@article {1307465,
	title = {Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma},
	journal = {Ophthalmology},
	volume = {125},
	number = {3},
	year = {2018},
	month = {2018 Mar},
	pages = {352-360},
	abstract = {PURPOSE: To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. DESIGN: Retrospective cohort study. PARTICIPANTS: Visual fields of 44 503 eyes from 26 130 participants. METHODS: Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n\&nbsp;= 97) to determine the usefulness of our model. MAIN OUTCOME MEASURES: Predictive models for GHT results reversal using VF features. RESULTS: For the 16 604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1\% for MD \&lt;\&nbsp;-12 dB to 13.8\% for MD >=-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD >=-3 dB) and 0.697 (-6 dB <= MD \&lt;\&nbsp;-3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P \&lt; 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7\%; P \&lt; 0.001) than predicting GHT results reversal (68.8\%) with a prescribed specificity 67.7\%. CONCLUSIONS: Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.},
	issn = {1549-4713},
	doi = {10.1016/j.ophtha.2017.09.021},
	author = {Wang, Mengyu and Pasquale, Louis R and Shen, Lucy Q and Boland, Michael V and Wellik, Sarah R and De Moraes, Carlos Gustavo and Myers, Jonathan S and Wang, Hui and Baniasadi, Neda and Li, Dian and Silva, Rafaella Nascimento E and Bex, Peter J and Tobias Elze}
}
