Impact of learning effect on reliability factors and global indices in visual field testing by standard automated perimetry in normal healthy subjects and primary open-angle glaucoma patients to obtain an accurate baseline perimetry chart.

Purpose To record and evaluate the reliability parameters (fixation loss (FL) %, false positive (FP) %) and global indices (mean sensitivity (MS), mean deviation (MD), pattern standard deviation in dB) in three visual field test sessions within two weeks to assess the learning effect in normal healthy subjects and POAG patients and comparison of learning effect gender wise and age wise in primary open-angle glaucoma (POAG) patients. Methods This study was a prospective observational study. An oculus visual field testing was done and analyzed in 30 eyes of POAG patients and 30 eyes of normal healthy subjects in three visits. Results There were 16 (53.3%) males and 14 (46.6%) females in the POAG group and 16 (53.33%) males and 14 (46.66%) females in the normal healthy subject group. A significant difference in data change between each visit in FL, FP, MD, MS was found though the difference was more pronounced in the second visit than in the third visit. The pattern standard deviation does not change significantly in subsequent visits in both groups. Gender wise and age wise no significant difference was found in the POAG group. Conclusion Significant improvement in reliability parameters and global indices with each subsequent visit in both the POAG group and normal patients signifies the importance of learning effect on these parameters and the need to perform at least three tests to get the baseline perimetry chart, especially in POAG patients, while in normal subjects, second perimetric result can be accepted. It was also concluded that the learning effect is not influenced by age and gender.

[1]  N. Ramli,et al.  The Association Between Visual Field Reliability Indices and Cognitive Impairment in Glaucoma Patients , 2019, Journal of glaucoma.

[2]  U. S. Tiwari,et al.  Influence of learning effect on reliability parameters and global indices of standard automated perimetry in cases of primary open angle glaucoma , 2018, Romanian journal of ophthalmology.

[3]  C. Gerardi,et al.  Quality of Life in Glaucoma: A Review of the Literature , 2016, Advances in Therapy.

[4]  A. Aydin,et al.  The influence of the learning effect on automated perimetry in a Turkish population. , 2015, Journal francais d'ophtalmologie.

[5]  M. Gordijn,et al.  Factors that influence standard automated perimetry test results in glaucoma: test reliability, technician experience, time of day, and season. , 2012, Investigative ophthalmology & visual science.

[6]  Philip P. Chen,et al.  Continued Visual Field Progression in Eyes With Prior Visual Field Progression in Patients With Open-Angle Glaucoma , 2010, Journal of glaucoma.

[7]  D. P. Castro,et al.  Learning effect of standard automated perimetry in healthy individuals. , 2008, Arquivos brasileiros de oftalmologia.

[8]  A Heijl,et al.  Practical recommendations for measuring rates of visual field change in glaucoma , 2008, British Journal of Ophthalmology.

[9]  Samin Hong,et al.  Learning effect of Humphrey Matrix perimetry. , 2007, Canadian journal of ophthalmology. Journal canadien d'ophtalmologie.

[10]  Chris A Johnson,et al.  Evaluation of the structure-function relationship in glaucoma. , 2005, Investigative ophthalmology & visual science.

[11]  Brenda W Gillespie,et al.  The collaborative initial glaucoma treatment study: baseline visual field and test-retest variability. , 2003, Investigative ophthalmology & visual science.

[12]  L. Zangwill,et al.  Discriminating between normal and glaucomatous eyes using the Heidelberg Retina Tomograph, GDx Nerve Fiber Analyzer, and Optical Coherence Tomograph. , 2001, Archives of ophthalmology.

[13]  M Zingirian,et al.  Learning effect, short-term fluctuation, and long-term fluctuation in frequency doubling technique. , 2000, American journal of ophthalmology.

[14]  L. Zangwill,et al.  Comparison of long-term variability for standard and short-wavelength automated perimetry in stable glaucoma patients. , 2000, American journal of ophthalmology.

[15]  A Heijl,et al.  SITA Fast, a new rapid perimetric threshold test. Description of methods and evaluation in patients with manifest and suspect glaucoma. , 1998, Acta ophthalmologica Scandinavica.

[16]  A Heijl,et al.  Evaluation of a new perimetric threshold strategy, SITA, in patients with manifest and suspect glaucoma. , 1998, Acta ophthalmologica Scandinavica.

[17]  J. Wild,et al.  Baseline alterations in blue-on-yellow normal perimetric sensitivity , 1996, Graefe's Archive for Clinical and Experimental Ophthalmology.

[18]  S. Sutherland,et al.  Factors associated with a learning effect in glaucoma patients using automated perimetry , 1990, Acta ophthalmologica.

[19]  G. Trick,et al.  Assessing the utility of reliability indices for automated visual fields. Testing ocular hypertensives. , 1989, Ophthalmology.

[20]  E. Werner,et al.  Effect of patient experience on the results of automated perimetry in clinically stable glaucoma patients. , 1988, Ophthalmology.

[21]  V. P. Costa,et al.  Flicker perimetry in healthy subjects: influence of age and gender, learning effect and short-term fluctuation. , 2007, Arquivos brasileiros de oftalmologia.

[22]  Josef Flammer,et al.  The learning and fatigue effect in automated perimetry , 2004, Graefe's Archive for Clinical and Experimental Ophthalmology.

[23]  A. Sommer,et al.  Reliability of visual field results over repeated testing. , 1991, Ophthalmology.

[24]  E. Werner,et al.  Effect of patient experience on the results of automated perimetry in glaucoma suspect patients. , 1990, Ophthalmology.

[25]  G. Lindgren,et al.  The effect of perimetric experience in normal subjects. , 1989, Archives of ophthalmology.