VisionGO is a two-stage calculator to predict the visual outcome of an NLP eye after open globe injury, and to show the contribution of each clinical feature. NLP Study is a series research program to study the eyes with no light perception (NLP) after ocular trauma. VisionGO uses machine learning algorithms, ophthalmologists can learn the probability of an NLP eye after open globe injury regaining vision by typing in several clinical features of an NLP eye after open globe injury. We hope this two-stage calculator can help ophthalmologists and patients better comprehend the severity of the injury, assist in decision-making of whether a vitrectomy should be performed, and predict the clinical course of the injured eye after performing a vitrectomy.
Pre-operative model can predict the probability of an NLP eye after OGI regaining vision by analyzing 10 clinical features observed before vitrectomy, including intraocular foreign body or not, perforating injury or not, TWL, DLP, iris status, cornea status, aqueous humor status, lens status, vitreous status, and time of vitrectomy.
Intra-operative model can predict the probability of an NLP eye after OGI regaining vision by analyzing 10 clinical features observed before vitrectomy and 6 features observed during vitrectomy, including intraocular foreign body or not, perforating injury or not, TWL, DLP, iris status, cornea status, aqueous humor status, lens status, vitreous status, time of vitrectomy, retinal residue, configuration of retinal detachment, retina status, retina reattachment, choroid reattachment, and ciliary body status.