Assessing Intereye Symmetry and Its Implications for Study Design

Maguire, Maureen G.

doi:10.1167/iovs.61.6.27

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…CCT and axial length) and biomechanical parameters (e.g. IOP and corneal displacements) in healthy subjects, [46][47][48][49][50] the potential variance between the left and right eyes could have obscured some correlations and rendered them undetectable in the present study. A comparison between the left and right eyes ONH/PPS shear strains in six pairs of donor eyes is presented in the Supplementary Material to provide data on the potential variance.…”

Section: Discussionmentioning

confidence: 74%

Biomechanical Correlations Between the Cornea and the Optic Nerve Head

Pan,

Kwok,

Pan

et al. 2024

Invest. Ophthalmol. Vis. Sci.

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A thin cornea is a potent risk factor for glaucoma. The underlying mechanisms remain unexplained. It has been postulated that central corneal thickness (CCT) may be a surrogate for biomechanical parameters of the posterior eye. In this study, we aimed to explore correlations of biomechanical responses between the cornea and the optic nerve head (ONH) and the peripapillary sclera (PPS) to elevated intraocular pressure (IOP), the primary risk factor of glaucoma. METHODS.Inflation tests were performed in nine pairs of human donor globes. One eye of each pair was randomly assigned for cornea or posterior eye inflation. IOP was raised from 5 to 30 millimeters of mercury (mmHg) at 0.5 mmHg steps in the whole globe and the cornea or the ONH/PPS was imaged using a 50 MHz ultrasound probe. Correlationbased ultrasound speckle tracking was used to calculate tissue displacements and strains. Associations of radial, tangential, and shear strains at 30 mmHg between the cornea and the ONH or PPS were evaluated. RESULTS.Corneal shear strain was significantly correlated with ONH shear strain (R = 0.857, P = 0.003) and PPS shear strain (R = 0.724, P = 0.028). CCT was not correlated with any strains in the cornea, ONH, or PPS. CONCLUSIONS.Our results suggested that an eye that experiences a larger shear strain in the cornea would likely experience a larger shear strain in its ONH and PPS at IOP elevations. The strong correlation between the cornea's and the ONH's shear response to IOP provides new insights and suggests a plausible explanation of the cornea's connection to glaucoma risk.

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Section: Discussionmentioning

confidence: 74%

Biomechanical Correlations Between the Cornea and the Optic Nerve Head

Pan,

Kwok,

Pan

et al. 2024

Invest. Ophthalmol. Vis. Sci.

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“…Ninety-one (91%) of 100 infants were in agreement between 2 eyes in the status of RW-ROP from clinical eye examination, with Kappa of 0.76 (95% CI = 0.61–0.91). 13 …”

Section: Resultsmentioning

confidence: 99%

Calculating Sensitivity, Specificity, and Predictive Values for Correlated Eye Data

Ying

Maguire

Glynn

et al. 2020

Invest. Ophthalmol. Vis. Sci.

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Purpose To describe and demonstrate appropriate statistical approaches for estimating sensitivity, specificity, predictive values and their 95% confidence intervals (95% CI) for correlated eye data. Methods We described generalized estimating equations (GEE) and cluster bootstrap to account for inter-eye correlation and applied them for analyzing the data from a clinical study of telemedicine for the detection of retinopathy of prematurity (ROP). Results Among 100 infants (200 eyes) selected for analysis, 20 infants had referral-warranted ROP (RW-ROP) in both eyes and 9 infants with RW-ROP only in one eye based on clinical eye examination. In the per-eye analysis that included both eyes of an infant, the image evaluation for RW-ROP had sensitivity of 83.7% and specificity of 86.8%. The 95% CI's from the naïve approach that ignored the inter-eye correlation were narrower than those of the GEE approach and cluster bootstrap for both sensitivity (width of 95% CI: 22.4% vs. 23.2% vs. 23.9%) and specificity (11.4% vs. 12.5% vs. 11.6%). The 95% CIs for sensitivity and specificity calculated from left eyes and right eyes separately were wider (35.2% and 30.8% respectively for sensitivity, 25.4% and 17.3% respectively for specificity). Conclusions When an ocular test is performed in both eyes of some or all of the study subjects, the statistical analyses are best performed at the eye-level and account for the inter-eye correlation by using either the GEE or cluster bootstrap. Ignoring the inter-eye correlation results in 95% CIs that are inappropriately narrow and analyzing data from two eyes separately are not efficient.

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“…The disease agreement between the two eyes of the same patient was assessed using the kappa statistic ( κ ), which measures the ratio between the observed proportion of agreement and the proportion of agreement expected by chance. Kappa values range from + 1 (perfect agreement) to -1 (perfect disagreement) [ 22 ].…”

Section: Methodsmentioning

confidence: 99%

Rate and Predictors of Misclassification of Active Diabetic Macular Edema as Detected by an Automated Retinal Image Analysis System

La Franca,

Rutigliani,

Checchin

et al. 2024

Ophthalmol Ther

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Introduction The aim of this work is to estimate the sensitivity, specificity, and misclassification rate of an automated retinal image analysis system (ARIAS) in diagnosing active diabetic macular edema (DME) and to identify factors associated with true and false positives. Methods We conducted a cross-sectional study of prospectively enrolled patients with diabetes mellitus (DM) referred to a tertiary medical retina center for screening or management of DME. All patients underwent two-field fundus photography (macula- and disc-centered) with a true-color confocal camera; images were processed by EyeArt V.2.1.0 (Woodland Hills, CA, USA). Active DME was defined as the presence of intraretinal or subretinal fluid on spectral-domain optical coherence tomography (SD-OCT). Sensitivity and specificity and their 95% confidence intervals (CIs) were calculated. Variables associated with true (i.e., DME labeled as present by ARIAS + fluid on SD-OCT) and false positives (i.e., DME labeled as present by ARIAS + no fluid on SD-OCT) of active DME were explored. Results A total of 298 eyes were included; 92 eyes (31%) had active DME. ARIAS sensitivity and specificity were 82.61% (95% CI 72.37–89.60) and 84.47% (95% CI 78.34–89.10). The misclassification rate was 16%. Factors associated with true positives included younger age ( p = 0.01), shorter DM duration ( p = 0.006), presence of hard exudates ( p = 0.005), and microaneurysms ( p = 0.002). Factors associated with false positives included longer DM duration ( p = 0.01), worse diabetic retinopathy severity ( p = 0.008), history of inactivated DME ( p < 0.001), and presence of hard exudates ( p < 0.001), microaneurysms ( p < 0.001), or epiretinal membrane ( p = 0.06). Conclusions The sensitivity of ARIAS was diminished in older patients and those without DME-related fundus lesions, while the specificity was reduced in cases with a history of inactivated DME. ARIAS performed well in screening for naïve DME but is not effective in surveillance inactivated DME.

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Assessing Intereye Symmetry and Its Implications for Study Design

Abstract: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Cited by 10 publications

References 16 publications

Biomechanical Correlations Between the Cornea and the Optic Nerve Head

Biomechanical Correlations Between the Cornea and the Optic Nerve Head

Calculating Sensitivity, Specificity, and Predictive Values for Correlated Eye Data

Rate and Predictors of Misclassification of Active Diabetic Macular Edema as Detected by an Automated Retinal Image Analysis System

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