A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department

Table 2 Risk factors for critical care outcome among chest pain patients

Risk factors	β	S.E	Z	P value	*OR (95%CI)*
Mode of arrival	− 0.995	0.305	−3.265	0.001	0.37 (0.204–0.672)
Reperfusion therapy	−1.151	0.193	−5.970	0.000	0.316 (0.217–0.461)
Killip	0.893	0.190	4.702	0.000	2.443 (1.684–3.545)
SBP	2.228	0.692	3.218	0.001	9.281 (2.389–36.05)
SCr	1.480	0.632	2.343	0.019	4.395 (1.274–15.161)
CKMB	0.709	0.130	5.460	0.000	2.031 (1.575–2.62)
NT-proBNP	0.490	0.135	3.626	0.000	1.633 (1.253–2.129)

SBP systolic blood pressure, SCr serum creatinine, CKMB creatine kinase-MB, NT-proBNP N-terminal pro brain natriuretic peptide

ISSN: 1471-227X