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Table 1 Baseline patient characteristics

From: Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients: machine learning model development and evaluation

Variable

Number of encounters

Training

Test

Cohort characteristics

Total n = 67,077

Total n = 53,661

Total n = 13,416

Demographic

 Age (years), mean (s.d)

57.0 ± 14.8

57.0 ± 14.7

56.9 ± 14.9

Gender, n(%)

 Male

29,608 (44.1)

23,386 (43.6)

5,934 (44.2)

 Female

37,469 (55.9)

30,275 (56.4)

7,482 (55.8)

Body mass index (kg/m2), mean (s.d)

24.5 ± 3.8

24.5 ± 3.8

24.5 ± 3.8

Disease characteristics

 Cancer, n(%)

866 (1.3)

688 (1.3)

178 (1.3)

 Hypertension, n(%)

13,962 (20.8)

13,015 (24.3)

3,750 (28.0)

 Diabetic mellitus, n(%)

6,068 (9.0)

6,068 (9.1)

1,194 (8.9)

 Liver disease, n(%)

2,282 (3.4)

1,761 (3.3)

383 (2.9)

 Renal disease, n(%)

843 (1.3)

690 (1.3)

162 (1.2)

 In-hospital death, n(%)

515 (0.8)

413(0.8)

102 (0.8)

Visit path

 Outpatient- immediate

2,734 (4.1)

2,186 (4.1)

548 (4.1)

 Outpatient- reservation

55,467 (82.7)

44,425 (82.8)

11,042 (82.3)

 Inpatient

12,956 (19.3)

10,374 (19.3)

2,585 (19.2)

 Emergency Room

5,868 (8.7)

4,676 (8.7)

1,192 (8.9)

 Department transfer, n(%)

5,967 (8.9)

4,764 (8.9)

1,203 (9.0)

 Length of stay after surgery,

mean (s.d.)

6.7 ± 4.7

6.7 ± 4.7

6.7 ± 4.6