To determine the association between myopia and open-angle glaucoma.
Systematic review and meta-analysis of observational studies.
Thirteen studies involving 48 161 individuals.
Articles published ...between 1994 and 2010 were identified in PubMed, Embase, and reference lists. Study-specific odds ratios (ORs) were pooled using a random effects model.
Odds ratios with 95% confidence intervals (CIs) of myopia as a risk factor for open-angle glaucoma.
Data from 11 population-based cross-sectional studies were included in the main analyses. The pooled OR of the association between myopia and glaucoma based on 11 risk estimates was 1.92 (95% CI, 1.54-2.38). On the basis of 7 risk estimates, the pooled ORs of the associations between low myopia (myopia up to -3 D) and glaucoma and between high myopia (≤-3 D myopic) and glaucoma were 1.65 (1.26-2.17) and 2.46 (1.93-3.15), respectively. There was considerable heterogeneity among studies that reported an association between any myopia and glaucoma (I(2)=53%) and low myopia and glaucoma (I(2)=29%), but not for high myopia and glaucoma (I(2)=0%). After omitting studies that contributed significantly to the heterogeneity, the pooled ORs were 1.88 (1.60-2.20) for any myopia and glaucoma and 1.77 (1.41-2.23) for low myopia and glaucoma.
Individuals with myopia have an increased risk of developing open-angle glaucoma.
The author(s) have no proprietary or commercial interest in any materials discussed in this article.
PurposeWe wanted to investigate the association of blood pressure (BP) status with the ganglion cell-inner plexiform layer (GCIPL) and retinal nerve fiber layer (RNFL) thickness of nonglaucomatous ...eyes and to elucidate whether this effect is related to vascular metrics proxying retinal perfusion. MethodsFor this case-control study, we prospectively included 96 eyes of 96 healthy subjects (age 50-65) from a large-scale population-based cohort in the northern Netherlands (n = 167,000) and allocated them to four groups (low BP, normal BP controls, treated arterial hypertension AHT, untreated AHT). We measured macular GCIPL and RNFL (mRNFL) and peripapillary RNFL (pRNFL) thicknesses with optical coherence tomography (OCT). We estimated retinal blood flow (RBF), retinal vascular resistance (RVR), and autoregulatory reserve (AR) from quantitative OCT-angiography, fundus imaging, BP, and intraocular pressure. We compared structural and vascular metrics across groups and performed mediation analysis. ResultsCompared to controls, GCIPL was thinner in the low BP group (P = 0.013), treated hypertensives (P = 0.007), and untreated hypertensives (P = 0.007). Treated hypertensives exhibited the thinnest mRNFL (P = 0.001), temporal pRNFL (P = 0.045), and inferior pRNFL (P = 0.034). The association of GCIPL thickness with BP was mediated by RBF within the combined low BP group and controls (P = 0.003), by RVR and AR within the combined treated hypertensives and controls (P = 0.001, P = 0.032), and by RVR within the combined untreated antihypertensives and controls (P = 0.022). ConclusionsInner retinal thinning was associated with both tails of the BP distribution and with ineffective autoregulation. Longitudinal studies could clarify whether these defects can explain the reported glaucomatous predisposition of these population groups.
Patients with Parkinson's disease experience visual symptoms, partially originating from retinal changes. Since 2011, multiple case-control studies using spectral-domain OCT, which allows for ...studying individual retinal layers, have been published. The aim of this study was to substantiate the occurrence, extent, and location of retinal degeneration in Parkinson's by meta-analysis.
Spectral-domain OCT case-control data were collected by performing a search in PubMed and Embase with terms: “optical coherence tomography” and “parkinson”, up to November 5th, 2018. Studies with fewer than 10 patients or controls were excluded. We performed a random effects meta-analysis. Heterogeneity was evaluated with I2 statistics; publication bias with Egger's and Begg's tests.
Out of 77 identified studies, 36 were included, totaling 1916 patients and 2006 controls. A significant thinning of the peripapillary retinal nerve fiber layer (d = −0.42; 95% confidence interval −0.54 to −0.29) and the combined ganglion cell and inner plexiform layers (d = −0.40; −0.72, to −0.07) was found. The inner nuclear layer and outer plexiform layer did not show significant changes. Heterogeneity ranged from 3 to 92%; no publication bias was found.
Parkinson's patients show significant thinning of the inner retinal layers, resembling changes found in glaucoma and other neurodegenerative diseases like Alzheimer's. Study of different cell layers in-vivo is possible by moving from time-to spectral domain OCT. Retinal degeneration may be affiliated with neurodegenerative pathology overall, and could serve as a biomarker in neurodegenerative disorders. Longitudinal research including clinical correlations is needed to determine usefulness in Parkinson's disease.
•Retinal cell layers are thinner in Parkinson's compared to healthy controls, overall.•The retinal nerve fiber layer, ganglion cells and inner plexiform layer are thinner.•The inner nuclear layer and outer plexiform layer showed no difference.•The peripapillary nasal sector appears to be less affected compared to other sectors.•The macula is thinner, however the fovea appears to be less affected.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this study, we mathematically predict retinal vascular resistance (RVR) and retinal blood flow (RBF), we test predictions using laser speckle flowgraphy (LSFG), we estimate the range of vascular ...autoregulation, and we examine the relationship of RBF with the retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC). Fundus, optical coherence tomography (OCT), and OCT-angiography images, systolic/diastolic blood pressure (SBP/DBP), and intraocular pressure (IOP) measurements were obtained from 36 human subjects. We modeled two circulation markers (RVR and RBF) and estimated individualized lower/higher autoregulation limits (LARL/HARL), using retinal vessel calibers, fractal dimension, perfusion pressure, and population-based hematocrit values. Quantitative LSFG waveforms were extracted from vessels of the same eyes, before and during IOP elevation. LSFG metrics explained most variance in RVR (
= 0.77/
= 6.9·10
) and RBF (
= 0.65/
= 1.0·10
), suggesting that the markers strongly reflect blood flow physiology. Higher RBF was associated with thicker RNFL (
= 4.0·10
) and GCC (
= 0.003), thus also verifying agreement with structural measurements. LARL was at SBP/DBP of 105/65 mmHg for the average subject without arterial hypertension and at 115/75 mmHg for the average hypertensive subject. Moreover, during IOP elevation, changes in RBF were more pronounced than changes in RVR. These observations physiologically imply that healthy subjects are already close to LARL, thus prone to hypoperfusion. In conclusion, we modeled two clinical markers and described a novel method to predict individualized autoregulation limits. These findings could improve understanding of retinal perfusion and pave the way for personalized intervention decisions, when treating patients with coexisting ophthalmic and cardiovascular pathologies.
We describe and test a new approach to quantify retinal blood flow, based on standard clinical examinations and imaging techniques, linked together with a physiological model. We use these findings to generate individualized estimates of the autoregulation range. We provide evidence that healthy subjects are closer to the lower autoregulation limit than thought before. This suggests that some retinas are less prepared to withstand hypoperfusion, even after small intraocular pressure rises or blood pressure drops.
Glaucoma in myopia: diagnostic dilemmas Tan, Nicholas Y Q; Sng, Chelvin C A; Jonas, Jost B ...
British journal of ophthalmology,
10/2019, Volume:
103, Issue:
10
Journal Article
Peer reviewed
Open access
Myopic eyes have an increased risk of glaucoma. However, glaucomatous changes in a myopic eye are often difficult to detect. Classic structural and functional investigations to diagnose glaucoma may ...be confounded by myopia. Here, we identify some of the common pitfalls in interpreting these structural parameters, and the possible solutions that could be taken to overcome them. For instance, in myopic eyes, we discuss the limitations and potential sources of error when using neuroretinal rim parameters, and retinal nerve fibre layer and ganglion cell-inner plexiform layer thickness measurements. In addition, we also review new developments and potential adjuncts in structural imaging such as the assessment of the retinal nerve fibre layer texture, and the examination of the microcirculation of the optic nerve head using optical coherence tomography angiography. For the functional assessment of glaucoma, we discuss perimetric strategies that may aid in detecting characteristic visual field defects in myopic glaucoma. Ultimately, the evaluation of glaucoma in myopia requires a multimodal approach, to allow correlation between structural and functional assessments. This review provides overview on how to navigate this diagnostic dilemma.
Purpose
OCT can be used for glaucoma assessment, but its usefulness may depend on image quality, disease stage and segmentation algorithm. We aimed to determine how layer thicknesses as assessed with ...different algorithms depend on image quality and disease stage, how reproducible the algorithms are, and if the algorithms (dis)agree.
Methods
Optic disc OCT data (Canon OCT‐HS100) from 20 healthy subjects and 28 early, 29 moderate, and 23 severe glaucoma patients were assessed with four different algorithms (CANON, IOWA, FWHM, DOCTRAP). We measured retinal nerve fibre layer thickness (RNFLT) and total retinal thickness (TRT) along the 1.7‐mm‐radius OCT measurement circle centred at the optic disc. In healthy subjects, image quality was degraded with neutral density filters (0.3–0.9 optical density OD); three scans were made to assess repeatability. Results were analysed with ANOVA with Bonferroni corrected t‐tests for post hoc analysis and with intraclass correlation coefficient (ICC) analysis.
Results
For all algorithms, RNFLT was more sensitive to image quality than TRT. Both RNFLT and TRT showed differences between healthy and glaucoma (all algorithms p < 0.001 for both RNFLT and TRT) and between early and moderate glaucoma (RNFLT: p = 0.001 to p = 0.09; TRT: p < 0.001 to p = 0.03); neither was able to discriminate between moderate and severe glaucoma (p = 0.08 to p = 1.0). Generally, repeatability was excellent (ICC >0.75); agreement between algorithms varied from moderate to excellent.
Conclusions
OCT becomes less informative with glaucoma progression, irrespective of the algorithm. For good‐quality scans, RNFLT and TRT perform similarly; TRT may be advantageous with poor image quality.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
The alternative mechanical theory of glaucoma, in which an increased pressure difference across the lamina cribrosa (difference between intraocular and intracranial pressure; IOP and ICP), rather ...than solely an elevated IOP, leads to structural and functional vision loss, is still controversial. If the theory is true, a drug that simultaneously lowers both the IOP and ICP may be ineffective. The aim of this study was to determine how acetazolamide (AAZ; a drug prescribed in glaucoma that aims to lower the IOP) affects both IOP and ICP in glaucoma patients and to compare the magnitude and time course of the induced pressure changes with those of healthy subjects not taking AAZ. IOP and noninvasive ICP (measured through emissions from the ear) were measured in 20 glaucoma patients taking 125 mg of AAZ twice daily. Measurements were taken for 30 minutes before taking the drug and for 2 hours post-ingestion. Comparisons were made with 13 age-similar controls. After 12 hours with no anti-glaucoma medication, AAZ did not further reduce IOP in glaucoma patients compared to controls (P = 0.58) but did reduce ICP compared to controls (P = 0.035), by approximately 4 mmHg. Our findings suggest that there are periods during the day when the pressure difference across the lamina cribrosa is larger in case of AAZ use. Future studies should focus on improving the noninvasive ICP testing, different doses and dosing schedules of AAZ, and the time course of IOP in glaucoma patients not taking AAZ.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We investigated relationship of glaucoma with measurements related to autonomic dysfunction, including heart rate variability (HRV) and blood pressure (BP).
Glaucoma was defined using a ...questionnaire-based algorithm for 86,841 LifeLines Cohort Study participants. Baseline HRV (root mean square of successive differences RMSSD) was calculated from resting electrocardiograms; systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) were oscillometric-based measurements. We used a generalized linear mixed model, adjusted for age, age square, sex, body mass index, and familial relationships to assess the relationship of baseline HRV and BP (continuous and quartiles), hypertension, and antihypertensive medication with glaucoma at follow up (median, 3.8 years).
The odds ratio (OR) of glaucoma was 0.95 (95% confidence interval CI, 0.92-0.99) per unit increase in log-transformed RMSSD (in ms), indicating that autonomous dysfunction (low HRV) is associated with a higher risk of glaucoma. Per 10-mm Hg increase in BP, we found ORs of 1.03 (95% CI, 1.01-1.05; P = 0.015) for SBP, 1.01 (95% CI, 0.97-1.05; P = 0.55) for DBP, 1.03 (95% CI, 1.00-1.06; P = 0.083) for MAP, and 1.04 (95% CI, 1.01-1.07; P = 0.006) for PP. The OR for the lowest versus highest RMSSD quartile was 1.15 (95% CI, 1.05-1.27; P = 0.003). The ORs for the highest versus second quartile were 1.09 (95% CI, 0.99-1.19; P = 0.091) for SBP and 1.13 (95% CI, 1.02-1.24; P = 0.015) for PP. Glaucoma was more common among hypertensives (OR, 1.25; 95% CI, 1.16-1.35; P < 0.001); among those using angiotensin-converting enzyme (ACE) inhibitors (OR, 1.35; 95% CI, 1.18-1.55; P < 0.001); and among those using calcium-channel blockers (OR, 1.19; 95% CI, 1.01-1.40; P = 0.039).
Low HRV, high SBP, high PP, and hypertension were associated with glaucoma. Longitudinal studies may elucidate if autonomic dysregulation and high BP also predict glaucoma incidence.
We have systematically extracted all available heritability (h2) estimates of glaucoma and related endophenotypes from the literature and summarized the evidence by meta-analysis. Glaucoma ...endophenotypes were classified into 10 clusters: intraocular pressure, anterior chamber size, central corneal thickness, cup-to-disc ratio, disc size, cup size, corneal hysteresis, retinal nerve fiber layer thickness, cup shape, and peripapillary atrophy. Random-effects meta-analyses were performed for each cluster. For clusters with n ≥ 10 h2 estimates, we also performed subgroup and meta-regression analyses. The literature search yielded 53 studies. The h2 of primary open-angle glaucoma ranged from 0.17 to 0.81, and was 0.65 for primary angle-closure glaucoma in a single study. The pooled endophenotype h2 estimates were intraocular pressure, 0.43 (0.38–0.48); anterior chamber size, 0.67 (0.60–0.74); central corneal thickness, 0.81 (0.73–0.87); cup-to-disc ratio, 0.56 (0.44–0.68); disc size, 0.61 (0.37–0.81); cup size, 0.58 (0.35–0.78); corneal hysteresis, 0.40 (0.29–0.51); retinal nerve fiber layer thickness, 0.73 (0.42–0.91); cup shape, 0.62 (0.22–0.90); and peripapillary atrophy, 0.73 (0.70–0.75). We identified mean age, ethnicity, and study design as major sources of heterogeneity. Our results confirm the strong influence of genetic factors on glaucoma and its endophenotypes. These pooled h2 estimates provide the most accurate assessment to date of the total genetic variation that can ultimately be explained by gene-finding studies.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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