Glaucoma patients have progressive optic neuropathy with vision field (VF) loss. Variational Bayes linear regression (VBLR) helps to accurately model and predict the VF progression. This study uses a VBLR-based VF measurement algorithm and compares its efficiency against the Swedish interactive thresholding algorithm (SITA).

The study had 73 open-angle glaucoma patients with 122 eyes. The VBLR program and AP-7700 perimetry (KOWA) helped to measure the VF. The SITA and Humphrey field analyzer also measured the VF. The 24-2 test grid took the VF measurements. The two algorithms got compared using visual sensitivities, measurement duration, and test-retest reproducibility.

The SITA standard’s MD values were −7.9 and −8.7 dB (1st and 2nd measurements). The VBLR-VF MD values were at −8.2 and −8.0 dB respectively. Neither these values nor test-retest reproducibility of the 2 algorithms had any significant differences. The MD values’ correlation coefficient for the two algorithms was 0.97 or 0.98. The SITA mean measurement duration was 6 min 02 sec or 6 min 00 sec (1st or 2nd measurement). The VBLR-VF had a significantly shorter duration at 5 min 23 sec or 5 min 30 sec for the first and second measurement, respectively.

The VBLR-VF reduced the test duration as compared to the SITA standard. It also maintained the same level of accuracy.