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Editors Selection IGR 24-3

Intraocular Pressure: 24-hour IOP variability

Comment by Tony Realini on:

23965 The circadian curve of intraocular pressure: can we estimate its characteristics during office hours?, Fogagnolo P; Orzalesi N; Ferreras A et al., Investigative Ophthalmology and Visual Science, 2009; 50: 2209-2215

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Can 24-hour IOP variability be estimated accurately during office hours? Fogagnolo et al. (626) retrospectively analyzed 24-hour IOP data on 30 glaucoma subjects and 29 healthy controls collected both in the sitting and supine positions, then compared office-hours values to the full 24-hour data. Peak 24-hour IOP in the habitual position (sitting while awake and supine at night) occurred outside office hours in 42% of glaucoma patients, 62% of elderly controls (> 65 yrs), and 91% of young controls (< 30 yrs). Peak office-hours sitting IOP estimated mean 24-hour IOP to within + 1 mmHg in 70% of glaucoma patients. 24-hour IOP fluctuation (24-hour peak minus 24-hour trough) was best approximated by the difference between the peak and trough values from among the office-hours sitting and supine measurements; this difference estimated 24-hour fluctuation to within + 2 mmHg in 50% of glaucoma patients. The study has several important limitations. Like all 24-hour studies, the very act of measuring IOP at night alters the conditions which may regulate IOP (such as sleep patterns, exposure to light, etc.). Inherent to this study was the use of Goldmann tonometry for sitting IOP and the Tonopen for supine IOP, thus introducing fluctuations due to instrumentation differences. Also, this was a retrospective study and carries all of the known limitations of such. With these limitations in mind, the study reveals important information on the use of officehours measurements to estimate 24-hour IOP behavior. The latter is expensive and difficult to obtain in clinical practice. Therefore, being able to estimate peak IOP in 70% and IOP fluctuation in 50% of glaucoma patients is useful. Unfortunately, we cannot know in which 30% of our patients the daytime peak data is not representative of true circadian IOP peak; nor can we know in which 50% daytime IOP fluctuation fails to predict circadian fluctuation.

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