Comparing the usefulness of a new algorithm to measure visual field using the variational Bayes linear regression in glaucoma patients, in comparison to the Swedish interactive thresholding algorithm

Author:

Murata Hiroshi,Asaoka RyoORCID,Fujino YuriORCID,Matsuura MasatoORCID,Hirasawa KazunoriORCID,Shimada Satoshi,Shoji Nobuyuki

Abstract

Background/aimsWe previously reported that the visual field (VF) prediction model using the variational Bayes linear regression (VBLR) is useful for accurately predicting VF progression in glaucoma (Invest Ophthalmol Vis Sci. 2014, 2018). We constructed a VF measurement algorithm using VBLR, and the purpose of this study was to investigate its usefulness.Method122 eyes of 73 patients with open-angle glaucoma were included in the current study. VF measurement was performed using the currently proposed VBLR programme with AP-7700 perimetry (KOWA). VF measurements were also conducted using the Swedish interactive thresholding algorithm (SITA) standard programme with Humphrey field analyser. VF measurements were performed using the 24–2 test grid. Visual sensitivities, test–retest reproducibility and measurement duration were compared between the two algorithms.ResultMean mean deviation (MD) values with SITA standard were −7.9 and −8.7 dB (first and second measurements), whereas those with VBLR-VF were −8.2 and −8.0 dB, respectively. There were no significant differences across these values. The correlation coefficient of MD values between the 2 algorithms was 0.97 or 0.98. Test–retest reproducibility did not differ between the two algorithms. Mean measurement duration with SITA standard was 6 min and 02 s or 6 min and 00 s (first or second measurement), whereas a significantly shorter duration was associated with VBLR-VF (5 min and 23 s or 5 min and 30 s).ConclusionVBLR-VF reduced test duration while maintaining the same accuracy as the SITA-standard.

Funder

Suzuken Memorial Foundation

Ministry of Education, Culture, Sports, Science and Technology

Mitsui Sumitomo Insurance Welfare Foundation

Japan Science and Technology Agency

the University of Tokyo Gap Fund Program

Publisher

BMJ

Subject

Cellular and Molecular Neuroscience,Sensory Systems,Ophthalmology

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