Table 2.

Logistic Regression Analyses and Additional Predictive Value of Blood Biomarkers for ADHF and RTI

	ADHF		RTI
	Clinical Model	Clinical Model+Biomarkers Panel	Clinical Model	Clinical Model+Biomarkers Panel
Logistic regression, OR
NIHSS at admission	1.09 (1.02–1.16), P=0.006*	1.06 (1–1.14), P=0.048 †	1.12 (1.09–1.16), P<0.0001 ‡	1.10 (1.07–1.14), P<0.0001 ‡
Age	1.04 (0.99–1.11), P=0.07	1.02 (0.98–1.08), P=0.26	1.02 (1–1.04), P=0.02 †	1.01 (0.99–1.03), P=0.2
Coronary disease	3.24 (1.18–8.44), P=0.02 †	2.8 (1.01–7.36), P=0.047 †	…	…
Sex, female	1.36 (0.5–3.83), P=0.52	1.16 (0.43–3.26), P=0.76	0.8 (0.51–1.35), P=0.38	0.8 (0.5–1.3), P=0.37
Biomarker combination	…	10.1 (3–52.2), P<0.0001 ‡	…	3.73 (2.06–6.75), P<0.0001 ‡
ROC curve
AUC	0.80 (0.70–0.88)	0.88 (0.83–0.93)	0.78 (0.73–0.82)	0.81 (0.77–0.88)
De Long test	…	P=0.038 †	…	P=0.048 †
Cross‐validation AUC	0.79 (0.72–0.87)	0.87 (0.82–0.92)	0.78 (0.74–0.83)	0.82 (0.78–0.85)
De Long test	…	P=0.02 †	…	P=0.002*

The table represents the comparison between predictive models, with or without biomarker combinations. For logistic regression models, OR (95% CI) and P values are given. For the evaluation of the performance of the models, the AUC (95% CI) of the models without doing cross‐validation and carrying out a 10‐fold cross‐validation is represented. AUC indicates area under the curve; NIHSS, National Institutes of Health Stroke Scale; OR, odds ratio; and ROC, receiver operator characteristic.

^* P<0.01.

^† P<0.05.

^‡ P<0.001.