Literature DB >> 24457362

Evaluation of corneal elevation, pachymetry and keratometry in keratoconic eyes with respect to the stage of Amsler-Krumeich classification.

Kazutaka Kamiya1, Rie Ishii, Kimiya Shimizu, Akihito Igarashi.   

Abstract

AIM: To evaluate corneal elevation, pachymetry and keratometry in keratoconic eyes according to the clinical stage of the disease.
METHODS: This prospective comparative study was performed on one hundred and twenty-six eyes of 83 patients who had keratoconus, and 42 normal eyes of 42 age-matched subjects. Corneal elevation, pachymetry and keratometry were measured using a rotating Scheimpflug camera (Pentacam HR, Oculus) in these eyes. The area under the receiver operating characteristic (AUROC) curves was used to analyse the diagnostic significance of these parameters, with respect to each stage of Amsler-Krumeich classifications. AUROC was calculated to describe the predictive accuracy of the different indices and to determine the cut-off points where sensitivity and specificity were maximised.
RESULTS: Posterior (0.980) and anterior (0.977) elevation differences showed the highest AUROCs, followed by dioptres (D) value (0.941), percentage thickness increase (PTI) 2 mm (0.931), PTI 4 mm (0.927), progression index (0.927), minimal pachymetry (0.923), average keratometry (0.914), anterior elevation (0.909), PTI 6 mm (0.906), posterior elevation (0.898), central pachymetry (0.889), PTI 8 mm (0.870), PTI 10 mm (0.864), corneal thickness spatial profile 2 mm (0.835) and cylinder (0.796). The differences in AUROC curves between anterior and posterior elevation difference measurements and other diagnostic parameters tended to be larger at the earlier stages of keratoconus.
CONCLUSIONS: Anterior and posterior corneal surface height data obtained by enhanced ectasia display, effectively discriminates keratoconus from normal corneas. Elevation difference measurements may provide useful information for improving the diagnostic accuracy of keratoconus, especially in the early stage of the disease.

Entities:  

Keywords:  Cornea

Mesh:

Year:  2014        PMID: 24457362     DOI: 10.1136/bjophthalmol-2013-304132

Source DB:  PubMed          Journal:  Br J Ophthalmol        ISSN: 0007-1161            Impact factor:   4.638


  45 in total

1.  Correlation of basic indicators with stages of keratoconus assessed by Pentacam tomography.

Authors:  Xian-Li Du; Min Chen; Li-Xin Xie
Journal:  Int J Ophthalmol       Date:  2015-12-18       Impact factor: 1.779

2.  Response to O'Brart: 'Is accelerated cross-linking the way forward? Yes or No'.

Authors:  M Tsatsos; C MacGregor; N Kopsachilis; P Hossain; D Anderson
Journal:  Eye (Lond)       Date:  2014-11-14       Impact factor: 3.775

3.  Keratoconus after 40 years of age: a longitudinal comparative population-based study.

Authors:  Hassan Hashemi; Soheila Asgari; Shiva Mehravaran; Mohammad Hassan Emamian; Akbar Fotouhi
Journal:  Int Ophthalmol       Date:  2019-11-07       Impact factor: 2.031

4.  A statistical approach to classification of keratoconus.

Authors:  Murat Ucar; Hasan Basri Cakmak; Baha Sen
Journal:  Int J Ophthalmol       Date:  2016-09-18       Impact factor: 1.779

5.  A retrospective analysis of vision correction and safety in keratoconus patients wearing Toris K soft contact lenses.

Authors:  Pinar Sultan; Cezmi Dogan; Guzin Iskeleli
Journal:  Int Ophthalmol       Date:  2016-02-19       Impact factor: 2.031

6.  Use of machine learning to achieve keratoconus detection skills of a corneal expert.

Authors:  Eyal Cohen; Dor Bank; Nir Sorkin; Raja Giryes; David Varssano
Journal:  Int Ophthalmol       Date:  2022-08-11       Impact factor: 2.029

7.  5-year follow-up of combined non-topography guided photorefractive keratectomy and corneal collagen cross linking for keratoconus.

Authors:  Abdulrahman Mohammed Al-Amri
Journal:  Int J Ophthalmol       Date:  2018-01-18       Impact factor: 1.779

8.  [Early diagnosis of keratoconus].

Authors:  Stefan J Lang; P Maier; T Böhringer; T Reinhard
Journal:  Ophthalmologe       Date:  2021-07-23       Impact factor: 1.059

9.  Evaluation of Intraocular Pressure and Other Biomechanical Parameters to Distinguish between Subclinical Keratoconus and Healthy Corneas.

Authors:  Cristina Peris-Martínez; María Amparo Díez-Ajenjo; María Carmen García-Domene; María Dolores Pinazo-Durán; María José Luque-Cobija; María Ángeles Del Buey-Sayas; Susana Ortí-Navarro
Journal:  J Clin Med       Date:  2021-04-28       Impact factor: 4.241

10.  Keratoconus detection of changes using deep learning of colour-coded maps.

Authors:  Xu Chen; Jiaxin Zhao; Katja C Iselin; Davide Borroni; Davide Romano; Akilesh Gokul; Charles N J McGhee; Yitian Zhao; Mohammad-Reza Sedaghat; Hamed Momeni-Moghaddam; Mohammed Ziaei; Stephen Kaye; Vito Romano; Yalin Zheng
Journal:  BMJ Open Ophthalmol       Date:  2021-07-13
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