A predictive model for early diagnosis of keratoconus
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 char...
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| Format: | Article |
| Language: | English |
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BMC
2020-07-01
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| Series: | BMC Ophthalmology |
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| Online Access: | http://link.springer.com/article/10.1186/s12886-020-01531-9 |
| _version_ | 1819026798540750848 |
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| author | Gracia Castro-Luna Antonio Pérez-Rueda |
| author_facet | Gracia Castro-Luna Antonio Pérez-Rueda |
| author_sort | Gracia Castro-Luna |
| collection | DOAJ |
| description | 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 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°. |
| first_indexed | 2024-12-21T05:32:18Z |
| format | Article |
| id | doaj.art-ff005ac5b93a44b5908c23dcb585eec4 |
| institution | Directory Open Access Journal |
| issn | 1471-2415 |
| language | English |
| last_indexed | 2024-12-21T05:32:18Z |
| publishDate | 2020-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Ophthalmology |
| spelling | doaj.art-ff005ac5b93a44b5908c23dcb585eec42022-12-21T19:14:31ZengBMCBMC Ophthalmology1471-24152020-07-012011910.1186/s12886-020-01531-9A predictive model for early diagnosis of keratoconusGracia Castro-Luna0Antonio Pérez-Rueda1Department of Nursing, Physiotherapy and Medicine, The University of AlmeríaUGC Ophthalmology, Torrecárdenas University HospitalAbstract 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°.http://link.springer.com/article/10.1186/s12886-020-01531-9KeratoconusCorneal topographyHigh order aberrationsComa |
| spellingShingle | Gracia Castro-Luna Antonio Pérez-Rueda A predictive model for early diagnosis of keratoconus BMC Ophthalmology Keratoconus Corneal topography High order aberrations Coma |
| title | A predictive model for early diagnosis of keratoconus |
| title_full | A predictive model for early diagnosis of keratoconus |
| title_fullStr | A predictive model for early diagnosis of keratoconus |
| title_full_unstemmed | A predictive model for early diagnosis of keratoconus |
| title_short | A predictive model for early diagnosis of keratoconus |
| title_sort | predictive model for early diagnosis of keratoconus |
| topic | Keratoconus Corneal topography High order aberrations Coma |
| url | http://link.springer.com/article/10.1186/s12886-020-01531-9 |
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