ROC curves: use of uncorrected visual acuity (LogMAR) to detect significant refractive error.

<p>ROC curves: use of uncorrected visual acuity (LogMAR) to detect significant refractive error.</p

Sensitivity and specificity of an uncorrected visual acuity cut-off of poorer than 0.20logMAR to detect different refractive conditions (right eye data).

*<p>n = 1.</p

ROC curves: use of uncorrected visual acuity (LogMAR) to detect hyperopia.

<p>ROC curves: use of uncorrected visual acuity (LogMAR) to detect hyperopia.</p

The prevalence of significant refractive error, myopia, hyperopia and astigmatism.

<p> <i>CIs: Confidence Intervals.</i></p><p> <i>n = number of cases of specified refractive error.</i></p

ROC curves: use of uncorrected visual acuity (LogMAR) to detect astigmatism.

<p>ROC curves: use of uncorrected visual acuity (LogMAR) to detect astigmatism.</p

Optimal cut-off points for uncorrected visual acuity (LogMAR) to detect different refractive conditions.

*<p>n = 1.</p

ROC curve: use of uncorrected visual acuity (LogMAR) to detect myopia in 12-13-year-olds.

<p>ROC curve: use of uncorrected visual acuity (LogMAR) to detect myopia in 12-13-year-olds.</p

Scatterplot of uncorrected visual acuity (LogMAR) with spherical refraction for differing levels of astigmatism.

<p>The solid black lines represent 0.00 and 0.20 logMAR.</p

Variation of uncorrected LogMAR acuity with refractive status.

<p>Definitions: myopia≤−1.00DS; hyperopia>+3.50DS; astigmatism>1.50DC.</p