography (VAE-NTT) in the VAE-NTT group, 2296 eyes with healthy corneas in the control group (CG), and 410 eyes with ectasia in the ectasia group. An index, termed as Boosted Ectasia Susceptibility Tomography Index (BESTi), was derived using MLRA to identify a cutoff point to distinguish patients in the 3 groups. The groups were divided into 2 subgroups with an equal number of patients: validation set and external validation (EV) set. Results:2893 patients with 2893 eyes were included. BESTi had an area under the curve (AUC) of 0.91 with 86.02% sensitivity (Se) and 83.97% specificity (Sp) between CG and the VAE-NTT group in the EV set, which was significantly greater than those of the Belin-Ambrósio Deviation Index (BAD-D) (AUC: 0.81; Se: 66.67%; Sp: 82.67%; P <.0001) and Pentacam random forest index (PRFI) (AUC: 0.87; Se: 78.49%; Sp: 79.88%; P =.021). Conclusions: BESTi facilitated early detection of ectasia in subclinical KC and demonstrated higher Se and Sp than PRFI and BAD-D for detecting subclinical KC.-
Descrição: dc.descriptionFaculty of Medicine of São José do Rio Preto, São José do Rio Preto-
Descrição: dc.descriptionBase Hospital of São José do Rio Preto, São José do Rio Preto-
Descrição: dc.descriptionVisum Eye Center, São José do Rio Preto-
Descrição: dc.descriptionDepartment of Computer Science and Statistics Institute of Biosciences Letters and Exact Sciences São Paulo State University at São José do Rio Preto-
Descrição: dc.descriptionRio Claro Eye Institute, Rio Claro-
Descrição: dc.descriptionDepartment of Civil Engineering and Industrial Design School of Engineering University of Liverpool-
Descrição: dc.descriptionDepartment of Ophthalmology Federal University of São Paulo-
Descrição: dc.descriptionComputing Institute Federal University of Alagoas-
Descrição: dc.descriptionDepartment of Ophthalmology Federal University the State of Rio de Janeiro-
Descrição: dc.descriptionDepartment of Computer Science and Statistics Institute of Biosciences Letters and Exact Sciences São Paulo State University at São José do Rio Preto-
Formato: dc.format1168-1174-
Idioma: dc.languageen-
Relação: dc.relationJournal of Cataract and Refractive Surgery-
???dc.source???: dc.sourceScopus-
Título: dc.titleNew artificial intelligence index based on Scheimpflug corneal tomography to distinguish subclinical keratoconus from healthy corneas-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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