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Background: The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore, to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models.Methods: The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 early-stage keratoconus and 83 established keratoconus. The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of early-stage keratoconus was calculated with the statistically significant variables.Results: Statistically significant differences were observed when comparing normal corneas with early-stage keratoconus/ in variables of the vertical asymmetry to 90° and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90° and posterior coma to 90°. The model properly diagnosed 92% of cases with a sensitivity of 97.59%, specificity 98.78%, accuracy 98.18% and precision 98.78%.Conclusions: The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90° and the posterior coma to 90°. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]