A model of visual limitation in patients with keratoconus

• Published in: Scientific reports Vol. 10; no. 1; p. 19335
• Main Authors: Pérez-Rueda, Antonio, Castro-Luna, Gracia
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 09-11-2020; Nature Publishing Group
• Subjects: 692/699; 692/699/3161; 692/699/3161/3163; Acuity; Adult; Area Under Curve; Cornea; Corneal Topography; Corneal Wavefront Aberration; Cross-Sectional Studies; Diabetic retinopathy; Female; Humanities and Social Sciences; Humans; Keratoconus; Keratoconus - physiopathology; Male; Middle Aged; multidisciplinary; Patients; Refraction, Ocular; Regression Analysis; ROC Curve; Science; Science (multidisciplinary); Spain; Topography; Variables; Vision Disorders - physiopathology; Visual Acuity; Young Adult; Spain
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-020-76489-1

This paper aims to calculate a relevance model of visual limitation (V.L.) in keratoconus patients based on refractive and topographic parameters. A cross-sectional study was carried out in Torrecárdenas Hospital, Almería, Spain, between February 2018 and July 2019. It included 250 keratoconus patients. Two groups were created according to a grading system of V.L. based on RETICS (Red Temática de Investigación Cooperativa en Salud) classification: keratoconus patients with no V.L. (best spectacle-corrected visual acuity (BSCVA) ≤ 0.05 logMAR) and keratoconus patients with V.L. (BSCVA > 0.05 logMAR). Correlations and a binary logistic regression were established. V.L. was correlated with maximum curvature (
r
 = 0.649, p < 0.001) and root mean square higher-order aberrations (HOARMS) (
r
 = 0.625, p < 0.001). Binary logistic regression included V.L. as the dependent variable and spherical equivalent, HOARMS, spherical aberration and interaction between the anterior and posterior vertical coma as independent variables. The model was a good fit. Area under the curve (A.U.C.) of receiver operating characteristic (R.O.C.) curve was 0.924, sensitivity 91.90%, specificity 83.60%, accuracy 88.94%; and precision 91.17%. Binary logistic regression model of V.L. is a good fit model to predict the early loss of visual acuity in keratoconus patients.