Table 2.

Univariable Analysis by In-Hospital Mortality and ICU Admission Considering Postal Code Areas According to Country Reference

	Survived(N = 8427)	Died (N = 1678)	p	Non-ICU admitted(N = 9329)	ICU admitted(N = 779)	p
Age (years), median (IQR)	65.0 (52.0–77.0)	82.0 (74.0–87.0)	< 0.001	69.0 (54.0–81.0)	64.0 (55.0–71.0)	< 0.001
Female gender, n (%)	3854 (45.7)	644 (38.4)	< 0.001	4285 (45.9)	214 (27.5)	< 0.001
Immigrants, n (%)	975 (22.2)	69 (8.3)	< 0.001	961 (19.6)	83 (25.7)	0.010
Income (postal code percentile, IQR)	0.60 (0.29–0.80)	0.58 (0.22–0.77)	< 0.001	0.60 (0.26–0.80)	0.63 (0.35–0.81)	0.036
Postal code median populationdensity (percentile, IQR)	0.84 (0.49–0.94)	0.82 (0.49–0.93)	0.224	0.84 (0.49–0.94)	0.76 (0.45–0.92)	< 0.001
Hospital Experience Index,median (IQR)	745 (302–1392)	503 (233–1089)	< 0.001	718 (300–1351)	346 (201–1001)	< 0.001
Emergency Department SaturationIndex, median (IQR)	12.9 (2.9–39.9)	8.7 (1.7–29.8)	< 0.001	12.95 (2.95–41.21)	4.05 (0.58–18.64)	< 0.001
Length of stay, median (IQR)	8.0 (5.0–13.0)	6.0 (3.0–12.0)	< 0.001	7.00 (4.00–12.00)	22.00 (11.00–42.00)	< 0.001

According to the R statistical software when a p value is less than 0.001 the value obtained is p<0.001. If it is strictly necessary to indicate the exact p value we could compute it, but it probably would be in the order of 1e-4 which does not provide more information than <0.001