{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T14:57:52Z","timestamp":1773500272402,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2020,11,13]],"date-time":"2020-11-13T00:00:00Z","timestamp":1605225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,11,13]],"date-time":"2020-11-13T00:00:00Z","timestamp":1605225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eye"],"published-print":{"date-parts":[[2021,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Objective<\/jats:title>\n                <jats:p>To determine the diagnostic ability of isolated-check visual evoked potential (icVEP), pattern visual evoked potential (pVEP), and standard automated perimetry (SAP) between dysthyroid optic neuropathy (DON) and thyroid-associated ophthalmopathy (TAO) without DON (non-DON).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>This is a case-control study, 49 bilateral patients (26 DON and 23 non-DON) were included. icVEP, pVEP, and SAP were conducted in all the subjects, icVEP parameters compared were signal-to-noise ratios (SNRs) under 8, 16, and 32% depth of modulation (DOM). pVEP parameters compared were amplitude and latency. SAP parameters were mean deviation (MD) and pattern standard deviation (PSD). The area under the receiver operating characteristic (ROC) curve (AUC), net reclassification index (NRI), integrated discrimination index (IDI), and decision curve analysis (DCA) were applied for analysis.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In icVEP, values of SNR in DON were significantly smaller than non-DON (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05). In pVEP, P100 latent time in DON was significantly larger than non-DON (<jats:italic>p<\/jats:italic>\u2009=\u20090.0026). In SAP, value of PSD in DON was larger than non-DON (<jats:italic>p<\/jats:italic>\u2009=\u20090.0006), and value of MD in DON was smaller (<jats:italic>p<\/jats:italic>\u2009=\u20090.0007). AUC, NRI, and IDI among the three tests were not significantly different. DCA showed that SNR of icVEP under 8% DOM was the farthest from the two extreme curves.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>icVEP, pVEP, and SAP have equal diagnostic capabilities to discern between DON and non-DON. In addition, icVEP may represent a significant ancillary diagnostic approach to DON detection, with more clinical benefit.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1038\/s41433-020-01274-3","type":"journal-article","created":{"date-parts":[[2020,11,13]],"date-time":"2020-11-13T12:02:52Z","timestamp":1605268972000},"page":"2556-2563","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Comparing isolated-check visual evoked potential, pattern visual evoked potential, and standard automated perimetry in dysthyroid optic neuropathy eyes"],"prefix":"10.1038","volume":"35","author":[{"given":"Xin","family":"Qi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boding","family":"Tong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weikun","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1257-2423","authenticated-orcid":false,"given":"Ban","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,11,13]]},"reference":[{"key":"1274_CR1","doi-asserted-by":"publisher","first-page":"1555","DOI":"10.1038\/s41433-018-0144-x","volume":"32","author":"Y Wong","year":"2018","unstructured":"Wong Y, Dickinson J, Perros P, Dayan C, Veeramani P, Morris D, et al. 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