AI Article Synopsis
- The research aimed to develop a clinical diagnostic model for primary open-angle glaucoma (POAG) using frequency-domain optical coherence tomography (FD-OCT).
- The study analyzed a total of 232 eyes, comparing retinal nerve fiber layer (RNFL) thickness measurements from healthy individuals and early POAG patients to create and test four diagnostic models.
- Findings revealed that newer area partition models showed better diagnostic accuracy than traditional models, with the simplest model (ONH-N) being especially convenient for clinical use.
Article Abstract
Aim: To build a clinical diagnostic model of primary open angle glaucoma (POAG) using the normal probability chart of frequency-domain optical coherence tomography (FD-OCT).
Methods: This is a cross-sectional study. Total 133 eyes from 133 healthy subjects and 99 eyes from 99 early POAG patients were included in the study. The retinal nerve fibre layer (RNFL) thickness parameters of optic nerve head (ONH) and RNFL3.45 scan were measured in one randomly selected eye of each subject using RTVue-100 FD-OCT. Then, we used these parameters to establish the diagnostic models. Four different diagnostic models based on two different area partition strategies on ONH and RNFL3.45 parameters, including ONH traditional area partition model (ONH-T), ONH new area partition model (ONH-N), RNFL3.45 traditional area partition model (RNFL3.45-T) and RNFL3.45 new area partition model (RNFL3.45-N), were built and tested by cross-validation.
Results: The new area partition models had higher area under the receiver operating characteristic (AROC; ONH-N: 0.990; RNFL3.45-N: 0.939) than corresponding traditional area partition models (ONH-T: 0.979; RNFL3.45-T: 0.881). There was no statistical difference among AROC of ONH-T, ONH-N, and RNFL3.45-N. Nevertheless, ONH-N was the simplest model.
Conclusion: The new area partition models had higher diagnostic accuracy than corresponding traditional area partition models, which can improve the diagnostic ability of early POAG. In particular, the simplest ONH-N diagnostic model may be convenient for clinical application.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010378 | PMC |
| http://dx.doi.org/10.18240/ijo.2018.06.09 | DOI Listing |
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