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Shetty V, Sankhe P, Haldipurkar SS, Haldipurkar T, Dhamankar R, Kashelkar P, Shah D, Mhatre P, Singh Setia M. Diagnostic Performance of the PalmScan VF2000 Virtual Reality Visual Field Analyzer for Identification and Classification of Glaucoma. JOVR [Internet]. 2022Jan.21 [cited 2024Jul.17];17(1):33–41. Available from: https://knepublishing.com/index.php/JOVR/article/view/10168

https://doi.org/10.18502/jovr.v17i1.10168

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  • Cited by 2 articles

authors

  • Vijay Shetty

    Vijay Shetty

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Prachi Sankhe

    Prachi Sankhe

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Suhas S Haldipurkar

    Suhas S Haldipurkar

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Tanvi Haldipurkar

    Tanvi Haldipurkar

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Rita Dhamankar

    Rita Dhamankar

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Priyanka Kashelkar

    Priyanka Kashelkar

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Dhruven Shah

    Dhruven Shah

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Paresh Mhatre

    Paresh Mhatre

    Laxmi Eye Institute, Panvel, Maharashtra, India
  • Maninder Singh Setia

    Maninder Singh Setia

    Laxmi Eye Institute, Panvel, Maharashtra, India
    https://orcid.org/0000-0003-1291-9033

Published Date

  • Jan 21, 2022
This journal is publishing all the articles under Creative Commons Attribution License CC BY 4.0.

Diagnostic Performance of the PalmScan VF2000 Virtual Reality Visual Field Analyzer for Identification and Classification of Glaucoma

Journal of Ophthalmic and Vision Research (JOVR) / January–March 2022, Volume 17, Issue 1 / Pages 33–41

Abstract

Purpose: To evaluate the diagnostic test properties of the Palm Scan VF2000® Virtual Reality Visual Field Analyzer for diagnosis and classification of the severity of glaucoma.


Methods: This study was a prospective cross-sectional analysis of 166 eyes from 97 participants. All of them were examined by the Humphrey® Field Analyzer (used as the gold standard) and the Palm Scan VF 2000® Virtual Reality Visual Field Analyzer on the same day by the same examiner. We estimated the kappa statistic (including 95% confidence interval [CI]) as a measure of agreement between these two methods. The diagnostic test properties were assessed using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).


Results: The sensitivity, specificity, PPV, and NPV for the Virtual Reality Visual Field Analyzer for the classification of individuals as glaucoma/non-glaucoma was 100%. The general agreement for the classification of glaucoma between these two instruments was 0.63 (95% CI: 0.56–0.78). The agreement for mild glaucoma was 0.76 (95% CI: 0.61–0.92), for moderate glaucoma was 0.37 (0.14–0.60), and for severe glaucoma was 0.70 (95% CI: 0.55–0.85). About 28% of moderate glaucoma cases were misclassified as mild and 17% were misclassified as severe by the virtual reality visual field analyzer. Furthermore, 20% of severe cases were misclassified as moderate by this instrument.


Conclusion: The instrument is 100% sensitive and specific in detection of glaucoma. However, among patients with glaucoma, there is a relatively high proportion of misclassification of severity of glaucoma. Thus, although useful for screening of glaucoma, it cannot replace the Humphrey® Field Analyzer for the clinical management in its current form.

Keywords:

Glaucoma, Sensitivity, Specificity, Test Properties, Virtual Reality Perimetry

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