A perimetric learner's index

Jonny Olsson, Peter Åsman, Anders Heijl

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Certain individuals need earlier perimetric experience before producing normal fields on automated static threshold perimetry. Mid-peripheral depressions and an unaffected central field are typical findings in such cases. We have devised a learner's index, to detect defect patterns that may be due to such perimetric inexperience. Methods: The central visual field was partitioned into 5 concentric zones and averages of deviations from the age-corrected normal threshold values were studied in each zone. The third test session in 74 randomly selected normal subjects provided an experienced reference material. Visual field results typical of normal individuals lacking perimetric experience were represented by the first field test obtained from each of 7 subjects ('learners') from the same group, who showed significant learning during three test sessions. A linear discriminant function, learner's index, was constructed that discriminates between typically experienced and typically inexperienced field results in normals. Results: Average deviation from age-corrected normal threshold increased with increasing eccentricity in the learner's initial fields. Clinical examples illustrate the intended use of the new index. Conclusions: The learner's index highlights those first field tests from eyes with normal visual fields, that deviate significantly from a normal experienced result in the direction of a learner's result. Patients showing significant learner's index are candidates for repeated visual field testing.

Original languageEnglish
Pages (from-to)665-668
Number of pages4
JournalActa Ophthalmologica Scandinavica
Volume75
Issue number6
DOIs
Publication statusPublished - 1997

Subject classification (UKÄ)

  • Ophthalmology

Free keywords

  • Computer-assisted field interpretation
  • Discriminatory analysis
  • Learning
  • Perimetric experience
  • Static computerized perimetry
  • Visual fields

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