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Editors Selection IGR 15-1

Clinical Examination Methods: The long and short of IOP fluctuation

Kaweh Mansouri

Comment by Kaweh Mansouri on:

70205 Correlation between short-term and long-term intraocular pressure fluctuation in glaucoma patients, Tojo N; Abe S; Miyakoshi M et al., Clinical Ophthalmology, 2016; 10: 1713-1717


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The role of IOP fluctuations in the pathogenesis of glaucoma remains unclear. In this retrospective study, Tojo et al., investigated the (yet unknown) correlation between short-term and long-term IOP fluctuations. They enrolled 50 patients with different types of glaucoma. As a surrogate for short-term IOP fluctuations, patients underwent one 24-h recording session with the Triggerfish contact lens sensor (CLS), which obtains an indirect measurement of IOP-related variations. Long-term IOP fluctuations were defined as a combination of mean, SD, and peak IOP over an average 5.4 year period. The authors found that CLS-derived short-term IOP fluctuations were significantly correlated with long-term IOP fluctuations.

This finding, although of interest, should be considered with caution, as the study is subject to several limitations. Firstly, as we have suggested in the past,1 using the absolute range of CLS values without any statistical modeling (e.g., cosinor or other) may not be appropriate since the CLS output is subject to extreme values as a result of artefacts. Yet, this is how the authors defined CLS-derived fluctuations in this study. Unsurprisingly, the mean CLS IOP fluctuation was a very high 445 (143 SD) mVeq., attesting to the need for statistical smoothing.;

Secondly, Spearman rank correlation was used for calculating the association between shortterm and long-term IOP fluctuations. The strength of these correlations, however, was not reported in the paper, merely the value of statistical significance. Looking at the figures, one gets the impression that the observed correlations were due to the inclusion of a few extreme CLS outliers. The authors should have reported whether their findings would have remained the same after exclusion of those outliers.

The relationship between short-term and long-term IOP flucations for the management of glaucoma remains unclear.

Thirdly, the authors did not report (nor consider) the role of medication changes during the long follow-up period. Fourth, the studied population was a mixed group of glaucoma types, some of which have profoundly different IOP behavior.

These shortcomings point to the inappropriateness of using a retrospective design to answer research topics that require a rigorous prospective design. Nevertheless, the relationship between short-term and long-term IOP flucations for the management of glaucoma remains unclear and important to study.

References

  1. Mansouri K, et al. Analysis of continuous 24-hour intraocular pressure patterns in glaucoma. Invest Ophthalmol Vis Sci 2012;53(13):8050-8056.


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