Table 2 Stratified patient characteristics.

From: Patient-specific COVID-19 resource utilization prediction using fusion AI model

Variables

Total cohort (2844 patients)

Train (2275 patients)

Test (569 patients)

AGE, mean(SD)

55.6 (17.9)

55.5 (18.0)

55.7 (17.9)

GENDER [mean age/std]

   

 Male

1470 (46%) [56.7 (16.8)]

1115 (46%) [56.8 (17.0)]

254 (42%) [56.5 (16.2)]

 Female

1719 (54%) [54.5 (18.8)]

1298 (54%) [54.5 (18.8)]

351 (58%) [55.2 (19.1)]

Race

   

 African American

1678 (56.4%)

1357 (56.1%)

321 (54.4%)

 Caucasian/White

593 (19.7%)

474 (19.6%)

119 (19.7%)

Asian

79 (2.6%)

62 (2.6%)

17 (2.8%)

 American Indian or Alaska Native

11 (0.4%)

6 (0.3%)

5(0.8%)

 Multiple

10 (0.3%)

6 (0.3%)

4 (0.7%)

 Native Hawaiian Pacific Islander

6 (0.2%)

2 (0.1%)

4 (0.7%)

 Unknown

638 (21.1%)

511 (21.1%)

127 (21.0%)

Ethnic group

   

 Hispanic or Latino

233 (7.7%)

188 (7.8%)

45 (7.4%)

 Non-Hispanic or Latino

2131 (70.5%)

1706 (70.6%)

425 (70.3%)

 Unknown

659 (21.8)

524 (21.7%)

135 (22.3%)

Comorbidities

   

 Respiratory disease

1799 (59.5%)

1435 (59.3%)

364 (60.2%)

 Hypertension

1372 (45.4%)

1092 (45.2%)

280 (46.3%)

 Renal disease

1016 (33.6%)

806 (33.3%)

210 (34.7%)

 Diabetes

467 (15.4%)

380 (15.7%)

87 (14.4%)