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Updated: Mar 17, 2026

Assessing Early Stage Open-Angle Glaucoma in Patients by Isolated-Check Visual Evoked Potential
Published on: May 25, 2020
Predictive model for recovery of visual field after surgery of pituitary adenoma
Junwon Lee1, Seung Woo Kim2, Dong Wook Kim3
1Department of Ophthalmology, Institute of Vision Research, Yonsei University College of Medicine, 134 Shinchon-Dong, Seodaemun-Gu, Seoul, 120-752, South Korea.
Abstract:
Visual field defect is a major indication for surgery of pituitary adenoma, but visual outcome after surgery is difficult to predict. We developed a nomogram that predicts postoperative restoration of visual field defects in patients with pituitary adenoma. This study was a retrospective cohort investigation of patients who were treated for pituitary adenoma between January 2009 and December 2013. We enrolled 111 eyes of 57 patients who completed one ophthalmological evaluation preoperatively and at least two evaluations within 6 months after surgery. Serial changes in visual fields and retinal nerve fiber layer (RNFL) thickness were evaluated. Multiple logistic regression analysis was performed to select prognostic variables, and a nomogram to predict restoration of visual field defects was constructed. Visual field defects continuously improved until 3 months after surgery. However, average, superior, and inferior RNFL thickness continuously decreased until 6 months after surgery. Multiple logistic regression analysis revealed that worse preoperative visual field defect (p = 0.018), high MRI compression grade (p = 0.009), and inferior RNFL thinning (p = 0.011) were significantly associated with worse visual outcome. The nomogram that predicts the visual restoration showed an area under the receiver operating characteristic curve of 0.84. In conclusion, we developed a nomogram that predicted the restoration of visual field defects after removal of pituitary adenoma. This would allow tailored counseling of individual patients by precisely predicting visual recovery after surgery.
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