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BJO Online First, published on March 13, 2014 as 10.1136/bjophthalmol-2013-303980 Review
Intraocular pressure fluctuation and glaucoma progression: what do we know? Matthew C Leidl,1 Catherine J Choi,2 Zeba A Syed,3 Samir A Melki2,3,4,5 1
Nassau University Medical Center, East Meadow, New York, USA 2 Massachusetts Eye & Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA 3 Harvard Medical School, Boston, Massachusetts, USA 4 Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA 5 Boston Eye Group, Boston, Massachusetts, USA Correspondence to Dr Samir Melki, Boston Eye Group, 1101 Beacon Street, Brookline, MA 02446, USA; [email protected] Received 8 July 2013 Revised 11 November 2013 Accepted 17 February 2014
ABSTRACT While mean intraocular pressure (IOP) has long been known to correlate with glaucomatous damage, the role of IOP fluctuation is less clearly defined. There is extensive evidence in the literature for and against the value of short-term and long-term IOP fluctuation in the evaluation and prognosis of patients with glaucoma. We present here the arguments made by both sides, as well as a discussion of the pitfalls of prior research and potential directions for future studies. Until a reliable method is developed that allows for constant IOP monitoring, many variables will continue to hinder us from drawing adequate conclusions regarding the significance of IOP variation. INTRODUCTION Intraocular pressure (IOP) is a significant factor in the diagnosis and management of glaucomatous disease. There is a well-established link between elevations in IOP and visual field (VF) deterioration, and lowering IOP may both slow this progression.1–4 and improve the appearance of glaucomatous optic discs.5 6 There are numerous methods for monitoring IOP, though the Goldmann applanation tonometer is likely the most frequently used. The device measures the amount of force required to flatten a section of the cornea, thereby indirectly calculating the IOP.7 A more in-depth discussion of tonometry is beyond the scope of this paper, though Stamper provides an excellent, highly recommended discussion of the topic. Studies show that IOP tends to fluctuate throughout the day and over longer intervals.8–12 It has been difficult to determine the significance of these variations due to a lack of standardisation in the time between assessments, the method of measurement, and the definition of fluctuation itself.10 13 Nonetheless, many important findings have been made, as discussed below.
LONG-TERM IOP FLUCTUATION The definition of long-term IOP fluctuation varies across studies. One definition refers to the difference between the highest and lowest IOP values over a given period, with measurements occurring on different days.14 Alternatively, numerous studies define IOP fluctuation as the SD in IOP over a given time.1 2 11 13 15–22 To cite: Leidl MC, Choi CJ, Syed ZA, et al. Br J Ophthalmol Published Online First: [ please include Day Month Year] doi:10.1136/bjophthalmol2013-303980
Studies that argue that long-term IOP fluctuation is significant
Several studies suggest that long-term IOP fluctuation is an important prognostic indicator for glaucomatous damage. Hong et al16 reviewed 408 eyes
Leidl MC, et al. Br JArticle Ophthalmolauthor 2014;0:1–5. Copyright (ordoi:10.1136/bjophthalmol-2013-303980 their employer) 2014. Produced
with either primary open-angle glaucoma (POAG) or chronic primary angle-closure glaucoma (PACG), all of which had an IOP less than 18 mm Hg following phacoemulsification, posterior chamber intraocular lens implantation, and trabeculectomy. Over at least 3 years of follow-up, the authors found that, of patients with a SD in IOP greater than 2 mm Hg, 30% of those with POAG and 28.6% of those with chronic PACG demonstrated VF loss, compared to 9.7% and 10%, respectively, of those patients with SD in IOP not exceeding 2 mm Hg. Notably, the mean IOP between the two groups of patients was not significantly different, suggesting that long-term IOP fluctuation is associated with VF loss rather than the absolute value at any given time. Hong et al15 later studied 688 eyes in patients with POAG or chronic PACG who had undergone phacoemulsification after trabeculectomy. They found that after 3 years of follow-up, patients with POAG and an IOP SD greater than 2 mm Hg after surgery had a markedly worse mean VF deviation than did patients with an IOP SD of no more than 2 mm Hg. Fukuchi et al22 similarly found that patients with normal tension glaucoma (NTG) designated as fast progressors based on VF had a higher SD and range in follow-up IOP compared to slow progressors, They found no such correlation for patients with open-angle glaucoma (OAG). A cohort from the Advanced Glaucoma Intervention Study included 509 eyes with refractory OAG not well controlled with medication.11 The authors found that for each 1 mm Hg increase in IOP fluctuation (SD in IOP), the odds of VF progression increased by about 30%. Eyes with IOP fluctuation of 3 mm Hg or more demonstrated greater VF deterioration than those with fluctuation less than 3 mm Hg. Rao et al20 report similar results in a large, retrospective analysis of patients with treated POAG or PACG. They found that of mean IOP, peak IOP and IOP fluctuation (SD in IOP over several follow-up visits), peak IOP and IOP fluctuation were significantly associated with disease progression in univariate analysis, while only IOP fluctuation remained significantly associated in multivariate analysis. They note that for each 1 mm Hg increase in IOP fluctuation, progression worsened by 0.35% per year. Lee et al17 performed a multicentre, retrospective chart review of 151 patients with POAG, ocular hypertension (OHT), NTG, or findings suspicious for glaucoma. They found that IOP SD was significantly associated with progression—each 1 mm Hg increase in SD increased the risk for glaucoma progression by a factor of 4.2 in patients with measurements before disease worsening or treatment initiation.
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Review Studies that argue that long-term IOP fluctuation is not significant A number of studies have reported that long-term IOP fluctuation has no role in ocular disease. A randomised cohort from the Early Manifest Glaucoma Trial consisting of 129 treated and 126 control patients with glaucoma found a non-significant, positive correlation between time to progression of disease and IOP SD, while mean IOP, had a significant, negative correlation.1 Additionally, a retrospective cohort study of patients from the Glaucoma Progression Study followed 587 eyes with various subtypes of glaucoma.2 Multivariate analysis determined that peak IOP, but not SD in IOP, was associated with glaucoma progression. Medeiros et al18 found comparable results in their study of 252 eyes in 126 patients with untreated OHT. They noted a significant, positive correlation between mean IOP and SD in IOP, but that IOP fluctuation was not a significant marker for progression to glaucoma in either univariate or multivariate analysis, while mean IOP was. Fogagnolo et al19 analysed IOP fluctuation in 52 patients with treated POAG, of whom 28 progressed during the study period. Over four follow-up visits, each 6 months apart, the authors found no significant difference in either short-term or long-term IOP fluctuation between patients who progressed and those who remained stable. Lee et al21 found comparable results in patients with NTG and at least 5 years of follow-up, reporting no significant association between SD in IOP and VF progression in univariate or multivariate analysis. Bengtsson and Heijl studied a cohort of 90 patients from the Malmö Ocular Hypertension Study, which prospectively followed patients with normal VFs and an IOP of at least 22 mm Hg.23 They defined IOP variation using several parameters including: variation in measurements obtained at 0800, 1130 and 1530; the maximum range from a series of diurnal curves; and the difference between highest and lowest IOP throughout the entire study period (mean follow-up of 8.5 years). They found that IOP fluctuation defined in each of these manners was not an independent risk factor for glaucoma development in patients with high-risk OHT. Finally, Realini et al24 conducted a chart review with the primary goal of checking for asymmetry in IOP fluctuation between fellow eyes. With a minimum of 1 year of follow-up, they found that IOP fluctuation between fellow eyes did not vary significantly between healthy patients and those with glaucoma.
SHORT-TERM IOP FLUCTUATION As with long-term IOP fluctuation, there is no consensus on how to define short-term IOP fluctuation. One commonly used definition applied by Lee et al10 defines it as the difference between the highest and lowest IOP over 24 h or less, though the SD in IOP based on a curve has also been advocated.19 Most studies of repeated IOP measurements throughout the day have determined that values tend to peak early in the morning and decline over the course of the day, though the exact timing of peaks and nadirs is not entirely uniform across reports.9 12 25–37
Studies that argue that short-term IOP fluctuation is significant Numerous reports demonstrate a correlation between increased short-term IOP fluctuation and pressure-related eye diseases. David et al28 assessed 690 IOP curves made from four to six 2
measurements over the course of 10.5 h, and found that the difference in mean IOP peak and trough differed significantly between healthy eyes (5 mm Hg), eyes with OAG and chronic angle-closure glaucoma (ACG) (5.8 mm Hg), and eyes with OHT (6.8 mm Hg). A more recent study also showed that IOP fluctuation is significantly higher in eyes with primary chronic ACG (7.69±3.03 mm Hg) or POAG (8.31±2.58 mm Hg) compared to normal eyes (4.83±2.46 mm Hg).38 Similarly, Grippo et al39 followed the protocol of prior works and combined results to determine that daytime IOP variation—though not nighttime variation—was significantly greater in subjects with OHT and glaucoma than healthy individuals. Baskaran et al40 determined that the difference between the peak and trough IOP in patients with primary angle closure (PAC) and PACG was significantly greater than that in PAC suspects and controls. Further, Kim et al41 noted that during waking hours, patients with NTG had a significantly greater degree of IOP fluctuation than controls. Tajunisah et al42 reported similar results in a study of glaucoma suspects, noting that the mean magnitude in IOP variation for patients with POAG, NTG, glaucoma suspicion and OHT was significantly higher than that for controls. Saccà et al43 note that patients with POAG had a greater relative daily IOP fluctuation (7–9.6%) than patients with NTG (−4.7–6.4%) or healthy eyes (−3.4–6.9%). Twenty-three patients of a cohort of 29 with OHT were available for final analysis in a 5-year follow-up study of IOP by Thomas et al,44 which found that four patients had progressed to glaucoma. Diurnal IOP profiles of these patients with readings taken every 2 h from 10:00 to 18:00 determined that the mean IOP variation was 8.6 mm Hg in the patients who progressed, compared to 5.4 mm Hg in those who did not. One study used frequency doubling technology (FDT) perimetry to study 33 eyes with OHT while measuring IOP at 0830, 1030 and 1530.45 The authors discovered that office IOP fluctuation was significantly greater in patients with abnormal FDT perimetry results (median 5 mm Hg) compared to those with normal FDT perimetry results (median 2 mm Hg). Office IOP fluctuation was also correlated with the number of depressed points on FDT perimetry. Similarly, Sakata et al46 shows that 24 h IOP fluctuation in the habitual position in patients with NTG had a significant, negative correlation with mean VF deviation. Analysis of daytime IOP curves from 149 patients with OHT found that 33 of the eyes studied had a difference of more than 5 mm Hg between the peak and trough IOP in their diurnal curve.47 Of these, 64% had VF defects within 4 years. By contrast, of those eyes with a fluctuation in IOP not exceeding 5 mm Hg, 84% had normal VFs after at least 5 years; these differences were significant. In a prospective study, Asrani et al48 reported on 105 eyes from 64 patients with OAG who were monitored via VF and home tonometry five times daily. Patients in the highest quartile of home IOP range (at least 11.8 mm Hg) had a cumulative risk of VF progression of 88% over 8 years, compared to 57% for patients in the lowest quartile for IOP range (no more than 7.7 mm Hg). A study of 3561 IOP profiles from 720 patients performed by Jonas et al49 analysed patients with healthy eyes, ocular HTN, preperimetric glaucoma ( patients with normal VF data, but a glaucomatous-appearing optic nerve), POAG, secondary OAG and NTG. The authors found that mean IOP fluctuation was significantly greater in patients with OHT, preperimetric glaucoma, or secondary OAG as compared with healthy eyes. Interestingly, there was no significant difference in mean IOP Leidl MC, et al. Br J Ophthalmol 2014;0:1–5. doi:10.1136/bjophthalmol-2013-303980
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Review fluctuation in those with perimetric POAG compared to those with preperimetric glaucoma, OHT, or normal eyes. Moreover, eyes with NTG had no significant difference in IOP fluctuation compared to healthy eyes, but a significantly lower IOP fluctuation than eyes with OHT or preperimetric glaucoma. By contrast, Jonas et al50 studied 855 eyes with NTG or POAG by monitoring IOP at 1700, 2100, 0000, 0700 and 1200. Here, 163 eyes were noted to have glaucoma progression, which were analysed to reveal that in eyes with NTG, there was a significant, negative association between glaucoma progression and IOP amplitude.
Studies that argue that short-term IOP fluctuation is not significant Several reports suggest that short-term IOP fluctuations may not be significant. Sung et al51 examined 24 h IOP and VF data over approximately 6 years in patients with newly diagnosed NTG. Univariate analysis showed no correlation between VF progression and either 24 h or follow-up IOP fluctuation, among other findings. Similarly, Lee et al36 monitored diurnal IOP in 177 patients with NTG. In univariate and multivariate analysis, the authors found no significant correlation between IOP fluctuation and either pattern standard or mean deviation on VF. Additionally, a series of 14 patients with newly diagnosed, untreated POAG, by Sehi et al52 found no significant association between diurnal changes in IOP and optic nerve head appearance. Likewise, Wang et al53 state that they found no significant association between 24 h IOP fluctuation and mean VF deviation in patients with POAG. Further, in patients with unilateral POAG, they found no difference in SD of diurnal IOP variation or IOP fluctuation between fellow eyes. As indicated above, in their analysis of patients with POAG, Jonas et al50 found no association between glaucoma progression and IOP amplitude. They also reported no significant association between IOP fluctuation and glaucoma progression in an analysis of patients with NTG and POAG as a single group. Also alluded to previously, Fogagnolo et al19 found no significant difference between patients with POAG who progressed and those who remained stable in regard to short-term IOP fluctuation. Finally, Smith measured IOP every 2 h from 0500 to 1500 and attained VFs in patients with OHT, suspected glaucoma and glaucoma.54 Analysis found mean diurnal IOP variation in 400 eyes with VF defects was not significantly different compared to 400 eyes without VF defects.
PROBLEMS WITH IOP ANALYSIS In addition to the aforementioned lack of standardised definitions for IOP fluctuation, many other problems are present in these analyses. First, there are numerous factors that may transiently influence IOP, including the Valsalva manoeuvre, eye squeezing, tear film deficiencies, astigmatism and eyelid closure.55–57 IOP has also been shown to increase as patients move from seated to supine positions,58–60 and following Humphrey VF analysis61 suggesting that physical and emotional factors may contribute to IOP elevation. Another continually referenced issue is that single IOP measurements reflect IOP only at a given instant, which could alter IOP-related calculations.13 14 28 62 63 Multiple studies report that peak IOPs tend to occur outside of normal office hours, limiting the use of office hour curves.8 36 53 54 64 In fact, Jonas et al37 reviewed 3025 diurnal IOP curves from 1072 eyes with OHT, POAG, preperimetric POAG, NTG and secondary openLeidl MC, et al. Br J Ophthalmol 2014;0:1–5. doi:10.1136/bjophthalmol-2013-303980
angle glaucoma, and found that any single IOP reading taken between 0700 and 2100 had more than a 75% chance of not being the peak IOP for that patient’s 24 h curve. While 24 h IOP monitoring may provide the most accurate measurements, it is often limited by expense and inconvenience.62 64 It is also unclear how such sampling impacts IOP, as the very process of remaining in a hospital for testing may alter an individual’s IOP curve.35 Additionally, Bagga et al65 point out that such studies assume that waking patients up in the middle of the night for measurements has no impact on IOP, which is likely an oversimplification. It has also been questioned whether or not patterns in IOP fluctuation remain stable from 1 day to the next, or between fellow eyes. Wilensky determined that 81% of controls had the same diurnal IOP pattern in each eye, compared to 58% of those with OHT and 53% of those with OAG.66 Realini et al67 68 found that healthy subjects and those with POAG show fair to good agreement in terms of individual IOP values at a given time on different days 1 week apart, but have poor agreement as regards the change in IOP between the different days. Hatanaka et al69 report that IOP in eyes with untreated OAG and OHT measured from 08:00 to 16:00 over two consecutive days showed a repeatable pattern. Early results with continuous IOP sensors suggest fair to good IOP correlation over different days and between fellow eyes in healthy, young patients,70 and repeatable nocturnal, but not daytime, IOP peaks in patients with POAG.71 Conversely, a study of patients with POAG or OHT found IOP at the same time on different days to have a range of ±14.9 to ±20.5% pretreatment and ±21.2 to ±23.1% post-treatment.72
FUTURE OF IOP ANALYSIS In light of these differing conclusions regarding IOP fluctuation, a reliable method to measure the 24 h IOP curve is paramount. Fogagnolo et al64 have used regression analysis to predict diurnal IOP based on seated and supine measurements every 3 h in three populations (healthy, young and healthy, elderly patients, and patients with POAG). Based on mathematical analysis, they determined that even by their best estimate of a 24 h IOP curve, values were incorrect in 40% of healthy, young patients, 5% of healthy, elderly patients, and 20% of those with POAG. They concluded that seated IOP alone is inadequate for providing information about peak and mean IOP, and IOP fluctuation. Bagga et al65 assert that a telemetric device must be created to measure IOP throughout the night if we are to truly understand IOP variation. There have been several animal studies on the use of surface and implantable IOP monitors, suggesting they may be safe and accurate.73–78 Authors have also begun reporting promising results in human studies of contact lens-based IOP sensors.55 70 71 76 79 80 Potential limitations of this technology that must be addressed include: user discomfort; effects on visual acuity; power supply to allow for IOP monitoring over several days or months; and a continued reliance on measurements inferred in reference to corneal properties as opposed to a true measure of ocular tension.
CONCLUSION In spite of the uncertainties and inconsistencies surrounding IOP fluctuation, short-term and long-term measurements are worth considering as potential factors in disease progression. A reliable method of continuous measurement is a sine qua non for studying the influence of IOP fluctuation on glaucoma 3
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Review progression. Such a device should achieve as many of the following goals as possible: be safe and biocompatible; provide accurate, reproducible measurements over a prolonged period of time; measure IOP as frequently as possible; function independently of ocular health and/or corneal properties; be directly correlated with currently validated IOP measurement devices; and allow ambulatory measurements by the patient. Until such a tonometer is available, it is likely that a true understanding of IOP fluctuation will remain elusive.
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Method of literature search In preparation for this review article, we conducted a comprehensive search of ophthalmology literature published between 1960 and 2013 using the following search terms: intraocular pressure; intraocular pressure fluctuation; intraocular pressure variation; diurnal intraocular pressure; significance of intraocular pressure fluctuation; diurnal intraocular pressure fluctuation importance of intraocular pressure fluctuation. Targeted searches were also performed for selected papers noted in the bibliographies of articles found with the above search terms, or which came recommended from other sources. Contributors SAM developed the idea for this review paper and oversaw its writing, editing, and submission. SAM is also the guarantor of this article. CJC and ZAS reviewed and edited the article. They also made contributions to further clarify several key points in the paper. MCL conducted the initial literature search and composed the manuscript.
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Competing interests None. Provenance and peer review Not commissioned; externally peer reviewed.
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Barkana Y, Anis S, Liebmann J, et al. Clinical utility of intraocular pressure monitoring outside of normal office hours in patients with glaucoma. Arch Ophthalmol 2006;124:793–7. Drance SM. Diurnal variation of intraocular pressure in treated glaucoma: significance in patients with chronic simple glaucoma. Arch Ophthalmol 1963;70:302–11. Fogagnolo P, Orzalesi N, Ferreras A, et al. The circadian curve of intraocular pressure: can we estimate its characteristics during office hours? Invest Ophthalmol Vis Sci 2009;50:2209–15. Bagga H, Liu JH, Weinreb RN. Intraocular pressure measurements throughout the 24 h. Curr Opin Ophthalmol 2009;20:79–83. Wilensky JT. Diurnal variations in intraocular pressure. Trans Am Ophthalmol Soc 1991;89:757–90. Realini T, Weinreb RN, Wisniewski S. Short-term repeatability of diurnal intraocular pressure patterns in glaucomatous individuals. Ophthalmology 2011;118:47–51. Realini T, Weinreb RN, Wisniewski SR. Diurnal intraocular pressure patterns are not repeatable in the short term in healthy individuals. Ophthalmology 2010;117:1700–4. Hatanaka M, Babic M, Susanna Junior R. Twenty-four-hour repeatability of diurnal intraocular pressure patterns in glaucomatous and ocular hypertensive individuals. Clinics (Sao Paulo) 2011;66:1235–6. Mottet B, Aptel F, Romanet JP, et al. 24-Hour intraocular pressure rhythm in young healthy subjects evaluated with continuous monitoring using a contact lens sensor. JAMA Ophthalmol 2013;131:1507–16. Mansouri K, Liu JH, Weinreb RN, et al. Analysis of continuous 24-hour intraocular pressure patterns in glaucoma. Invest Ophthalmol Vis Sci 2013;53:8050–6. Rotchford AP, Uppal S, Lakshmanan A, et al. Day-to-day variability in intraocular pressure in glaucoma and ocular hypertension. Br J Ophthalmol 2012;96:967–70. Akaishi T, Ishida N, Shimazaki A, et al. Continuous monitoring of circadian variations in intraocular pressure by telemetry system throughout a 12-week treatment with timolol maleate in rabbits. J Ocul Pharmacol Ther 2005;21:436–44. McLaren JW, Brubaker RF, FitzSimon JS. Continuous measurement of intraocular pressure in rabbits by telemetry. Invest Ophthalmol Vis Sci 1996;37:966–75. Schnell CR, Debon C, Percicot CL. Measurement of intraocular pressure by telemetry in conscious, unrestrained rabbits. Invest Ophthalmol Vis Sci 1996;37:958–65. Sánchez I, Laukhin V, Moya A, et al. Prototype of a nanostructured sensing contact lens for noninvasive intraocular pressure monitoring. Invest Ophthalmol Vis Sci 2011;52:8310–15. Todani A, Behlau I, Fava MA, et al. Intraocular pressure measurement by radio wave telemetry. Invest Ophthalmol Vis Sci 2011;52:9573–80. Downs JC, Burgoyne CF, Seigfreid WP, et al. 24-hour IOP telemetry in the nonhuman primate: implant system performance and initial characterization of IOP at multiple timescales. Invest Ophthalmol Vis Sci 2011;52:7365–75. Pajic B, Pajic-Eggspuchler B, Haefliger I. Continuous IOP fluctuation recording in normal tension glaucoma patients. Curr Eye Res 2011;36:1129–38. Lorenz K, Korb C, Herzog N, et al. Tolerability of 24-hour intraocular pressure monitoring of a pressure-sensitive contact lens. J Glaucoma 2013;22:311–16.
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Intraocular pressure fluctuation and glaucoma progression: what do we know? Matthew C Leidl, Catherine J Choi, Zeba A Syed, et al. Br J Ophthalmol published online March 13, 2014
doi: 10.1136/bjophthalmol-2013-303980
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References
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BJO Online First, published on March 13, 2014 as 10.1136/bjophthalmol-2013-303980 Review
Intraocular pressure fluctuation and glaucoma progression: what do we know? Matthew C Leidl,1 Catherine J Choi,2 Zeba A Syed,3 Samir A Melki2,3,4,5 1
Nassau University Medical Center, East Meadow, New York, USA 2 Massachusetts Eye & Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA 3 Harvard Medical School, Boston, Massachusetts, USA 4 Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA 5 Boston Eye Group, Boston, Massachusetts, USA Correspondence to Dr Samir Melki, Boston Eye Group, 1101 Beacon Street, Brookline, MA 02446, USA; [email protected] Received 8 July 2013 Revised 11 November 2013 Accepted 17 February 2014
ABSTRACT While mean intraocular pressure (IOP) has long been known to correlate with glaucomatous damage, the role of IOP fluctuation is less clearly defined. There is extensive evidence in the literature for and against the value of short-term and long-term IOP fluctuation in the evaluation and prognosis of patients with glaucoma. We present here the arguments made by both sides, as well as a discussion of the pitfalls of prior research and potential directions for future studies. Until a reliable method is developed that allows for constant IOP monitoring, many variables will continue to hinder us from drawing adequate conclusions regarding the significance of IOP variation. INTRODUCTION Intraocular pressure (IOP) is a significant factor in the diagnosis and management of glaucomatous disease. There is a well-established link between elevations in IOP and visual field (VF) deterioration, and lowering IOP may both slow this progression.1–4 and improve the appearance of glaucomatous optic discs.5 6 There are numerous methods for monitoring IOP, though the Goldmann applanation tonometer is likely the most frequently used. The device measures the amount of force required to flatten a section of the cornea, thereby indirectly calculating the IOP.7 A more in-depth discussion of tonometry is beyond the scope of this paper, though Stamper provides an excellent, highly recommended discussion of the topic. Studies show that IOP tends to fluctuate throughout the day and over longer intervals.8–12 It has been difficult to determine the significance of these variations due to a lack of standardisation in the time between assessments, the method of measurement, and the definition of fluctuation itself.10 13 Nonetheless, many important findings have been made, as discussed below.
LONG-TERM IOP FLUCTUATION The definition of long-term IOP fluctuation varies across studies. One definition refers to the difference between the highest and lowest IOP values over a given period, with measurements occurring on different days.14 Alternatively, numerous studies define IOP fluctuation as the SD in IOP over a given time.1 2 11 13 15–22 To cite: Leidl MC, Choi CJ, Syed ZA, et al. Br J Ophthalmol Published Online First: [ please include Day Month Year] doi:10.1136/bjophthalmol2013-303980
Studies that argue that long-term IOP fluctuation is significant
Several studies suggest that long-term IOP fluctuation is an important prognostic indicator for glaucomatous damage. Hong et al16 reviewed 408 eyes
Leidl MC, et al. Br JArticle Ophthalmolauthor 2014;0:1–5. Copyright (ordoi:10.1136/bjophthalmol-2013-303980 their employer) 2014. Produced
with either primary open-angle glaucoma (POAG) or chronic primary angle-closure glaucoma (PACG), all of which had an IOP less than 18 mm Hg following phacoemulsification, posterior chamber intraocular lens implantation, and trabeculectomy. Over at least 3 years of follow-up, the authors found that, of patients with a SD in IOP greater than 2 mm Hg, 30% of those with POAG and 28.6% of those with chronic PACG demonstrated VF loss, compared to 9.7% and 10%, respectively, of those patients with SD in IOP not exceeding 2 mm Hg. Notably, the mean IOP between the two groups of patients was not significantly different, suggesting that long-term IOP fluctuation is associated with VF loss rather than the absolute value at any given time. Hong et al15 later studied 688 eyes in patients with POAG or chronic PACG who had undergone phacoemulsification after trabeculectomy. They found that after 3 years of follow-up, patients with POAG and an IOP SD greater than 2 mm Hg after surgery had a markedly worse mean VF deviation than did patients with an IOP SD of no more than 2 mm Hg. Fukuchi et al22 similarly found that patients with normal tension glaucoma (NTG) designated as fast progressors based on VF had a higher SD and range in follow-up IOP compared to slow progressors, They found no such correlation for patients with open-angle glaucoma (OAG). A cohort from the Advanced Glaucoma Intervention Study included 509 eyes with refractory OAG not well controlled with medication.11 The authors found that for each 1 mm Hg increase in IOP fluctuation (SD in IOP), the odds of VF progression increased by about 30%. Eyes with IOP fluctuation of 3 mm Hg or more demonstrated greater VF deterioration than those with fluctuation less than 3 mm Hg. Rao et al20 report similar results in a large, retrospective analysis of patients with treated POAG or PACG. They found that of mean IOP, peak IOP and IOP fluctuation (SD in IOP over several follow-up visits), peak IOP and IOP fluctuation were significantly associated with disease progression in univariate analysis, while only IOP fluctuation remained significantly associated in multivariate analysis. They note that for each 1 mm Hg increase in IOP fluctuation, progression worsened by 0.35% per year. Lee et al17 performed a multicentre, retrospective chart review of 151 patients with POAG, ocular hypertension (OHT), NTG, or findings suspicious for glaucoma. They found that IOP SD was significantly associated with progression—each 1 mm Hg increase in SD increased the risk for glaucoma progression by a factor of 4.2 in patients with measurements before disease worsening or treatment initiation.
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Review Studies that argue that long-term IOP fluctuation is not significant A number of studies have reported that long-term IOP fluctuation has no role in ocular disease. A randomised cohort from the Early Manifest Glaucoma Trial consisting of 129 treated and 126 control patients with glaucoma found a non-significant, positive correlation between time to progression of disease and IOP SD, while mean IOP, had a significant, negative correlation.1 Additionally, a retrospective cohort study of patients from the Glaucoma Progression Study followed 587 eyes with various subtypes of glaucoma.2 Multivariate analysis determined that peak IOP, but not SD in IOP, was associated with glaucoma progression. Medeiros et al18 found comparable results in their study of 252 eyes in 126 patients with untreated OHT. They noted a significant, positive correlation between mean IOP and SD in IOP, but that IOP fluctuation was not a significant marker for progression to glaucoma in either univariate or multivariate analysis, while mean IOP was. Fogagnolo et al19 analysed IOP fluctuation in 52 patients with treated POAG, of whom 28 progressed during the study period. Over four follow-up visits, each 6 months apart, the authors found no significant difference in either short-term or long-term IOP fluctuation between patients who progressed and those who remained stable. Lee et al21 found comparable results in patients with NTG and at least 5 years of follow-up, reporting no significant association between SD in IOP and VF progression in univariate or multivariate analysis. Bengtsson and Heijl studied a cohort of 90 patients from the Malmö Ocular Hypertension Study, which prospectively followed patients with normal VFs and an IOP of at least 22 mm Hg.23 They defined IOP variation using several parameters including: variation in measurements obtained at 0800, 1130 and 1530; the maximum range from a series of diurnal curves; and the difference between highest and lowest IOP throughout the entire study period (mean follow-up of 8.5 years). They found that IOP fluctuation defined in each of these manners was not an independent risk factor for glaucoma development in patients with high-risk OHT. Finally, Realini et al24 conducted a chart review with the primary goal of checking for asymmetry in IOP fluctuation between fellow eyes. With a minimum of 1 year of follow-up, they found that IOP fluctuation between fellow eyes did not vary significantly between healthy patients and those with glaucoma.
SHORT-TERM IOP FLUCTUATION As with long-term IOP fluctuation, there is no consensus on how to define short-term IOP fluctuation. One commonly used definition applied by Lee et al10 defines it as the difference between the highest and lowest IOP over 24 h or less, though the SD in IOP based on a curve has also been advocated.19 Most studies of repeated IOP measurements throughout the day have determined that values tend to peak early in the morning and decline over the course of the day, though the exact timing of peaks and nadirs is not entirely uniform across reports.9 12 25–37
Studies that argue that short-term IOP fluctuation is significant Numerous reports demonstrate a correlation between increased short-term IOP fluctuation and pressure-related eye diseases. David et al28 assessed 690 IOP curves made from four to six 2
measurements over the course of 10.5 h, and found that the difference in mean IOP peak and trough differed significantly between healthy eyes (5 mm Hg), eyes with OAG and chronic angle-closure glaucoma (ACG) (5.8 mm Hg), and eyes with OHT (6.8 mm Hg). A more recent study also showed that IOP fluctuation is significantly higher in eyes with primary chronic ACG (7.69±3.03 mm Hg) or POAG (8.31±2.58 mm Hg) compared to normal eyes (4.83±2.46 mm Hg).38 Similarly, Grippo et al39 followed the protocol of prior works and combined results to determine that daytime IOP variation—though not nighttime variation—was significantly greater in subjects with OHT and glaucoma than healthy individuals. Baskaran et al40 determined that the difference between the peak and trough IOP in patients with primary angle closure (PAC) and PACG was significantly greater than that in PAC suspects and controls. Further, Kim et al41 noted that during waking hours, patients with NTG had a significantly greater degree of IOP fluctuation than controls. Tajunisah et al42 reported similar results in a study of glaucoma suspects, noting that the mean magnitude in IOP variation for patients with POAG, NTG, glaucoma suspicion and OHT was significantly higher than that for controls. Saccà et al43 note that patients with POAG had a greater relative daily IOP fluctuation (7–9.6%) than patients with NTG (−4.7–6.4%) or healthy eyes (−3.4–6.9%). Twenty-three patients of a cohort of 29 with OHT were available for final analysis in a 5-year follow-up study of IOP by Thomas et al,44 which found that four patients had progressed to glaucoma. Diurnal IOP profiles of these patients with readings taken every 2 h from 10:00 to 18:00 determined that the mean IOP variation was 8.6 mm Hg in the patients who progressed, compared to 5.4 mm Hg in those who did not. One study used frequency doubling technology (FDT) perimetry to study 33 eyes with OHT while measuring IOP at 0830, 1030 and 1530.45 The authors discovered that office IOP fluctuation was significantly greater in patients with abnormal FDT perimetry results (median 5 mm Hg) compared to those with normal FDT perimetry results (median 2 mm Hg). Office IOP fluctuation was also correlated with the number of depressed points on FDT perimetry. Similarly, Sakata et al46 shows that 24 h IOP fluctuation in the habitual position in patients with NTG had a significant, negative correlation with mean VF deviation. Analysis of daytime IOP curves from 149 patients with OHT found that 33 of the eyes studied had a difference of more than 5 mm Hg between the peak and trough IOP in their diurnal curve.47 Of these, 64% had VF defects within 4 years. By contrast, of those eyes with a fluctuation in IOP not exceeding 5 mm Hg, 84% had normal VFs after at least 5 years; these differences were significant. In a prospective study, Asrani et al48 reported on 105 eyes from 64 patients with OAG who were monitored via VF and home tonometry five times daily. Patients in the highest quartile of home IOP range (at least 11.8 mm Hg) had a cumulative risk of VF progression of 88% over 8 years, compared to 57% for patients in the lowest quartile for IOP range (no more than 7.7 mm Hg). A study of 3561 IOP profiles from 720 patients performed by Jonas et al49 analysed patients with healthy eyes, ocular HTN, preperimetric glaucoma ( patients with normal VF data, but a glaucomatous-appearing optic nerve), POAG, secondary OAG and NTG. The authors found that mean IOP fluctuation was significantly greater in patients with OHT, preperimetric glaucoma, or secondary OAG as compared with healthy eyes. Interestingly, there was no significant difference in mean IOP Leidl MC, et al. Br J Ophthalmol 2014;0:1–5. doi:10.1136/bjophthalmol-2013-303980
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Review fluctuation in those with perimetric POAG compared to those with preperimetric glaucoma, OHT, or normal eyes. Moreover, eyes with NTG had no significant difference in IOP fluctuation compared to healthy eyes, but a significantly lower IOP fluctuation than eyes with OHT or preperimetric glaucoma. By contrast, Jonas et al50 studied 855 eyes with NTG or POAG by monitoring IOP at 1700, 2100, 0000, 0700 and 1200. Here, 163 eyes were noted to have glaucoma progression, which were analysed to reveal that in eyes with NTG, there was a significant, negative association between glaucoma progression and IOP amplitude.
Studies that argue that short-term IOP fluctuation is not significant Several reports suggest that short-term IOP fluctuations may not be significant. Sung et al51 examined 24 h IOP and VF data over approximately 6 years in patients with newly diagnosed NTG. Univariate analysis showed no correlation between VF progression and either 24 h or follow-up IOP fluctuation, among other findings. Similarly, Lee et al36 monitored diurnal IOP in 177 patients with NTG. In univariate and multivariate analysis, the authors found no significant correlation between IOP fluctuation and either pattern standard or mean deviation on VF. Additionally, a series of 14 patients with newly diagnosed, untreated POAG, by Sehi et al52 found no significant association between diurnal changes in IOP and optic nerve head appearance. Likewise, Wang et al53 state that they found no significant association between 24 h IOP fluctuation and mean VF deviation in patients with POAG. Further, in patients with unilateral POAG, they found no difference in SD of diurnal IOP variation or IOP fluctuation between fellow eyes. As indicated above, in their analysis of patients with POAG, Jonas et al50 found no association between glaucoma progression and IOP amplitude. They also reported no significant association between IOP fluctuation and glaucoma progression in an analysis of patients with NTG and POAG as a single group. Also alluded to previously, Fogagnolo et al19 found no significant difference between patients with POAG who progressed and those who remained stable in regard to short-term IOP fluctuation. Finally, Smith measured IOP every 2 h from 0500 to 1500 and attained VFs in patients with OHT, suspected glaucoma and glaucoma.54 Analysis found mean diurnal IOP variation in 400 eyes with VF defects was not significantly different compared to 400 eyes without VF defects.
PROBLEMS WITH IOP ANALYSIS In addition to the aforementioned lack of standardised definitions for IOP fluctuation, many other problems are present in these analyses. First, there are numerous factors that may transiently influence IOP, including the Valsalva manoeuvre, eye squeezing, tear film deficiencies, astigmatism and eyelid closure.55–57 IOP has also been shown to increase as patients move from seated to supine positions,58–60 and following Humphrey VF analysis61 suggesting that physical and emotional factors may contribute to IOP elevation. Another continually referenced issue is that single IOP measurements reflect IOP only at a given instant, which could alter IOP-related calculations.13 14 28 62 63 Multiple studies report that peak IOPs tend to occur outside of normal office hours, limiting the use of office hour curves.8 36 53 54 64 In fact, Jonas et al37 reviewed 3025 diurnal IOP curves from 1072 eyes with OHT, POAG, preperimetric POAG, NTG and secondary openLeidl MC, et al. Br J Ophthalmol 2014;0:1–5. doi:10.1136/bjophthalmol-2013-303980
angle glaucoma, and found that any single IOP reading taken between 0700 and 2100 had more than a 75% chance of not being the peak IOP for that patient’s 24 h curve. While 24 h IOP monitoring may provide the most accurate measurements, it is often limited by expense and inconvenience.62 64 It is also unclear how such sampling impacts IOP, as the very process of remaining in a hospital for testing may alter an individual’s IOP curve.35 Additionally, Bagga et al65 point out that such studies assume that waking patients up in the middle of the night for measurements has no impact on IOP, which is likely an oversimplification. It has also been questioned whether or not patterns in IOP fluctuation remain stable from 1 day to the next, or between fellow eyes. Wilensky determined that 81% of controls had the same diurnal IOP pattern in each eye, compared to 58% of those with OHT and 53% of those with OAG.66 Realini et al67 68 found that healthy subjects and those with POAG show fair to good agreement in terms of individual IOP values at a given time on different days 1 week apart, but have poor agreement as regards the change in IOP between the different days. Hatanaka et al69 report that IOP in eyes with untreated OAG and OHT measured from 08:00 to 16:00 over two consecutive days showed a repeatable pattern. Early results with continuous IOP sensors suggest fair to good IOP correlation over different days and between fellow eyes in healthy, young patients,70 and repeatable nocturnal, but not daytime, IOP peaks in patients with POAG.71 Conversely, a study of patients with POAG or OHT found IOP at the same time on different days to have a range of ±14.9 to ±20.5% pretreatment and ±21.2 to ±23.1% post-treatment.72
FUTURE OF IOP ANALYSIS In light of these differing conclusions regarding IOP fluctuation, a reliable method to measure the 24 h IOP curve is paramount. Fogagnolo et al64 have used regression analysis to predict diurnal IOP based on seated and supine measurements every 3 h in three populations (healthy, young and healthy, elderly patients, and patients with POAG). Based on mathematical analysis, they determined that even by their best estimate of a 24 h IOP curve, values were incorrect in 40% of healthy, young patients, 5% of healthy, elderly patients, and 20% of those with POAG. They concluded that seated IOP alone is inadequate for providing information about peak and mean IOP, and IOP fluctuation. Bagga et al65 assert that a telemetric device must be created to measure IOP throughout the night if we are to truly understand IOP variation. There have been several animal studies on the use of surface and implantable IOP monitors, suggesting they may be safe and accurate.73–78 Authors have also begun reporting promising results in human studies of contact lens-based IOP sensors.55 70 71 76 79 80 Potential limitations of this technology that must be addressed include: user discomfort; effects on visual acuity; power supply to allow for IOP monitoring over several days or months; and a continued reliance on measurements inferred in reference to corneal properties as opposed to a true measure of ocular tension.
CONCLUSION In spite of the uncertainties and inconsistencies surrounding IOP fluctuation, short-term and long-term measurements are worth considering as potential factors in disease progression. A reliable method of continuous measurement is a sine qua non for studying the influence of IOP fluctuation on glaucoma 3
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Review progression. Such a device should achieve as many of the following goals as possible: be safe and biocompatible; provide accurate, reproducible measurements over a prolonged period of time; measure IOP as frequently as possible; function independently of ocular health and/or corneal properties; be directly correlated with currently validated IOP measurement devices; and allow ambulatory measurements by the patient. Until such a tonometer is available, it is likely that a true understanding of IOP fluctuation will remain elusive.
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Method of literature search In preparation for this review article, we conducted a comprehensive search of ophthalmology literature published between 1960 and 2013 using the following search terms: intraocular pressure; intraocular pressure fluctuation; intraocular pressure variation; diurnal intraocular pressure; significance of intraocular pressure fluctuation; diurnal intraocular pressure fluctuation importance of intraocular pressure fluctuation. Targeted searches were also performed for selected papers noted in the bibliographies of articles found with the above search terms, or which came recommended from other sources. Contributors SAM developed the idea for this review paper and oversaw its writing, editing, and submission. SAM is also the guarantor of this article. CJC and ZAS reviewed and edited the article. They also made contributions to further clarify several key points in the paper. MCL conducted the initial literature search and composed the manuscript.
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Competing interests None. Provenance and peer review Not commissioned; externally peer reviewed.
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Intraocular pressure fluctuation and glaucoma progression: what do we know? Matthew C Leidl, Catherine J Choi, Zeba A Syed, et al. Br J Ophthalmol published online March 13, 2014
doi: 10.1136/bjophthalmol-2013-303980
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References
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