Table 4.

Multiple linear regression analysis between admission NIHSS score and WMH volume, with/without stratification by stroke subtype

	All patients		Large artery atherosclerosis		Small vessel occlusion		Cardioembolism
	(n = 5035)		(n = 1965)		(n = 895)		(n = 1035)
	Coefficient	P-value	Coefficient	P-value	Coefficient	P-value	Coefficient	P-value
	(95% CI)		(95% CI)		(95% CI)		(95% CI)
Log-transformed WMH	0.050	0.54	−0.019	0.88	0.251	0.01	−0.208	0.35
	(-0.109–0.210)		(−0.258–0.220)		(0.060–0.441)		(−0.644–0.229)
Age	0.048	<0.001	0.056	<0.001	0.013	0.07	0.081	<0.001
	(0.037–0.060)		(0.037–0.075)		(−0.001–0.027)		(0.046–0.117)
Log-transformed infarct volume	1.759	<0.001	1.519	<0.001	0.738	<0.001	2.079	<0.001
	(1.673–1.846)		(1.382–1.657)		(0.457–1.012)		(1.867–2.292)

Coefficient (95% CI) were derived from imputed dataset (n = 5035). Results are from multiple linear regression analysis using the NIHSS score as a dependent variable. Data for patients with undetermined (n = 1021) or other determined (n = 119) strokes are not shown. WMH volume and infarct volume (on diffusion-weighted MRI) were transformed into a logarithmic scale. Covariates with P < 0.2 in the simple linear regression analysis for the entire study population (age, sex, hypertension, smoking, coronary artery disease, atrial fibrillation, previous use of antiplatelet, thrombolysis, log-transformed WMH volume, log-transformed infarct volume, body mass index, haemoglobin, fasting glucose, and total cholesterol) were entered into the multivariable model (Supplementary Table 6).