1naresh
Array ( [urn:ac.highwire.org:guest:identity] => Array ( [runtime-id] => urn:ac.highwire.org:guest:identity [type] => guest [service-id] => ajnr-ac.highwire.org [access-type] => Controlled [privilege] => Array ( [urn:ac.highwire.org:guest:privilege] => Array ( [runtime-id] => urn:ac.highwire.org:guest:privilege [type] => privilege-set [privilege-set] => GUEST ) ) [credentials] => Array ( [method] => guest ) ) ) 1nareshArray ( [urn:ac.highwire.org:guest:identity] => Array ( [runtime-id] => urn:ac.highwire.org:guest:identity [type] => guest [service-id] => ajnr-ac.highwire.org [access-type] => Controlled [privilege] => Array ( [urn:ac.highwire.org:guest:privilege] => Array ( [runtime-id] => urn:ac.highwire.org:guest:privilege [type] => privilege-set [privilege-set] => GUEST ) ) [credentials] => Array ( [method] => guest ) ) )Table 1:Differentiation of stroke MMD from nonstroke MMD (n = 107)
Variables Univariate Analyses Multivariate Logistic Regression χ2 or t P OR (95% CI) P Modified brain frailty scorea 10.88 .03 2.00 (1.14–3.51) .02 Age –1.63 .11 Sexa 3.27 .07 0.43 (0.17–1.05) .63 Hypertension 1.01 .32 Dyslipidemiaa 2.79 .09 2.74 (0.88–8.55) .08 Diabetes mellitus 0.02 .88 History of smoking 2.35 .13 PCA involvementa 10.52 .001 5.52 (1.03–1.36) .02
aP < .10 threshold for entry into multivariate logistic regression.