Abstract
A key question to the ophthalmologist from their patient when a disease is diagnosed or treatments are proposed, is what to expect. Here, prediction tools can play an important role.
In this issue of Clinical and Experimental Ophthalmology, Choe and colleagues describe a decision tree-based model that can predict a parafoveal scotoma in patients whose 24–2 visual field test shows normal para- and perifoveal points. This model uses the macular ganglion cell-inner plexiform layer thickness, as measured by optical coherence tomography (OCT). Its application allows the clinician to identify those patients with early glaucoma, who normally would have only a 24–2 test, but who need the 10–2 test to show visual field loss.
Flicking through recent issues of the journal, one finds reports of numerous prediction tools that are likely to be useful in clinical practice across a range of ophthalmic diseases.
In this issue of Clinical and Experimental Ophthalmology, Choe and colleagues describe a decision tree-based model that can predict a parafoveal scotoma in patients whose 24–2 visual field test shows normal para- and perifoveal points. This model uses the macular ganglion cell-inner plexiform layer thickness, as measured by optical coherence tomography (OCT). Its application allows the clinician to identify those patients with early glaucoma, who normally would have only a 24–2 test, but who need the 10–2 test to show visual field loss.
Flicking through recent issues of the journal, one finds reports of numerous prediction tools that are likely to be useful in clinical practice across a range of ophthalmic diseases.
Original language | English |
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Pages (from-to) | 479-480 |
Number of pages | 2 |
Journal | Clinical and Experimental Ophthalmology |
Volume | 50 |
Issue number | 5 |
Early online date | 26 May 2022 |
DOIs | |
Publication status | Published - Jul 2022 |
Keywords
- Ophthalmology
- Patient care
- Prediction tools