While evaluators tend to agree, the differences between evaluators` observations are close to zero. When one appraiser is generally higher or lower than the other by a consistent amount, the distortion of zero is different. If evaluators tend to disagree, but in the absence of a consistent model where one rating is higher than the other, the average is close to zero. Confidence limits (usually 95%) can be calculated both for distortion and for each of the compliance limits. Since there is no general consensus on the point value of the regression and progression of the p-value, or whether there should be a requirement for consistent points to show this behavior and whether it should be maintained in the following areas, progressor currently remains a subjective analysis. For this reason, and because there is no generally recognized gold standard for visual field progression, this study investigates the usefulness of Progressor by determining the degree of consistency between expert observers with both progressive and standard clinical techniques (manual comparison of serial expressions from an automated perimeter). Although these statements were made more than a decade ago, they are probably still true today, even though the knowledge of whether a patient`s glaucoma is progressive or stable is essential to the management of the disease. Several scoring systems have been designed to identify visual field progression for research purposes2-5, but none have been widely accepted in general clinical practice. However, the unintended clinical assessment is contradictory: even expert observers show significant disagreement as to whether a series of facial fields is synonymous with progression or stability.1 One possible reason is that the standard edition of most automated perimeters provides insufficient information on progression or stability. Thus, if the clinician is trying to decide whether or not a series of expenses is a progressive disease, the task is to manually compare the sensitivity values by decibels (or treated versions) or graphs for all fields in the series.
This task is made even more complex by the contributions of variability “within the test” (short-term fluctuation) 6 and variability “between the test” (long-term fluctuation) 7, which are known to be increased in glaucoma to normal value.8 For these reasons and because the numerical grids produced by automated perimeters are easily accessible to numerical analysis, a large number of software and statistical approaches have been used to support the determination of visual field progression. Glaucoma. A set of methods is based on estimates of the variation in the summary quantities of the field, such as.B. Regression analysis of the mean error value,9 average deviation,10 other global measures,10 Whole field measurement and loss of quadrantic sensitivity,11 and trend and regression analysis of different estimates of the sensitivity of the whole field or its parts.12-14 The analysis of synthetic measures, whether based on the whole field or on clusters of points. was found to be “remarkably bad”15 and “of low value”16 in detecting glaukoma changes. . . .