Clinical Evaluation of Swedish Interactive Thresholding Algorithm–Faster Compared With Swedish Interactive Thresholding Algorithm–Standard in Normal Subjects, Glaucoma Suspects, and Patients With Glaucoma

Abstract

To compare the visual fields results obtained using the Swedish interactive thresholding algorithm-Standard (SS) and the Swedish interactive thresholding algorithm-Faster (SFR) in normal subjects, glaucoma suspects, and patients with glaucoma and to quantify potential time-saving benefits of the SFR algorithm. DESIGN: Prospective, cross-sectional study. METHODS: One randomly selected eye from 364 patients (77 normal subjects, 178 glaucoma suspects, and 109 patients with glaucoma) seen in a single institution underwent testing using both SS and SFR on the Humphrey Field Analyzer. Cumulative test time using each algorithm was compared after accounting for different rates of test reliability. Pointwise and cluster analysis was performed to determine whether there were systematic differences between algorithms. RESULTS: Using SFR had a greater rate of unreliable results (29.3%) compared with SS (7.7%, P < .0001). This was mainly because of high false positive rates and seeding point errors. However, modeled test times showed that using SFR could obtain a greater number of reliable results within a shorter period of time. SFR resulted in higher sensitivity values (on average 0.5 dB for patients with glaucoma) that was greater under conditions of field loss (<19 dB). Cluster analysis showed no systematic patterns of sensitivity differences between algorithms. CONCLUSIONS: After accounting for different rates of test reliability, SFR can result in significant time savings compared with SS. Clinicians should be cognizant of false positive rates and seeding point errors as common sources of error for SFR. Results between algorithms are not directly interchangeable, especially if there is a visual field deficit <19 dB.

Validation of a novel functional test for assessing metamorphopsia using epiretinal membranes as a model

“…Further studies and refinements to the current test are required before the LST can be widely adopted in clinical practice. As expected, there was a longer test duration in the context of subjects with pathology, and again, a Bayesian approach would be useful to shorten test time 39 .…”

“…We acknowledge the limitations of using a staircase method in the length of the test, not unlike clinical perimetry. However, like clinical perimetry, the implementation of Bayesian and adaptive approaches to thresholding could eventually speed up the test for practical clinical use 39 . The LST is delivered through a computer-based system that has the potential to be adapted to allow it to be performed on portable tablet or screen devices which have become increasingly popular as a tool for assessing visual function in clinical practice 40 .…”

Uptake, Persistence, and Performance of Weekly Home Monitoring of Visual Field in a Large Cohort of Patients With Glaucoma

“…19,20 A recent study that considered gaze tracking during the SITA faster test algorithm found that 20% of participants made >6° eye movement errors >20% of the time. 21 Thus, the concern is not so much whether FL occur during the test but what effect it has on visual field outcomes. Three groups have considered this issue and all show that high FLs have no to little association with field outcomes and minor impact on test reliability.…”

Comparative Study Between the SORS and Dynamic Strategy Visual Field Testing Methods on Glaucomatous and Healthy Subjects

“…Other techniques looked for speed gains by estimating the starting light intensity at a next query location and thereby reducing the number of stimuli presented per location. Dynamic strategy (DS), 10,15 Swedish interactive threshold algorithm (SITA) standard, 16,17 SITA fast, 12,18 SITA faster, 19,20 and tendency-oriented perimetry (TOP) 21 are examples of such methods. DS uses a staircasing approach as also found in conventional techniques but with an adaptive step whose size depends on the steepness of the probability of seeing curve (POSC).…”