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      Development of a Visual Field Simulation Model of Longitudinal Point-Wise Sensitivity Changes From a Clinical Glaucoma Cohort

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          Abstract

          Purpose

          To develop a new visual field simulation model that can recreate real-world longitudinal results at a point-wise level from a clinical glaucoma cohort.

          Methods

          A cohort of 367 glaucoma eyes from 265 participants seen over 10.1 ± 2.5 years were included to obtain estimates of “true” longitudinal visual field point-wise sensitivity and estimates of measurement variability. These two components were then combined to reconstruct visual field results in a manner that accounted for correlated measurement error. To determine how accurately the simulated results reflected the clinical cohort, longitudinal variability estimates of mean deviation (MD) were determined by calculating the SD of the residuals from linear regression models fitted to the MD values over time for each eye in the simulated and clinical cohorts. The new model was compared to a previous model that does not account for spatially correlated errors.

          Results

          The SD of all the residuals for the clinical and simulated cohorts was 1.1 dB (95% confidence interval [CI]: 1.1–1.2 dB) and 1.1 dB (95% CI: 1.1–1.1 dB), respectively, whereas it was 0.4 dB (95% CI: 0.4–0.4 dB) using the previous simulation model that did not account for correlated errors.

          Conclusions

          A new simulation model accounting for correlated measurement errors between visual field locations performed better than a previous model in estimating visual field variability in glaucoma.

          Translational Relevance

          This model can provide a powerful framework to better understand use of visual field testing in clinical practice and trials and to evaluate new methods for detecting progression.

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          Most cited references39

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          Efficient and unbiased modifications of the QUEST threshold method: theory, simulations, experimental evaluation and practical implementation.

          QUEST [Watson and Pelli, Perception and Psychophysics, 13, 113-120 (1983)] is an efficient method of measuring thresholds which is based on three steps: (1) Specification of prior knowledge and assumptions, including an initial probability density function (p.d.f.) of threshold (i.e. relative probability of different thresholds in the population). (2) A method for choosing the stimulus intensity of any trial. (3) A method for choosing the final threshold estimate. QUEST introduced a Bayesian framework for combining prior knowledge with the results of previous trials to calculate a current p.d.f.; this is then used to implement Steps 2 and 3. While maintaining this Bayesian approach, this paper evaluates whether modifications of the QUEST method (particularly Step 2, but also Steps 1 and 3) can lead to greater precision and reduced bias. Four variations of the QUEST method (differing in Step 2) were evaluated by computer simulations. In addition to the standard method of setting the stimulus intensity to the mode of the current p.d.f. of threshold, the alternatives of using the mean and the median were evaluated. In the fourth variation--the Minimum Variance Method--the next stimulus intensity is chosen to minimize the expected variance at the end of the next trial. An exact enumeration technique with up to 20 trials was used for both yes-no and two-alternative forced-choice (2AFC) experiments. In all cases, using the mean (here called ZEST) provided better precision than using the median which in turn was better than using the mode. The Minimum Variance Method provided slightly better precision than ZEST. The usual threshold criterion--based on the "ideal sweat factor"--may not provide optimum precision; efficiency can generally be improved by optimizing the threshold criterion. We therefore recommend either using ZEST with the optimum threshold criterion or the more complex Minimum Variance Method. A distinction is made between "measurement bias", which is derived from the mean of repeated threshold estimates for a single real threshold, and "interpretation bias", which is derived from the mean of real thresholds yielding a single threshold estimate. If their assumptions are correct, the current methods have no interpretation bias, but they do have measurement bias. Interpretation bias caused by errors in the assumptions used by ZEST is evaluated. The precisions and merits of yes-no and 2AFC techniques are compared.(ABSTRACT TRUNCATED AT 400 WORDS)
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            Glaucoma and disability: which tasks are affected, and at what stage of disease?

            To summarize recent work from clinical and epidemiological studies that describe how, and at what stage, glaucoma affects the performance of important vision-related activities. Difficulties with the extremes of lighting are the most frequent complaint in glaucoma. Individuals with bilateral glaucoma also self-report difficulty with a broad array of tasks, including reading, walking, and driving. Bilateral glaucoma is associated with driving cessation and limitation, bumping into objects, slower walking, and falls. Some, but not all, studies also demonstrate higher accident rates in glaucoma. Measurable effects on reading speed have only been observed with field damage severe enough to affect binocular central acuity. Glaucoma with bilateral visual field loss is associated with increased symptoms and a measurable decline in mobility and driving. Further work is necessary to establish whether unilateral glaucoma has a significant impact on patients, to determine whether reading difficulty is common in patients with bilateral glaucoma, and to establish the effects of lighting conditions on task performance in glaucoma.
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              A new generation of algorithms for computerized threshold perimetry, SITA.

              The purpose of this work was to develop a new family of test algorithms for computerized static threshold perimetry which significantly reduces test time without any reduction of data quality. A comprehensive visual field model constructed from available knowledge of normal and glaucomatous visual fields is continuously updated during testing. The model produces threshold estimates and also estimates of the certainty to which the threshold is known at each point. Testing is interrupted at each test location at predetermined levels of threshold certainty. New time-saving methods are employed for estimation of false answers, and test pacing is optimized. After completion of the test, all threshold estimates are re-computed, taking into account the complete body of patient responses. Computer simulations were used to optimize the different parameters of the new algorithms, to evaluate the relative importance of those parameters, and to evaluate the performance of the algorithm as a whole in comparison with a standard algorithm. Simulated test results obtained with this algorithm were slightly more accurate than those of the Humphrey Full Threshold test algorithm. The number of simulated stimuli presented was reduced by an average of 29% in normal fields and 26% in glaucomatous fields. Actual clinical test time should be further reduced, since the influence of the improved timing algorithm was not included in the simulations. We applied new methods which take available knowledge of visual field physiology and pathophysiology into account, and employ modern computer-intensive mathematical methods for real time estimates of threshold values and threshold error estimates. In this way it was possible to design a family of testing algorithms which significantly reduced perimetric test time without any loss of quality in results.
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                Author and article information

                Journal
                Transl Vis Sci Technol
                Transl Vis Sci Technol
                tvst
                Transl Vis Sci Technol
                TVST
                Translational Vision Science & Technology
                The Association for Research in Vision and Ophthalmology
                2164-2591
                June 2018
                22 June 2018
                : 7
                : 3
                : 22
                Affiliations
                [1 ]Duke Eye Center and Department of Ophthalmology, Duke University School of Medicine, Durham, NC, USA
                [2 ]University of California, San Diego, Department of Ophthalmology, La Jolla, CA, USA
                [3 ]Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
                [4 ]The University of Melbourne, Ophthalmology, Department of Surgery, Melbourne, VIC, Australia
                Author notes
                Correspondence: Felipe A. Medeiros, Duke Eye Center, Duke University, 2351 Erwin Rd, Durham, NC 27705, USA. e-mail: felipe.medeiros@ 123456duke.edu
                Article
                tvst-07-03-04 TVST-17-0669
                10.1167/tvst.7.3.22
                6016506
                7b635e2b-56cc-4bb7-98a0-d9eb43aac836
                Copyright 2018 The Authors

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

                History
                : 8 December 2017
                : 3 April 2018
                Categories
                Articles

                visual field,glaucoma,longitudinal,simulations
                visual field, glaucoma, longitudinal, simulations

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