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Table 3 Relationship between qualitative variables and failure of treatment

From: The efficacy of machine learning models in forecasting treatment failure in thoracolumbar burst fractures treated with short-segment posterior spinal fixation

Variable

Failure of treatment

Statistical analysis

Yes

N (%)

No

N (%)

Sex

Male

29 (14.2)

175 (85.8)

P = 0.621

Female

15 (11.7)

113 (88.3)

Cause of Injury

Road Traffic

28 (15.5)

153 (84.5)

N/A

Fall

15 (14.2)

91 (85.8)

Sport

2 (16.6)

10(83.3)

Assault

1 (3.4)

28 (96.6)

Other

0(0.00)

4 (100.0)

Level of Vertebra

T10

3(20.0)

12(80.0)

N/A

T11

6 (22.2)

21(77.8)

T12

19(15.0)

108(85.0)

L1

10 (8.9)

102 (91.1)

L2

6(11.8)

45 (88.2)

Smoking

Yes

14(25.9)

40(74.1)

P = 0.231

No

35 (12.8)

239 (87.2)

Diabetes

Yes

14(25.9)

40 (74.1)

P = 0.182

No

30 (10.8)

248 (89.2)

Index level instrumentation

Yes

7(6.5)

101 (93.5)

P = 0.002

No

37 (16.5)

187 (83.5)

Posterolateral fusion

Yes

25(15.8)

133 (84.2)

P = 0.163

No

19 (10.9)

155 (89.1)

Use of crosslinks

Yes

14 (13.7)

88 (86.3)

P = 0.474

No

30 (13.0)

200 (87.0)