Aberraciones corneales anteriores y posteriores medidas mediante imágenes de Scheimpflug en el queratocono en niños

2020

BMC Ophthalmol

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°.

Section: Discussionmentioning

confidence: 99%

A predictive model for early diagnosis of keratoconus

2020

BMC Ophthalmol

“…However, it is not easy to diagnose subclinical keratoconus based on topographic variables. This study calculates a diagnostic model based on the aberrometry data of the anterior and posterior corneal surface provided by the Pentacam The selection of the sample was made that there were no differences between the age groups [14-17, 19-22, 24, 27, 32], sex [16,[24][25]32], and eye [24][25]. This is an advantage when interpreting results that aren´t biased by age and sex.…”

Section: Discussionmentioning

confidence: 99%

“…The purpose in most of them was to analyze the topographic parameters to find differences between a healthy patient and an incipient corneal ectasia without symptoms. However in all of them, many different classification methods have been used: Amsler-Krumeich [27,[30][31], Alió and Shabayek [15,23], KISA % index [24] or KSS [32]. All this methodological variability leads to an outstanding selection and classification bias when making comparisons between studies.…”

Section: Discussionmentioning

confidence: 99%

“…The main purpose of this study is to calculate a binary logistic model to predictive the early stage keratoconus. Other authors [19,24,33] have established binary logistic models for keratoconus diagnosis but not for earlystage keratoconus. The results analyze the probability of ESKC using three variables: MCT, anterior coma to 90º and posterior to 90º.…”

Section: Discussionmentioning

confidence: 99%

“…The sample size has been estimated with the Ene 3.0 calculator for the mean of a continuous variable (total corneal coma) in three pre-established strata. Thus, we based on the study by Prakash et al [24] where values of total corneal coma aberration (µm) were obtained in normal patients (0.3±0.1), subclinical(early) keratoconus (0.5±0.3) and clinical keratoconus (2.1±1.3). The reference population is all patients over or equal to 18 years old with keratoconus in the province of Almeria.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A predictive model for early diagnosis of keratoconus

2020

Preprint

Abstract 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 90º and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90º and posterior coma to 90º. 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 90º and the posterior coma to 90º.

A model of visual limitation in patients with keratoconus

2020

Sci Rep

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.