Literature DB >> 23375190

Anterior segment characteristics of keratoconus eyes in a sample of Asian population.

Fereshteh Abolbashari1, Norhani Mohidin, Seyed Mahdi Ahmadi Hosseini, Bariah Mohd Ali, Shamala Retnasabapathy.   

Abstract

PURPOSE: To assess changes in anterior segment parameters of keratoconus eyes at different stages of the disease in a sample of the Asian population.
METHODS: Files of 32 patients (48 eyes) diagnosed as clinical keratoconus were assessed and the following parameters noted: central corneal thickness (CCT), thinnest corneal thickness (TCT), location of thinnest pachymetry, anterior chamber depth (ACD) at the centre from posterior corneal surface, ACD at 1, 2 and 3mm inferior-paracentral, ACD at thinnest pachymetry, anterior chamber volume (ACV) and anterior chamber angle (ACA). For analysis, keratoconus eyes were classified into 3 subgroups according to mean keratometry readings (mild: K≤47.0D, moderate: 47.0<K<52.0D, and severe: K≥52.0D). Forty-five subjects (45 right eyes) were recruited as a control group. They underwent Pentacam tomographic evaluation. The same parameters were recorded for control subjects as in the keratoconus patients.
RESULTS: Each keratoconus subgroup comprised of 16 eyes. CCT, TCT, ACD at centre, ACD at 1, 2mm inferior-paracentral and ACD at thinnest pachymetry were statistically different between mild and severe keratoconus groups (P<0.05). There were also significant differences between normal with each of the moderate and severe keratoconus groups (P<0.05). Non-significant differences were found in ACV (P=0.84) and ACA (P=0.71) between all measured groups.
CONCLUSION: With the exception of ACV and ACA, parameters that include CCT, TCT, ACD at centre, thinnest pachymetry and 1, 2 mm inferior-paracentral were significantly altered with progression of keratoconus. These findings may be useful in monitoring and management of keratoconus patients.
Copyright © 2013 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

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Mesh:

Year:  2013        PMID: 23375190     DOI: 10.1016/j.clae.2013.01.005

Source DB:  PubMed          Journal:  Cont Lens Anterior Eye        ISSN: 1367-0484            Impact factor:   3.077


  11 in total

1.  Anterior segment parameters in Indian young adults using the Pentacam.

Authors:  Seyed Mahdi Ahmadi Hosseini; Fereshteh Abolbashari; Norhani Mohidin
Journal:  Int Ophthalmol       Date:  2013-03-01       Impact factor: 2.031

2.  Assessment of Macular Parameter Changes in Patients with Keratoconus Using Optical Coherence Tomography.

Authors:  Srujana Sahebjada; Fakir M Amirul Islam; Sanj Wickremasinghe; Mark Daniell; Paul N Baird
Journal:  J Ophthalmol       Date:  2015-05-12       Impact factor: 1.909

3.  Comparison of keratometric and pachymetric parameters with Scheimpflug imaging in normal and keratoconic Asian eyes.

Authors:  Hou-Boon Lim; Gavin S Tan; Li Lim; Hla Myint Htoon
Journal:  Clin Ophthalmol       Date:  2014-11-12

4.  Normative values and contralateral comparison of anterior chamber parameters measured by Pentacam and its correlation with corneal biomechanical factors.

Authors:  Mohammad Reza Sedaghat; Vahid Mohammad Zadeh; Kaveh Fadakar; Sakineh Kadivar; Mojtaba Abrishami
Journal:  Saudi J Ophthalmol       Date:  2016-12-01

5.  Ocular dimensions of the Chinese adolescents with keratoconus.

Authors:  Weijun Jian; Yang Shen; Yingjun Chen; Mi Tian; Xingtao Zhou
Journal:  BMC Ophthalmol       Date:  2018-02-13       Impact factor: 2.209

6.  Evaluation of Anterior Segment Parameters in Obesity.

Authors:  Alime Gunes; Feyzahan Uzun; Emine Esra Karaca; Mustafa Kalaycı
Journal:  Korean J Ophthalmol       Date:  2015-07-21

7.  Anterior segment characteristics in normal and keratoconus eyes evaluated with a combined Scheimpflug/Placido corneal imaging device.

Authors:  Masoud Safarzadeh; Nader Nasiri
Journal:  J Curr Ophthalmol       Date:  2016-06-25

8.  The influence of corneal collagen cross-linking on anterior chamber in keratoconus.

Authors:  Nihat Polat; Abuzer Gunduz; Cemil Colak
Journal:  Indian J Ophthalmol       Date:  2017-04       Impact factor: 1.848

9.  Evaluating the Performance of Various Machine Learning Algorithms to Detect Subclinical Keratoconus.

Authors:  Ke Cao; Karin Verspoor; Srujana Sahebjada; Paul N Baird
Journal:  Transl Vis Sci Technol       Date:  2020-04-24       Impact factor: 3.283

10.  Comparison of Anterior Chamber Depth between Normal and Keratoconic Eyes: A Systematic Review and Meta-Analysis.

Authors:  Hassan Hashemi; AbbasAli Yekta; Negareh Yazdani; Hadi Ostadimoghaddam; Mehdi Khabazkhoob
Journal:  J Curr Ophthalmol       Date:  2020-03-23
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