April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Distribution of Intraocular Pressure Measurements During Follow-up and its Relationship with Rates of Visual Field Progression
Author Affiliations & Notes
  • Sara Ghobraiel
    Department of Ophthalmology, New York University, New York, NY 10016, NY
  • Gustavo V De Moraes
    Department of Ophthalmology, New York University, New York, NY 10016, NY
    Einhorn Clinical Research Center, New York Eye and Ear Infirmary, New York, NY
  • Jonathan S Myers
    Glaucoma Service, WIlls Eye Institute, Philadelphia, PA
  • Jeffrey M Liebmann
    Department of Ophthalmology, New York University, New York, NY 10016, NY
    Einhorn Clinical Research Center, New York Eye and Ear Infirmary, New York, NY
  • Robert Ritch
    Einhorn Clinical Research Center, New York Eye and Ear Infirmary, New York, NY
    Department of Ophthalmology, New York Medical College, Valhalla, NY
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 111. doi:
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      Sara Ghobraiel, Gustavo V De Moraes, Jonathan S Myers, Jeffrey M Liebmann, Robert Ritch; Distribution of Intraocular Pressure Measurements During Follow-up and its Relationship with Rates of Visual Field Progression. Invest. Ophthalmol. Vis. Sci. 2014;55(13):111.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: Although intraocular pressure (IOP) is the only proven modifiable risk factor for glaucoma progression, there is conflicting literature regarding which IOP parameter is the most important. We hypothesized that no single parameter should be analyzed individually, but rather that the density distribution of its values may give more information regarding visual field (VF) progression. In particular, this study investigated whether ‘kurtosis’ and ‘skewness’ are associated with faster rates of VF progression.

Methods: We included one randomly selected eye for each of 277 treated glaucoma patients with at least 10 IOP measurements followed from 1999 to 2008. 59% were female and mean age was 66 years. IOP mean and fluctuation (defined as the standard deviation, SD), kurtosis, skewness, central corneal thickness (CCT), and VF progression were analyzed using pointwise linear regression analysis. Patients were divided into 2 groups based on the median split of their mean follow-up IOP (16 mmHg). Fast progression was defined if there were at least 2 adjacent VF points in the same hemifield progressing faster than -1.0 dB/yr at p<0.01. Cox proportional hazards were used to identify significant predictors in multivariable analyses adjusting for CCT and all IOP parameters together.

Results: The mean (SD) follow-up IOP was 15.2 (2.6) mmHg spanning 6.8(1.7) years of follow up. In 72% of the eyes, the series of IOP measurements followed a Gaussian distribution. 36% reached a progression endpoint. In all tested models, IOP mean, peak, and fluctuation were significant predictors of progression (all p<0.05). When all eyes were included, skewness to the right (i.e. higher IOP) was an independent predictor of progression (Hazard Ratio, HR=1.53, p=0.028) while higher kurtosis reached borderline significance (HR=1.09, p=0.078). Skewness to the right was independently associated with faster progression in the sub-group with higher mean IOP (HR=1.67, p=0.029) although this effect was not observed in the sub-group with lower mean IOP (p=0.767). Higher kurtosis had a marginal effect in the subgroup with lower mean IOP (HR=1.215, p=0.132).

Conclusions: The majority of patients’ IOP measurements followed a Gaussian distribution. Instead of focusing on a single IOP parameter, the distribution of measurements over time provides more information regarding the risk of faster VF progression.

Keywords: 568 intraocular pressure • 642 perimetry  
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