A Strategy for Seeding Point Error Assessment for Retesting (SPEAR) in Perimetry Applied to Normal Subjects, Glaucoma Suspects, and Patients With Glaucoma

• Published in: American journal of ophthalmology Vol. 221; pp. 115 - 130
• Main Authors: Phu, Jack, Kalloniatis, Michael
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.2021; Elsevier Limited
• Subjects: Adult; Age; Aged; Algorithms; Automation; Cross-Sectional Studies; False Positive Reactions; Female; Glaucoma; Glaucoma, Open-Angle - physiopathology; Healthy Volunteers; Humans; Male; Middle Aged; Ocular Hypertension - physiopathology; Optic nerve; Patients; Predictive Value of Tests; Reproducibility of Results; Retrospective Studies; ROC Curve; Vision Disorders - physiopathology; Visual Field Tests - standards; Visual Fields - physiology
• ISSN: 0002-9394; 1879-1891; 1879-1891
• DOI: 10.1016/j.ajo.2020.07.047

We sought to determine the impact of seeding point errors (SPEs) as a source of low test reliability in perimetry and to develop a strategy to mitigate this error early in the test. Cross-sectional study. Visual field test results from 1 eye of 364 patients (77 normal eyes, 178 glaucoma suspect eyes, and 109 glaucoma eyes) were used to develop models for identifying SPE. Two test cohorts (326 undertaking Swedish interactive thresholding algorithm [SITA]-Faster and 327 glaucoma eyes undertaking SITA-Standard) were used to prospectively evaluate the models for identifying SPEs. Global visual field metrics were compared among reliable and unreliable results. Regression models were used to identify factors distinguishing SPEs from non-SPEs. Models were evaluated using receiver operating characteristic (ROC) curves. In the test cohorts, SITA-Faster produced a higher rate of unreliable visual field results (30%-49.7%) compared with SITA-Standard (10.8%-16.6%). SPEs contributed to most of the unreliable results in SITA-Faster (57.5%-64.9%) compared with gaze tracker deviations accounting for most of the unreliable results in SITA-Standard (40%-77.8%). In SITA-Faster, results with SPEs had worse global indices and more clusters of sensitivity reduction than reliable results. Our best model (using 9 test locations) can identify SPEs with an area under the ROC curve of 0.89. SPEs contribute to a large proportion of unreliable visual field test results, particularly when using SITA-Faster. We propose a useful model for identifying SPEs early in the test that can then guide retesting using both SITA algorithms. We provide a simplified framework for the perimetrist to improve the overall fidelity of the test result. •Seeding point errors are common in SITA-Faster, causing low test reliability.•Seeding point errors result in worse visual field global index results.•Seeding point errors can be identified early in the test for retesting.•A flowchart for perimetrists to identify these errors is provided.