Table 2.

Logistic regression of each predictor on PVL separately.

Dataset	Number of predictors	Predictor	B	S.E.	p
Case 1	4	SBP32	−0.093	0.032	0.004
		DBP40	0.160	0.065	0.014
		DBP44	−0.258	0.086	0.003
		pO240	−0.064	0.019	0.001
	5	SBP32	−0.120	0.038	0.002
		DBP4	−0.138	0.058	0.017
		DBP40	0.208	0.071	0.003
		DBP44	−0.254	0.089	0.004
		pO240	−0.068	0.021	0.001
Case 2	4	SBPmin	−0.095	0.031	0.002
		DBPadm	−0.063	0.029	0.029
		DBPmin	−0.085	0.056	0.128
		pO2min	−0.036	0.018	0.047
	3	SBPmin	−0.108	0.030	0.000
		DBPadm	−0.079	0.028	0.004
		pO2min	−0.041	0.018	0.024
Case 3	4	HRskw	−0.885	0.339	0.009
		SBPmin	−0.090	0.032	0.005
		DBPadm	−0.090	0.030	0.003
		DBPmin	−0.089	0.054	0.102
	7	HRskw	−1.019	0.382	0.008
		SBPmin	−0.170	0.045	0.000
		SBPskw	1.282	0.477	0.007
		DBPadm	−0.126	0.034	0.000
		DBPskw	−1.741	0.538	0.001
		pCO2krt	0.410	0.172	0.017
		pO2krt	−0.329	0.130	0.011