Mustafa Değer Bilgeç1, Eray Atalay2, Ömer Sözer1, Hüseyin Gürsoy1, Muzaffer Bilgin3, Nilgün Yıldırım1. 1. Department of Ophthalmology, Eskişehir Osmangazi University Medical School, Eskişehir, Turkey. 2. Department of Ophthalmology, Eskişehir Osmangazi University Medical School, Eskişehir, Turkey. eatalay@ogu.edu.tr. 3. Department of Biostatistics, Eskişehir Osmangazi University Medical School, Eskişehir, Turkey.
Abstract
PURPOSE: To identify the effect of corneal geometrical and biomechanical parameters on the intraocular pressure (IOP) measurements obtained by Goldmann Applanation Tonometer (GAT), non-contact tonometer, iCare Pro Rebound Tonometer (IRT), Tonopen and Ocular Response Analyzer (ORA, Goldmann-correlated IOP: IOPg, corneal compensated IOP: IOPcc). METHODS: We prospectively recruited patients with a tomographically confirmed diagnosis of keratoconus. IOP measurements were performed in the following order: non-contact tonometry, ORA, IRT, GAT and Tonopen. The means of the three IOP measurements were used for the analysis. Correlation analyses were performed to assess the association between tonometer readings and the corneal geometrical and biomechanical parameters including ORA waveform parameters. Tonometer variability was assessed using a stepwise linear regression analysis. RESULTS: Fifty-one patients with keratoconus (27 females, mean age 30.8 ± 8.7 years) were evaluated. The highest mean IOP was measured by IOPcc (14.6 ± 2.3 mmHg) followed by IRT IOP (13.0 ± 3.2 mmHg), Tonopen IOP 12.0 ± 2.6 mmHg), GAT IOP (11.7 ± 3.1 mmHg), NCT IOP (10.2 ± 3.2 mmHg) and IOPg (10.2 ± 3.6 mmHg). NCT and IOPg were affected from all corneal parameters including thickness, curvature and biomechanical parameters. While GAT and IRT had significant correlations with corneal resistance factor (CRF) and corneal hysteresis, IOPcc only had a significant correlation with CRF. None of the corneal factors had any statistically significant correlation with Tonopen. CRF predicted tonometer measurement variability in 7 of the 15 inter-device variability assessments. CONCLUSION: Tonopen was the least affected from the corneal parameters followed by IOPcc and GAT. CRF was a strong determinant of tonometer variability.
PURPOSE: To identify the effect of corneal geometrical and biomechanical parameters on the intraocular pressure (IOP) measurements obtained by Goldmann Applanation Tonometer (GAT), non-contact tonometer, iCare Pro Rebound Tonometer (IRT), Tonopen and Ocular Response Analyzer (ORA, Goldmann-correlated IOP: IOPg, corneal compensated IOP: IOPcc). METHODS: We prospectively recruited patients with a tomographically confirmed diagnosis of keratoconus. IOP measurements were performed in the following order: non-contact tonometry, ORA, IRT, GAT and Tonopen. The means of the three IOP measurements were used for the analysis. Correlation analyses were performed to assess the association between tonometer readings and the corneal geometrical and biomechanical parameters including ORA waveform parameters. Tonometer variability was assessed using a stepwise linear regression analysis. RESULTS: Fifty-one patients with keratoconus (27 females, mean age 30.8 ± 8.7 years) were evaluated. The highest mean IOP was measured by IOPcc (14.6 ± 2.3 mmHg) followed by IRT IOP (13.0 ± 3.2 mmHg), Tonopen IOP 12.0 ± 2.6 mmHg), GAT IOP (11.7 ± 3.1 mmHg), NCT IOP (10.2 ± 3.2 mmHg) and IOPg (10.2 ± 3.6 mmHg). NCT and IOPg were affected from all corneal parameters including thickness, curvature and biomechanical parameters. While GAT and IRT had significant correlations with corneal resistance factor (CRF) and corneal hysteresis, IOPcc only had a significant correlation with CRF. None of the corneal factors had any statistically significant correlation with Tonopen. CRF predicted tonometer measurement variability in 7 of the 15 inter-device variability assessments. CONCLUSION: Tonopen was the least affected from the corneal parameters followed by IOPcc and GAT. CRF was a strong determinant of tonometer variability.
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