Influence of learning effect on reliability parameters and global indices of standard automated perimetry in cases of primary open angle glaucoma

Abstract

Aim. To find out the influence of learning effect on various reliability parameters and global indices of standard automated perimetry in cases of primary open angle glaucoma.Method. Thirty eyes of 30 patients of Primary Open Angle Glaucoma constituted material for this prospective observational study. All the patients underwent standard automated perimetry three times on three different days within one week on G program of Octopus Visual Field Analyzer. The details of reliability indices, global indices, and test duration were compiled and analyzed.Result. A male preponderance was observed with a mean age of 53.43 years. The mean false positive was found to be 11.13, 6.07, and 2.40 on visit 1, visit 2, and visit 3, respectively. The mean false negative was found to be 13.73, 9.33, and 6.30 on visit 1, visit 2, and visit 3, respectively. The mean fixation loss was found to be 7.53, 3.83, and 1.60 on visit 1, visit 2, and visit 3, respectively. The mean deviation was found to be -10.14, -5.75, and -3.11 on visit 1, visit 2, and visit 3, respectively. The pattern standard deviation was found to be 5.58, 4.63, and 4.35 on visit 1, visit 2, and visit 3, respectively. The mean test duration was found to be 7.68, 6.21, & 5.51 minutes for visit 1, visit 2 and visit 3, respectively. All the values were statistically highly significant except for the pattern standard deviation. Conclusion. At least three standard automated perimetry tests should be performed for all glaucoma patients in order to obtain a base line perimetry chart.

Frequency of Visual Fields Needed to Detect Glaucoma Progression: A Computer Simulation Using Linear Mixed Effects Model

“…The SAP test requires the patient’s cooperation and is influenced by some factors such as the patients’ concentration 21,25. Hence, the simulated SAP MD involved the expected variability (or noise) similar to real-world clinical data.…”

“…LMM regards the dependency between observations in a longitudinal study. In addition, it considers a specific behavior for each individual during the therapy by defining different intercepts and slopes for each person 17,23–25. The random intercept parameter denotes that each subject has a basic level of MD measurement at diagnosis, which continues over time, and the random slope parameter denotes the rate of VF loss for each participant.…”

“…In addition, it considers a specific behavior for each individual during the therapy by defining different intercepts and slopes for each person. 17,[23][24][25] The random intercept parameter denotes that each subject has a basic level of MD measurement at diagnosis, which continues over time, and the random slope parameter denotes the rate of VF loss for each participant. In this study, true simulated MD values were generated from early glaucoma (between 0 and −6 dB) with a mean population of −3 dB.…”

“…The SAP test requires the patient's cooperation and is influenced by some factors such as the patients' concentration. 21,25 Hence, the simulated SAP MD involved the expected variability (or noise) similar to real-world clinical data. For this purpose, an LMM with random intercept and slope was fitted on the MD values of the Rotterdam Eye Hospital data set.…”

The learning effect in Humphrey Field Analyser testing in glaucoma patients: how many practice sessions are enough?

“…3 This learning curve has been reported consistently in other studies, and there is general agreement in the literature that at least three initial tests should be performed. 5,6 However, repeating the tests for reliable results is sometimes problematic, as glaucoma should often be diagnosed as quickly as possible. 5 The learning curve is due to the psychological phenomenon of the visual system adapting to the process or improvement in the patients' recognition of the stimulus.…”