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Table 1 Patients Demographicsa

From: Predicting venous thromboembolism in hospitalized trauma patients: a combination of the Caprini score and data-driven machine learning model

Demographics

Total(N = 903)

VTE(N = 193)

Non-VTE(N = 710)

Gender

 Male

561 (62.13%)

115

446

 Female

342 (37.87%)

78

264

Age

51 (38 ~ 65)

56 (46 ~ 73)

49 (36 ~ 62)

ISS

9 (5 ~ 20)

13 (9 ~ 26)

9 (4 ~ 16)

BMI

23.35 ± 3.62

24.05 ± 4.27

23.17 ± 3.41

Mechanism of Injury

 Blunt

871 (96.46%)

190

681

 Penetrating

32 (3.54%)

3

29

Injury Cause

 Crush injury

55 (6.09%)

11

44

 Fall injury

324 (35.88%)

62

262

 High fall injury

165 (18.27%)

49

116

 Firearm injury

5 (0.55%)

2

3

 Machine injury

50 (5.54%)

5

45

 Sharp injury

15 (1.66%)

1

14

 Traffic accident

250 (27.69%)

60

190

 Other

39 (4.32%)

3

36

Surgery

 Yes

879 (97.34%)

187

692

 No

24 (2.66%)

6

18

Central venous access

 Yes

50 (5.54%)

24

26

 No

853 (94.46%)

169

684

Caprini Score

9 (5 ~ 11)

11 (10 ~ 12)

8 (4 ~ 10)

Chemoprophylaxis

 LMWH Use

642 (71.10%)

173

469

Length of Stay

12 (8 ~ 19)

18 (11 ~ 30)

10 (7 ~ 16)

Death in Hospital

4 (0.44%)

1

3

Days after Injury for VTE diagnosis

NA

11 (5 ~ 17)

NA

  1. a Note: categorized data is described by “n(%)”; data conforming to the normal distribution is described by “x ± s”; data that does not conform to the normal distribution is described by the median and quartile; Abbreviations: ISS Injury Severity Score. LMWH Low Molecular Weight Heparin. NA not applicable