Multicenter Normative Data for Mesopic Microperimetry.

ABSTRACT:

Purpose

The purpose of this study was to provide a large, multi-center normative dataset for the Macular Integrity Assessment (MAIA) microperimeter and compare the goodness-of-fit and prediction interval calibration-error for a panel of hill-of-vision models.

Methods

Microperimetry examinations of healthy eyes from five independent study groups and one previously available dataset were included (1137 tests from 531 eyes of 432 participants [223 women and 209 men]). Linear mixed models (LMMs) were fitted to the data to obtain interpretable hill-of-vision models. A panel of regression models to predict normative data was compared using cross-validation with site-wise splits. The mean absolute error (MAE) and miscalibration area (area between the calibration curve and the ideal

SUBMITTER: Pfau M 

PROVIDER: S-EPMC11512566 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature