| Autor: |
Vahid Mohammadzadeh, MD, Erica Su, MS, Lynn Shi, MD, Anne L. Coleman, MD, PhD, Simon K. Law, MD, PharmD, Joseph Caprioli, MD, Robert E. Weiss, PhD, Kouros Nouri-Mahdavi, MD, MS |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Ophthalmology Science, Vol 2, Iss 3, Pp 100187- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2666-9145 |
| DOI: |
10.1016/j.xops.2022.100187 |
| Popis: |
Purpose: To investigate spatiotemporal correlations among ganglion cell complex (GCC) superpixel thickness measurements and explore underlying patterns of longitudinal change across the macular region. Design: Longitudinal cohort study. Subjects: One hundred eleven eyes from 111 subjects from the Advanced Glaucoma Progression Study with ≥ 4 visits and ≥ 2 years of follow-up. Methods: We further developed our proposed Bayesian hierarchical model for studying longitudinal GCC thickness changes across macular superpixels in a cohort of glaucoma patients. Global priors were introduced for macular superpixel parameters to combine data across superpixels and better estimate population slopes and intercepts. Main Outcome Measures: Bayesian residual analysis to inspect cross-superpixel correlations for subject random effects and residuals. Principal component analysis (PCA) to explore underlying patterns of longitudinal macular change. Results: Average (standard deviation [SD]) follow-up and baseline 10-2 visual field mean deviation were 3.6 (0.4) years and −8.9 (5.9) dB, respectively. Superpixel-level random effects and residuals had the greatest correlations with nearest neighbors; correlations were higher in the superior than in the inferior region and strongest among random intercepts, followed by random slopes, residuals, and residual SDs. PCA of random intercepts showed a first large principal component (PC) across superpixels that approximated a global intercept, a second PC that contrasted the superior and inferior macula, and a third PC, contrasting inner and nasal superpixels with temporal and peripheral superpixels. PCs for slopes, residual SDs, and residuals were remarkably similar to those of random intercepts. Conclusions: Introduction of cross-superpixel random intercepts and slopes is expected to improve estimation of population and subject parameters. Further model enhancement may be possible by including cross-superpixel random effects and correlations to address spatiotemporal relationships in longitudinal data sets. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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