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1.
Ophthalmologe ; 118(3): 288-290, 2021 03.
Article in German | MEDLINE | ID: mdl-33666729
2.
Br J Ophthalmol ; 103(4): 551-557, 2019 04.
Article in English | MEDLINE | ID: mdl-29858179

ABSTRACT

AIM: To define variables for the evaluation of keratoconus progression and to determine cut-off values. METHODS: In this retrospective cohort study (2010-2016), 265 eyes of 165 patients diagnosed with keratoconus underwent two Scheimpflug measurements (Pentacam) that took place 1 year apart ±3 months. Variables used for keratoconus detection were evaluated for progression and a correlation analysis was performed. By logistic regression analysis, a keratoconus progression index (KPI) was defined. Receiver-operating characteristic curve (ROC) analysis was performed and Youden Index calculated to determine cut-off values. RESULTS: Variables used for keratoconus detection showed a weak correlation with each other (eg, correlation r=0.245 between RPImin and Kmax, p<0.001). Therefore, we used parameters that took several variables into consideration (eg, D-index, index of surface variance, index for height asymmetry, KPI). KPI was defined by logistic regression and consisted of a Pachymin coefficient of -0.78 (p=0.001), a maximum elevation of back surface coefficient of 0.27 and coefficient of corneal curvature at the zone 3 mm away from the thinnest point on the posterior corneal surface of -12.44 (both p<0.001). The two variables with the highest Youden Index in the ROC analysis were D-index and KPI: D-index had a cut-off of 0.4175 (70.6% sensitivity) and Youden Index of 0.606. Cut-off for KPI was -0.78196 (84.7% sensitivity) and a Youden Index of 0.747; both 90% specificity. CONCLUSIONS: Keratoconus progression should be defined by evaluating parameters that consider several corneal changes; we suggest D-index and KPI to detect progression.


Subject(s)
Cornea/pathology , Corneal Pachymetry/methods , Corneal Topography/methods , Keratoconus/diagnosis , Adult , Disease Progression , Female , Follow-Up Studies , Humans , Male , Middle Aged , ROC Curve , Retrospective Studies , Time Factors , Young Adult
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