The Distribution of Vertical Cup-To-Disc Ratio and Its Determinants in the Iranian Adult Population

Hashemi, Hassan; Pakzad, Reza; Khabazkhoob, Mehdi; Emamian, Mohammad Hassan; Yekta, Abbasali; Fotouhi, Akbar

doi:10.1016/j.joco.2019.06.002

Cited by 9 publications

(22 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The correlation was thus linear, positive and significant. The relationship between BMI and IOP has been extensively explored and most of the studies similar to our study confirm existence of a significant relationship between BMI and IOP [8][9][10][11][12].…”

Section: Discussionsupporting

confidence: 75%

“…Despite this dissimilarity, the two significant predictors in the present study, SBP and BMI, were found to be predictors of higher IOP in their study. Hashemi, et al [11] in their multivariate model had sex, diabetes, SBP, BMI, education, CCT and myopic shift to be significant independent predictors of IOP. Of all these significant predictors SBP and BMI were observed to be significant predictors of IOP.…”

Section: Discussionmentioning

confidence: 95%

See 1 more Smart Citation

Association of Various Systemic Factors with Intraocular Pressure

Garg¹,

Gupta²,

Yadav³

et al. 2018

Int J Ophthalmol Clin Res

View full text Add to dashboard Cite

Introduction: Raised intraocular pressure (IOP) is the principal modifiable risk factor for the development and progression of glaucoma. Glaucoma is defined as progressive optic neuropathy, based on visual field loss and/ or optic disc findings, is more likely to be associated with elevated intraocular pressure (IOP), although IOP is not the only risk factor for glaucomatous optic nerve damage. The complex physiology involved in aqueous humor formation and its maintenance indicates its dependence on other systemic, physical, physiological and environmental factors, thus effects IOP. The factors studied were age, gender, systemic blood pressure (BP) and body mass index (BMI). Material and method:A cross sectional hospitalbased study was conducted where 800 adults of varying demographic profiles were included with their written and informed consent taken. A detailed history from all the patients including signs and symptoms of glaucoma was taken, demographic and anthropometric details noted. Ocular examination included visual acuity by Snellen's drum, refraction, intraocular pressure (IOP) by Goldman's applanation tonometer, gonioscopy using Zeiss fourmirror lens, visual field changes seen by Humphrey field analyzer (HFA) using 30-2 program (version 40), slit-lamp examination, fundus evaluation by both direct and indirect ophthalmoscopy, and 90D lens. The statistical analysis was done using SPSS (Statistical Package for Social Sciences) Version 15.0 statistical Analysis Software. The values were represented in Number (%) and Mean ± SD.Results: Mean age of patients was 57.21 ± 9.81 years. With increasing age proportion of those with IOP up to 20 mmHg showed a significant incremental trend. It was observed that mean age of subjects having 20-24 mmHg IOP was minimum (54.17 ± 9.26 years) followed by 16 -20 mmHg (56.77 ± 9.61 years), 12 -16 mmHg (58.50 ± 9.73 years), > 24 mmHg (60.20 ± 10.92 years) and < 12 mmHg (61.56 ± 7.54 years). Statistically, this difference was significant (p < 0.001). There was a weak and inverse significant correlation between age and IOP (r =-0.075; p = 0.003). Majority of subjects were females (50.5%). Proportion of those having IOP in ≤ 16 mm range was higher among males (45.7%) as compared to that in females (35.7%). Statistically, this difference was significant (p < 0.001). A weak positive and significant correlation was observed between IOP and BMI. Statistically, the difference in BMI of subjects in different IOP categories was significant (p < 0.001). Difference in mean IOP of normotensive (16.95 ± 3.35 mmHg) and hypertensives (17.11 ± 3.53 mmHg) was not found to be statistically significant. Mean SBP and DBP of subjects with IOP < 12 mmHg, 20 -24 mmHg and > 24 mmHg were found to be significantly higher as compared to those with IOP 16 -20 mmHg and 20 -24 mmHg. Conclusion:The present study shows the association between age, gender, BMI and blood pressure, depicting the multivariable of IOP. Thus, the measurement of IOP is essential in all the patients with variable demographic, anthrop...

show abstract

Section: Discussionsupporting

confidence: 75%

Section: Discussionmentioning

confidence: 95%

Association of Various Systemic Factors with Intraocular Pressure

Garg¹,

Gupta²,

Yadav³

et al. 2018

Int J Ophthalmol Clin Res

View full text Add to dashboard Cite

show abstract

“…Three large population-based studies found lower cup to disc ratio in patients with higher BMI [ 97 – 99 ]. However, none of them included pediatric patients, and two of them included patients older than 40 [ 97 ] and 45 years [ 98 ]. On the other hand, 3/5 of our studies were conducted in children [ 26 , 30 , 31 ] and the other two on adults [ 27 , 28 ] also did not have similar compositions to the population-based studies.…”

Section: Discussionmentioning

confidence: 99%

Spectral-domain OCT measurements in obesity: A systematic review and meta-analysis

2022

View full text Add to dashboard Cite

Background Previous studies proposed possible applications of spectral-domain optical coherence tomography (SD-OCT) measurements in prognosticating pathologies observed in overweight/obesity, including ocular, vascular, and neurologic consequences. Therefore, we conducted a systematic review and meta-analysis to investigate the changes in the in SD-OCT measurements of the patients with higher body mass index (BMI) compared to normal weight individuals. Materials and methods We conducted a systematic search on PubMed, Scopus, and Embase. The search results underwent two-phase title/abstract and full-text screenings. We then analyzed SD-OCT measurements differences in patients with high BMI and controls, and performed meta-regression, sub-group analysis, quality assessment, and publication bias assessment. The measurements included macular thickness, cup to disc ratio, ganglion cell-inner plexiform layer (GC-IPL) and its sub-sectors, RNFL and peripapillary RNFL (pRNFL) and their sub-layers, and choroidal thickness and its sub-sectors. Results 19 studies were included in this meta-analysis accounting for 1813 individuals, 989 cases and 824 controls. There was an overall trend towards decreased thickness in high BMI patients, but only two measurements reached statistical significance: temporal retinal nerve fiber layer (RNFL) (Standardized mean difference (SMD): -0.33, 95% confidence interval (CI): -0.53 to -0.14, p<0.01) and the choroidal region 1.0 mm nasal to fovea (SMD: -0.38, 95% CI: -0.60 to -0.16, p<0.01). Conclusion Some ocular layers are thinner in patients with higher BMI than the controls. These SD-OCT measurements might correlate with adverse events related to increased body weight and have prognostic abilities. As SD-OCT is a robust, rapid and non-invasive tool, future guidelines and studies are needed to evaluate the possibility of their integration into care of the patients with obesity.

show abstract

“…Studies show that patients with diabetes have higher intraocular pressure (IOP) than patients without diabetes and that increased fasting blood sugar (FBS) is associated with higher IOP. [1][2][3][4][5][6] However, the link between diabetes and IOP is complex as diabetes alters corneal hysteresis (CH) and corneal resistance factor (CRF), possibly confounding the true correlation between diabetes and IOP. 7,8 The Ocular Response Analyzer (ORA) noncontact tonometer (NCT) generates both a Goldmann-correlated IOP (IOPg) and a cornea-compensated IOP (IOPcc), with the latter adjusting for corneal biomechanical properties.…”

Section: Introductionmentioning

confidence: 99%

Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes

Laville

Kang

Cousins

et al. 2019

American Journal of Ophthalmology

View full text Add to dashboard Cite

A genetic correlation is the proportion of phenotypic variance between traits that is shared on a genetic basis. Here we explore genetic correlations between diabetes-and glaucoma-related traits. Design: Cross-sectional study. Methods: We assembled genome-wide association study summary statistics from Europeanderived participants regarding diabetes-related traits like fasting blood sugar (FBS) and type 2 diabetes (T2D) and glaucoma-related traits (intraocular pressure (IOP), central corneal thickness (CCT), corneal hysteresis (CH), corneal resistance factor (CRF), cup-disc ratio (CDR), and primary open-angle glaucoma (POAG)). We included data from the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database, the UK Biobank and the International Glaucoma Genetics Consortium. We calculated genetic correlation (r g) between traits using linkage disequilibrium score regression. We also calculated genetic correlations between IOP, CCT and selected diabetes-related traits based on individual level phenotype data in two Northern European population-based samples using pedigree information and Sequential Oligogenic Linkage Analysis Routines (SOLAR). Results: Overall, there was little r g between diabetes-and glaucoma-related traits. Specifically, we found a non-significant negative correlation between T2D and POAG (r g =-0.14; p=0.16). Using SOLAR, the genetic correlations between measured IOP, CCT, FBS, fasting insulin and hemoglobin A1c, were null. In contrast, genetic correlations between IOP and POAG (r g ≥0.45; p≤3.0E-04) and between CDR and POAG were high (r g =0.57; p=2.8E-10). However, genetic correlations between corneal properties (CCT, CRF and CH) and POAG were low (r g range:-0.18-0.11) and non-significant (p≥0.07). Conclusion: These analyses suggest there is limited genetic correlation between diabetes-and glaucoma-related traits.

show abstract

The Distribution of Vertical Cup-To-Disc Ratio and Its Determinants in the Iranian Adult Population

Cited by 9 publications

References 29 publications

Association of Various Systemic Factors with Intraocular Pressure

Association of Various Systemic Factors with Intraocular Pressure

Spectral-domain OCT measurements in obesity: A systematic review and meta-analysis

Genetic Correlations Between Diabetes and Glaucoma: An Analysis of Continuous and Dichotomous Phenotypes

Contact Info

Product

Resources

About