Table 5.

Optimal Cut Points for Diagnostic Classification Derived by the Maximum Kolmogorov-Smirnov Metric

	Cognitively unimpaired vs dementia			Mild cognitive impairment vs dementia			Cognitively unimpaired vs mild cognitive impairment
	All participants	MA participants	NHW participants	All participants	MA participants	NHW participants	All participants	MA participants	NHW participants
Model 1	0.409 (0.754–0.882)	0.243 (0.579–0.836)	0.624 (0.806–0.801)	0.541 (0.745–0.807)	0.346 (0.586–0.755)	0.776 (0.686–0.802)	0.360 (0.485–0.744)	0.329 (0.608–0.677)	0.353 (0.541–0.534)
Model 2	0.356 (0.829–0.857)	0.198 (0.771–0.818)	0.487 (0.921–0.646)	0.563 (0.727–0.819)	0.299 (0.686–0.707)	0.755 (0.730–0.757)	0.307 (0.718–0.598)	0.321 (0.662–0.709)	0.527 (0.306–0.795)
Model 3	0.438 (0.813–0.898)	0.141 (0.821–0.775)	0.546 (0.908–0.731)	0.555 (0.756–0.828)	0.283 (0.707–0.701)	0.617 (0.895–0.568)	0.295 (0.744–0.572)	0.306 (0.697–0.664)	0.517 (0.369–0.769)

Abbreviations: MA = Mexican American, NHW = non-Hispanic White.

Note: Optimal cut points for diagnostic classification derived by the maximum Kolmogorov-Smirnov metric (sensitivity, specificity) across the whole sample and with stratification for ethnicity.

Model 1 = adjusts for site; Model 2 = adjusts for site, age, and sex; Model 3 = adjust for site, age, sex, body mass index, diabetes, tobacco use, and Apolipoprotein E ε4 allele.