Estimating the Risk of Developing Glaucoma

Medeiros, Felipe A.

doi:10.2174/1874364100903010050

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…Younger patients (≤30 years) were referred for reasons directly related to glaucoma potentially indicating that clinical data for this age group were more carefully interpreted. Patients who were subsequently determined to be normal, misdiagnosed or suffer from conditions differential to glaucoma primarily were within age groups before or around the time of expected glaucoma onset . Older patients were also more likely to be recommended for active management rather than surveillance even in the presence of comparable clinical findings.…”

Section: Discussionmentioning

confidence: 99%

Clinical model assisting with the collaborative care of glaucoma patients and suspects

Jamous

Kalloniatis

Hennessy

et al. 2014

Clinical Exper Ophthalmology

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Section: Discussionmentioning

confidence: 99%

Clinical model assisting with the collaborative care of glaucoma patients and suspects

Jamous

Kalloniatis

Hennessy

et al. 2014

Clinical Exper Ophthalmology

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Potential effects of systematic errors in intraocular pressure measurements on screening for ocular hypertension

Turner

Graham

Avolio

et al. 2013

Eye

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Aim Raised intraocular pressure (IOP) increases the risk of glaucoma. Eye-care professionals measure IOP to screen for ocular hypertension (OHT) (IOP421 mm Hg) and to monitor glaucoma treatment. Tonometers commonly develop significant systematic measurement errors within months of calibration, and may not be verified often enough. There is no published evidence indicating how accurate tonometers should be. We analysed IOP measurements from a population study to estimate the sensitivity of detection of OHT to systematic errors in IOP measurements. Methods We analysed IOP data from 3654 participants in the Blue Mountains Eye Study, Australia. An inverse cumulative distribution indicating the proportion of individuals with highest IOP421 mm Hg was calculated. A second-order polynomial was fitted to the distribution and used to calculate over-and under-detection of OHT that would be caused by systematic measurement errors between À 4 and þ 4 mm Hg. We calculated changes in the apparent prevalence of OHT caused by systematic errors in IOP. Results A tonometer that consistently under-or over-reads by 1 mm Hg will miss 34% of individuals with OHT, or yield 58% more positive screening tests, respectively. Tonometers with systematic errors of À 4 and þ 4 mm Hg would miss 76% of individuals with OHT and would over-detect OHT by a factor of seven. Over-and under-detection of OHT are not strongly affected by cutoff IOP. Conclusion We conclude that tonometers should be maintained and verified at intervals short enough to control systematic errors in IOP measurements to substantially less than 1 mm Hg.

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