May 2007
Volume 48, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2007
Prevalence of Glaucomatous Risk Factors in Patients From a Managed-Care Setting: A Pilot Evaluation
Author Affiliations & Notes
  • E. Fang
    Assistant Chief of Ophthalmology, Consultative Glaucoma Service, Los Angeles, California
  • S. K. Law
    Jules Stein Eye Institute, Los Angeles, California
  • J. G. Walt
    Allergan, Inc, Irvine, California
  • T. H. Chiang
    Allergan,Inc, Irvine, California
  • Footnotes
    Commercial Relationships E. Fang, None; S.K. Law, None; J.G. Walt, Allergan, E; T.H. Chiang, Allergan, E.
  • Footnotes
    Support Funded by unrestricted grants
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 2396. doi:
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      E. Fang, S. K. Law, J. G. Walt, T. H. Chiang; Prevalence of Glaucomatous Risk Factors in Patients From a Managed-Care Setting: A Pilot Evaluation. Invest. Ophthalmol. Vis. Sci. 2007;48(13):2396.

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

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Abstract

Purpose:: To determine the prevalence of glaucomatous risk factors (RFs) in glaucoma patients in a managed-care practice.

Methods:: Retrospective review of medical records of 1,189 glaucoma patients. Diagnosis and documentation information of 15 RFs reported to be associated with glaucoma progression were collected. The 15 RFs included age > 70, family history, African American origin, high intraocular pressure (IOP), increase cup/disc (C/D) ratio, poor visual field score, disc hemorrhage, pseudoexfoliation sign, low central corneal thickness (CCT), high myopia, cardiovascular disease, systemic hypertension, diabetes mellitus (DM), migraine headache, and vasospasm. The average risk score for the population was calculated using the predictive model based on 5 risk factors (age, IOP, CCT, C/D ratio, VF score, and DM) derived by Medeiros et al. (2005), where a higher score indicates greater risk.

Results:: 1,182 of 1,189 patients for which medical records were available had a clear diagnosis in the charts. Mean age (63.0 ± 11.9 years) and the average IOP (18.3 ± 4.7 mm Hg) was calculated. Average value of C/D ratio was 0.52 ± 0.18, pattern standard deviation was 2.59 ± 1.99 dB, and CCT was 552 ± 34 microns. The glaucomatous RF with the highest incidence was systemic hypertension (39.0%), followed by age > 70 (27.2%), DM (23.6%), African American origin (23.0%), and a family history of glaucoma (18.2%). An average risk score was 42 for this population.

Conclusions:: 3 of the 5 most prevalent glaucomatous RFs from this population were not included in the predictive model. The prevalence of RFs and risk scores may be compared with a non-glaucoma patient population or a population of glaucoma patients without glaucomatous RFs to determine the relative risk difference. Existing models for calculating glaucoma risk scores do not consider several important risk factors, and these variables should be considered in future calculation models.

Keywords: clinical (human) or epidemiologic studies: health care delivery/economics/manpower • clinical (human) or epidemiologic studies: outcomes/complications • clinical (human) or epidemiologic studies: prevalence/incidence 
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