Research code: 94063103
Ethics code: IR.GUMS.REC.1394.263
Soltani Moghadam R, Azaripour E, Akbari M, Behboudi H, Mohammad Amin H. Predicting the Keratoconus Disease Severity Based on Pachymetric Progression Indices Measured by Pentacam. JGUMS 2022; 31 (2) :150-165
URL:
http://journal.gums.ac.ir/article-1-2452-en.html
1- Department of Eye, Eye Research Center, Amiralmomen in Hospital, Faculty of Medicine, Guilan University of Medical Science, Rasht, Iran.
2- Department of Eye, Eye Research Center, Amiralmomenin Hospital, Faculty of Medicine, Guilan University of Medical Science, Rasht, Iran. , eazaripour@yahoo.com
3- Department of Eye, Eye Research Center, Amiralmomenin Hospital, Faculty of Medicine, Guilan University of Medical Science, Rasht, Iran.
Abstract: (987 Views)
Background Keratoconus (KCN) is a bilateral, progressive, and non-inflammatory disorder in the cornea, which results in thinning and protrusion of the cornea.
Objective This study aims to determine the effectiveness of using pachymetric progression indices (PPIs) in grading the severity of KCN disease.
Methods In this study, 76 patients with different stages of KCN were enrolled. The severity of KCN was graded according to maximum keratometry, cornea thickness, and spherical equivalent. The PPIs measured by Pentacam and the demographic characteristics were recorded and their correlation with the severity of KCN was assessed.
Results In terms of KCN severity, 18% of patients were at grade 1, 31% at grade 2, 42% at grade 3, and 7% at grade 4. The power of PPIs in predicting KCN grade 4, grade 3 and grade 2 based on the area under the curve ranged from 0.722 to 0.993.
Conclusion The PPIs (Minimum, Maximum, Average) can predict the severity of KCN disease with good sensitivity and specificity.
Review Paper:
Applicable |
Subject:
Special Received: 2021/12/20 | Accepted: 2022/06/11 | Published: 2022/07/1